Merge branch 'main' into feat/milvus-support

# Conflicts:
#	api/core/tool/dataset_index_tool.py
#	web/app/components/base/icons/src/vender/line/general/index.ts

.github/workflows/check_no_chinese_comments.py

@@ -19,7 +19,7 @@ def check_file_for_chinese_comments(file_path):
 
 def main():
     has_chinese = False
-    excluded_files = ["model_template.py", 'stopwords.py', 'commands.py', 'indexing_runner.py']
+    excluded_files = ["model_template.py", 'stopwords.py', 'commands.py', 'indexing_runner.py', 'web_reader_tool.py']
 
     for root, _, files in os.walk("."):
         for file in files:

api/app.py

@@ -22,7 +22,7 @@ from extensions.ext_database import db
 from extensions.ext_login import login_manager
 
 # DO NOT REMOVE BELOW
-from models import model, account, dataset, web, task, source
+from models import model, account, dataset, web, task, source, tool
 from events import event_handlers
 # DO NOT REMOVE ABOVE
 

api/controllers/console/__init__.py

@@ -18,7 +18,10 @@ from .auth import login, oauth, data_source_oauth, activate
 from .datasets import datasets, datasets_document, datasets_segments, file, hit_testing, data_source
 
 # Import workspace controllers
-from .workspace import workspace, members, providers, account
+from .workspace import workspace, members, model_providers, account, tool_providers
 
 # Import explore controllers
 from .explore import installed_app, recommended_app, completion, conversation, message, parameter, saved_message, audio
+
+# Import universal chat controllers
+from .universal_chat import chat, conversation, message, parameter, audio

api/controllers/console/app/app.py

@@ -24,6 +24,7 @@ model_config_fields = {
     'suggested_questions_after_answer': fields.Raw(attribute='suggested_questions_after_answer_dict'),
     'speech_to_text': fields.Raw(attribute='speech_to_text_dict'),
     'more_like_this': fields.Raw(attribute='more_like_this_dict'),
+    'sensitive_word_avoidance': fields.Raw(attribute='sensitive_word_avoidance_dict'),
     'model': fields.Raw(attribute='model_dict'),
     'user_input_form': fields.Raw(attribute='user_input_form_list'),
     'pre_prompt': fields.String,
@@ -96,7 +97,8 @@ class AppListApi(Resource):
         args = parser.parse_args()
 
         app_models = db.paginate(
-            db.select(App).where(App.tenant_id == current_user.current_tenant_id).order_by(App.created_at.desc()),
+            db.select(App).where(App.tenant_id == current_user.current_tenant_id,
+                                 App.is_universal == False).order_by(App.created_at.desc()),
             page=args['page'],
             per_page=args['limit'],
             error_out=False)
@@ -147,6 +149,7 @@ class AppListApi(Resource):
                 suggested_questions_after_answer=json.dumps(model_configuration['suggested_questions_after_answer']),
                 speech_to_text=json.dumps(model_configuration['speech_to_text']),
                 more_like_this=json.dumps(model_configuration['more_like_this']),
+                sensitive_word_avoidance=json.dumps(model_configuration['sensitive_word_avoidance']),
                 model=json.dumps(model_configuration['model']),
                 user_input_form=json.dumps(model_configuration['user_input_form']),
                 pre_prompt=model_configuration['pre_prompt'],
@@ -438,6 +441,7 @@ class AppCopy(Resource):
             suggested_questions_after_answer=app_config.suggested_questions_after_answer,
             speech_to_text=app_config.speech_to_text,
             more_like_this=app_config.more_like_this,
+            sensitive_word_avoidance=app_config.sensitive_word_avoidance,
             model=app_config.model,
             user_input_form=app_config.user_input_form,
             pre_prompt=app_config.pre_prompt,

api/controllers/console/app/conversation.py

@@ -95,6 +95,7 @@ class CompletionConversationApi(Resource):
         'status': fields.String,
         'from_source': fields.String,
         'from_end_user_id': fields.String,
+        'from_end_user_session_id': fields.String(attribute='end_user.session_id'),
         'from_account_id': fields.String,
         'read_at': TimestampField,
         'created_at': TimestampField,
@@ -135,6 +136,8 @@ class CompletionConversationApi(Resource):
 
         query = db.select(Conversation).where(Conversation.app_id == app.id, Conversation.mode == 'completion')
 
+        query = query.options(joinedload(Conversation.end_user))
+
         if args['keyword']:
             query = query.join(
                 Message, Message.conversation_id == Conversation.id
@@ -160,7 +163,7 @@ class CompletionConversationApi(Resource):
 
         if args['end']:
             end_datetime = datetime.strptime(args['end'], '%Y-%m-%d %H:%M')
-            end_datetime = end_datetime.replace(second=0)
+            end_datetime = end_datetime.replace(second=59)
 
             end_datetime_timezone = timezone.localize(end_datetime)
             end_datetime_utc = end_datetime_timezone.astimezone(utc_timezone)
@@ -246,6 +249,7 @@ class ChatConversationApi(Resource):
         'status': fields.String,
         'from_source': fields.String,
         'from_end_user_id': fields.String,
+        'from_end_user_session_id': fields.String(attribute='end_user.session_id'),
         'from_account_id': fields.String,
         'summary': fields.String(attribute='summary_or_query'),
         'read_at': TimestampField,
@@ -288,6 +292,8 @@ class ChatConversationApi(Resource):
 
         query = db.select(Conversation).where(Conversation.app_id == app.id, Conversation.mode == 'chat')
 
+        query = query.options(joinedload(Conversation.end_user))
+
         if args['keyword']:
             query = query.join(
                 Message, Message.conversation_id == Conversation.id
@@ -316,7 +322,7 @@ class ChatConversationApi(Resource):
 
         if args['end']:
             end_datetime = datetime.strptime(args['end'], '%Y-%m-%d %H:%M')
-            end_datetime = end_datetime.replace(second=0)
+            end_datetime = end_datetime.replace(second=59)
 
             end_datetime_timezone = timezone.localize(end_datetime)
             end_datetime_utc = end_datetime_timezone.astimezone(utc_timezone)

api/controllers/console/app/model_config.py

@@ -43,6 +43,7 @@ class ModelConfigResource(Resource):
             suggested_questions_after_answer=json.dumps(model_configuration['suggested_questions_after_answer']),
             speech_to_text=json.dumps(model_configuration['speech_to_text']),
             more_like_this=json.dumps(model_configuration['more_like_this']),
+            sensitive_word_avoidance=json.dumps(model_configuration['sensitive_word_avoidance']),
             model=json.dumps(model_configuration['model']),
             user_input_form=json.dumps(model_configuration['user_input_form']),
             pre_prompt=model_configuration['pre_prompt'],

api/controllers/console/explore/conversation.py

@@ -65,7 +65,10 @@ class ConversationApi(InstalledAppResource):
             raise NotChatAppError()
 
         conversation_id = str(c_id)
+        try:
             ConversationService.delete(app_model, conversation_id, current_user)
+        except ConversationNotExistsError:
+            raise NotFound("Conversation Not Exists.")
         WebConversationService.unpin(app_model, conversation_id, current_user)
 
         return {"result": "success"}, 204

api/controllers/console/explore/parameter.py

@@ -4,6 +4,10 @@ from flask_restful import marshal_with, fields
 from controllers.console import api
 from controllers.console.explore.wraps import InstalledAppResource
 
+from core.llm.llm_builder import LLMBuilder
+from models.provider import ProviderName
+from models.model import InstalledApp
+
 
 class AppParameterApi(InstalledAppResource):
     """Resource for app variables."""
@@ -27,16 +31,17 @@ class AppParameterApi(InstalledAppResource):
     }
 
     @marshal_with(parameters_fields)
-    def get(self, installed_app):
+    def get(self, installed_app: InstalledApp):
         """Retrieve app parameters."""
         app_model = installed_app.app
         app_model_config = app_model.app_model_config
+        provider_name = LLMBuilder.get_default_provider(installed_app.tenant_id, 'whisper-1')
 
         return {
             'opening_statement': app_model_config.opening_statement,
             'suggested_questions': app_model_config.suggested_questions_list,
             'suggested_questions_after_answer': app_model_config.suggested_questions_after_answer_dict,
-            'speech_to_text': app_model_config.speech_to_text_dict,
+            'speech_to_text': app_model_config.speech_to_text_dict if provider_name == ProviderName.OPENAI.value else { 'enabled': False },
             'more_like_this': app_model_config.more_like_this_dict,
             'user_input_form': app_model_config.user_input_form_list
         }

api/controllers/console/universal_chat/audio.py

+# -*- coding:utf-8 -*-
+import logging
+
+from flask import request
+from werkzeug.exceptions import InternalServerError
+
+import services
+from controllers.console import api
+from controllers.console.app.error import AppUnavailableError, ProviderNotInitializeError, \
+    ProviderQuotaExceededError, ProviderModelCurrentlyNotSupportError, CompletionRequestError, \
+    NoAudioUploadedError, AudioTooLargeError, \
+    UnsupportedAudioTypeError, ProviderNotSupportSpeechToTextError
+from controllers.console.universal_chat.wraps import UniversalChatResource
+from core.llm.error import LLMBadRequestError, LLMAPIUnavailableError, LLMAuthorizationError, LLMAPIConnectionError, \
+    LLMRateLimitError, ProviderTokenNotInitError, QuotaExceededError, ModelCurrentlyNotSupportError
+from services.audio_service import AudioService
+from services.errors.audio import NoAudioUploadedServiceError, AudioTooLargeServiceError, \
+    UnsupportedAudioTypeServiceError, ProviderNotSupportSpeechToTextServiceError
+from models.model import AppModelConfig
+
+
+class UniversalChatAudioApi(UniversalChatResource):
+    def post(self, universal_app):
+        app_model = universal_app
+        app_model_config: AppModelConfig = app_model.app_model_config
+
+        if not app_model_config.speech_to_text_dict['enabled']:
+            raise AppUnavailableError()
+
+        file = request.files['file']
+
+        try:
+            response = AudioService.transcript(
+                tenant_id=app_model.tenant_id,
+                file=file,
+            )
+
+            return response
+        except services.errors.app_model_config.AppModelConfigBrokenError:
+            logging.exception("App model config broken.")
+            raise AppUnavailableError()
+        except NoAudioUploadedServiceError:
+            raise NoAudioUploadedError()
+        except AudioTooLargeServiceError as e:
+            raise AudioTooLargeError(str(e))
+        except UnsupportedAudioTypeServiceError:
+            raise UnsupportedAudioTypeError()
+        except ProviderNotSupportSpeechToTextServiceError:
+            raise ProviderNotSupportSpeechToTextError()
+        except ProviderTokenNotInitError:
+            raise ProviderNotInitializeError()
+        except QuotaExceededError:
+            raise ProviderQuotaExceededError()
+        except ModelCurrentlyNotSupportError:
+            raise ProviderModelCurrentlyNotSupportError()
+        except (LLMBadRequestError, LLMAPIConnectionError, LLMAPIUnavailableError,
+                LLMRateLimitError, LLMAuthorizationError) as e:
+            raise CompletionRequestError(str(e))
+        except ValueError as e:
+            raise e
+        except Exception as e:
+            logging.exception("internal server error.")
+            raise InternalServerError()
+        
+
+api.add_resource(UniversalChatAudioApi, '/universal-chat/audio-to-text')
\ No newline at end of file

api/controllers/console/universal_chat/chat.py

+import json
+import logging
+from typing import Generator, Union
+
+from flask import Response, stream_with_context
+from flask_login import current_user
+from flask_restful import reqparse
+from werkzeug.exceptions import InternalServerError, NotFound
+
+import services
+from controllers.console import api
+from controllers.console.app.error import ConversationCompletedError, AppUnavailableError, ProviderNotInitializeError, \
+    ProviderQuotaExceededError, ProviderModelCurrentlyNotSupportError, CompletionRequestError
+from controllers.console.universal_chat.wraps import UniversalChatResource
+from core.constant import llm_constant
+from core.conversation_message_task import PubHandler
+from core.llm.error import ProviderTokenNotInitError, QuotaExceededError, ModelCurrentlyNotSupportError, \
+    LLMBadRequestError, LLMAPIConnectionError, LLMAPIUnavailableError, LLMRateLimitError, LLMAuthorizationError
+from libs.helper import uuid_value
+from services.completion_service import CompletionService
+
+
+class UniversalChatApi(UniversalChatResource):
+    def post(self, universal_app):
+        app_model = universal_app
+
+        parser = reqparse.RequestParser()
+        parser.add_argument('query', type=str, required=True, location='json')
+        parser.add_argument('conversation_id', type=uuid_value, location='json')
+        parser.add_argument('model', type=str, required=True, location='json')
+        parser.add_argument('tools', type=list, required=True, location='json')
+        args = parser.parse_args()
+
+        app_model_config = app_model.app_model_config
+
+        # update app model config
+        args['model_config'] = app_model_config.to_dict()
+        args['model_config']['model']['name'] = args['model']
+
+        if not llm_constant.models[args['model']]:
+            raise ValueError("Model not exists.")
+
+        args['model_config']['model']['provider'] = llm_constant.models[args['model']]
+        args['model_config']['agent_mode']['tools'] = args['tools']
+
+        args['inputs'] = {}
+
+        del args['model']
+        del args['tools']
+
+        try:
+            response = CompletionService.completion(
+                app_model=app_model,
+                user=current_user,
+                args=args,
+                from_source='console',
+                streaming=True,
+                is_model_config_override=True,
+            )
+
+            return compact_response(response)
+        except services.errors.conversation.ConversationNotExistsError:
+            raise NotFound("Conversation Not Exists.")
+        except services.errors.conversation.ConversationCompletedError:
+            raise ConversationCompletedError()
+        except services.errors.app_model_config.AppModelConfigBrokenError:
+            logging.exception("App model config broken.")
+            raise AppUnavailableError()
+        except ProviderTokenNotInitError:
+            raise ProviderNotInitializeError()
+        except QuotaExceededError:
+            raise ProviderQuotaExceededError()
+        except ModelCurrentlyNotSupportError:
+            raise ProviderModelCurrentlyNotSupportError()
+        except (LLMBadRequestError, LLMAPIConnectionError, LLMAPIUnavailableError,
+                LLMRateLimitError, LLMAuthorizationError) as e:
+            raise CompletionRequestError(str(e))
+        except ValueError as e:
+            raise e
+        except Exception as e:
+            logging.exception("internal server error.")
+            raise InternalServerError()
+
+
+class UniversalChatStopApi(UniversalChatResource):
+    def post(self, universal_app, task_id):
+        PubHandler.stop(current_user, task_id)
+
+        return {'result': 'success'}, 200
+
+
+def compact_response(response: Union[dict | Generator]) -> Response:
+    if isinstance(response, dict):
+        return Response(response=json.dumps(response), status=200, mimetype='application/json')
+    else:
+        def generate() -> Generator:
+            try:
+                for chunk in response:
+                    yield chunk
+            except services.errors.conversation.ConversationNotExistsError:
+                yield "data: " + json.dumps(api.handle_error(NotFound("Conversation Not Exists.")).get_json()) + "\n\n"
+            except services.errors.conversation.ConversationCompletedError:
+                yield "data: " + json.dumps(api.handle_error(ConversationCompletedError()).get_json()) + "\n\n"
+            except services.errors.app_model_config.AppModelConfigBrokenError:
+                logging.exception("App model config broken.")
+                yield "data: " + json.dumps(api.handle_error(AppUnavailableError()).get_json()) + "\n\n"
+            except ProviderTokenNotInitError:
+                yield "data: " + json.dumps(api.handle_error(ProviderNotInitializeError()).get_json()) + "\n\n"
+            except QuotaExceededError:
+                yield "data: " + json.dumps(api.handle_error(ProviderQuotaExceededError()).get_json()) + "\n\n"
+            except ModelCurrentlyNotSupportError:
+                yield "data: " + json.dumps(api.handle_error(ProviderModelCurrentlyNotSupportError()).get_json()) + "\n\n"
+            except (LLMBadRequestError, LLMAPIConnectionError, LLMAPIUnavailableError,
+                    LLMRateLimitError, LLMAuthorizationError) as e:
+                yield "data: " + json.dumps(api.handle_error(CompletionRequestError(str(e))).get_json()) + "\n\n"
+            except ValueError as e:
+                yield "data: " + json.dumps(api.handle_error(e).get_json()) + "\n\n"
+            except Exception:
+                logging.exception("internal server error.")
+                yield "data: " + json.dumps(api.handle_error(InternalServerError()).get_json()) + "\n\n"
+
+        return Response(stream_with_context(generate()), status=200,
+                        mimetype='text/event-stream')
+
+
+api.add_resource(UniversalChatApi, '/universal-chat/messages')
+api.add_resource(UniversalChatStopApi, '/universal-chat/messages/<string:task_id>/stop')

api/controllers/console/universal_chat/conversation.py

+# -*- coding:utf-8 -*-
+from flask_login import current_user
+from flask_restful import fields, reqparse, marshal_with
+from flask_restful.inputs import int_range
+from werkzeug.exceptions import NotFound
+
+from controllers.console import api
+from controllers.console.universal_chat.wraps import UniversalChatResource
+from libs.helper import TimestampField, uuid_value
+from services.conversation_service import ConversationService
+from services.errors.conversation import LastConversationNotExistsError, ConversationNotExistsError
+from services.web_conversation_service import WebConversationService
+
+conversation_fields = {
+    'id': fields.String,
+    'name': fields.String,
+    'inputs': fields.Raw,
+    'status': fields.String,
+    'introduction': fields.String,
+    'created_at': TimestampField,
+    'model_config': fields.Raw,
+}
+
+conversation_infinite_scroll_pagination_fields = {
+    'limit': fields.Integer,
+    'has_more': fields.Boolean,
+    'data': fields.List(fields.Nested(conversation_fields))
+}
+
+
+class UniversalChatConversationListApi(UniversalChatResource):
+
+    @marshal_with(conversation_infinite_scroll_pagination_fields)
+    def get(self, universal_app):
+        app_model = universal_app
+
+        parser = reqparse.RequestParser()
+        parser.add_argument('last_id', type=uuid_value, location='args')
+        parser.add_argument('limit', type=int_range(1, 100), required=False, default=20, location='args')
+        parser.add_argument('pinned', type=str, choices=['true', 'false', None], location='args')
+        args = parser.parse_args()
+
+        pinned = None
+        if 'pinned' in args and args['pinned'] is not None:
+            pinned = True if args['pinned'] == 'true' else False
+
+        try:
+            return WebConversationService.pagination_by_last_id(
+                app_model=app_model,
+                user=current_user,
+                last_id=args['last_id'],
+                limit=args['limit'],
+                pinned=pinned
+            )
+        except LastConversationNotExistsError:
+            raise NotFound("Last Conversation Not Exists.")
+
+
+class UniversalChatConversationApi(UniversalChatResource):
+    def delete(self, universal_app, c_id):
+        app_model = universal_app
+        conversation_id = str(c_id)
+
+        try:
+            ConversationService.delete(app_model, conversation_id, current_user)
+        except ConversationNotExistsError:
+            raise NotFound("Conversation Not Exists.")
+
+        WebConversationService.unpin(app_model, conversation_id, current_user)
+
+        return {"result": "success"}, 204
+
+
+class UniversalChatConversationRenameApi(UniversalChatResource):
+
+    @marshal_with(conversation_fields)
+    def post(self, universal_app, c_id):
+        app_model = universal_app
+        conversation_id = str(c_id)
+
+        parser = reqparse.RequestParser()
+        parser.add_argument('name', type=str, required=True, location='json')
+        args = parser.parse_args()
+
+        try:
+            return ConversationService.rename(app_model, conversation_id, current_user, args['name'])
+        except ConversationNotExistsError:
+            raise NotFound("Conversation Not Exists.")
+
+
+class UniversalChatConversationPinApi(UniversalChatResource):
+
+    def patch(self, universal_app, c_id):
+        app_model = universal_app
+        conversation_id = str(c_id)
+
+        try:
+            WebConversationService.pin(app_model, conversation_id, current_user)
+        except ConversationNotExistsError:
+            raise NotFound("Conversation Not Exists.")
+
+        return {"result": "success"}
+
+
+class UniversalChatConversationUnPinApi(UniversalChatResource):
+    def patch(self, universal_app, c_id):
+        app_model = universal_app
+        conversation_id = str(c_id)
+        WebConversationService.unpin(app_model, conversation_id, current_user)
+
+        return {"result": "success"}
+
+
+api.add_resource(UniversalChatConversationRenameApi, '/universal-chat/conversations/<uuid:c_id>/name')
+api.add_resource(UniversalChatConversationListApi, '/universal-chat/conversations')
+api.add_resource(UniversalChatConversationApi, '/universal-chat/conversations/<uuid:c_id>')
+api.add_resource(UniversalChatConversationPinApi, '/universal-chat/conversations/<uuid:c_id>/pin')
+api.add_resource(UniversalChatConversationUnPinApi, '/universal-chat/conversations/<uuid:c_id>/unpin')

api/controllers/console/universal_chat/message.py

+# -*- coding:utf-8 -*-
+import logging
+
+from flask_login import current_user
+from flask_restful import reqparse, fields, marshal_with
+from flask_restful.inputs import int_range
+from werkzeug.exceptions import NotFound, InternalServerError
+
+import services
+from controllers.console import api
+from controllers.console.app.error import ProviderNotInitializeError, \
+    ProviderQuotaExceededError, ProviderModelCurrentlyNotSupportError, CompletionRequestError
+from controllers.console.explore.error import AppSuggestedQuestionsAfterAnswerDisabledError
+from controllers.console.universal_chat.wraps import UniversalChatResource
+from core.llm.error import LLMRateLimitError, LLMBadRequestError, LLMAuthorizationError, LLMAPIConnectionError, \
+    ProviderTokenNotInitError, LLMAPIUnavailableError, QuotaExceededError, ModelCurrentlyNotSupportError
+from libs.helper import uuid_value, TimestampField
+from services.errors.conversation import ConversationNotExistsError
+from services.errors.message import MessageNotExistsError, SuggestedQuestionsAfterAnswerDisabledError
+from services.message_service import MessageService
+
+
+class UniversalChatMessageListApi(UniversalChatResource):
+    feedback_fields = {
+        'rating': fields.String
+    }
+
+    agent_thought_fields = {
+        'id': fields.String,
+        'chain_id': fields.String,
+        'message_id': fields.String,
+        'position': fields.Integer,
+        'thought': fields.String,
+        'tool': fields.String,
+        'tool_input': fields.String,
+        'created_at': TimestampField
+    }
+
+    message_fields = {
+        'id': fields.String,
+        'conversation_id': fields.String,
+        'inputs': fields.Raw,
+        'query': fields.String,
+        'answer': fields.String,
+        'feedback': fields.Nested(feedback_fields, attribute='user_feedback', allow_null=True),
+        'created_at': TimestampField,
+        'agent_thoughts': fields.List(fields.Nested(agent_thought_fields))
+    }
+
+    message_infinite_scroll_pagination_fields = {
+        'limit': fields.Integer,
+        'has_more': fields.Boolean,
+        'data': fields.List(fields.Nested(message_fields))
+    }
+
+    @marshal_with(message_infinite_scroll_pagination_fields)
+    def get(self, universal_app):
+        app_model = universal_app
+
+        parser = reqparse.RequestParser()
+        parser.add_argument('conversation_id', required=True, type=uuid_value, location='args')
+        parser.add_argument('first_id', type=uuid_value, location='args')
+        parser.add_argument('limit', type=int_range(1, 100), required=False, default=20, location='args')
+        args = parser.parse_args()
+
+        try:
+            return MessageService.pagination_by_first_id(app_model, current_user,
+                                                     args['conversation_id'], args['first_id'], args['limit'])
+        except services.errors.conversation.ConversationNotExistsError:
+            raise NotFound("Conversation Not Exists.")
+        except services.errors.message.FirstMessageNotExistsError:
+            raise NotFound("First Message Not Exists.")
+
+
+class UniversalChatMessageFeedbackApi(UniversalChatResource):
+    def post(self, universal_app, message_id):
+        app_model = universal_app
+        message_id = str(message_id)
+
+        parser = reqparse.RequestParser()
+        parser.add_argument('rating', type=str, choices=['like', 'dislike', None], location='json')
+        args = parser.parse_args()
+
+        try:
+            MessageService.create_feedback(app_model, message_id, current_user, args['rating'])
+        except services.errors.message.MessageNotExistsError:
+            raise NotFound("Message Not Exists.")
+
+        return {'result': 'success'}
+
+
+class UniversalChatMessageSuggestedQuestionApi(UniversalChatResource):
+    def get(self, universal_app, message_id):
+        app_model = universal_app
+        message_id = str(message_id)
+
+        try:
+            questions = MessageService.get_suggested_questions_after_answer(
+                app_model=app_model,
+                user=current_user,
+                message_id=message_id
+            )
+        except MessageNotExistsError:
+            raise NotFound("Message not found")
+        except ConversationNotExistsError:
+            raise NotFound("Conversation not found")
+        except SuggestedQuestionsAfterAnswerDisabledError:
+            raise AppSuggestedQuestionsAfterAnswerDisabledError()
+        except ProviderTokenNotInitError:
+            raise ProviderNotInitializeError()
+        except QuotaExceededError:
+            raise ProviderQuotaExceededError()
+        except ModelCurrentlyNotSupportError:
+            raise ProviderModelCurrentlyNotSupportError()
+        except (LLMBadRequestError, LLMAPIConnectionError, LLMAPIUnavailableError,
+                LLMRateLimitError, LLMAuthorizationError) as e:
+            raise CompletionRequestError(str(e))
+        except Exception:
+            logging.exception("internal server error.")
+            raise InternalServerError()
+
+        return {'data': questions}
+
+
+api.add_resource(UniversalChatMessageListApi, '/universal-chat/messages')
+api.add_resource(UniversalChatMessageFeedbackApi, '/universal-chat/messages/<uuid:message_id>/feedbacks')
+api.add_resource(UniversalChatMessageSuggestedQuestionApi, '/universal-chat/messages/<uuid:message_id>/suggested-questions')

api/controllers/console/universal_chat/parameter.py

+# -*- coding:utf-8 -*-
+from flask_restful import marshal_with, fields
+
+from controllers.console import api
+from controllers.console.universal_chat.wraps import UniversalChatResource
+
+from core.llm.llm_builder import LLMBuilder
+from models.provider import ProviderName
+from models.model import App
+
+
+class UniversalChatParameterApi(UniversalChatResource):
+    """Resource for app variables."""
+    parameters_fields = {
+        'opening_statement': fields.String,
+        'suggested_questions': fields.Raw,
+        'suggested_questions_after_answer': fields.Raw,
+        'speech_to_text': fields.Raw,
+    }
+
+    @marshal_with(parameters_fields)
+    def get(self, universal_app: App):
+        """Retrieve app parameters."""
+        app_model = universal_app
+        app_model_config = app_model.app_model_config
+        provider_name = LLMBuilder.get_default_provider(universal_app.tenant_id, 'whisper-1')
+
+        return {
+            'opening_statement': app_model_config.opening_statement,
+            'suggested_questions': app_model_config.suggested_questions_list,
+            'suggested_questions_after_answer': app_model_config.suggested_questions_after_answer_dict,
+            'speech_to_text': app_model_config.speech_to_text_dict if provider_name == ProviderName.OPENAI.value else { 'enabled': False },
+        }
+
+
+api.add_resource(UniversalChatParameterApi, '/universal-chat/parameters')

api/controllers/console/universal_chat/wraps.py

+import json
+from functools import wraps
+
+from flask_login import login_required, current_user
+from flask_restful import Resource
+from controllers.console.setup import setup_required
+from controllers.console.wraps import account_initialization_required
+from extensions.ext_database import db
+from models.model import App, AppModelConfig
+
+
+def universal_chat_app_required(view=None):
+    def decorator(view):
+        @wraps(view)
+        def decorated(*args, **kwargs):
+            # get universal chat app
+            universal_app = db.session.query(App).filter(
+                App.tenant_id == current_user.current_tenant_id,
+                App.is_universal == True
+            ).first()
+
+            if universal_app is None:
+                # create universal app if not exists
+                universal_app = App(
+                    tenant_id=current_user.current_tenant_id,
+                    name='Universal Chat',
+                    mode='chat',
+                    is_universal=True,
+                    icon='',
+                    icon_background='',
+                    api_rpm=0,
+                    api_rph=0,
+                    enable_site=False,
+                    enable_api=False,
+                    status='normal'
+                )
+
+                db.session.add(universal_app)
+                db.session.flush()
+
+                app_model_config = AppModelConfig(
+                    provider="",
+                    model_id="",
+                    configs={},
+                    opening_statement='',
+                    suggested_questions=json.dumps([]),
+                    suggested_questions_after_answer=json.dumps({'enabled': True}),
+                    speech_to_text=json.dumps({'enabled': True}),
+                    more_like_this=None,
+                    sensitive_word_avoidance=None,
+                    model=json.dumps({
+                        "provider": "openai",
+                        "name": "gpt-3.5-turbo-16k",
+                        "completion_params": {
+                            "max_tokens": 800,
+                            "temperature": 0.8,
+                            "top_p": 1,
+                            "presence_penalty": 0,
+                            "frequency_penalty": 0
+                        }
+                    }),
+                    user_input_form=json.dumps([]),
+                    pre_prompt='',
+                    agent_mode=json.dumps({"enabled": True, "strategy": "function_call", "tools": []}),
+                )
+
+                app_model_config.app_id = universal_app.id
+                db.session.add(app_model_config)
+                db.session.flush()
+
+                universal_app.app_model_config_id = app_model_config.id
+                db.session.commit()
+
+            return view(universal_app, *args, **kwargs)
+        return decorated
+
+    if view:
+        return decorator(view)
+    return decorator
+
+
+class UniversalChatResource(Resource):
+    # must be reversed if there are multiple decorators
+    method_decorators = [universal_chat_app_required, account_initialization_required, login_required, setup_required]

api/controllers/console/workspace/tool_providers.py

+import json
+
+from flask_login import login_required, current_user
+from flask_restful import Resource, abort, reqparse
+from werkzeug.exceptions import Forbidden
+
+from controllers.console import api
+from controllers.console.setup import setup_required
+from controllers.console.wraps import account_initialization_required
+from core.tool.provider.errors import ToolValidateFailedError
+from core.tool.provider.tool_provider_service import ToolProviderService
+from extensions.ext_database import db
+from models.tool import ToolProvider, ToolProviderName
+
+
+class ToolProviderListApi(Resource):
+
+    @setup_required
+    @login_required
+    @account_initialization_required
+    def get(self):
+        tenant_id = current_user.current_tenant_id
+
+        tool_credential_dict = {}
+        for tool_name in ToolProviderName:
+            tool_credential_dict[tool_name.value] = {
+                'tool_name': tool_name.value,
+                'is_enabled': False,
+                'credentials': None
+            }
+
+        tool_providers = db.session.query(ToolProvider).filter(ToolProvider.tenant_id == tenant_id).all()
+
+        for p in tool_providers:
+            if p.is_enabled:
+                tool_credential_dict[p.tool_name] = {
+                    'tool_name': p.tool_name,
+                    'is_enabled': p.is_enabled,
+                    'credentials': ToolProviderService(tenant_id, p.tool_name).get_credentials(obfuscated=True)
+                }
+
+        return list(tool_credential_dict.values())
+
+
+class ToolProviderCredentialsApi(Resource):
+
+    @setup_required
+    @login_required
+    @account_initialization_required
+    def post(self, provider):
+        if provider not in [p.value for p in ToolProviderName]:
+            abort(404)
+
+        # The role of the current user in the ta table must be admin or owner
+        if current_user.current_tenant.current_role not in ['admin', 'owner']:
+            raise Forbidden(f'User {current_user.id} is not authorized to update provider token, '
+                            f'current_role is {current_user.current_tenant.current_role}')
+
+        parser = reqparse.RequestParser()
+        parser.add_argument('credentials', type=dict, required=True, nullable=False, location='json')
+        args = parser.parse_args()
+
+        tenant_id = current_user.current_tenant_id
+
+        tool_provider_service = ToolProviderService(tenant_id, provider)
+
+        try:
+            tool_provider_service.credentials_validate(args['credentials'])
+        except ToolValidateFailedError as ex:
+            raise ValueError(str(ex))
+
+        encrypted_credentials = json.dumps(tool_provider_service.encrypt_credentials(args['credentials']))
+
+        tenant = current_user.current_tenant
+
+        tool_provider_model = db.session.query(ToolProvider).filter(
+                ToolProvider.tenant_id == tenant.id,
+                ToolProvider.tool_name == provider,
+            ).first()
+
+        # Only allow updating token for CUSTOM provider type
+        if tool_provider_model:
+            tool_provider_model.encrypted_credentials = encrypted_credentials
+            tool_provider_model.is_enabled = True
+        else:
+            tool_provider_model = ToolProvider(
+                tenant_id=tenant.id,
+                tool_name=provider,
+                encrypted_credentials=encrypted_credentials,
+                is_enabled=True
+            )
+            db.session.add(tool_provider_model)
+
+        db.session.commit()
+
+        return {'result': 'success'}, 201
+
+
+class ToolProviderCredentialsValidateApi(Resource):
+
+    @setup_required
+    @login_required
+    @account_initialization_required
+    def post(self, provider):
+        if provider not in [p.value for p in ToolProviderName]:
+            abort(404)
+
+        parser = reqparse.RequestParser()
+        parser.add_argument('credentials', type=dict, required=True, nullable=False, location='json')
+        args = parser.parse_args()
+
+        result = True
+        error = None
+
+        tenant_id = current_user.current_tenant_id
+
+        tool_provider_service = ToolProviderService(tenant_id, provider)
+
+        try:
+            tool_provider_service.credentials_validate(args['credentials'])
+        except ToolValidateFailedError as ex:
+            result = False
+            error = str(ex)
+
+        response = {'result': 'success' if result else 'error'}
+
+        if not result:
+            response['error'] = error
+
+        return response
+
+
+api.add_resource(ToolProviderListApi, '/workspaces/current/tool-providers')
+api.add_resource(ToolProviderCredentialsApi, '/workspaces/current/tool-providers/<provider>/credentials')
+api.add_resource(ToolProviderCredentialsValidateApi,
+                 '/workspaces/current/tool-providers/<provider>/credentials-validate')

api/controllers/service_api/app/app.py

@@ -4,6 +4,10 @@ from flask_restful import fields, marshal_with
 from controllers.service_api import api
 from controllers.service_api.wraps import AppApiResource
 
+from core.llm.llm_builder import LLMBuilder
+from models.provider import ProviderName
+from models.model import App
+
 
 class AppParameterApi(AppApiResource):
     """Resource for app variables."""
@@ -28,15 +32,16 @@ class AppParameterApi(AppApiResource):
     }
 
     @marshal_with(parameters_fields)
-    def get(self, app_model, end_user):
+    def get(self, app_model: App, end_user):
         """Retrieve app parameters."""
         app_model_config = app_model.app_model_config
+        provider_name = LLMBuilder.get_default_provider(app_model.tenant_id, 'whisper-1')
 
         return {
             'opening_statement': app_model_config.opening_statement,
             'suggested_questions': app_model_config.suggested_questions_list,
             'suggested_questions_after_answer': app_model_config.suggested_questions_after_answer_dict,
-            'speech_to_text': app_model_config.speech_to_text_dict,
+            'speech_to_text': app_model_config.speech_to_text_dict if provider_name == ProviderName.OPENAI.value else { 'enabled': False },
             'more_like_this': app_model_config.more_like_this_dict,
             'user_input_form': app_model_config.user_input_form_list
         }

api/controllers/web/app.py

@@ -4,6 +4,10 @@ from flask_restful import marshal_with, fields
 from controllers.web import api
 from controllers.web.wraps import WebApiResource
 
+from core.llm.llm_builder import LLMBuilder
+from models.provider import ProviderName
+from models.model import App
+
 
 class AppParameterApi(WebApiResource):
     """Resource for app variables."""
@@ -27,15 +31,16 @@ class AppParameterApi(WebApiResource):
     }
 
     @marshal_with(parameters_fields)
-    def get(self, app_model, end_user):
+    def get(self, app_model: App, end_user):
         """Retrieve app parameters."""
         app_model_config = app_model.app_model_config
+        provider_name = LLMBuilder.get_default_provider(app_model.tenant_id, 'whisper-1')
 
         return {
             'opening_statement': app_model_config.opening_statement,
             'suggested_questions': app_model_config.suggested_questions_list,
             'suggested_questions_after_answer': app_model_config.suggested_questions_after_answer_dict,
-            'speech_to_text': app_model_config.speech_to_text_dict,
+            'speech_to_text': app_model_config.speech_to_text_dict if provider_name == ProviderName.OPENAI.value else { 'enabled': False },
             'more_like_this': app_model_config.more_like_this_dict,
             'user_input_form': app_model_config.user_input_form_list
         }

api/controllers/web/conversation.py

@@ -62,7 +62,10 @@ class ConversationApi(WebApiResource):
             raise NotChatAppError()
 
         conversation_id = str(c_id)
+        try:
             ConversationService.delete(app_model, conversation_id, end_user)
+        except ConversationNotExistsError:
+            raise NotFound("Conversation Not Exists.")
         WebConversationService.unpin(app_model, conversation_id, end_user)
 
         return {"result": "success"}, 204

api/controllers/web/wraps.py

@@ -38,6 +38,8 @@ def decode_jwt_token():
     app_model = db.session.query(App).filter(App.id == decoded['app_id']).first()
     if not app_model:
         raise NotFound()
+    if app_model.enable_site is False:
+        raise Unauthorized('Site is disabled.')
     end_user = db.session.query(EndUser).filter(EndUser.id == decoded['end_user_id']).first()
     if not end_user:
         raise NotFound()

api/core/agent/agent/calc_token_mixin.py

+from typing import cast, List
+
+from langchain import OpenAI
+from langchain.base_language import BaseLanguageModel
+from langchain.chat_models.openai import ChatOpenAI
+from langchain.schema import BaseMessage
+
+from core.constant import llm_constant
+
+
+class CalcTokenMixin:
+
+    def get_num_tokens_from_messages(self, llm: BaseLanguageModel, messages: List[BaseMessage], **kwargs) -> int:
+        llm = cast(ChatOpenAI, llm)
+        return llm.get_num_tokens_from_messages(messages)
+
+    def get_message_rest_tokens(self, llm: BaseLanguageModel, messages: List[BaseMessage], **kwargs) -> int:
+        """
+        Got the rest tokens available for the model after excluding messages tokens and completion max tokens
+
+        :param llm:
+        :param messages:
+        :return:
+        """
+        llm = cast(ChatOpenAI, llm)
+        llm_max_tokens = llm_constant.max_context_token_length[llm.model_name]
+        completion_max_tokens = llm.max_tokens
+        used_tokens = self.get_num_tokens_from_messages(llm, messages, **kwargs)
+        rest_tokens = llm_max_tokens - completion_max_tokens - used_tokens
+
+        return rest_tokens
+
+
+class ExceededLLMTokensLimitError(Exception):
+    pass

api/core/agent/agent/multi_dataset_router_agent.py

+from typing import Tuple, List, Any, Union, Sequence, Optional, cast
+
+from langchain.agents import OpenAIFunctionsAgent, BaseSingleActionAgent
+from langchain.callbacks.base import BaseCallbackManager
+from langchain.callbacks.manager import Callbacks
+from langchain.prompts.chat import BaseMessagePromptTemplate
+from langchain.schema import AgentAction, AgentFinish, BaseLanguageModel, SystemMessage
+from langchain.tools import BaseTool
+
+from core.tool.dataset_retriever_tool import DatasetRetrieverTool
+
+
+class MultiDatasetRouterAgent(OpenAIFunctionsAgent):
+    """
+    An Multi Dataset Retrieve Agent driven by Router.
+    """
+
+    def should_use_agent(self, query: str):
+        """
+        return should use agent
+
+        :param query:
+        :return:
+        """
+        return True
+
+    def plan(
+        self,
+        intermediate_steps: List[Tuple[AgentAction, str]],
+        callbacks: Callbacks = None,
+        **kwargs: Any,
+    ) -> Union[AgentAction, AgentFinish]:
+        """Given input, decided what to do.
+
+        Args:
+            intermediate_steps: Steps the LLM has taken to date, along with observations
+            **kwargs: User inputs.
+
+        Returns:
+            Action specifying what tool to use.
+        """
+        if len(self.tools) == 0:
+            return AgentFinish(return_values={"output": ''}, log='')
+        elif len(self.tools) == 1:
+            tool = next(iter(self.tools))
+            tool = cast(DatasetRetrieverTool, tool)
+            rst = tool.run(tool_input={'dataset_id': tool.dataset_id, 'query': kwargs['input']})
+            return AgentFinish(return_values={"output": rst}, log=rst)
+
+        if intermediate_steps:
+            _, observation = intermediate_steps[-1]
+            return AgentFinish(return_values={"output": observation}, log=observation)
+
+        return super().plan(intermediate_steps, callbacks, **kwargs)
+
+    async def aplan(
+            self,
+            intermediate_steps: List[Tuple[AgentAction, str]],
+            callbacks: Callbacks = None,
+            **kwargs: Any,
+    ) -> Union[AgentAction, AgentFinish]:
+        raise NotImplementedError()
+
+    @classmethod
+    def from_llm_and_tools(
+            cls,
+            llm: BaseLanguageModel,
+            tools: Sequence[BaseTool],
+            callback_manager: Optional[BaseCallbackManager] = None,
+            extra_prompt_messages: Optional[List[BaseMessagePromptTemplate]] = None,
+            system_message: Optional[SystemMessage] = SystemMessage(
+                content="You are a helpful AI assistant."
+            ),
+            **kwargs: Any,
+    ) -> BaseSingleActionAgent:
+        return super().from_llm_and_tools(
+            llm=llm,
+            tools=tools,
+            callback_manager=callback_manager,
+            extra_prompt_messages=extra_prompt_messages,
+            system_message=system_message,
+            **kwargs,
+        )

api/core/agent/agent/openai_function_call.py

+from datetime import datetime
+from typing import List, Tuple, Any, Union, Sequence, Optional
+
+import pytz
+from langchain.agents import OpenAIFunctionsAgent, BaseSingleActionAgent
+from langchain.agents.openai_functions_agent.base import _parse_ai_message, \
+    _format_intermediate_steps
+from langchain.callbacks.base import BaseCallbackManager
+from langchain.callbacks.manager import Callbacks
+from langchain.prompts.chat import BaseMessagePromptTemplate
+from langchain.schema import AgentAction, AgentFinish, SystemMessage, BaseLanguageModel
+from langchain.tools import BaseTool
+
+from core.agent.agent.calc_token_mixin import ExceededLLMTokensLimitError
+from core.agent.agent.openai_function_call_summarize_mixin import OpenAIFunctionCallSummarizeMixin
+
+
+class AutoSummarizingOpenAIFunctionCallAgent(OpenAIFunctionsAgent, OpenAIFunctionCallSummarizeMixin):
+
+    @classmethod
+    def from_llm_and_tools(
+            cls,
+            llm: BaseLanguageModel,
+            tools: Sequence[BaseTool],
+            callback_manager: Optional[BaseCallbackManager] = None,
+            extra_prompt_messages: Optional[List[BaseMessagePromptTemplate]] = None,
+            system_message: Optional[SystemMessage] = SystemMessage(
+                content="You are a helpful AI assistant."
+            ),
+            **kwargs: Any,
+    ) -> BaseSingleActionAgent:
+        return super().from_llm_and_tools(
+            llm=llm,
+            tools=tools,
+            callback_manager=callback_manager,
+            extra_prompt_messages=extra_prompt_messages,
+            system_message=cls.get_system_message(),
+            **kwargs,
+        )
+
+    def should_use_agent(self, query: str):
+        """
+        return should use agent
+
+        :param query:
+        :return:
+        """
+        original_max_tokens = self.llm.max_tokens
+        self.llm.max_tokens = 15
+
+        prompt = self.prompt.format_prompt(input=query, agent_scratchpad=[])
+        messages = prompt.to_messages()
+
+        predicted_message = self.llm.predict_messages(
+            messages, functions=self.functions, callbacks=None
+        )
+
+        function_call = predicted_message.additional_kwargs.get("function_call", {})
+
+        self.llm.max_tokens = original_max_tokens
+
+        return True if function_call else False
+
+    def plan(
+            self,
+            intermediate_steps: List[Tuple[AgentAction, str]],
+            callbacks: Callbacks = None,
+            **kwargs: Any,
+    ) -> Union[AgentAction, AgentFinish]:
+        """Given input, decided what to do.
+
+        Args:
+            intermediate_steps: Steps the LLM has taken to date, along with observations
+            **kwargs: User inputs.
+
+        Returns:
+            Action specifying what tool to use.
+        """
+        agent_scratchpad = _format_intermediate_steps(intermediate_steps)
+        selected_inputs = {
+            k: kwargs[k] for k in self.prompt.input_variables if k != "agent_scratchpad"
+        }
+        full_inputs = dict(**selected_inputs, agent_scratchpad=agent_scratchpad)
+        prompt = self.prompt.format_prompt(**full_inputs)
+        messages = prompt.to_messages()
+
+        # summarize messages if rest_tokens < 0
+        try:
+            messages = self.summarize_messages_if_needed(self.llm, messages, functions=self.functions)
+        except ExceededLLMTokensLimitError as e:
+            return AgentFinish(return_values={"output": str(e)}, log=str(e))
+
+        predicted_message = self.llm.predict_messages(
+            messages, functions=self.functions, callbacks=callbacks
+        )
+        agent_decision = _parse_ai_message(predicted_message)
+        return agent_decision
+
+    @classmethod
+    def get_system_message(cls):
+        # get current time
+        current_time = datetime.now()
+        current_timezone = pytz.timezone('UTC')
+        current_time = current_timezone.localize(current_time)
+
+        return SystemMessage(content="You are a helpful AI assistant.\n"
+                                     "Current time: {}\n"
+                                     "Respond directly if appropriate.".format(
+            current_time.strftime("%Y-%m-%d %H:%M:%S %Z%z")))
+
+    def return_stopped_response(
+            self,
+            early_stopping_method: str,
+            intermediate_steps: List[Tuple[AgentAction, str]],
+            **kwargs: Any,
+    ) -> AgentFinish:
+        try:
+            return super().return_stopped_response(early_stopping_method, intermediate_steps, **kwargs)
+        except ValueError:
+            return AgentFinish({"output": "I'm sorry, I don't know how to respond to that."}, "")

api/core/agent/agent/openai_function_call_summarize_mixin.py

+from typing import cast, List
+
+from langchain.chat_models import ChatOpenAI
+from langchain.chat_models.openai import _convert_message_to_dict
+from langchain.memory.summary import SummarizerMixin
+from langchain.schema import SystemMessage, HumanMessage, BaseMessage, AIMessage, BaseLanguageModel
+from pydantic import BaseModel
+
+from core.agent.agent.calc_token_mixin import ExceededLLMTokensLimitError, CalcTokenMixin
+
+
+class OpenAIFunctionCallSummarizeMixin(BaseModel, CalcTokenMixin):
+    moving_summary_buffer: str = ""
+    moving_summary_index: int = 0
+    summary_llm: BaseLanguageModel
+
+    def summarize_messages_if_needed(self, llm: BaseLanguageModel, messages: List[BaseMessage], **kwargs) -> List[BaseMessage]:
+        # calculate rest tokens and summarize previous function observation messages if rest_tokens < 0
+        rest_tokens = self.get_message_rest_tokens(llm, messages, **kwargs)
+        rest_tokens = rest_tokens - 20  # to deal with the inaccuracy of rest_tokens
+        if rest_tokens >= 0:
+            return messages
+
+        system_message = None
+        human_message = None
+        should_summary_messages = []
+        for message in messages:
+            if isinstance(message, SystemMessage):
+                system_message = message
+            elif isinstance(message, HumanMessage):
+                human_message = message
+            else:
+                should_summary_messages.append(message)
+
+        if len(should_summary_messages) > 2:
+            ai_message = should_summary_messages[-2]
+            function_message = should_summary_messages[-1]
+            should_summary_messages = should_summary_messages[self.moving_summary_index:-2]
+            self.moving_summary_index = len(should_summary_messages)
+        else:
+            error_msg = "Exceeded LLM tokens limit, stopped."
+            raise ExceededLLMTokensLimitError(error_msg)
+
+        new_messages = [system_message, human_message]
+
+        if self.moving_summary_index == 0:
+            should_summary_messages.insert(0, human_message)
+
+        summary_handler = SummarizerMixin(llm=self.summary_llm)
+        self.moving_summary_buffer = summary_handler.predict_new_summary(
+            messages=should_summary_messages,
+            existing_summary=self.moving_summary_buffer
+        )
+
+        new_messages.append(AIMessage(content=self.moving_summary_buffer))
+        new_messages.append(ai_message)
+        new_messages.append(function_message)
+
+        return new_messages
+
+    def get_num_tokens_from_messages(self, llm: BaseLanguageModel, messages: List[BaseMessage], **kwargs) -> int:
+        """Calculate num tokens for gpt-3.5-turbo and gpt-4 with tiktoken package.
+
+        Official documentation: https://github.com/openai/openai-cookbook/blob/
+        main/examples/How_to_format_inputs_to_ChatGPT_models.ipynb"""
+        llm = cast(ChatOpenAI, llm)
+        model, encoding = llm._get_encoding_model()
+        if model.startswith("gpt-3.5-turbo"):
+            # every message follows <im_start>{role/name}\n{content}<im_end>\n
+            tokens_per_message = 4
+            # if there's a name, the role is omitted
+            tokens_per_name = -1
+        elif model.startswith("gpt-4"):
+            tokens_per_message = 3
+            tokens_per_name = 1
+        else:
+            raise NotImplementedError(
+                f"get_num_tokens_from_messages() is not presently implemented "
+                f"for model {model}."
+                "See https://github.com/openai/openai-python/blob/main/chatml.md for "
+                "information on how messages are converted to tokens."
+            )
+        num_tokens = 0
+        for m in messages:
+            message = _convert_message_to_dict(m)
+            num_tokens += tokens_per_message
+            for key, value in message.items():
+                if key == "function_call":
+                    for f_key, f_value in value.items():
+                        num_tokens += len(encoding.encode(f_key))
+                        num_tokens += len(encoding.encode(f_value))
+                else:
+                    num_tokens += len(encoding.encode(value))
+
+                if key == "name":
+                    num_tokens += tokens_per_name
+        # every reply is primed with <im_start>assistant
+        num_tokens += 3
+
+        if kwargs.get('functions'):
+            for function in kwargs.get('functions'):
+                num_tokens += len(encoding.encode('name'))
+                num_tokens += len(encoding.encode(function.get("name")))
+                num_tokens += len(encoding.encode('description'))
+                num_tokens += len(encoding.encode(function.get("description")))
+                parameters = function.get("parameters")
+                num_tokens += len(encoding.encode('parameters'))
+                if 'title' in parameters:
+                    num_tokens += len(encoding.encode('title'))
+                    num_tokens += len(encoding.encode(parameters.get("title")))
+                num_tokens += len(encoding.encode('type'))
+                num_tokens += len(encoding.encode(parameters.get("type")))
+                if 'properties' in parameters:
+                    num_tokens += len(encoding.encode('properties'))
+                    for key, value in parameters.get('properties').items():
+                        num_tokens += len(encoding.encode(key))
+                        for field_key, field_value in value.items():
+                            num_tokens += len(encoding.encode(field_key))
+                            if field_key == 'enum':
+                                for enum_field in field_value:
+                                    num_tokens += 3
+                                    num_tokens += len(encoding.encode(enum_field))
+                            else:
+                                num_tokens += len(encoding.encode(field_key))
+                                num_tokens += len(encoding.encode(str(field_value)))
+                if 'required' in parameters:
+                    num_tokens += len(encoding.encode('required'))
+                    for required_field in parameters['required']:
+                        num_tokens += 3
+                        num_tokens += len(encoding.encode(required_field))
+
+        return num_tokens

api/core/agent/agent/openai_multi_function_call.py

+from datetime import datetime
+from typing import List, Tuple, Any, Union, Sequence, Optional
+
+import pytz
+from langchain.agents import BaseMultiActionAgent
+from langchain.agents.openai_functions_multi_agent.base import OpenAIMultiFunctionsAgent, _format_intermediate_steps, \
+    _parse_ai_message
+from langchain.callbacks.base import BaseCallbackManager
+from langchain.callbacks.manager import Callbacks
+from langchain.prompts.chat import BaseMessagePromptTemplate
+from langchain.schema import AgentAction, AgentFinish, SystemMessage, BaseLanguageModel
+from langchain.tools import BaseTool
+
+from core.agent.agent.calc_token_mixin import ExceededLLMTokensLimitError
+from core.agent.agent.openai_function_call_summarize_mixin import OpenAIFunctionCallSummarizeMixin
+
+
+class AutoSummarizingOpenMultiAIFunctionCallAgent(OpenAIMultiFunctionsAgent, OpenAIFunctionCallSummarizeMixin):
+
+    @classmethod
+    def from_llm_and_tools(
+            cls,
+            llm: BaseLanguageModel,
+            tools: Sequence[BaseTool],
+            callback_manager: Optional[BaseCallbackManager] = None,
+            extra_prompt_messages: Optional[List[BaseMessagePromptTemplate]] = None,
+            system_message: Optional[SystemMessage] = SystemMessage(
+                content="You are a helpful AI assistant."
+            ),
+            **kwargs: Any,
+    ) -> BaseMultiActionAgent:
+        return super().from_llm_and_tools(
+            llm=llm,
+            tools=tools,
+            callback_manager=callback_manager,
+            extra_prompt_messages=extra_prompt_messages,
+            system_message=cls.get_system_message(),
+            **kwargs,
+        )
+
+    def should_use_agent(self, query: str):
+        """
+        return should use agent
+
+        :param query:
+        :return:
+        """
+        original_max_tokens = self.llm.max_tokens
+        self.llm.max_tokens = 15
+
+        prompt = self.prompt.format_prompt(input=query, agent_scratchpad=[])
+        messages = prompt.to_messages()
+
+        predicted_message = self.llm.predict_messages(
+            messages, functions=self.functions, callbacks=None
+        )
+
+        function_call = predicted_message.additional_kwargs.get("function_call", {})
+
+        self.llm.max_tokens = original_max_tokens
+
+        return True if function_call else False
+
+    def plan(
+            self,
+            intermediate_steps: List[Tuple[AgentAction, str]],
+            callbacks: Callbacks = None,
+            **kwargs: Any,
+    ) -> Union[AgentAction, AgentFinish]:
+        """Given input, decided what to do.
+
+        Args:
+            intermediate_steps: Steps the LLM has taken to date, along with observations
+            **kwargs: User inputs.
+
+        Returns:
+            Action specifying what tool to use.
+        """
+        agent_scratchpad = _format_intermediate_steps(intermediate_steps)
+        selected_inputs = {
+            k: kwargs[k] for k in self.prompt.input_variables if k != "agent_scratchpad"
+        }
+        full_inputs = dict(**selected_inputs, agent_scratchpad=agent_scratchpad)
+        prompt = self.prompt.format_prompt(**full_inputs)
+        messages = prompt.to_messages()
+
+        # summarize messages if rest_tokens < 0
+        try:
+            messages = self.summarize_messages_if_needed(self.llm, messages, functions=self.functions)
+        except ExceededLLMTokensLimitError as e:
+            return AgentFinish(return_values={"output": str(e)}, log=str(e))
+
+        predicted_message = self.llm.predict_messages(
+            messages, functions=self.functions, callbacks=callbacks
+        )
+        agent_decision = _parse_ai_message(predicted_message)
+        return agent_decision
+
+    @classmethod
+    def get_system_message(cls):
+        # get current time
+        current_time = datetime.now()
+        current_timezone = pytz.timezone('UTC')
+        current_time = current_timezone.localize(current_time)
+
+        return SystemMessage(content="You are a helpful AI assistant.\n"
+                                     "Current time: {}\n"
+                                     "Respond directly if appropriate.".format(
+            current_time.strftime("%Y-%m-%d %H:%M:%S %Z%z")))

api/core/agent/agent/output_parser/structured_chat.py

+import json
+import re
+from typing import Union
+
+from langchain.agents.structured_chat.output_parser import StructuredChatOutputParser as LCStructuredChatOutputParser, \
+    logger
+from langchain.schema import AgentAction, AgentFinish, OutputParserException
+
+
+class StructuredChatOutputParser(LCStructuredChatOutputParser):
+    def parse(self, text: str) -> Union[AgentAction, AgentFinish]:
+        try:
+            action_match = re.search(r"```(.*?)\n(.*?)```?", text, re.DOTALL)
+            if action_match is not None:
+                response = json.loads(action_match.group(2).strip(), strict=False)
+                if isinstance(response, list):
+                    # gpt turbo frequently ignores the directive to emit a single action
+                    logger.warning("Got multiple action responses: %s", response)
+                    response = response[0]
+                if response["action"] == "Final Answer":
+                    return AgentFinish({"output": response["action_input"]}, text)
+                else:
+                    return AgentAction(
+                        response["action"], response.get("action_input", {}), text
+                    )
+            else:
+                return AgentFinish({"output": text}, text)
+        except Exception as e:
+            raise OutputParserException(f"Could not parse LLM output: {text}") from e

api/core/agent/agent/structured_chat.py

+import re
+from typing import List, Tuple, Any, Union, Sequence, Optional
+
+from langchain import BasePromptTemplate
+from langchain.agents import StructuredChatAgent, AgentOutputParser, Agent
+from langchain.agents.structured_chat.base import HUMAN_MESSAGE_TEMPLATE
+from langchain.base_language import BaseLanguageModel
+from langchain.callbacks.base import BaseCallbackManager
+from langchain.callbacks.manager import Callbacks
+from langchain.memory.summary import SummarizerMixin
+from langchain.prompts import SystemMessagePromptTemplate, HumanMessagePromptTemplate, ChatPromptTemplate
+from langchain.schema import AgentAction, AgentFinish, AIMessage, HumanMessage
+from langchain.tools import BaseTool
+from langchain.agents.structured_chat.prompt import PREFIX, SUFFIX
+
+from core.agent.agent.calc_token_mixin import CalcTokenMixin, ExceededLLMTokensLimitError
+
+
+FORMAT_INSTRUCTIONS = """Use a json blob to specify a tool by providing an action key (tool name) and an action_input key (tool input).
+The nouns in the format of "Thought", "Action", "Action Input", "Final Answer" must be expressed in English.
+Valid "action" values: "Final Answer" or {tool_names}
+
+Provide only ONE action per $JSON_BLOB, as shown:
+
+```
+{{{{
+  "action": $TOOL_NAME,
+  "action_input": $INPUT
+}}}}
+```
+
+Follow this format:
+
+Question: input question to answer
+Thought: consider previous and subsequent steps
+Action:
+```
+$JSON_BLOB
+```
+Observation: action result
+... (repeat Thought/Action/Observation N times)
+Thought: I know what to respond
+Action:
+```
+{{{{
+  "action": "Final Answer",
+  "action_input": "Final response to human"
+}}}}
+```"""
+
+
+class AutoSummarizingStructuredChatAgent(StructuredChatAgent, CalcTokenMixin):
+    moving_summary_buffer: str = ""
+    moving_summary_index: int = 0
+    summary_llm: BaseLanguageModel
+
+    def should_use_agent(self, query: str):
+        """
+        return should use agent
+        Using the ReACT mode to determine whether an agent is needed is costly,
+        so it's better to just use an Agent for reasoning, which is cheaper.
+
+        :param query:
+        :return:
+        """
+        return True
+
+    def plan(
+        self,
+        intermediate_steps: List[Tuple[AgentAction, str]],
+        callbacks: Callbacks = None,
+        **kwargs: Any,
+    ) -> Union[AgentAction, AgentFinish]:
+        """Given input, decided what to do.
+
+        Args:
+            intermediate_steps: Steps the LLM has taken to date,
+                along with observations
+            callbacks: Callbacks to run.
+            **kwargs: User inputs.
+
+        Returns:
+            Action specifying what tool to use.
+        """
+        full_inputs = self.get_full_inputs(intermediate_steps, **kwargs)
+
+        prompts, _ = self.llm_chain.prep_prompts(input_list=[self.llm_chain.prep_inputs(full_inputs)])
+        messages = []
+        if prompts:
+            messages = prompts[0].to_messages()
+
+        rest_tokens = self.get_message_rest_tokens(self.llm_chain.llm, messages)
+        if rest_tokens < 0:
+            full_inputs = self.summarize_messages(intermediate_steps, **kwargs)
+
+        full_output = self.llm_chain.predict(callbacks=callbacks, **full_inputs)
+        return self.output_parser.parse(full_output)
+
+    def summarize_messages(self, intermediate_steps: List[Tuple[AgentAction, str]], **kwargs):
+        if len(intermediate_steps) >= 2:
+            should_summary_intermediate_steps = intermediate_steps[self.moving_summary_index:-1]
+            should_summary_messages = [AIMessage(content=observation)
+                                       for _, observation in should_summary_intermediate_steps]
+            if self.moving_summary_index == 0:
+                should_summary_messages.insert(0, HumanMessage(content=kwargs.get("input")))
+
+            self.moving_summary_index = len(intermediate_steps)
+        else:
+            error_msg = "Exceeded LLM tokens limit, stopped."
+            raise ExceededLLMTokensLimitError(error_msg)
+
+        summary_handler = SummarizerMixin(llm=self.summary_llm)
+        if self.moving_summary_buffer and 'chat_history' in kwargs:
+            kwargs["chat_history"].pop()
+
+        self.moving_summary_buffer = summary_handler.predict_new_summary(
+            messages=should_summary_messages,
+            existing_summary=self.moving_summary_buffer
+        )
+
+        if 'chat_history' in kwargs:
+            kwargs["chat_history"].append(AIMessage(content=self.moving_summary_buffer))
+
+        return self.get_full_inputs([intermediate_steps[-1]], **kwargs)
+
+    @classmethod
+    def create_prompt(
+            cls,
+            tools: Sequence[BaseTool],
+            prefix: str = PREFIX,
+            suffix: str = SUFFIX,
+            human_message_template: str = HUMAN_MESSAGE_TEMPLATE,
+            format_instructions: str = FORMAT_INSTRUCTIONS,
+            input_variables: Optional[List[str]] = None,
+            memory_prompts: Optional[List[BasePromptTemplate]] = None,
+    ) -> BasePromptTemplate:
+        tool_strings = []
+        for tool in tools:
+            args_schema = re.sub("}", "}}}}", re.sub("{", "{{{{", str(tool.args)))
+            tool_strings.append(f"{tool.name}: {tool.description}, args: {args_schema}")
+        formatted_tools = "\n".join(tool_strings)
+        tool_names = ", ".join([('"' + tool.name + '"') for tool in tools])
+        format_instructions = format_instructions.format(tool_names=tool_names)
+        template = "\n\n".join([prefix, formatted_tools, format_instructions, suffix])
+        if input_variables is None:
+            input_variables = ["input", "agent_scratchpad"]
+        _memory_prompts = memory_prompts or []
+        messages = [
+            SystemMessagePromptTemplate.from_template(template),
+            *_memory_prompts,
+            HumanMessagePromptTemplate.from_template(human_message_template),
+        ]
+        return ChatPromptTemplate(input_variables=input_variables, messages=messages)
+
+    @classmethod
+    def from_llm_and_tools(
+            cls,
+            llm: BaseLanguageModel,
+            tools: Sequence[BaseTool],
+            callback_manager: Optional[BaseCallbackManager] = None,
+            output_parser: Optional[AgentOutputParser] = None,
+            prefix: str = PREFIX,
+            suffix: str = SUFFIX,
+            human_message_template: str = HUMAN_MESSAGE_TEMPLATE,
+            format_instructions: str = FORMAT_INSTRUCTIONS,
+            input_variables: Optional[List[str]] = None,
+            memory_prompts: Optional[List[BasePromptTemplate]] = None,
+            **kwargs: Any,
+    ) -> Agent:
+        return super().from_llm_and_tools(
+            llm=llm,
+            tools=tools,
+            callback_manager=callback_manager,
+            output_parser=output_parser,
+            prefix=prefix,
+            suffix=suffix,
+            human_message_template=human_message_template,
+            format_instructions=format_instructions,
+            input_variables=input_variables,
+            memory_prompts=memory_prompts,
+            **kwargs,
+        )

api/core/agent/agent_builder.py

-from typing import Optional
-
-from langchain import LLMChain
-from langchain.agents import ZeroShotAgent, AgentExecutor, ConversationalAgent
-from langchain.callbacks.manager import CallbackManager
-from langchain.memory.chat_memory import BaseChatMemory
-
-from core.callback_handler.agent_loop_gather_callback_handler import AgentLoopGatherCallbackHandler
-from core.callback_handler.dataset_tool_callback_handler import DatasetToolCallbackHandler
-from core.callback_handler.std_out_callback_handler import DifyStdOutCallbackHandler
-from core.llm.llm_builder import LLMBuilder
-
-
-class AgentBuilder:
-    @classmethod
-    def to_agent_chain(cls, tenant_id: str, tools, memory: Optional[BaseChatMemory],
-                       dataset_tool_callback_handler: DatasetToolCallbackHandler,
-                       agent_loop_gather_callback_handler: AgentLoopGatherCallbackHandler):
-        llm = LLMBuilder.to_llm(
-            tenant_id=tenant_id,
-            model_name=agent_loop_gather_callback_handler.model_name,
-            temperature=0,
-            max_tokens=1024,
-            callbacks=[agent_loop_gather_callback_handler, DifyStdOutCallbackHandler()]
-        )
-
-        for tool in tools:
-            tool.callbacks = [
-                agent_loop_gather_callback_handler,
-                dataset_tool_callback_handler,
-                DifyStdOutCallbackHandler()
-            ]
-
-        prompt = cls.build_agent_prompt_template(
-            tools=tools,
-            memory=memory,
-        )
-
-        agent_llm_chain = LLMChain(
-            llm=llm,
-            prompt=prompt,
-        )
-
-        agent = cls.build_agent(agent_llm_chain=agent_llm_chain, memory=memory)
-
-        agent_callback_manager = CallbackManager(
-            [agent_loop_gather_callback_handler, DifyStdOutCallbackHandler()]
-        )
-
-        agent_chain = AgentExecutor.from_agent_and_tools(
-            tools=tools,
-            agent=agent,
-            memory=memory,
-            callbacks=agent_callback_manager,
-            max_iterations=6,
-            early_stopping_method="generate",
-            # `generate` will continue to complete the last inference after reaching the iteration limit or request time limit
-        )
-
-        return agent_chain
-
-    @classmethod
-    def build_agent_prompt_template(cls, tools, memory: Optional[BaseChatMemory]):
-        if memory:
-            prompt = ConversationalAgent.create_prompt(
-                tools=tools,
-            )
-        else:
-            prompt = ZeroShotAgent.create_prompt(
-                tools=tools,
-            )
-
-        return prompt
-
-    @classmethod
-    def build_agent(cls, agent_llm_chain: LLMChain, memory: Optional[BaseChatMemory]):
-        if memory:
-            agent = ConversationalAgent(
-                llm_chain=agent_llm_chain
-            )
-        else:
-            agent = ZeroShotAgent(
-                llm_chain=agent_llm_chain
-            )
-
-        return agent

api/core/agent/agent_executor.py

+import enum
+import logging
+from typing import Union, Optional
+
+from langchain.agents import BaseSingleActionAgent, BaseMultiActionAgent
+from langchain.base_language import BaseLanguageModel
+from langchain.callbacks.manager import Callbacks
+from langchain.memory.chat_memory import BaseChatMemory
+from langchain.tools import BaseTool
+from pydantic import BaseModel, Extra
+
+from core.agent.agent.multi_dataset_router_agent import MultiDatasetRouterAgent
+from core.agent.agent.openai_function_call import AutoSummarizingOpenAIFunctionCallAgent
+from core.agent.agent.openai_multi_function_call import AutoSummarizingOpenMultiAIFunctionCallAgent
+from core.agent.agent.output_parser.structured_chat import StructuredChatOutputParser
+from core.agent.agent.structured_chat import AutoSummarizingStructuredChatAgent
+from langchain.agents import AgentExecutor as LCAgentExecutor
+
+from core.tool.dataset_retriever_tool import DatasetRetrieverTool
+
+
+class PlanningStrategy(str, enum.Enum):
+    ROUTER = 'router'
+    REACT = 'react'
+    FUNCTION_CALL = 'function_call'
+    MULTI_FUNCTION_CALL = 'multi_function_call'
+
+
+class AgentConfiguration(BaseModel):
+    strategy: PlanningStrategy
+    llm: BaseLanguageModel
+    tools: list[BaseTool]
+    summary_llm: BaseLanguageModel
+    dataset_llm: BaseLanguageModel
+    memory: Optional[BaseChatMemory] = None
+    callbacks: Callbacks = None
+    max_iterations: int = 6
+    max_execution_time: Optional[float] = None
+    early_stopping_method: str = "generate"
+    # `generate` will continue to complete the last inference after reaching the iteration limit or request time limit
+
+    class Config:
+        """Configuration for this pydantic object."""
+
+        extra = Extra.forbid
+        arbitrary_types_allowed = True
+
+
+class AgentExecuteResult(BaseModel):
+    strategy: PlanningStrategy
+    output: Optional[str]
+    configuration: AgentConfiguration
+
+
+class AgentExecutor:
+    def __init__(self, configuration: AgentConfiguration):
+        self.configuration = configuration
+        self.agent = self._init_agent()
+
+    def _init_agent(self) -> Union[BaseSingleActionAgent | BaseMultiActionAgent]:
+        if self.configuration.strategy == PlanningStrategy.REACT:
+            agent = AutoSummarizingStructuredChatAgent.from_llm_and_tools(
+                llm=self.configuration.llm,
+                tools=self.configuration.tools,
+                output_parser=StructuredChatOutputParser(),
+                summary_llm=self.configuration.summary_llm,
+                verbose=True
+            )
+        elif self.configuration.strategy == PlanningStrategy.FUNCTION_CALL:
+            agent = AutoSummarizingOpenAIFunctionCallAgent.from_llm_and_tools(
+                llm=self.configuration.llm,
+                tools=self.configuration.tools,
+                extra_prompt_messages=self.configuration.memory.buffer if self.configuration.memory else None,  # used for read chat histories memory
+                summary_llm=self.configuration.summary_llm,
+                verbose=True
+            )
+        elif self.configuration.strategy == PlanningStrategy.MULTI_FUNCTION_CALL:
+            agent = AutoSummarizingOpenMultiAIFunctionCallAgent.from_llm_and_tools(
+                llm=self.configuration.llm,
+                tools=self.configuration.tools,
+                extra_prompt_messages=self.configuration.memory.buffer if self.configuration.memory else None,  # used for read chat histories memory
+                summary_llm=self.configuration.summary_llm,
+                verbose=True
+            )
+        elif self.configuration.strategy == PlanningStrategy.ROUTER:
+            self.configuration.tools = [t for t in self.configuration.tools if isinstance(t, DatasetRetrieverTool)]
+            agent = MultiDatasetRouterAgent.from_llm_and_tools(
+                llm=self.configuration.dataset_llm,
+                tools=self.configuration.tools,
+                extra_prompt_messages=self.configuration.memory.buffer if self.configuration.memory else None,
+                verbose=True
+            )
+        else:
+            raise NotImplementedError(f"Unknown Agent Strategy: {self.configuration.strategy}")
+
+        return agent
+
+    def should_use_agent(self, query: str) -> bool:
+        return self.agent.should_use_agent(query)
+
+    def run(self, query: str) -> AgentExecuteResult:
+        agent_executor = LCAgentExecutor.from_agent_and_tools(
+            agent=self.agent,
+            tools=self.configuration.tools,
+            memory=self.configuration.memory,
+            max_iterations=self.configuration.max_iterations,
+            max_execution_time=self.configuration.max_execution_time,
+            early_stopping_method=self.configuration.early_stopping_method,
+            callbacks=self.configuration.callbacks
+        )
+
+        try:
+            output = agent_executor.run(query)
+        except Exception:
+            logging.exception("agent_executor run failed")
+            output = None
+
+        return AgentExecuteResult(
+            output=output,
+            strategy=self.configuration.strategy,
+            configuration=self.configuration
+        )

api/core/callback_handler/agent_loop_gather_callback_handler.py

+import json
 import logging
 import time
 
 from typing import Any, Dict, List, Union, Optional
 
+from langchain.agents import openai_functions_agent, openai_functions_multi_agent
 from langchain.callbacks.base import BaseCallbackHandler
-from langchain.schema import AgentAction, AgentFinish, LLMResult
+from langchain.schema import AgentAction, AgentFinish, LLMResult, ChatGeneration
 
 from core.callback_handler.entity.agent_loop import AgentLoop
 from core.conversation_message_task import ConversationMessageTask
@@ -20,6 +22,7 @@ class AgentLoopGatherCallbackHandler(BaseCallbackHandler):
         self.conversation_message_task = conversation_message_task
         self._agent_loops = []
         self._current_loop = None
+        self._message_agent_thought = None
         self.current_chain = None
 
     @property
@@ -29,6 +32,7 @@ class AgentLoopGatherCallbackHandler(BaseCallbackHandler):
     def clear_agent_loops(self) -> None:
         self._agent_loops = []
         self._current_loop = None
+        self._message_agent_thought = None
 
     @property
     def always_verbose(self) -> bool:
@@ -61,8 +65,20 @@ class AgentLoopGatherCallbackHandler(BaseCallbackHandler):
         # kwargs={}
         if self._current_loop and self._current_loop.status == 'llm_started':
             self._current_loop.status = 'llm_end'
+            if response.llm_output:
                 self._current_loop.prompt_tokens = response.llm_output['token_usage']['prompt_tokens']
+            completion_generation = response.generations[0][0]
+            if isinstance(completion_generation, ChatGeneration):
+                completion_message = completion_generation.message
+                if 'function_call' in completion_message.additional_kwargs:
+                    self._current_loop.completion \
+                        = json.dumps({'function_call': completion_message.additional_kwargs['function_call']})
+                else:
                     self._current_loop.completion = response.generations[0][0].text
+            else:
+                self._current_loop.completion = completion_generation.text
+
+            if response.llm_output:
                 self._current_loop.completion_tokens = response.llm_output['token_usage']['completion_tokens']
 
     def on_llm_error(
@@ -71,6 +87,7 @@ class AgentLoopGatherCallbackHandler(BaseCallbackHandler):
         logging.error(error)
         self._agent_loops = []
         self._current_loop = None
+        self._message_agent_thought = None
 
     def on_tool_start(
         self,
@@ -89,8 +106,15 @@ class AgentLoopGatherCallbackHandler(BaseCallbackHandler):
     ) -> Any:
         """Run on agent action."""
         tool = action.tool
-        tool_input = action.tool_input
-        action_name_position = action.log.index("\nAction:") + 1 if action.log else -1
+        tool_input = json.dumps({"query": action.tool_input}
+                                if isinstance(action.tool_input, str) else action.tool_input)
+        completion = None
+        if isinstance(action, openai_functions_agent.base._FunctionsAgentAction) \
+                or isinstance(action, openai_functions_multi_agent.base._FunctionsAgentAction):
+            thought = action.log.strip()
+            completion = json.dumps({'function_call': action.message_log[0].additional_kwargs['function_call']})
+        else:
+            action_name_position = action.log.index("Action:") if action.log else -1
             thought = action.log[:action_name_position].strip() if action.log else ''
 
         if self._current_loop and self._current_loop.status == 'llm_end':
@@ -98,6 +122,13 @@ class AgentLoopGatherCallbackHandler(BaseCallbackHandler):
             self._current_loop.thought = thought
             self._current_loop.tool_name = tool
             self._current_loop.tool_input = tool_input
+            if completion is not None:
+                self._current_loop.completion = completion
+
+            self._message_agent_thought = self.conversation_message_task.on_agent_start(
+                self.current_chain,
+                self._current_loop
+            )
 
     def on_tool_end(
         self,
@@ -120,10 +151,13 @@ class AgentLoopGatherCallbackHandler(BaseCallbackHandler):
             self._current_loop.completed_at = time.perf_counter()
             self._current_loop.latency = self._current_loop.completed_at - self._current_loop.started_at
 
-            self.conversation_message_task.on_agent_end(self.current_chain, self.model_name, self._current_loop)
+            self.conversation_message_task.on_agent_end(
+                self._message_agent_thought, self.model_name, self._current_loop
+            )
 
             self._agent_loops.append(self._current_loop)
             self._current_loop = None
+            self._message_agent_thought = None
 
     def on_tool_error(
         self, error: Union[Exception, KeyboardInterrupt], **kwargs: Any
@@ -132,6 +166,7 @@ class AgentLoopGatherCallbackHandler(BaseCallbackHandler):
         logging.error(error)
         self._agent_loops = []
         self._current_loop = None
+        self._message_agent_thought = None
 
     def on_agent_finish(self, finish: AgentFinish, **kwargs: Any) -> Any:
         """Run on agent end."""
@@ -141,10 +176,18 @@ class AgentLoopGatherCallbackHandler(BaseCallbackHandler):
             self._current_loop.completed = True
             self._current_loop.completed_at = time.perf_counter()
             self._current_loop.latency = self._current_loop.completed_at - self._current_loop.started_at
+            self._current_loop.thought = '[DONE]'
+            self._message_agent_thought = self.conversation_message_task.on_agent_start(
+                self.current_chain,
+                self._current_loop
+            )
 
-            self.conversation_message_task.on_agent_end(self.current_chain, self.model_name, self._current_loop)
+            self.conversation_message_task.on_agent_end(
+                self._message_agent_thought, self.model_name, self._current_loop
+            )
 
             self._agent_loops.append(self._current_loop)
             self._current_loop = None
+            self._message_agent_thought = None
         elif not self._current_loop and self._agent_loops:
             self._agent_loops[-1].status = 'agent_finish'

api/core/callback_handler/dataset_tool_callback_handler.py

+import json
 import logging
 
 from typing import Any, Dict, List, Union, Optional
@@ -43,9 +44,11 @@ class DatasetToolCallbackHandler(BaseCallbackHandler):
         input_str: str,
         **kwargs: Any,
     ) -> None:
-        tool_name = serialized.get('name')
-        dataset_id = tool_name[len("dataset-"):]
-        self.conversation_message_task.on_dataset_query_end(DatasetQueryObj(dataset_id=dataset_id, query=input_str))
+        # tool_name = serialized.get('name')
+        input_dict = json.loads(input_str.replace("'", "\""))
+        dataset_id = input_dict.get('dataset_id')
+        query = input_dict.get('query')
+        self.conversation_message_task.on_dataset_query_end(DatasetQueryObj(dataset_id=dataset_id, query=query))
 
     def on_tool_end(
         self,

api/core/callback_handler/entity/agent_loop.py

@@ -10,9 +10,9 @@ class AgentLoop(BaseModel):
     tool_output: str = None
 
     prompt: str = None
-    prompt_tokens: int = None
+    prompt_tokens: int = 0
     completion: str = None
-    completion_tokens: int = None
+    completion_tokens: int = 0
 
     latency: float = None
 

api/core/callback_handler/llm_callback_handler.py

 import logging
 import time
-from typing import Any, Dict, List, Union, Optional
+from typing import Any, Dict, List, Union
 
 from langchain.callbacks.base import BaseCallbackHandler
-from langchain.schema import AgentAction, AgentFinish, LLMResult, HumanMessage, AIMessage, SystemMessage, BaseMessage
+from langchain.schema import LLMResult, BaseMessage, BaseLanguageModel
 
 from core.callback_handler.entity.llm_message import LLMMessage
 from core.conversation_message_task import ConversationMessageTask, ConversationTaskStoppedException
-from core.llm.streamable_chat_open_ai import StreamableChatOpenAI
-from core.llm.streamable_open_ai import StreamableOpenAI
 
 
 class LLMCallbackHandler(BaseCallbackHandler):
     raise_error: bool = True
 
-    def __init__(self, llm: Union[StreamableOpenAI, StreamableChatOpenAI],
+    def __init__(self, llm: BaseLanguageModel,
                  conversation_message_task: ConversationMessageTask):
         self.llm = llm
         self.llm_message = LLMMessage()

api/core/callback_handler/main_chain_gather_callback_handler.py

@@ -20,15 +20,13 @@ class MainChainGatherCallbackHandler(BaseCallbackHandler):
         self._current_chain_result = None
         self._current_chain_message = None
         self.conversation_message_task = conversation_message_task
-        self.agent_loop_gather_callback_handler = AgentLoopGatherCallbackHandler(
-            llm_constant.agent_model_name,
-            conversation_message_task
-        )
+        self.agent_callback = None
 
     def clear_chain_results(self) -> None:
         self._current_chain_result = None
         self._current_chain_message = None
-        self.agent_loop_gather_callback_handler.current_chain = None
+        if self.agent_callback:
+            self.agent_callback.current_chain = None
 
     @property
     def always_verbose(self) -> bool:
@@ -58,7 +56,8 @@ class MainChainGatherCallbackHandler(BaseCallbackHandler):
                     started_at=time.perf_counter()
                 )
                 self._current_chain_message = self.conversation_message_task.init_chain(self._current_chain_result)
-                self.agent_loop_gather_callback_handler.current_chain = self._current_chain_message
+                if self.agent_callback:
+                    self.agent_callback.current_chain = self._current_chain_message
 
     def on_chain_end(self, outputs: Dict[str, Any], **kwargs: Any) -> None:
         """Print out that we finished a chain."""

api/core/chain/chain_builder.py

-from typing import Optional
-
-from core.callback_handler.std_out_callback_handler import DifyStdOutCallbackHandler
-from core.chain.sensitive_word_avoidance_chain import SensitiveWordAvoidanceChain
-from core.chain.tool_chain import ToolChain
-
-
-class ChainBuilder:
-    @classmethod
-    def to_tool_chain(cls, tool, **kwargs) -> ToolChain:
-        return ToolChain(
-            tool=tool,
-            input_key=kwargs.get('input_key', 'input'),
-            output_key=kwargs.get('output_key', 'tool_output'),
-            callbacks=[DifyStdOutCallbackHandler()]
-        )
-
-    @classmethod
-    def to_sensitive_word_avoidance_chain(cls, tool_config: dict, **kwargs) -> Optional[
-        SensitiveWordAvoidanceChain]:
-        sensitive_words = tool_config.get("words", "")
-        if tool_config.get("enabled", False) \
-                and sensitive_words:
-            return SensitiveWordAvoidanceChain(
-                sensitive_words=sensitive_words.split(","),
-                canned_response=tool_config.get("canned_response", ''),
-                output_key="sensitive_word_avoidance_output",
-                callbacks=[DifyStdOutCallbackHandler()],
-                **kwargs
-            )
-
-        return None

api/core/chain/llm_router_chain.py

-"""Base classes for LLM-powered router chains."""
-from __future__ import annotations
-
-from typing import Any, Dict, List, Optional, Type, cast, NamedTuple
-
-from langchain.base_language import BaseLanguageModel
-from langchain.callbacks.manager import CallbackManagerForChainRun
-from langchain.chains.base import Chain
-from pydantic import root_validator
-
-from langchain.chains import LLMChain
-from langchain.prompts import BasePromptTemplate
-from langchain.schema import BaseOutputParser, OutputParserException
-
-from libs.json_in_md_parser import parse_and_check_json_markdown
-
-
-class Route(NamedTuple):
-    destination: Optional[str]
-    next_inputs: Dict[str, Any]
-
-
-class LLMRouterChain(Chain):
-    """A router chain that uses an LLM chain to perform routing."""
-
-    llm_chain: LLMChain
-    """LLM chain used to perform routing"""
-
-    @root_validator()
-    def validate_prompt(cls, values: dict) -> dict:
-        prompt = values["llm_chain"].prompt
-        if prompt.output_parser is None:
-            raise ValueError(
-                "LLMRouterChain requires base llm_chain prompt to have an output"
-                " parser that converts LLM text output to a dictionary with keys"
-                " 'destination' and 'next_inputs'. Received a prompt with no output"
-                " parser."
-            )
-        return values
-
-    @property
-    def input_keys(self) -> List[str]:
-        """Will be whatever keys the LLM chain prompt expects.
-
-        :meta private:
-        """
-        return self.llm_chain.input_keys
-
-    def _validate_outputs(self, outputs: Dict[str, Any]) -> None:
-        super()._validate_outputs(outputs)
-        if not isinstance(outputs["next_inputs"], dict):
-            raise ValueError
-
-    def _call(
-            self,
-            inputs: Dict[str, Any],
-            run_manager: Optional[CallbackManagerForChainRun] = None,
-    ) -> Dict[str, Any]:
-        output = cast(
-            Dict[str, Any],
-            self.llm_chain.predict_and_parse(**inputs),
-        )
-        return output
-
-    @classmethod
-    def from_llm(
-        cls, llm: BaseLanguageModel, prompt: BasePromptTemplate, **kwargs: Any
-    ) -> LLMRouterChain:
-        """Convenience constructor."""
-        llm_chain = LLMChain(llm=llm, prompt=prompt)
-        return cls(llm_chain=llm_chain, **kwargs)
-
-    @property
-    def output_keys(self) -> List[str]:
-        return ["destination", "next_inputs"]
-
-    def route(self, inputs: Dict[str, Any]) -> Route:
-        result = self(inputs)
-        return Route(result["destination"], result["next_inputs"])
-
-
-class RouterOutputParser(BaseOutputParser[Dict[str, str]]):
-    """Parser for output of router chain int he multi-prompt chain."""
-
-    default_destination: str = "DEFAULT"
-    next_inputs_type: Type = str
-    next_inputs_inner_key: str = "input"
-
-    def parse(self, text: str) -> Dict[str, Any]:
-        try:
-            expected_keys = ["destination", "next_inputs"]
-            parsed = parse_and_check_json_markdown(text, expected_keys)
-            if not isinstance(parsed["destination"], str):
-                raise ValueError("Expected 'destination' to be a string.")
-            if not isinstance(parsed["next_inputs"], self.next_inputs_type):
-                raise ValueError(
-                    f"Expected 'next_inputs' to be {self.next_inputs_type}."
-                )
-            parsed["next_inputs"] = {self.next_inputs_inner_key: parsed["next_inputs"]}
-            if (
-                parsed["destination"].strip().lower()
-                == self.default_destination.lower()
-            ):
-                parsed["destination"] = None
-            else:
-                parsed["destination"] = parsed["destination"].strip()
-            return parsed
-        except Exception as e:
-            raise OutputParserException(
-                f"Parsing text\n{text}\n of llm router raised following error:\n{e}"
-            )

api/core/chain/main_chain_builder.py

-from typing import Optional, List, cast
-
-from langchain.chains import SequentialChain
-from langchain.chains.base import Chain
-from langchain.memory.chat_memory import BaseChatMemory
-
-from core.callback_handler.main_chain_gather_callback_handler import MainChainGatherCallbackHandler
-from core.callback_handler.std_out_callback_handler import DifyStdOutCallbackHandler
-from core.chain.chain_builder import ChainBuilder
-from core.chain.multi_dataset_router_chain import MultiDatasetRouterChain
-from core.conversation_message_task import ConversationMessageTask
-from extensions.ext_database import db
-from models.dataset import Dataset
-
-
-class MainChainBuilder:
-    @classmethod
-    def to_langchain_components(cls, tenant_id: str, agent_mode: dict, memory: Optional[BaseChatMemory],
-                                rest_tokens: int,
-                                conversation_message_task: ConversationMessageTask):
-        first_input_key = "input"
-        final_output_key = "output"
-
-        chains = []
-
-        chain_callback_handler = MainChainGatherCallbackHandler(conversation_message_task)
-
-        # agent mode
-        tool_chains, chains_output_key = cls.get_agent_chains(
-            tenant_id=tenant_id,
-            agent_mode=agent_mode,
-            rest_tokens=rest_tokens,
-            memory=memory,
-            conversation_message_task=conversation_message_task
-        )
-        chains += tool_chains
-
-        if chains_output_key:
-            final_output_key = chains_output_key
-
-        if len(chains) == 0:
-            return None
-
-        for chain in chains:
-            chain = cast(Chain, chain)
-            chain.callbacks.append(chain_callback_handler)
-
-        # build main chain
-        overall_chain = SequentialChain(
-            chains=chains,
-            input_variables=[first_input_key],
-            output_variables=[final_output_key],
-            memory=memory,  # only for use the memory prompt input key
-        )
-
-        return overall_chain
-
-    @classmethod
-    def get_agent_chains(cls, tenant_id: str, agent_mode: dict,
-                         rest_tokens: int,
-                         memory: Optional[BaseChatMemory],
-                         conversation_message_task: ConversationMessageTask):
-        # agent mode
-        chains = []
-        if agent_mode and agent_mode.get('enabled'):
-            tools = agent_mode.get('tools', [])
-
-            pre_fixed_chains = []
-            # agent_tools = []
-            datasets = []
-            for tool in tools:
-                tool_type = list(tool.keys())[0]
-                tool_config = list(tool.values())[0]
-                if tool_type == 'sensitive-word-avoidance':
-                    chain = ChainBuilder.to_sensitive_word_avoidance_chain(tool_config)
-                    if chain:
-                        pre_fixed_chains.append(chain)
-                elif tool_type == "dataset":
-                    # get dataset from dataset id
-                    dataset = db.session.query(Dataset).filter(
-                        Dataset.tenant_id == tenant_id,
-                        Dataset.id == tool_config.get("id")
-                    ).first()
-
-                    if dataset:
-                        datasets.append(dataset)
-
-            # add pre-fixed chains
-            chains += pre_fixed_chains
-
-            if len(datasets) > 0:
-                # tool to chain
-                multi_dataset_router_chain = MultiDatasetRouterChain.from_datasets(
-                    tenant_id=tenant_id,
-                    datasets=datasets,
-                    conversation_message_task=conversation_message_task,
-                    rest_tokens=rest_tokens,
-                    callbacks=[DifyStdOutCallbackHandler()]
-                )
-                chains.append(multi_dataset_router_chain)
-
-        final_output_key = cls.get_chains_output_key(chains)
-
-        return chains, final_output_key
-
-    @classmethod
-    def get_chains_output_key(cls, chains: List[Chain]):
-        if len(chains) > 0:
-            return chains[-1].output_keys[0]
-        return None

api/core/chain/multi_dataset_router_chain.py

-import math
-import re
-from typing import Mapping, List, Dict, Any, Optional
-
-from langchain import PromptTemplate
-from langchain.callbacks.manager import CallbackManagerForChainRun
-from langchain.chains.base import Chain
-from pydantic import Extra
-
-from core.callback_handler.dataset_tool_callback_handler import DatasetToolCallbackHandler
-from core.callback_handler.std_out_callback_handler import DifyStdOutCallbackHandler
-from core.chain.llm_router_chain import LLMRouterChain, RouterOutputParser
-from core.conversation_message_task import ConversationMessageTask
-from core.llm.llm_builder import LLMBuilder
-from core.tool.dataset_index_tool import DatasetTool
-from models.dataset import Dataset, DatasetProcessRule
-
-DEFAULT_K = 2
-CONTEXT_TOKENS_PERCENT = 0.3
-MULTI_PROMPT_ROUTER_TEMPLATE = """
-Given a raw text input to a language model select the model prompt best suited for \
-the input. You will be given the names of the available prompts and a description of \
-what the prompt is best suited for. You may also revise the original input if you \
-think that revising it will ultimately lead to a better response from the language \
-model.
-
-<< FORMATTING >>
-Return a markdown code snippet with a JSON object formatted to look like, \
-no any other string out of markdown code snippet:
-```json
-{{{{
-    "destination": string \\ name of the prompt to use or "DEFAULT"
-    "next_inputs": string \\ a potentially modified version of the original input
-}}}}
-```
-
-REMEMBER: "destination" MUST be one of the candidate prompt names specified below OR \
-it can be "DEFAULT" if the input is not well suited for any of the candidate prompts.
-REMEMBER: "next_inputs" can just be the original input if you don't think any \
-modifications are needed.
-
-<< CANDIDATE PROMPTS >>
-{destinations}
-
-<< INPUT >>
-{{input}}
-
-<< OUTPUT >>
-"""
-
-
-class MultiDatasetRouterChain(Chain):
-    """Use a single chain to route an input to one of multiple candidate chains."""
-
-    router_chain: LLMRouterChain
-    """Chain for deciding a destination chain and the input to it."""
-    dataset_tools: Mapping[str, DatasetTool]
-    """Map of name to candidate chains that inputs can be routed to."""
-
-    class Config:
-        """Configuration for this pydantic object."""
-
-        extra = Extra.forbid
-        arbitrary_types_allowed = True
-
-    @property
-    def input_keys(self) -> List[str]:
-        """Will be whatever keys the router chain prompt expects.
-
-        :meta private:
-        """
-        return self.router_chain.input_keys
-
-    @property
-    def output_keys(self) -> List[str]:
-        return ["text"]
-
-    @classmethod
-    def from_datasets(
-            cls,
-            tenant_id: str,
-            datasets: List[Dataset],
-            conversation_message_task: ConversationMessageTask,
-            rest_tokens: int,
-            **kwargs: Any,
-    ):
-        """Convenience constructor for instantiating from destination prompts."""
-        llm = LLMBuilder.to_llm(
-            tenant_id=tenant_id,
-            model_name='gpt-3.5-turbo',
-            temperature=0,
-            max_tokens=1024,
-            callbacks=[DifyStdOutCallbackHandler()]
-        )
-
-        destinations = ["[[{}]]: {}".format(d.id, d.description.replace('\n', ' ') if d.description
-                        else ('useful for when you want to answer queries about the ' + d.name))
-                        for d in datasets]
-        destinations_str = "\n".join(destinations)
-        router_template = MULTI_PROMPT_ROUTER_TEMPLATE.format(
-            destinations=destinations_str
-        )
-
-        router_prompt = PromptTemplate(
-            template=router_template,
-            input_variables=["input"],
-            output_parser=RouterOutputParser(),
-        )
-
-        router_chain = LLMRouterChain.from_llm(llm, router_prompt)
-        dataset_tools = {}
-        for dataset in datasets:
-            # fulfill description when it is empty
-            if dataset.available_document_count == 0 or dataset.available_document_count == 0:
-                continue
-
-            description = dataset.description
-            if not description:
-                description = 'useful for when you want to answer queries about the ' + dataset.name
-
-            k = cls._dynamic_calc_retrieve_k(dataset, rest_tokens)
-            if k == 0:
-                continue
-
-            dataset_tool = DatasetTool(
-                name=f"dataset-{dataset.id}",
-                description=description,
-                k=k,
-                dataset=dataset,
-                callbacks=[DatasetToolCallbackHandler(conversation_message_task), DifyStdOutCallbackHandler()]
-            )
-
-            dataset_tools[str(dataset.id)] = dataset_tool
-
-        return cls(
-            router_chain=router_chain,
-            dataset_tools=dataset_tools,
-            **kwargs,
-        )
-
-    @classmethod
-    def _dynamic_calc_retrieve_k(cls, dataset: Dataset, rest_tokens: int) -> int:
-        processing_rule = dataset.latest_process_rule
-        if not processing_rule:
-            return DEFAULT_K
-
-        if processing_rule.mode == "custom":
-            rules = processing_rule.rules_dict
-            if not rules:
-                return DEFAULT_K
-
-            segmentation = rules["segmentation"]
-            segment_max_tokens = segmentation["max_tokens"]
-        else:
-            segment_max_tokens = DatasetProcessRule.AUTOMATIC_RULES['segmentation']['max_tokens']
-
-        # when rest_tokens is less than default context tokens
-        if rest_tokens < segment_max_tokens * DEFAULT_K:
-            return rest_tokens // segment_max_tokens
-
-        context_limit_tokens = math.floor(rest_tokens * CONTEXT_TOKENS_PERCENT)
-
-        # when context_limit_tokens is less than default context tokens, use default_k
-        if context_limit_tokens <= segment_max_tokens * DEFAULT_K:
-            return DEFAULT_K
-
-        # Expand the k value when there's still some room left in the 30% rest tokens space
-        return context_limit_tokens // segment_max_tokens
-
-    def _call(
-        self,
-        inputs: Dict[str, Any],
-        run_manager: Optional[CallbackManagerForChainRun] = None,
-    ) -> Dict[str, Any]:
-        if len(self.dataset_tools) == 0:
-            return {"text": ''}
-        elif len(self.dataset_tools) == 1:
-            return {"text": next(iter(self.dataset_tools.values())).run(inputs['input'])}
-
-        route = self.router_chain.route(inputs)
-
-        destination = ''
-        if route.destination:
-            pattern = r'\b[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}\b'
-            match = re.search(pattern, route.destination, re.IGNORECASE)
-            if match:
-                destination = match.group()
-
-        if not destination:
-            return {"text": ''}
-        elif destination in self.dataset_tools:
-            return {"text": self.dataset_tools[destination].run(
-                route.next_inputs['input']
-            )}
-        else:
-            raise ValueError(
-                f"Received invalid destination chain name '{destination}'"
-            )

api/core/chain/tool_chain.py

-from typing import List, Dict, Optional, Any
-
-from langchain.callbacks.manager import CallbackManagerForChainRun, AsyncCallbackManagerForChainRun
-from langchain.chains.base import Chain
-from langchain.tools import BaseTool
-
-
-class ToolChain(Chain):
-    input_key: str = "input"  #: :meta private:
-    output_key: str = "output"  #: :meta private:
-
-    tool: BaseTool
-
-    @property
-    def _chain_type(self) -> str:
-        return "tool_chain"
-
-    @property
-    def input_keys(self) -> List[str]:
-        """Expect input key.
-
-        :meta private:
-        """
-        return [self.input_key]
-
-    @property
-    def output_keys(self) -> List[str]:
-        """Return output key.
-
-        :meta private:
-        """
-        return [self.output_key]
-
-    def _call(
-            self,
-            inputs: Dict[str, Any],
-            run_manager: Optional[CallbackManagerForChainRun] = None,
-    ) -> Dict[str, Any]:
-        input = inputs[self.input_key]
-        output = self.tool.run(input, self.verbose)
-        return {self.output_key: output}
-
-    async def _acall(
-            self,
-            inputs: Dict[str, Any],
-            run_manager: Optional[AsyncCallbackManagerForChainRun] = None,
-    ) -> Dict[str, Any]:
-        """Run the logic of this chain and return the output."""
-        input = inputs[self.input_key]
-        output = await self.tool.arun(input, self.verbose)
-        return {self.output_key: output}

api/core/completion.py

 import logging
+import re
 from typing import Optional, List, Union, Tuple
 
 from langchain.base_language import BaseLanguageModel
@@ -8,20 +9,21 @@ from langchain.llms import BaseLLM
 from langchain.schema import BaseMessage, HumanMessage
 from requests.exceptions import ChunkedEncodingError
 
+from core.agent.agent_executor import AgentExecuteResult, PlanningStrategy
+from core.callback_handler.main_chain_gather_callback_handler import MainChainGatherCallbackHandler
 from core.constant import llm_constant
 from core.callback_handler.llm_callback_handler import LLMCallbackHandler
 from core.callback_handler.std_out_callback_handler import DifyStreamingStdOutCallbackHandler, \
     DifyStdOutCallbackHandler
 from core.conversation_message_task import ConversationMessageTask, ConversationTaskStoppedException
 from core.llm.error import LLMBadRequestError
+from core.llm.fake import FakeLLM
 from core.llm.llm_builder import LLMBuilder
-from core.chain.main_chain_builder import MainChainBuilder
 from core.llm.streamable_chat_open_ai import StreamableChatOpenAI
 from core.llm.streamable_open_ai import StreamableOpenAI
 from core.memory.read_only_conversation_token_db_buffer_shared_memory import \
     ReadOnlyConversationTokenDBBufferSharedMemory
-from core.memory.read_only_conversation_token_db_string_buffer_shared_memory import \
-    ReadOnlyConversationTokenDBStringBufferSharedMemory
+from core.orchestrator_rule_parser import OrchestratorRuleParser
 from core.prompt.prompt_builder import PromptBuilder
 from core.prompt.prompt_template import JinjaPromptTemplate
 from core.prompt.prompts import MORE_LIKE_THIS_GENERATE_PROMPT
@@ -69,18 +71,33 @@ class Completion:
             streaming=streaming
         )
 
-        # build main chain include agent
-        main_chain = MainChainBuilder.to_langchain_components(
+        chain_callback = MainChainGatherCallbackHandler(conversation_message_task)
+
+        # init orchestrator rule parser
+        orchestrator_rule_parser = OrchestratorRuleParser(
             tenant_id=app.tenant_id,
-            agent_mode=app_model_config.agent_mode_dict,
+            app_model_config=app_model_config
+        )
+
+        # parse sensitive_word_avoidance_chain
+        sensitive_word_avoidance_chain = orchestrator_rule_parser.to_sensitive_word_avoidance_chain([chain_callback])
+        if sensitive_word_avoidance_chain:
+            query = sensitive_word_avoidance_chain.run(query)
+
+        # get agent executor
+        agent_executor = orchestrator_rule_parser.to_agent_executor(
+            conversation_message_task=conversation_message_task,
+            memory=memory,
             rest_tokens=rest_tokens_for_context_and_memory,
-            memory=ReadOnlyConversationTokenDBStringBufferSharedMemory(memory=memory) if memory else None,
-            conversation_message_task=conversation_message_task
+            chain_callback=chain_callback
         )
 
-        chain_output = ''
-        if main_chain:
-            chain_output = main_chain.run(query)
+        # run agent executor
+        agent_execute_result = None
+        if agent_executor:
+            should_use_agent = agent_executor.should_use_agent(query)
+            if should_use_agent:
+                agent_execute_result = agent_executor.run(query)
 
         # run the final llm
         try:
@@ -90,7 +107,7 @@ class Completion:
                 app_model_config=app_model_config,
                 query=query,
                 inputs=inputs,
-                chain_output=chain_output,
+                agent_execute_result=agent_execute_result,
                 conversation_message_task=conversation_message_task,
                 memory=memory,
                 streaming=streaming
@@ -105,9 +122,20 @@ class Completion:
 
     @classmethod
     def run_final_llm(cls, tenant_id: str, mode: str, app_model_config: AppModelConfig, query: str, inputs: dict,
-                      chain_output: str,
+                      agent_execute_result: Optional[AgentExecuteResult],
                       conversation_message_task: ConversationMessageTask,
                       memory: Optional[ReadOnlyConversationTokenDBBufferSharedMemory], streaming: bool):
+        # When no extra pre prompt is specified,
+        # the output of the agent can be used directly as the main output content without calling LLM again
+        if not app_model_config.pre_prompt and agent_execute_result and agent_execute_result.output \
+                and agent_execute_result.strategy != PlanningStrategy.ROUTER:
+            final_llm = FakeLLM(response=agent_execute_result.output,
+                                origin_llm=agent_execute_result.configuration.llm,
+                                streaming=streaming)
+            final_llm.callbacks = cls.get_llm_callbacks(final_llm, streaming, conversation_message_task)
+            response = final_llm.generate([[HumanMessage(content=query)]])
+            return response
+
         final_llm = LLMBuilder.to_llm_from_model(
             tenant_id=tenant_id,
             model=app_model_config.model_dict,
@@ -122,7 +150,7 @@ class Completion:
             pre_prompt=app_model_config.pre_prompt,
             query=query,
             inputs=inputs,
-            chain_output=chain_output,
+            agent_execute_result=agent_execute_result,
             memory=memory
         )
 
@@ -142,16 +170,9 @@ class Completion:
     @classmethod
     def get_main_llm_prompt(cls, mode: str, llm: BaseLanguageModel, model: dict,
                             pre_prompt: str, query: str, inputs: dict,
-                            chain_output: Optional[str],
+                            agent_execute_result: Optional[AgentExecuteResult],
                             memory: Optional[ReadOnlyConversationTokenDBBufferSharedMemory]) -> \
             Tuple[Union[str | List[BaseMessage]], Optional[List[str]]]:
-        # disable template string in query
-        # query_params = JinjaPromptTemplate.from_template(template=query).input_variables
-        # if query_params:
-        #     for query_param in query_params:
-        #         if query_param not in inputs:
-        #             inputs[query_param] = '{{' + query_param + '}}'
-
         if mode == 'completion':
             prompt_template = JinjaPromptTemplate.from_template(
                 template=("""Use the following context as your learned knowledge, inside <context></context> XML tags.
@@ -165,18 +186,13 @@ When answer to user:
 - If you don't know when you are not sure, ask for clarification. 
 Avoid mentioning that you obtained the information from the context.
 And answer according to the language of the user's question.
-""" if chain_output else "")
+""" if agent_execute_result else "")
                          + (pre_prompt + "\n" if pre_prompt else "")
                          + "{{query}}\n"
             )
 
-            if chain_output:
-                inputs['context'] = chain_output
-                # context_params = JinjaPromptTemplate.from_template(template=chain_output).input_variables
-                # if context_params:
-                #     for context_param in context_params:
-                #         if context_param not in inputs:
-                #             inputs[context_param] = '{{' + context_param + '}}'
+            if agent_execute_result:
+                inputs['context'] = agent_execute_result.output
 
             prompt_inputs = {k: inputs[k] for k in prompt_template.input_variables if k in inputs}
             prompt_content = prompt_template.format(
@@ -206,8 +222,8 @@ And answer according to the language of the user's question.
                 if pre_prompt_inputs:
                     human_inputs.update(pre_prompt_inputs)
 
-            if chain_output:
-                human_inputs['context'] = chain_output
+            if agent_execute_result:
+                human_inputs['context'] = agent_execute_result.output
                 human_message_prompt += """Use the following context as your learned knowledge, inside <context></context> XML tags.
 
 <context>
@@ -240,18 +256,10 @@ And answer according to the language of the user's question.
                               - max_tokens - curr_message_tokens
                 rest_tokens = max(rest_tokens, 0)
                 histories = cls.get_history_messages_from_memory(memory, rest_tokens)
-
-                # disable template string in query
-                # histories_params = JinjaPromptTemplate.from_template(template=histories).input_variables
-                # if histories_params:
-                #     for histories_param in histories_params:
-                #         if histories_param not in human_inputs:
-                #             human_inputs[histories_param] = '{{' + histories_param + '}}'
-
                 human_message_prompt += "\n\n" if human_message_prompt else ""
                 human_message_prompt += "Here is the chat histories between human and assistant, " \
-                                        "inside <histories></histories> XML tags.\n\n<histories>"
-                human_message_prompt += histories + "</histories>"
+                                        "inside <histories></histories> XML tags.\n\n<histories>\n"
+                human_message_prompt += histories + "\n</histories>"
 
             human_message_prompt += query_prompt
 
@@ -263,10 +271,13 @@ And answer according to the language of the user's question.
 
             messages.append(human_message)
 
-            return messages, ['\nHuman:']
+            for message in messages:
+                message.content = re.sub(r'<\|.*?\|>', '', message.content)
+
+            return messages, ['\nHuman:', '</histories>']
 
     @classmethod
-    def get_llm_callbacks(cls, llm: Union[StreamableOpenAI, StreamableChatOpenAI],
+    def get_llm_callbacks(cls, llm: BaseLanguageModel,
                           streaming: bool,
                           conversation_message_task: ConversationMessageTask) -> List[BaseCallbackHandler]:
         llm_callback_handler = LLMCallbackHandler(llm, conversation_message_task)
@@ -277,8 +288,7 @@ And answer according to the language of the user's question.
 
     @classmethod
     def get_history_messages_from_memory(cls, memory: ReadOnlyConversationTokenDBBufferSharedMemory,
-                                         max_token_limit: int) -> \
-            str:
+                                         max_token_limit: int) -> str:
         """Get memory messages."""
         memory.max_token_limit = max_token_limit
         memory_key = memory.memory_variables[0]
@@ -329,7 +339,7 @@ And answer according to the language of the user's question.
             pre_prompt=app_model_config.pre_prompt,
             query=query,
             inputs=inputs,
-            chain_output=None,
+            agent_execute_result=None,
             memory=None
         )
 
@@ -379,6 +389,7 @@ And answer according to the language of the user's question.
             query=message.query,
             inputs=message.inputs,
             chain_output=None,
+            agent_execute_result=None,
             memory=None
         )
 

api/core/conversation_message_task.py

@@ -52,7 +52,7 @@ class ConversationMessageTask:
             message=self.message,
             conversation=self.conversation,
             chain_pub=False,  # disabled currently
-            agent_thought_pub=False  # disabled currently
+            agent_thought_pub=True
         )
 
     def init(self):
@@ -69,6 +69,7 @@ class ConversationMessageTask:
                 "suggested_questions": self.app_model_config.suggested_questions_list,
                 "suggested_questions_after_answer": self.app_model_config.suggested_questions_after_answer_dict,
                 "more_like_this": self.app_model_config.more_like_this_dict,
+                "sensitive_word_avoidance": self.app_model_config.sensitive_word_avoidance_dict,
                 "user_input_form": self.app_model_config.user_input_form_list,
             }
 
@@ -207,7 +208,28 @@ class ConversationMessageTask:
 
         self._pub_handler.pub_chain(message_chain)
 
-    def on_agent_end(self, message_chain: MessageChain, agent_model_name: str,
+    def on_agent_start(self, message_chain: MessageChain, agent_loop: AgentLoop) -> MessageAgentThought:
+        message_agent_thought = MessageAgentThought(
+            message_id=self.message.id,
+            message_chain_id=message_chain.id,
+            position=agent_loop.position,
+            thought=agent_loop.thought,
+            tool=agent_loop.tool_name,
+            tool_input=agent_loop.tool_input,
+            message=agent_loop.prompt,
+            answer=agent_loop.completion,
+            created_by_role=('account' if isinstance(self.user, Account) else 'end_user'),
+            created_by=self.user.id
+        )
+
+        db.session.add(message_agent_thought)
+        db.session.flush()
+
+        self._pub_handler.pub_agent_thought(message_agent_thought)
+
+        return message_agent_thought
+
+    def on_agent_end(self, message_agent_thought: MessageAgentThought, agent_model_name: str,
                      agent_loop: AgentLoop):
         agent_message_unit_price = llm_constant.model_prices[agent_model_name]['prompt']
         agent_answer_unit_price = llm_constant.model_prices[agent_model_name]['completion']
@@ -222,34 +244,18 @@ class ConversationMessageTask:
             agent_answer_unit_price
         )
 
-        message_agent_loop = MessageAgentThought(
-            message_id=self.message.id,
-            message_chain_id=message_chain.id,
-            position=agent_loop.position,
-            thought=agent_loop.thought,
-            tool=agent_loop.tool_name,
-            tool_input=agent_loop.tool_input,
-            observation=agent_loop.tool_output,
-            tool_process_data='',  # currently not support
-            message=agent_loop.prompt,
-            message_token=loop_message_tokens,
-            message_unit_price=agent_message_unit_price,
-            answer=agent_loop.completion,
-            answer_token=loop_answer_tokens,
-            answer_unit_price=agent_answer_unit_price,
-            latency=agent_loop.latency,
-            tokens=agent_loop.prompt_tokens + agent_loop.completion_tokens,
-            total_price=loop_total_price,
-            currency=llm_constant.model_currency,
-            created_by_role=('account' if isinstance(self.user, Account) else 'end_user'),
-            created_by=self.user.id
-        )
-
-        db.session.add(message_agent_loop)
+        message_agent_thought.observation = agent_loop.tool_output
+        message_agent_thought.tool_process_data = ''  # currently not support
+        message_agent_thought.message_token = loop_message_tokens
+        message_agent_thought.message_unit_price = agent_message_unit_price
+        message_agent_thought.answer_token = loop_answer_tokens
+        message_agent_thought.answer_unit_price = agent_answer_unit_price
+        message_agent_thought.latency = agent_loop.latency
+        message_agent_thought.tokens = agent_loop.prompt_tokens + agent_loop.completion_tokens
+        message_agent_thought.total_price = loop_total_price
+        message_agent_thought.currency = llm_constant.model_currency
         db.session.flush()
 
-        self._pub_handler.pub_agent_thought(message_agent_loop)
-
     def on_dataset_query_end(self, dataset_query_obj: DatasetQueryObj):
         dataset_query = DatasetQuery(
             dataset_id=dataset_query_obj.dataset_id,
@@ -346,16 +352,14 @@ class PubHandler:
             content = {
                 'event': 'agent_thought',
                 'data': {
+                    'id': message_agent_thought.id,
                     'task_id': self._task_id,
                     'message_id': self._message.id,
                     'chain_id': message_agent_thought.message_chain_id,
-                    'agent_thought_id': message_agent_thought.id,
                     'position': message_agent_thought.position,
                     'thought': message_agent_thought.thought,
                     'tool': message_agent_thought.tool,
                     'tool_input': message_agent_thought.tool_input,
-                    'observation': message_agent_thought.observation,
-                    'answer': message_agent_thought.answer,
                     'mode': self._conversation.mode,
                     'conversation_id': self._conversation.id
                 }
@@ -388,6 +392,15 @@ class PubHandler:
     def _is_stopped(self):
         return redis_client.get(self._stopped_cache_key) is not None
 
+    @classmethod
+    def ping(cls, user: Union[Account | EndUser], task_id: str):
+        content = {
+            'event': 'ping'
+        }
+
+        channel = cls.generate_channel_name(user, task_id)
+        redis_client.publish(channel, json.dumps(content))
+
     @classmethod
     def stop(cls, user: Union[Account | EndUser], task_id: str):
         stopped_cache_key = cls.generate_stopped_cache_key(user, task_id)

api/core/data_loader/file_extractor.py

 import tempfile
 from pathlib import Path
-from typing import List, Union
+from typing import List, Union, Optional
 
+import requests
 from langchain.document_loaders import TextLoader, Docx2txtLoader
 from langchain.schema import Document
 
@@ -13,6 +14,9 @@ from core.data_loader.loader.pdf import PdfLoader
 from extensions.ext_storage import storage
 from models.model import UploadFile
 
+SUPPORT_URL_CONTENT_TYPES = ['application/pdf', 'text/plain']
+USER_AGENT = "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36"
+
 
 class FileExtractor:
     @classmethod
@@ -22,6 +26,25 @@ class FileExtractor:
             file_path = f"{temp_dir}/{next(tempfile._get_candidate_names())}{suffix}"
             storage.download(upload_file.key, file_path)
 
+            return cls.load_from_file(file_path, return_text, upload_file)
+
+    @classmethod
+    def load_from_url(cls, url: str, return_text: bool = False) -> Union[List[Document] | str]:
+        response = requests.get(url, headers={
+            "User-Agent": USER_AGENT
+        })
+
+        with tempfile.TemporaryDirectory() as temp_dir:
+            suffix = Path(url).suffix
+            file_path = f"{temp_dir}/{next(tempfile._get_candidate_names())}{suffix}"
+            with open(file_path, 'wb') as file:
+                file.write(response.content)
+
+            return cls.load_from_file(file_path, return_text)
+
+    @classmethod
+    def load_from_file(cls, file_path: str, return_text: bool = False,
+                       upload_file: Optional[UploadFile] = None) -> Union[List[Document] | str]:
         input_file = Path(file_path)
         delimiter = '\n'
         if input_file.suffix == '.xlsx':

api/core/llm/fake.py

+import time
+from typing import List, Optional, Any, Mapping
+
+from langchain.callbacks.manager import CallbackManagerForLLMRun
+from langchain.chat_models.base import SimpleChatModel
+from langchain.schema import BaseMessage, ChatResult, AIMessage, ChatGeneration, BaseLanguageModel
+
+
+class FakeLLM(SimpleChatModel):
+    """Fake ChatModel for testing purposes."""
+
+    streaming: bool = False
+    """Whether to stream the results or not."""
+    response: str
+    origin_llm: Optional[BaseLanguageModel] = None
+
+    @property
+    def _llm_type(self) -> str:
+        return "fake-chat-model"
+
+    def _call(
+        self,
+        messages: List[BaseMessage],
+        stop: Optional[List[str]] = None,
+        run_manager: Optional[CallbackManagerForLLMRun] = None,
+        **kwargs: Any,
+    ) -> str:
+        """First try to lookup in queries, else return 'foo' or 'bar'."""
+        return self.response
+
+    @property
+    def _identifying_params(self) -> Mapping[str, Any]:
+        return {"response": self.response}
+
+    def get_num_tokens(self, text: str) -> int:
+        return self.origin_llm.get_num_tokens(text) if self.origin_llm else 0
+
+    def _generate(
+        self,
+        messages: List[BaseMessage],
+        stop: Optional[List[str]] = None,
+        run_manager: Optional[CallbackManagerForLLMRun] = None,
+        **kwargs: Any,
+    ) -> ChatResult:
+        output_str = self._call(messages, stop=stop, run_manager=run_manager, **kwargs)
+        if self.streaming:
+            for token in output_str:
+                if run_manager:
+                    run_manager.on_llm_new_token(token)
+                    time.sleep(0.01)
+
+        message = AIMessage(content=output_str)
+        generation = ChatGeneration(message=message)
+        llm_output = {"token_usage": {
+            'prompt_tokens': 0,
+            'completion_tokens': 0,
+            'total_tokens': 0,
+        }}
+        return ChatResult(generations=[generation], llm_output=llm_output)

api/core/llm/provider/azure_provider.py

@@ -10,6 +10,9 @@ from core.llm.provider.errors import ValidateFailedError
 from models.provider import ProviderName
 
 
+AZURE_OPENAI_API_VERSION = '2023-07-01-preview'
+
+
 class AzureProvider(BaseProvider):
     def get_models(self, model_id: Optional[str] = None, credentials: Optional[dict] = None) -> list[dict]:
         return []
@@ -50,9 +53,10 @@ class AzureProvider(BaseProvider):
         """
         config = self.get_provider_api_key(model_id=model_id)
         config['openai_api_type'] = 'azure'
+        config['openai_api_version'] = AZURE_OPENAI_API_VERSION
         if model_id == 'text-embedding-ada-002':
             config['deployment'] = model_id.replace('.', '') if model_id else None
-            config['chunk_size'] = 1
+            config['chunk_size'] = 16
         else:
             config['deployment_name'] = model_id.replace('.', '') if model_id else None
         return config
@@ -69,7 +73,7 @@ class AzureProvider(BaseProvider):
         except:
             config = {
                 'openai_api_type': 'azure',
-                'openai_api_version': '2023-03-15-preview',
+                'openai_api_version': AZURE_OPENAI_API_VERSION,
                 'openai_api_base': '',
                 'openai_api_key': ''
             }
@@ -78,7 +82,7 @@ class AzureProvider(BaseProvider):
             if not config.get('openai_api_key'):
                 config = {
                     'openai_api_type': 'azure',
-                    'openai_api_version': '2023-03-15-preview',
+                    'openai_api_version': AZURE_OPENAI_API_VERSION,
                     'openai_api_base': '',
                     'openai_api_key': ''
                 }
@@ -100,7 +104,7 @@ class AzureProvider(BaseProvider):
                 raise ValueError('Config must be a object.')
 
             if 'openai_api_version' not in config:
-                config['openai_api_version'] = '2023-03-15-preview'
+                config['openai_api_version'] = AZURE_OPENAI_API_VERSION
 
             self.check_embedding_model(credentials=config)
         except ValidateFailedError as e:
@@ -119,7 +123,7 @@ class AzureProvider(BaseProvider):
         """
         return json.dumps({
             'openai_api_type': 'azure',
-            'openai_api_version': '2023-03-15-preview',
+            'openai_api_version': AZURE_OPENAI_API_VERSION,
             'openai_api_base': config['openai_api_base'],
             'openai_api_key': self.encrypt_token(config['openai_api_key'])
         })

api/core/llm/streamable_azure_chat_open_ai.py

-from langchain.callbacks.manager import Callbacks
-from langchain.schema import BaseMessage, LLMResult
+from langchain.callbacks.manager import Callbacks, CallbackManagerForLLMRun
+from langchain.chat_models.openai import _convert_dict_to_message
+from langchain.schema import BaseMessage, LLMResult, ChatResult, ChatGeneration
 from langchain.chat_models import AzureChatOpenAI
-from typing import Optional, List, Dict, Any
+from typing import Optional, List, Dict, Any, Tuple, Union
 
 from pydantic import root_validator
 
@@ -9,6 +10,11 @@ from core.llm.wrappers.openai_wrapper import handle_openai_exceptions
 
 
 class StreamableAzureChatOpenAI(AzureChatOpenAI):
+    request_timeout: Optional[Union[float, Tuple[float, float]]] = (5.0, 300.0)
+    """Timeout for requests to OpenAI completion API. Default is 600 seconds."""
+    max_retries: int = 1
+    """Maximum number of retries to make when generating."""
+
     @root_validator()
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
@@ -71,3 +77,43 @@ class StreamableAzureChatOpenAI(AzureChatOpenAI):
         params['model_kwargs'] = model_kwargs
 
         return params
+
+    def _generate(
+        self,
+        messages: List[BaseMessage],
+        stop: Optional[List[str]] = None,
+        run_manager: Optional[CallbackManagerForLLMRun] = None,
+        **kwargs: Any,
+    ) -> ChatResult:
+        message_dicts, params = self._create_message_dicts(messages, stop)
+        params = {**params, **kwargs}
+        if self.streaming:
+            inner_completion = ""
+            role = "assistant"
+            params["stream"] = True
+            function_call: Optional[dict] = None
+            for stream_resp in self.completion_with_retry(
+                messages=message_dicts, **params
+            ):
+                if len(stream_resp["choices"]) > 0:
+                    role = stream_resp["choices"][0]["delta"].get("role", role)
+                    token = stream_resp["choices"][0]["delta"].get("content") or ""
+                    inner_completion += token
+                    _function_call = stream_resp["choices"][0]["delta"].get("function_call")
+                    if _function_call:
+                        if function_call is None:
+                            function_call = _function_call
+                        else:
+                            function_call["arguments"] += _function_call["arguments"]
+                    if run_manager:
+                        run_manager.on_llm_new_token(token)
+            message = _convert_dict_to_message(
+                {
+                    "content": inner_completion,
+                    "role": role,
+                    "function_call": function_call,
+                }
+            )
+            return ChatResult(generations=[ChatGeneration(message=message)])
+        response = self.completion_with_retry(messages=message_dicts, **params)
+        return self._create_chat_result(response)

api/core/llm/streamable_azure_open_ai.py

 from langchain.callbacks.manager import Callbacks
 from langchain.llms import AzureOpenAI
 from langchain.schema import LLMResult
-from typing import Optional, List, Dict, Mapping, Any
+from typing import Optional, List, Dict, Mapping, Any, Union, Tuple
 
 from pydantic import root_validator
 
@@ -11,6 +11,10 @@ from core.llm.wrappers.openai_wrapper import handle_openai_exceptions
 class StreamableAzureOpenAI(AzureOpenAI):
     openai_api_type: str = "azure"
     openai_api_version: str = ""
+    request_timeout: Optional[Union[float, Tuple[float, float]]] = (5.0, 300.0)
+    """Timeout for requests to OpenAI completion API. Default is 600 seconds."""
+    max_retries: int = 1
+    """Maximum number of retries to make when generating."""
 
     @root_validator()
     def validate_environment(cls, values: Dict) -> Dict:

api/core/llm/streamable_chat_anthropic.py

 from typing import List, Optional, Any, Dict
 
+from httpx import Timeout
 from langchain.callbacks.manager import Callbacks
 from langchain.chat_models import ChatAnthropic
-from langchain.schema import BaseMessage, LLMResult
+from langchain.schema import BaseMessage, LLMResult, SystemMessage, AIMessage, HumanMessage, ChatMessage
+from pydantic import root_validator
 
 from core.llm.wrappers.anthropic_wrapper import handle_anthropic_exceptions
 
@@ -12,6 +14,14 @@ class StreamableChatAnthropic(ChatAnthropic):
     Wrapper around Anthropic's large language model.
     """
 
+    default_request_timeout: Optional[float] = Timeout(timeout=300.0, connect=5.0)
+
+    @root_validator()
+    def prepare_params(cls, values: Dict) -> Dict:
+        values['model_name'] = values.get('model')
+        values['max_tokens'] = values.get('max_tokens_to_sample')
+        return values
+
     @handle_anthropic_exceptions
     def generate(
             self,
@@ -37,3 +47,16 @@ class StreamableChatAnthropic(ChatAnthropic):
         del params['presence_penalty']
 
         return params
+
+    def _convert_one_message_to_text(self, message: BaseMessage) -> str:
+        if isinstance(message, ChatMessage):
+            message_text = f"\n\n{message.role.capitalize()}: {message.content}"
+        elif isinstance(message, HumanMessage):
+            message_text = f"{self.HUMAN_PROMPT} {message.content}"
+        elif isinstance(message, AIMessage):
+            message_text = f"{self.AI_PROMPT} {message.content}"
+        elif isinstance(message, SystemMessage):
+            message_text = f"<admin>{message.content}</admin>"
+        else:
+            raise ValueError(f"Got unknown type {message}")
+        return message_text
\ No newline at end of file

api/core/llm/streamable_chat_open_ai.py

@@ -3,7 +3,7 @@ import os
 from langchain.callbacks.manager import Callbacks
 from langchain.schema import BaseMessage, LLMResult
 from langchain.chat_models import ChatOpenAI
-from typing import Optional, List, Dict, Any
+from typing import Optional, List, Dict, Any, Union, Tuple
 
 from pydantic import root_validator
 
@@ -11,6 +11,10 @@ from core.llm.wrappers.openai_wrapper import handle_openai_exceptions
 
 
 class StreamableChatOpenAI(ChatOpenAI):
+    request_timeout: Optional[Union[float, Tuple[float, float]]] = (5.0, 300.0)
+    """Timeout for requests to OpenAI completion API. Default is 600 seconds."""
+    max_retries: int = 1
+    """Maximum number of retries to make when generating."""
 
     @root_validator()
     def validate_environment(cls, values: Dict) -> Dict:

api/core/llm/streamable_open_ai.py

@@ -2,7 +2,7 @@ import os
 
 from langchain.callbacks.manager import Callbacks
 from langchain.schema import LLMResult
-from typing import Optional, List, Dict, Any, Mapping
+from typing import Optional, List, Dict, Any, Mapping, Union, Tuple
 from langchain import OpenAI
 from pydantic import root_validator
 
@@ -10,6 +10,10 @@ from core.llm.wrappers.openai_wrapper import handle_openai_exceptions
 
 
 class StreamableOpenAI(OpenAI):
+    request_timeout: Optional[Union[float, Tuple[float, float]]] = (5.0, 300.0)
+    """Timeout for requests to OpenAI completion API. Default is 600 seconds."""
+    max_retries: int = 1
+    """Maximum number of retries to make when generating."""
 
     @root_validator()
     def validate_environment(cls, values: Dict) -> Dict:

api/core/orchestrator_rule_parser.py

+import math
+from typing import Optional
+
+from langchain import WikipediaAPIWrapper
+from langchain.callbacks.manager import Callbacks
+from langchain.chat_models import ChatOpenAI
+from langchain.memory.chat_memory import BaseChatMemory
+from langchain.tools import BaseTool, Tool, WikipediaQueryRun
+from pydantic import BaseModel, Field
+
+from core.agent.agent_executor import AgentExecutor, PlanningStrategy, AgentConfiguration
+from core.callback_handler.agent_loop_gather_callback_handler import AgentLoopGatherCallbackHandler
+from core.callback_handler.dataset_tool_callback_handler import DatasetToolCallbackHandler
+from core.callback_handler.main_chain_gather_callback_handler import MainChainGatherCallbackHandler
+from core.callback_handler.std_out_callback_handler import DifyStdOutCallbackHandler
+from core.chain.sensitive_word_avoidance_chain import SensitiveWordAvoidanceChain
+from core.conversation_message_task import ConversationMessageTask
+from core.llm.llm_builder import LLMBuilder
+from core.tool.dataset_retriever_tool import DatasetRetrieverTool
+from core.tool.provider.serpapi_provider import SerpAPIToolProvider
+from core.tool.serpapi_wrapper import OptimizedSerpAPIWrapper, OptimizedSerpAPIInput
+from core.tool.web_reader_tool import WebReaderTool
+from extensions.ext_database import db
+from models.dataset import Dataset, DatasetProcessRule
+from models.model import AppModelConfig
+
+
+class OrchestratorRuleParser:
+    """Parse the orchestrator rule to entities."""
+
+    def __init__(self, tenant_id: str, app_model_config: AppModelConfig):
+        self.tenant_id = tenant_id
+        self.app_model_config = app_model_config
+        self.agent_summary_model_name = "gpt-3.5-turbo-16k"
+        self.dataset_retrieve_model_name = "gpt-3.5-turbo"
+
+    def to_agent_executor(self, conversation_message_task: ConversationMessageTask, memory: Optional[BaseChatMemory],
+                       rest_tokens: int, chain_callback: MainChainGatherCallbackHandler) \
+            -> Optional[AgentExecutor]:
+        if not self.app_model_config.agent_mode_dict:
+            return None
+
+        agent_mode_config = self.app_model_config.agent_mode_dict
+        model_dict = self.app_model_config.model_dict
+
+        chain = None
+        if agent_mode_config and agent_mode_config.get('enabled'):
+            tool_configs = agent_mode_config.get('tools', [])
+            agent_model_name = model_dict.get('name', 'gpt-4')
+
+            # add agent callback to record agent thoughts
+            agent_callback = AgentLoopGatherCallbackHandler(
+                model_name=agent_model_name,
+                conversation_message_task=conversation_message_task
+            )
+
+            chain_callback.agent_callback = agent_callback
+
+            agent_llm = LLMBuilder.to_llm(
+                tenant_id=self.tenant_id,
+                model_name=agent_model_name,
+                temperature=0,
+                max_tokens=1500,
+                callbacks=[agent_callback, DifyStdOutCallbackHandler()]
+            )
+
+            planning_strategy = PlanningStrategy(agent_mode_config.get('strategy', 'router'))
+
+            # only OpenAI chat model (include Azure) support function call, use ReACT instead
+            if not isinstance(agent_llm, ChatOpenAI) \
+                    and planning_strategy in [PlanningStrategy.FUNCTION_CALL, PlanningStrategy.MULTI_FUNCTION_CALL]:
+                planning_strategy = PlanningStrategy.REACT
+
+            summary_llm = LLMBuilder.to_llm(
+                tenant_id=self.tenant_id,
+                model_name=self.agent_summary_model_name,
+                temperature=0,
+                max_tokens=500,
+                callbacks=[DifyStdOutCallbackHandler()]
+            )
+
+            tools = self.to_tools(
+                tool_configs=tool_configs,
+                conversation_message_task=conversation_message_task,
+                model_name=self.agent_summary_model_name,
+                rest_tokens=rest_tokens,
+                callbacks=[agent_callback, DifyStdOutCallbackHandler()]
+            )
+
+            if len(tools) == 0:
+                return None
+
+            dataset_llm = LLMBuilder.to_llm(
+                tenant_id=self.tenant_id,
+                model_name=self.dataset_retrieve_model_name,
+                temperature=0,
+                max_tokens=500,
+                callbacks=[DifyStdOutCallbackHandler()]
+            )
+
+            agent_configuration = AgentConfiguration(
+                strategy=planning_strategy,
+                llm=agent_llm,
+                tools=tools,
+                summary_llm=summary_llm,
+                dataset_llm=dataset_llm,
+                memory=memory,
+                callbacks=[chain_callback, agent_callback],
+                max_iterations=10,
+                max_execution_time=400.0,
+                early_stopping_method="generate"
+            )
+
+            return AgentExecutor(agent_configuration)
+
+        return chain
+
+    def to_sensitive_word_avoidance_chain(self, callbacks: Callbacks = None, **kwargs) \
+            -> Optional[SensitiveWordAvoidanceChain]:
+        """
+        Convert app sensitive word avoidance config to chain
+
+        :param kwargs:
+        :return:
+        """
+        if not self.app_model_config.sensitive_word_avoidance_dict:
+            return None
+
+        sensitive_word_avoidance_config = self.app_model_config.sensitive_word_avoidance_dict
+        sensitive_words = sensitive_word_avoidance_config.get("words", "")
+        if sensitive_word_avoidance_config.get("enabled", False) and sensitive_words:
+            return SensitiveWordAvoidanceChain(
+                sensitive_words=sensitive_words.split(","),
+                canned_response=sensitive_word_avoidance_config.get("canned_response", ''),
+                output_key="sensitive_word_avoidance_output",
+                callbacks=callbacks,
+                **kwargs
+            )
+
+        return None
+
+    def to_tools(self, tool_configs: list, conversation_message_task: ConversationMessageTask,
+                 model_name: str, rest_tokens: int, callbacks: Callbacks = None) -> list[BaseTool]:
+        """
+        Convert app agent tool configs to tools
+
+        :param rest_tokens:
+        :param tool_configs: app agent tool configs
+        :param model_name:
+        :param conversation_message_task:
+        :param callbacks:
+        :return:
+        """
+        tools = []
+        for tool_config in tool_configs:
+            tool_type = list(tool_config.keys())[0]
+            tool_val = list(tool_config.values())[0]
+            if not tool_val.get("enabled") or tool_val.get("enabled") is not True:
+                continue
+
+            tool = None
+            if tool_type == "dataset":
+                tool = self.to_dataset_retriever_tool(tool_val, conversation_message_task, rest_tokens)
+            elif tool_type == "web_reader":
+                tool = self.to_web_reader_tool(model_name)
+            elif tool_type == "google_search":
+                tool = self.to_google_search_tool()
+            elif tool_type == "wikipedia":
+                tool = self.to_wikipedia_tool()
+
+            if tool:
+                tool.callbacks.extend(callbacks)
+                tools.append(tool)
+
+        return tools
+
+    def to_dataset_retriever_tool(self, tool_config: dict, conversation_message_task: ConversationMessageTask,
+                                  rest_tokens: int) \
+            -> Optional[BaseTool]:
+        """
+        A dataset tool is a tool that can be used to retrieve information from a dataset
+        :param rest_tokens:
+        :param tool_config:
+        :param conversation_message_task:
+        :return:
+        """
+        # get dataset from dataset id
+        dataset = db.session.query(Dataset).filter(
+            Dataset.tenant_id == self.tenant_id,
+            Dataset.id == tool_config.get("id")
+        ).first()
+
+        if dataset and dataset.available_document_count == 0 and dataset.available_document_count == 0:
+            return None
+
+        k = self._dynamic_calc_retrieve_k(dataset, rest_tokens)
+        tool = DatasetRetrieverTool.from_dataset(
+            dataset=dataset,
+            k=k,
+            callbacks=[DatasetToolCallbackHandler(conversation_message_task)]
+        )
+
+        return tool
+
+    def to_web_reader_tool(self, model_name: str) -> Optional[BaseTool]:
+        """
+        A tool for reading web pages
+
+        :return:
+        """
+        summary_llm = LLMBuilder.to_llm(
+            tenant_id=self.tenant_id,
+            model_name=model_name,
+            temperature=0,
+            max_tokens=500,
+            callbacks=[DifyStdOutCallbackHandler()]
+        )
+
+        tool = WebReaderTool(
+            llm=summary_llm,
+            max_chunk_length=4000,
+            continue_reading=True,
+            callbacks=[DifyStdOutCallbackHandler()]
+        )
+
+        return tool
+
+    def to_google_search_tool(self) -> Optional[BaseTool]:
+        tool_provider = SerpAPIToolProvider(tenant_id=self.tenant_id)
+        func_kwargs = tool_provider.credentials_to_func_kwargs()
+        if not func_kwargs:
+            return None
+
+        tool = Tool(
+            name="google_search",
+            description="A tool for performing a Google search and extracting snippets and webpages "
+                        "when you need to search for something you don't know or when your information "
+                        "is not up to date."
+                        "Input should be a search query.",
+            func=OptimizedSerpAPIWrapper(**func_kwargs).run,
+            args_schema=OptimizedSerpAPIInput,
+            callbacks=[DifyStdOutCallbackHandler()]
+        )
+
+        return tool
+
+    def to_wikipedia_tool(self) -> Optional[BaseTool]:
+        class WikipediaInput(BaseModel):
+            query: str = Field(..., description="search query.")
+
+        return WikipediaQueryRun(
+            name="wikipedia",
+            api_wrapper=WikipediaAPIWrapper(doc_content_chars_max=4000),
+            args_schema=WikipediaInput,
+            callbacks=[DifyStdOutCallbackHandler()]
+        )
+
+    @classmethod
+    def _dynamic_calc_retrieve_k(cls, dataset: Dataset, rest_tokens: int) -> int:
+        DEFAULT_K = 2
+        CONTEXT_TOKENS_PERCENT = 0.3
+        processing_rule = dataset.latest_process_rule
+        if not processing_rule:
+            return DEFAULT_K
+
+        if processing_rule.mode == "custom":
+            rules = processing_rule.rules_dict
+            if not rules:
+                return DEFAULT_K
+
+            segmentation = rules["segmentation"]
+            segment_max_tokens = segmentation["max_tokens"]
+        else:
+            segment_max_tokens = DatasetProcessRule.AUTOMATIC_RULES['segmentation']['max_tokens']
+
+        # when rest_tokens is less than default context tokens
+        if rest_tokens < segment_max_tokens * DEFAULT_K:
+            return rest_tokens // segment_max_tokens
+
+        context_limit_tokens = math.floor(rest_tokens * CONTEXT_TOKENS_PERCENT)
+
+        # when context_limit_tokens is less than default context tokens, use default_k
+        if context_limit_tokens <= segment_max_tokens * DEFAULT_K:
+            return DEFAULT_K
+
+        # Expand the k value when there's still some room left in the 30% rest tokens space
+        return context_limit_tokens // segment_max_tokens

api/core/tool/dataset_retriever_tool.py

+import re
+from typing import Type
+
+from flask import current_app
+from langchain.embeddings import OpenAIEmbeddings
+from langchain.tools import BaseTool
+from pydantic import Field, BaseModel
+
+from core.callback_handler.index_tool_callback_handler import DatasetIndexToolCallbackHandler
+from core.embedding.cached_embedding import CacheEmbedding
+from core.index.keyword_table_index.keyword_table_index import KeywordTableIndex, KeywordTableConfig
+from core.index.vector_index.vector_index import VectorIndex
+from core.llm.llm_builder import LLMBuilder
+from extensions.ext_database import db
+from models.dataset import Dataset
+
+
+class DatasetRetrieverToolInput(BaseModel):
+    dataset_id: str = Field(..., description="ID of dataset to be queried. MUST be UUID format.")
+    query: str = Field(..., description="Query for the dataset to be used to retrieve the dataset.")
+
+
+class DatasetRetrieverTool(BaseTool):
+    """Tool for querying a Dataset."""
+    name: str = "dataset"
+    args_schema: Type[BaseModel] = DatasetRetrieverToolInput
+    description: str = "use this to retrieve a dataset. "
+
+    tenant_id: str
+    dataset_id: str
+    k: int = 3
+
+    @classmethod
+    def from_dataset(cls, dataset: Dataset, **kwargs):
+        description = dataset.description.replace('\n', '').replace('\r', '')
+        if not description:
+            description = 'useful for when you want to answer queries about the ' + dataset.name
+
+        description += '\nID of dataset MUST be ' + dataset.id
+        return cls(
+            tenant_id=dataset.tenant_id,
+            dataset_id=dataset.id,
+            description=description,
+            **kwargs
+        )
+
+    def _run(self, dataset_id: str, query: str) -> str:
+        pattern = r'\b[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}\b'
+        match = re.search(pattern, dataset_id, re.IGNORECASE)
+        if match:
+            dataset_id = match.group()
+
+        dataset = db.session.query(Dataset).filter(
+            Dataset.tenant_id == self.tenant_id,
+            Dataset.id == dataset_id
+        ).first()
+
+        if not dataset:
+            return f'[{self.name} failed to find dataset with id {dataset_id}.]'
+
+        if dataset.indexing_technique == "economy":
+            # use keyword table query
+            kw_table_index = KeywordTableIndex(
+                dataset=dataset,
+                config=KeywordTableConfig(
+                    max_keywords_per_chunk=5
+                )
+            )
+
+            documents = kw_table_index.search(query, search_kwargs={'k': self.k})
+        else:
+            model_credentials = LLMBuilder.get_model_credentials(
+                tenant_id=dataset.tenant_id,
+                model_provider=LLMBuilder.get_default_provider(dataset.tenant_id, 'text-embedding-ada-002'),
+                model_name='text-embedding-ada-002'
+            )
+
+            embeddings = CacheEmbedding(OpenAIEmbeddings(
+                **model_credentials
+            ))
+
+            vector_index = VectorIndex(
+                dataset=dataset,
+                config=current_app.config,
+                embeddings=embeddings
+            )
+
+            if self.k > 0:
+                documents = vector_index.search(
+                    query,
+                    search_type='similarity',
+                    search_kwargs={
+                        'k': self.k
+                    }
+                )
+            else:
+                documents = []
+
+            hit_callback = DatasetIndexToolCallbackHandler(dataset.id)
+            hit_callback.on_tool_end(documents)
+
+        return str("\n".join([document.page_content for document in documents]))
+
+    async def _arun(self, tool_input: str) -> str:
+        raise NotImplementedError()

api/core/tool/provider/base.py

+import base64
+from abc import ABC, abstractmethod
+from typing import Optional
+
+from extensions.ext_database import db
+from libs import rsa
+from models.account import Tenant
+from models.tool import ToolProvider, ToolProviderName
+
+
+class BaseToolProvider(ABC):
+    def __init__(self, tenant_id: str):
+        self.tenant_id = tenant_id
+
+    @abstractmethod
+    def get_provider_name(self) -> ToolProviderName:
+        raise NotImplementedError
+
+    @abstractmethod
+    def encrypt_credentials(self, credentials: dict) -> Optional[dict]:
+        raise NotImplementedError
+
+    @abstractmethod
+    def get_credentials(self, obfuscated: bool = False) -> Optional[dict]:
+        raise NotImplementedError
+
+    @abstractmethod
+    def credentials_to_func_kwargs(self) -> Optional[dict]:
+        raise NotImplementedError
+
+    @abstractmethod
+    def credentials_validate(self, credentials: dict):
+        raise NotImplementedError
+
+    def get_provider(self, must_enabled: bool = False) -> Optional[ToolProvider]:
+        """
+        Returns the Provider instance for the given tenant_id and tool_name.
+        """
+        query = db.session.query(ToolProvider).filter(
+            ToolProvider.tenant_id == self.tenant_id,
+            ToolProvider.tool_name == self.get_provider_name().value
+        )
+
+        if must_enabled:
+            query = query.filter(ToolProvider.is_enabled == True)
+
+        return query.first()
+
+    def encrypt_token(self, token) -> str:
+        tenant = db.session.query(Tenant).filter(Tenant.id == self.tenant_id).first()
+        encrypted_token = rsa.encrypt(token, tenant.encrypt_public_key)
+        return base64.b64encode(encrypted_token).decode()
+
+    def decrypt_token(self, token: str, obfuscated: bool = False) -> str:
+        token = rsa.decrypt(base64.b64decode(token), self.tenant_id)
+
+        if obfuscated:
+            return self._obfuscated_token(token)
+
+        return token
+
+    def _obfuscated_token(self, token: str) -> str:
+        return token[:6] + '*' * (len(token) - 8) + token[-2:]

api/core/tool/provider/errors.py

+class ToolValidateFailedError(Exception):
+    description = "Tool Provider Validate failed"

api/core/tool/provider/serpapi_provider.py

+from typing import Optional
+
+from core.tool.provider.base import BaseToolProvider
+from core.tool.provider.errors import ToolValidateFailedError
+from core.tool.serpapi_wrapper import OptimizedSerpAPIWrapper
+from models.tool import ToolProviderName
+
+
+class SerpAPIToolProvider(BaseToolProvider):
+    def get_provider_name(self) -> ToolProviderName:
+        """
+        Returns the name of the provider.
+
+        :return:
+        """
+        return ToolProviderName.SERPAPI
+
+    def get_credentials(self, obfuscated: bool = False) -> Optional[dict]:
+        """
+        Returns the credentials for SerpAPI as a dictionary.
+
+        :param obfuscated: obfuscate credentials if True
+        :return:
+        """
+        tool_provider = self.get_provider(must_enabled=True)
+        if not tool_provider:
+            return None
+
+        credentials = tool_provider.credentials
+        if not credentials:
+            return None
+
+        if credentials.get('api_key'):
+            credentials['api_key'] = self.decrypt_token(credentials.get('api_key'), obfuscated)
+
+        return credentials
+
+    def credentials_to_func_kwargs(self) -> Optional[dict]:
+        """
+        Returns the credentials function kwargs as a dictionary.
+
+        :return:
+        """
+        credentials = self.get_credentials()
+        if not credentials:
+            return None
+
+        return {
+            'serpapi_api_key': credentials.get('api_key')
+        }
+
+    def credentials_validate(self, credentials: dict):
+        """
+        Validates the given credentials.
+
+        :param credentials:
+        :return:
+        """
+        if 'api_key' not in credentials or not credentials.get('api_key'):
+            raise ToolValidateFailedError("SerpAPI api_key is required.")
+
+        api_key = credentials.get('api_key')
+
+        try:
+            OptimizedSerpAPIWrapper(serpapi_api_key=api_key).run(query='test')
+        except Exception as e:
+            raise ToolValidateFailedError("SerpAPI api_key is invalid. {}".format(e))
+
+    def encrypt_credentials(self, credentials: dict) -> Optional[dict]:
+        """
+        Encrypts the given credentials.
+
+        :param credentials:
+        :return:
+        """
+        credentials['api_key'] = self.encrypt_token(credentials.get('api_key'))
+        return credentials

api/core/tool/provider/tool_provider_service.py

+from typing import Optional
+
+from core.tool.provider.base import BaseToolProvider
+from core.tool.provider.serpapi_provider import SerpAPIToolProvider
+
+
+class ToolProviderService:
+
+    def __init__(self, tenant_id: str, provider_name: str):
+        self.provider = self._init_provider(tenant_id, provider_name)
+
+    def _init_provider(self, tenant_id: str, provider_name: str) -> BaseToolProvider:
+        if provider_name == 'serpapi':
+            return SerpAPIToolProvider(tenant_id)
+        else:
+            raise Exception('tool provider {} not found'.format(provider_name))
+
+    def get_credentials(self, obfuscated: bool = False) -> Optional[dict]:
+        """
+        Returns the credentials for Tool as a dictionary.
+
+        :param obfuscated:
+        :return:
+        """
+        return self.provider.get_credentials(obfuscated)
+
+    def credentials_validate(self, credentials: dict):
+        """
+        Validates the given credentials.
+
+        :param credentials:
+        :raises: ValidateFailedError
+        """
+        return self.provider.credentials_validate(credentials)
+
+    def encrypt_credentials(self, credentials: dict):
+        """
+        Encrypts the given credentials.
+
+        :param credentials:
+        :return:
+        """
+        return self.provider.encrypt_credentials(credentials)

api/core/tool/serpapi_wrapper.py

+from langchain import SerpAPIWrapper
+from pydantic import Field, BaseModel
+
+
+class OptimizedSerpAPIInput(BaseModel):
+    query: str = Field(..., description="search query.")
+
+
+class OptimizedSerpAPIWrapper(SerpAPIWrapper):
+
+    @staticmethod
+    def _process_response(res: dict, num_results: int = 5) -> str:
+        """Process response from SerpAPI."""
+        if "error" in res.keys():
+            raise ValueError(f"Got error from SerpAPI: {res['error']}")
+        if "answer_box" in res.keys() and type(res["answer_box"]) == list:
+            res["answer_box"] = res["answer_box"][0]
+        if "answer_box" in res.keys() and "answer" in res["answer_box"].keys():
+            toret = res["answer_box"]["answer"]
+        elif "answer_box" in res.keys() and "snippet" in res["answer_box"].keys():
+            toret = res["answer_box"]["snippet"]
+        elif (
+            "answer_box" in res.keys()
+            and "snippet_highlighted_words" in res["answer_box"].keys()
+        ):
+            toret = res["answer_box"]["snippet_highlighted_words"][0]
+        elif (
+            "sports_results" in res.keys()
+            and "game_spotlight" in res["sports_results"].keys()
+        ):
+            toret = res["sports_results"]["game_spotlight"]
+        elif (
+            "shopping_results" in res.keys()
+            and "title" in res["shopping_results"][0].keys()
+        ):
+            toret = res["shopping_results"][:3]
+        elif (
+            "knowledge_graph" in res.keys()
+            and "description" in res["knowledge_graph"].keys()
+        ):
+            toret = res["knowledge_graph"]["description"]
+        elif 'organic_results' in res.keys() and len(res['organic_results']) > 0:
+            toret = ""
+            for result in res["organic_results"][:num_results]:
+                if "link" in result:
+                    toret += "----------------\nlink: " + result["link"] + "\n"
+                if "snippet" in result:
+                    toret += "snippet: " + result["snippet"] + "\n"
+        else:
+            toret = "No good search result found"
+        return "search result:\n" + toret

api/core/tool/web_reader_tool.py

+import hashlib
+import json
+import os
+import re
+import site
+import subprocess
+import tempfile
+import unicodedata
+from contextlib import contextmanager
+from typing import Type
+
+import requests
+from bs4 import BeautifulSoup, NavigableString, Comment, CData
+from langchain.base_language import BaseLanguageModel
+from langchain.chains.summarize import load_summarize_chain
+from langchain.schema import Document
+from langchain.text_splitter import RecursiveCharacterTextSplitter
+from langchain.tools.base import BaseTool
+from newspaper import Article
+from pydantic import BaseModel, Field
+from regex import regex
+
+from core.data_loader import file_extractor
+from core.data_loader.file_extractor import FileExtractor
+
+FULL_TEMPLATE = """
+TITLE: {title}
+AUTHORS: {authors}
+PUBLISH DATE: {publish_date}
+TOP_IMAGE_URL: {top_image}
+TEXT:
+
+{text}
+"""
+
+
+class WebReaderToolInput(BaseModel):
+    url: str = Field(..., description="URL of the website to read")
+    summary: bool = Field(
+        default=False,
+        description="When the user's question requires extracting the summarizing content of the webpage, "
+                    "set it to true."
+    )
+    cursor: int = Field(
+        default=0,
+        description="Start reading from this character."
+        "Use when the first response was truncated"
+        "and you want to continue reading the page."
+        "The value cannot exceed 24000.",
+    )
+
+
+class WebReaderTool(BaseTool):
+    """Reader tool for getting website title and contents. Gives more control than SimpleReaderTool."""
+
+    name: str = "web_reader"
+    args_schema: Type[BaseModel] = WebReaderToolInput
+    description: str = "use this to read a website. " \
+                       "If you can answer the question based on the information provided, " \
+                       "there is no need to use."
+    page_contents: str = None
+    url: str = None
+    max_chunk_length: int = 4000
+    summary_chunk_tokens: int = 4000
+    summary_chunk_overlap: int = 0
+    summary_separators: list[str] = ["\n\n", "。", ".", " ", ""]
+    continue_reading: bool = True
+    llm: BaseLanguageModel
+
+    def _run(self, url: str, summary: bool = False, cursor: int = 0) -> str:
+        try:
+            if not self.page_contents or self.url != url:
+                page_contents = get_url(url)
+                self.page_contents = page_contents
+                self.url = url
+            else:
+                page_contents = self.page_contents
+        except Exception as e:
+            return f'Read this website failed, caused by: {str(e)}.'
+
+        if summary:
+            character_splitter = RecursiveCharacterTextSplitter.from_tiktoken_encoder(
+                chunk_size=self.summary_chunk_tokens,
+                chunk_overlap=self.summary_chunk_overlap,
+                separators=self.summary_separators
+            )
+
+            texts = character_splitter.split_text(page_contents)
+            docs = [Document(page_content=t) for t in texts]
+
+            # only use first 5 docs
+            if len(docs) > 5:
+                docs = docs[:5]
+
+            chain = load_summarize_chain(self.llm, chain_type="refine", callbacks=self.callbacks)
+            try:
+                page_contents = chain.run(docs)
+                # todo use cache
+            except Exception as e:
+                return f'Read this website failed, caused by: {str(e)}.'
+        else:
+            page_contents = page_result(page_contents, cursor, self.max_chunk_length)
+
+            if self.continue_reading and len(page_contents) >= self.max_chunk_length:
+                page_contents += f"\nPAGE WAS TRUNCATED. IF YOU FIND INFORMATION THAT CAN ANSWER QUESTION " \
+                                 f"THEN DIRECT ANSWER AND STOP INVOKING web_reader TOOL, OTHERWISE USE " \
+                                 f"CURSOR={cursor+len(page_contents)} TO CONTINUE READING."
+
+        return page_contents
+
+    async def _arun(self, url: str) -> str:
+        raise NotImplementedError
+
+
+def page_result(text: str, cursor: int, max_length: int) -> str:
+    """Page through `text` and return a substring of `max_length` characters starting from `cursor`."""
+    return text[cursor: cursor + max_length]
+
+
+def get_url(url: str) -> str:
+    """Fetch URL and return the contents as a string."""
+    headers = {
+        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36"
+    }
+    supported_content_types = file_extractor.SUPPORT_URL_CONTENT_TYPES + ["text/html"]
+
+    head_response = requests.head(url, headers=headers, allow_redirects=True, timeout=(5, 10))
+
+    if head_response.status_code != 200:
+        return "URL returned status code {}.".format(head_response.status_code)
+
+    # check content-type
+    main_content_type = head_response.headers.get('Content-Type').split(';')[0].strip()
+    if main_content_type not in supported_content_types:
+        return "Unsupported content-type [{}] of URL.".format(main_content_type)
+
+    if main_content_type in file_extractor.SUPPORT_URL_CONTENT_TYPES:
+        return FileExtractor.load_from_url(url, return_text=True)
+
+    response = requests.get(url, headers=headers, allow_redirects=True, timeout=(5, 30))
+    a = extract_using_readabilipy(response.text)
+
+    if not a['plain_text'] or not a['plain_text'].strip():
+        return get_url_from_newspaper3k(url)
+
+    res = FULL_TEMPLATE.format(
+        title=a['title'],
+        authors=a['byline'],
+        publish_date=a['date'],
+        top_image="",
+        text=a['plain_text'] if a['plain_text'] else "",
+    )
+
+    return res
+
+
+def get_url_from_newspaper3k(url: str) -> str:
+
+    a = Article(url)
+    a.download()
+    a.parse()
+
+    res = FULL_TEMPLATE.format(
+        title=a.title,
+        authors=a.authors,
+        publish_date=a.publish_date,
+        top_image=a.top_image,
+        text=a.text,
+    )
+
+    return res
+
+
+def extract_using_readabilipy(html):
+    with tempfile.NamedTemporaryFile(delete=False, mode='w+') as f_html:
+        f_html.write(html)
+        f_html.close()
+    html_path = f_html.name
+
+    # Call Mozilla's Readability.js Readability.parse() function via node, writing output to a temporary file
+    article_json_path = html_path + ".json"
+    jsdir = os.path.join(find_module_path('readabilipy'), 'javascript')
+    with chdir(jsdir):
+        subprocess.check_call(["node", "ExtractArticle.js", "-i", html_path, "-o", article_json_path])
+
+    # Read output of call to Readability.parse() from JSON file and return as Python dictionary
+    with open(article_json_path, "r", encoding="utf-8") as json_file:
+        input_json = json.loads(json_file.read())
+
+    # Deleting files after processing
+    os.unlink(article_json_path)
+    os.unlink(html_path)
+
+    article_json = {
+        "title": None,
+        "byline": None,
+        "date": None,
+        "content": None,
+        "plain_content": None,
+        "plain_text": None
+    }
+    # Populate article fields from readability fields where present
+    if input_json:
+        if "title" in input_json and input_json["title"]:
+            article_json["title"] = input_json["title"]
+        if "byline" in input_json and input_json["byline"]:
+            article_json["byline"] = input_json["byline"]
+        if "date" in input_json and input_json["date"]:
+            article_json["date"] = input_json["date"]
+        if "content" in input_json and input_json["content"]:
+            article_json["content"] = input_json["content"]
+            article_json["plain_content"] = plain_content(article_json["content"], False, False)
+            article_json["plain_text"] = extract_text_blocks_as_plain_text(article_json["plain_content"])
+        if "textContent" in input_json and input_json["textContent"]:
+            article_json["plain_text"] = input_json["textContent"]
+            article_json["plain_text"] = re.sub(r'\n\s*\n', '\n', article_json["plain_text"])
+
+    return article_json
+
+
+def find_module_path(module_name):
+    for package_path in site.getsitepackages():
+        potential_path = os.path.join(package_path, module_name)
+        if os.path.exists(potential_path):
+            return potential_path
+
+    return None
+
+@contextmanager
+def chdir(path):
+    """Change directory in context and return to original on exit"""
+    # From https://stackoverflow.com/a/37996581, couldn't find a built-in
+    original_path = os.getcwd()
+    os.chdir(path)
+    try:
+        yield
+    finally:
+        os.chdir(original_path)
+
+
+def extract_text_blocks_as_plain_text(paragraph_html):
+    # Load article as DOM
+    soup = BeautifulSoup(paragraph_html, 'html.parser')
+    # Select all lists
+    list_elements = soup.find_all(['ul', 'ol'])
+    # Prefix text in all list items with "* " and make lists paragraphs
+    for list_element in list_elements:
+        plain_items = "".join(list(filter(None, [plain_text_leaf_node(li)["text"] for li in list_element.find_all('li')])))
+        list_element.string = plain_items
+        list_element.name = "p"
+    # Select all text blocks
+    text_blocks = [s.parent for s in soup.find_all(string=True)]
+    text_blocks = [plain_text_leaf_node(block) for block in text_blocks]
+    # Drop empty paragraphs
+    text_blocks = list(filter(lambda p: p["text"] is not None, text_blocks))
+    return text_blocks
+
+
+def plain_text_leaf_node(element):
+    # Extract all text, stripped of any child HTML elements and normalise it
+    plain_text = normalise_text(element.get_text())
+    if plain_text != "" and element.name == "li":
+        plain_text = "* {}, ".format(plain_text)
+    if plain_text == "":
+        plain_text = None
+    if "data-node-index" in element.attrs:
+        plain = {"node_index": element["data-node-index"], "text": plain_text}
+    else:
+        plain = {"text": plain_text}
+    return plain
+
+
+def plain_content(readability_content, content_digests, node_indexes):
+    # Load article as DOM
+    soup = BeautifulSoup(readability_content, 'html.parser')
+    # Make all elements plain
+    elements = plain_elements(soup.contents, content_digests, node_indexes)
+    if node_indexes:
+        # Add node index attributes to nodes
+        elements = [add_node_indexes(element) for element in elements]
+    # Replace article contents with plain elements
+    soup.contents = elements
+    return str(soup)
+
+
+def plain_elements(elements, content_digests, node_indexes):
+    # Get plain content versions of all elements
+    elements = [plain_element(element, content_digests, node_indexes)
+                for element in elements]
+    if content_digests:
+        # Add content digest attribute to nodes
+        elements = [add_content_digest(element) for element in elements]
+    return elements
+
+
+def plain_element(element, content_digests, node_indexes):
+    # For lists, we make each item plain text
+    if is_leaf(element):
+        # For leaf node elements, extract the text content, discarding any HTML tags
+        # 1. Get element contents as text
+        plain_text = element.get_text()
+        # 2. Normalise the extracted text string to a canonical representation
+        plain_text = normalise_text(plain_text)
+        # 3. Update element content to be plain text
+        element.string = plain_text
+    elif is_text(element):
+        if is_non_printing(element):
+            # The simplified HTML may have come from Readability.js so might
+            # have non-printing text (e.g. Comment or CData). In this case, we
+            # keep the structure, but ensure that the string is empty.
+            element = type(element)("")
+        else:
+            plain_text = element.string
+            plain_text = normalise_text(plain_text)
+            element = type(element)(plain_text)
+    else:
+        # If not a leaf node or leaf type call recursively on child nodes, replacing
+        element.contents = plain_elements(element.contents, content_digests, node_indexes)
+    return element
+
+
+def add_node_indexes(element, node_index="0"):
+    # Can't add attributes to string types
+    if is_text(element):
+        return element
+    # Add index to current element
+    element["data-node-index"] = node_index
+    # Add index to child elements
+    for local_idx, child in enumerate(
+            [c for c in element.contents if not is_text(c)], start=1):
+        # Can't add attributes to leaf string types
+        child_index = "{stem}.{local}".format(
+            stem=node_index, local=local_idx)
+        add_node_indexes(child, node_index=child_index)
+    return element
+
+
+def normalise_text(text):
+    """Normalise unicode and whitespace."""
+    # Normalise unicode first to try and standardise whitespace characters as much as possible before normalising them
+    text = strip_control_characters(text)
+    text = normalise_unicode(text)
+    text = normalise_whitespace(text)
+    return text
+
+
+def strip_control_characters(text):
+    """Strip out unicode control characters which might break the parsing."""
+    # Unicode control characters
+    #   [Cc]: Other, Control [includes new lines]
+    #   [Cf]: Other, Format
+    #   [Cn]: Other, Not Assigned
+    #   [Co]: Other, Private Use
+    #   [Cs]: Other, Surrogate
+    control_chars = set(['Cc', 'Cf', 'Cn', 'Co', 'Cs'])
+    retained_chars = ['\t', '\n', '\r', '\f']
+
+    # Remove non-printing control characters
+    return "".join(["" if (unicodedata.category(char) in control_chars) and (char not in retained_chars) else char for char in text])
+
+
+def normalise_unicode(text):
+    """Normalise unicode such that things that are visually equivalent map to the same unicode string where possible."""
+    normal_form = "NFKC"
+    text = unicodedata.normalize(normal_form, text)
+    return text
+
+
+def normalise_whitespace(text):
+    """Replace runs of whitespace characters with a single space as this is what happens when HTML text is displayed."""
+    text = regex.sub(r"\s+", " ", text)
+    # Remove leading and trailing whitespace
+    text = text.strip()
+    return text
+
+def is_leaf(element):
+    return (element.name in ['p', 'li'])
+
+
+def is_text(element):
+    return isinstance(element, NavigableString)
+
+
+def is_non_printing(element):
+    return any(isinstance(element, _e) for _e in [Comment, CData])
+
+
+def add_content_digest(element):
+    if not is_text(element):
+        element["data-content-digest"] = content_digest(element)
+    return element
+
+
+def content_digest(element):
+    if is_text(element):
+        # Hash
+        trimmed_string = element.string.strip()
+        if trimmed_string == "":
+            digest = ""
+        else:
+            digest = hashlib.sha256(trimmed_string.encode('utf-8')).hexdigest()
+    else:
+        contents = element.contents
+        num_contents = len(contents)
+        if num_contents == 0:
+            # No hash when no child elements exist
+            digest = ""
+        elif num_contents == 1:
+            # If single child, use digest of child
+            digest = content_digest(contents[0])
+        else:
+            # Build content digest from the "non-empty" digests of child nodes
+            digest = hashlib.sha256()
+            child_digests = list(
+                filter(lambda x: x != "", [content_digest(content) for content in contents]))
+            for child in child_digests:
+                digest.update(child.encode('utf-8'))
+            digest = digest.hexdigest()
+    return digest

api/migrations/versions/2beac44e5f5f_add_is_universal_in_apps.py

+"""add is_universal in apps
+
+Revision ID: 2beac44e5f5f
+Revises: d3d503a3471c
+Create Date: 2023-07-07 12:11:29.156057
+
+"""
+from alembic import op
+import sqlalchemy as sa
+
+
+# revision identifiers, used by Alembic.
+revision = '2beac44e5f5f'
+down_revision = 'a5b56fb053ef'
+branch_labels = None
+depends_on = None
+
+
+def upgrade():
+    # ### commands auto generated by Alembic - please adjust! ###
+    with op.batch_alter_table('apps', schema=None) as batch_op:
+        batch_op.add_column(sa.Column('is_universal', sa.Boolean(), server_default=sa.text('false'), nullable=False))
+
+    # ### end Alembic commands ###
+
+
+def downgrade():
+    # ### commands auto generated by Alembic - please adjust! ###
+    with op.batch_alter_table('apps', schema=None) as batch_op:
+        batch_op.drop_column('is_universal')
+
+    # ### end Alembic commands ###

api/migrations/versions/7ce5a52e4eee_add_tool_providers.py

+"""add tool providers
+
+Revision ID: 7ce5a52e4eee
+Revises: 2beac44e5f5f
+Create Date: 2023-07-10 10:26:50.074515
+
+"""
+from alembic import op
+import sqlalchemy as sa
+from sqlalchemy.dialects import postgresql
+
+# revision identifiers, used by Alembic.
+revision = '7ce5a52e4eee'
+down_revision = '2beac44e5f5f'
+branch_labels = None
+depends_on = None
+
+
+def upgrade():
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.create_table('tool_providers',
+    sa.Column('id', postgresql.UUID(), server_default=sa.text('uuid_generate_v4()'), nullable=False),
+    sa.Column('tenant_id', postgresql.UUID(), nullable=False),
+    sa.Column('tool_name', sa.String(length=40), nullable=False),
+    sa.Column('encrypted_credentials', sa.Text(), nullable=True),
+    sa.Column('is_enabled', sa.Boolean(), server_default=sa.text('false'), nullable=False),
+    sa.Column('created_at', sa.DateTime(), server_default=sa.text('CURRENT_TIMESTAMP(0)'), nullable=False),
+    sa.Column('updated_at', sa.DateTime(), server_default=sa.text('CURRENT_TIMESTAMP(0)'), nullable=False),
+    sa.PrimaryKeyConstraint('id', name='tool_provider_pkey'),
+    sa.UniqueConstraint('tenant_id', 'tool_name', name='unique_tool_provider_tool_name')
+    )
+    with op.batch_alter_table('app_model_configs', schema=None) as batch_op:
+        batch_op.add_column(sa.Column('sensitive_word_avoidance', sa.Text(), nullable=True))
+
+    # ### end Alembic commands ###
+
+
+def downgrade():
+    # ### commands auto generated by Alembic - please adjust! ###
+    with op.batch_alter_table('app_model_configs', schema=None) as batch_op:
+        batch_op.drop_column('sensitive_word_avoidance')
+
+    op.drop_table('tool_providers')
+    # ### end Alembic commands ###

api/models/model.py

@@ -40,6 +40,7 @@ class App(db.Model):
     api_rph = db.Column(db.Integer, nullable=False)
     is_demo = db.Column(db.Boolean, nullable=False, server_default=db.text('false'))
     is_public = db.Column(db.Boolean, nullable=False, server_default=db.text('false'))
+    is_universal = db.Column(db.Boolean, nullable=False, server_default=db.text('false'))
     created_at = db.Column(db.DateTime, nullable=False, server_default=db.text('CURRENT_TIMESTAMP(0)'))
     updated_at = db.Column(db.DateTime, nullable=False, server_default=db.text('CURRENT_TIMESTAMP(0)'))
 
@@ -88,6 +89,7 @@ class AppModelConfig(db.Model):
     user_input_form = db.Column(db.Text)
     pre_prompt = db.Column(db.Text)
     agent_mode = db.Column(db.Text)
+    sensitive_word_avoidance = db.Column(db.Text)
 
     @property
     def app(self):
@@ -116,14 +118,35 @@ class AppModelConfig(db.Model):
     def more_like_this_dict(self) -> dict:
         return json.loads(self.more_like_this) if self.more_like_this else {"enabled": False}
 
+    @property
+    def sensitive_word_avoidance_dict(self) -> dict:
+        return json.loads(self.sensitive_word_avoidance) if self.sensitive_word_avoidance \
+            else {"enabled": False, "words": [], "canned_response": []}
+
     @property
     def user_input_form_list(self) -> dict:
         return json.loads(self.user_input_form) if self.user_input_form else []
 
     @property
     def agent_mode_dict(self) -> dict:
-        return json.loads(self.agent_mode) if self.agent_mode else {"enabled": False, "tools": []}
-
+        return json.loads(self.agent_mode) if self.agent_mode else {"enabled": False, "strategy": None, "tools": []}
+
+    def to_dict(self) -> dict:
+        return {
+            "provider": "",
+            "model_id": "",
+            "configs": {},
+            "opening_statement": self.opening_statement,
+            "suggested_questions": self.suggested_questions_list,
+            "suggested_questions_after_answer": self.suggested_questions_after_answer_dict,
+            "speech_to_text": self.speech_to_text_dict,
+            "more_like_this": self.more_like_this_dict,
+            "sensitive_word_avoidance": self.sensitive_word_avoidance_dict,
+            "model": self.model_dict,
+            "user_input_form": self.user_input_form_list,
+            "pre_prompt": self.pre_prompt,
+            "agent_mode": self.agent_mode_dict
+        }
 
 class RecommendedApp(db.Model):
     __tablename__ = 'recommended_apps'
@@ -203,7 +226,7 @@ class Conversation(db.Model):
     system_instruction_tokens = db.Column(db.Integer, nullable=False, server_default=db.text('0'))
     status = db.Column(db.String(255), nullable=False)
     from_source = db.Column(db.String(255), nullable=False)
-    from_end_user_id = db.Column(UUID)
+    from_end_user_id = db.Column(UUID, db.ForeignKey('end_users.id'))
     from_account_id = db.Column(UUID)
     read_at = db.Column(db.DateTime)
     read_account_id = db.Column(UUID)
@@ -213,6 +236,8 @@ class Conversation(db.Model):
     messages = db.relationship("Message", backref="conversation", lazy='select', passive_deletes="all")
     message_annotations = db.relationship("MessageAnnotation", backref="conversation", lazy='select', passive_deletes="all")
 
+    end_user = db.relationship("EndUser", backref="conversations")
+
     is_deleted = db.Column(db.Boolean, nullable=False, server_default=db.text('false'))
 
     @property
@@ -235,6 +260,9 @@ class Conversation(db.Model):
                     if 'speech_to_text' in override_model_configs else {"enabled": False}
                 model_config['more_like_this'] = override_model_configs['more_like_this'] \
                     if 'more_like_this' in override_model_configs else {"enabled": False}
+                model_config['sensitive_word_avoidance'] = override_model_configs['sensitive_word_avoidance'] \
+                    if 'sensitive_word_avoidance' in override_model_configs \
+                    else {"enabled": False, "words": [], "canned_response": []}
                 model_config['user_input_form'] = override_model_configs['user_input_form']
             else:
                 model_config['configs'] = override_model_configs
@@ -251,6 +279,7 @@ class Conversation(db.Model):
             model_config['suggested_questions_after_answer'] = app_model_config.suggested_questions_after_answer_dict
             model_config['speech_to_text'] = app_model_config.speech_to_text_dict
             model_config['more_like_this'] = app_model_config.more_like_this_dict
+            model_config['sensitive_word_avoidance'] = app_model_config.sensitive_word_avoidance_dict
             model_config['user_input_form'] = app_model_config.user_input_form_list
 
         model_config['model_id'] = self.model_id
@@ -391,6 +420,11 @@ class Message(db.Model):
     def in_debug_mode(self):
         return self.override_model_configs is not None
 
+    @property
+    def agent_thoughts(self):
+        return db.session.query(MessageAgentThought).filter(MessageAgentThought.message_id == self.id)\
+            .order_by(MessageAgentThought.position.asc()).all()
+
 
 class MessageFeedback(db.Model):
     __tablename__ = 'message_feedbacks'

api/models/tool.py

+import json
+from enum import Enum
+
+from sqlalchemy.dialects.postgresql import UUID
+
+from extensions.ext_database import db
+
+
+class ToolProviderName(Enum):
+    SERPAPI = 'serpapi'
+
+    @staticmethod
+    def value_of(value):
+        for member in ToolProviderName:
+            if member.value == value:
+                return member
+        raise ValueError(f"No matching enum found for value '{value}'")
+
+
+class ToolProvider(db.Model):
+    __tablename__ = 'tool_providers'
+    __table_args__ = (
+        db.PrimaryKeyConstraint('id', name='tool_provider_pkey'),
+        db.UniqueConstraint('tenant_id', 'tool_name', name='unique_tool_provider_tool_name')
+    )
+
+    id = db.Column(UUID, server_default=db.text('uuid_generate_v4()'))
+    tenant_id = db.Column(UUID, nullable=False)
+    tool_name = db.Column(db.String(40), nullable=False)
+    encrypted_credentials = db.Column(db.Text, nullable=True)
+    is_enabled = db.Column(db.Boolean, nullable=False, server_default=db.text('false'))
+    created_at = db.Column(db.DateTime, nullable=False, server_default=db.text('CURRENT_TIMESTAMP(0)'))
+    updated_at = db.Column(db.DateTime, nullable=False, server_default=db.text('CURRENT_TIMESTAMP(0)'))
+
+    @property
+    def credentials_is_set(self):
+        """
+         Returns True if the encrypted_config is not None, indicating that the token is set.
+         """
+        return self.encrypted_credentials is not None
+
+    @property
+    def credentials(self):
+        """
+        Returns the decrypted config.
+        """
+        return json.loads(self.encrypted_credentials) if self.encrypted_credentials is not None else None

api/requirements.txt

@@ -10,8 +10,8 @@ flask-session2==1.3.1
 flask-cors==3.0.10
 gunicorn~=20.1.0
 gevent~=22.10.2
-langchain==0.0.230
-openai~=0.27.5
+langchain==0.0.239
+openai~=0.27.8
 psycopg2-binary~=2.9.6
 pycryptodome==3.17
 python-dotenv==1.0.0
@@ -36,3 +36,8 @@ pypdfium2==4.16.0
 resend~=0.5.1
 pyjwt~=2.6.0
 anthropic~=0.3.4
+newspaper3k==0.2.8
+google-api-python-client==2.90.0
+wikipedia==1.4.0
+readabilipy==0.2.0
+google-search-results==2.4.2
\ No newline at end of file

api/services/app_model_config_service.py

 import re
 import uuid
 
+from core.agent.agent_executor import PlanningStrategy
 from core.constant import llm_constant
 from models.account import Account
 from services.dataset_service import DatasetService
@@ -31,6 +32,16 @@ MODELS_BY_APP_MODE = {
     ]
 }
 
+SUPPORT_AGENT_MODELS = [
+    "gpt-4",
+    "gpt-4-32k",
+    "gpt-3.5-turbo",
+    "gpt-3.5-turbo-16k",
+]
+
+SUPPORT_TOOLS = ["dataset", "google_search", "web_reader", "wikipedia"]
+
+
 class AppModelConfigService:
     @staticmethod
     def is_dataset_exists(account: Account, dataset_id: str) -> bool:
@@ -58,7 +69,8 @@ class AppModelConfigService:
         if not isinstance(cp["max_tokens"], int) or cp["max_tokens"] <= 0 or cp["max_tokens"] > \
                 llm_constant.max_context_token_length[model_name]:
             raise ValueError(
-                "max_tokens must be an integer greater than 0 and not exceeding the maximum value of the corresponding model")
+                "max_tokens must be an integer greater than 0 "
+                "and not exceeding the maximum value of the corresponding model")
 
         # temperature
         if 'temperature' not in cp:
@@ -149,11 +161,6 @@ class AppModelConfigService:
         if not isinstance(config["speech_to_text"]["enabled"], bool):
             raise ValueError("enabled in speech_to_text must be of boolean type")
 
-        provider_name = LLMBuilder.get_default_provider(account.current_tenant_id, 'whisper-1')
-
-        if config["speech_to_text"]["enabled"] and provider_name != 'openai':
-            raise ValueError("provider not support speech to text")
-
         # more_like_this
         if 'more_like_this' not in config or not config["more_like_this"]:
             config["more_like_this"] = {
@@ -169,6 +176,33 @@ class AppModelConfigService:
         if not isinstance(config["more_like_this"]["enabled"], bool):
             raise ValueError("enabled in more_like_this must be of boolean type")
 
+        # sensitive_word_avoidance
+        if 'sensitive_word_avoidance' not in config or not config["sensitive_word_avoidance"]:
+            config["sensitive_word_avoidance"] = {
+                "enabled": False
+            }
+
+        if not isinstance(config["sensitive_word_avoidance"], dict):
+            raise ValueError("sensitive_word_avoidance must be of dict type")
+
+        if "enabled" not in config["sensitive_word_avoidance"] or not config["sensitive_word_avoidance"]["enabled"]:
+            config["sensitive_word_avoidance"]["enabled"] = False
+
+        if not isinstance(config["sensitive_word_avoidance"]["enabled"], bool):
+            raise ValueError("enabled in sensitive_word_avoidance must be of boolean type")
+
+        if "words" not in config["sensitive_word_avoidance"] or not config["sensitive_word_avoidance"]["words"]:
+            config["sensitive_word_avoidance"]["words"] = ""
+
+        if not isinstance(config["sensitive_word_avoidance"]["words"], str):
+            raise ValueError("words in sensitive_word_avoidance must be of string type")
+
+        if "canned_response" not in config["sensitive_word_avoidance"] or not config["sensitive_word_avoidance"]["canned_response"]:
+            config["sensitive_word_avoidance"]["canned_response"] = ""
+
+        if not isinstance(config["sensitive_word_avoidance"]["canned_response"], str):
+            raise ValueError("canned_response in sensitive_word_avoidance must be of string type")
+
         # model
         if 'model' not in config:
             raise ValueError("model is required")
@@ -274,6 +308,12 @@ class AppModelConfigService:
         if not isinstance(config["agent_mode"]["enabled"], bool):
             raise ValueError("enabled in agent_mode must be of boolean type")
 
+        if "strategy" not in config["agent_mode"] or not config["agent_mode"]["strategy"]:
+            config["agent_mode"]["strategy"] = PlanningStrategy.ROUTER.value
+
+        if config["agent_mode"]["strategy"] not in [member.value for member in list(PlanningStrategy.__members__.values())]:
+            raise ValueError("strategy in agent_mode must be in the specified strategy list")
+
         if "tools" not in config["agent_mode"] or not config["agent_mode"]["tools"]:
             config["agent_mode"]["tools"] = []
 
@@ -282,8 +322,8 @@ class AppModelConfigService:
 
         for tool in config["agent_mode"]["tools"]:
             key = list(tool.keys())[0]
-            if key not in ["sensitive-word-avoidance", "dataset"]:
-                raise ValueError("Keys in agent_mode.tools list can only be 'sensitive-word-avoidance' or 'dataset'")
+            if key not in SUPPORT_TOOLS:
+                raise ValueError("Keys in agent_mode.tools must be in the specified tool list")
 
             tool_item = tool[key]
 
@@ -293,19 +333,7 @@ class AppModelConfigService:
             if not isinstance(tool_item["enabled"], bool):
                 raise ValueError("enabled in agent_mode.tools must be of boolean type")
 
-            if key == "sensitive-word-avoidance":
-                if "words" not in tool_item or not tool_item["words"]:
-                    tool_item["words"] = ""
-
-                if not isinstance(tool_item["words"], str):
-                    raise ValueError("words in sensitive-word-avoidance must be of string type")
-
-                if "canned_response" not in tool_item or not tool_item["canned_response"]:
-                    tool_item["canned_response"] = ""
-
-                if not isinstance(tool_item["canned_response"], str):
-                    raise ValueError("canned_response in sensitive-word-avoidance must be of string type")
-            elif key == "dataset":
+            if key == "dataset":
                 if 'id' not in tool_item:
                     raise ValueError("id is required in dataset")
 
@@ -324,6 +352,7 @@ class AppModelConfigService:
             "suggested_questions_after_answer": config["suggested_questions_after_answer"],
             "speech_to_text": config["speech_to_text"],
             "more_like_this": config["more_like_this"],
+            "sensitive_word_avoidance": config["sensitive_word_avoidance"],
             "model": {
                 "provider": config["model"]["provider"],
                 "name": config["model"]["name"],

api/services/completion_service.py

@@ -37,6 +37,8 @@ class CompletionService:
         if not query:
             raise ValueError('query is required')
 
+        query = query.replace('\x00', '')
+
         conversation_id = args['conversation_id'] if 'conversation_id' in args else None
 
         conversation = None
@@ -140,6 +142,7 @@ class CompletionService:
                     suggested_questions=json.dumps(model_config['suggested_questions']),
                     suggested_questions_after_answer=json.dumps(model_config['suggested_questions_after_answer']),
                     more_like_this=json.dumps(model_config['more_like_this']),
+                    sensitive_word_avoidance=json.dumps(model_config['sensitive_word_avoidance']),
                     model=json.dumps(model_config['model']),
                     user_input_form=json.dumps(model_config['user_input_form']),
                     pre_prompt=model_config['pre_prompt'],
@@ -171,7 +174,7 @@ class CompletionService:
 
         generate_worker_thread.start()
 
-        # wait for 5 minutes to close the thread
+        # wait for 10 minutes to close the thread
         cls.countdown_and_close(generate_worker_thread, pubsub, user, generate_task_id)
 
         return cls.compact_response(pubsub, streaming)
@@ -179,9 +182,9 @@ class CompletionService:
     @classmethod
     def get_real_user_instead_of_proxy_obj(cls, user: Union[Account, EndUser]):
         if isinstance(user, Account):
-            user = db.session.query(Account).get(user.id)
+            user = db.session.query(Account).filter(Account.id == user.id).first()
         elif isinstance(user, EndUser):
-            user = db.session.query(EndUser).get(user.id)
+            user = db.session.query(EndUser).filter(EndUser.id == user.id).first()
         else:
             raise Exception("Unknown user type")
 
@@ -227,12 +230,15 @@ class CompletionService:
 
     @classmethod
     def countdown_and_close(cls, worker_thread, pubsub, user, generate_task_id) -> threading.Thread:
-        # wait for 5 minutes to close the thread
-        timeout = 300
+        # wait for 10 minutes to close the thread
+        timeout = 600
 
         def close_pubsub():
             sleep_iterations = 0
             while sleep_iterations < timeout and worker_thread.is_alive():
+                if sleep_iterations > 0 and sleep_iterations % 10 == 0:
+                    PubHandler.ping(user, generate_task_id)
+
                 time.sleep(1)
                 sleep_iterations += 1
 
@@ -370,7 +376,7 @@ class CompletionService:
                     if len(value) > max_length:
                         raise ValueError(f'{variable} in input form must be less than {max_length} characters')
 
-            filtered_inputs[variable] = value
+            filtered_inputs[variable] = value.replace('\x00', '') if value else None
 
         return filtered_inputs
 
@@ -385,7 +391,7 @@ class CompletionService:
                         result = json.loads(result)
                         if result.get('error'):
                             cls.handle_error(result)
-
+                        if 'data' in result:
                             return cls.get_message_response_data(result.get('data'))
             except ValueError as e:
                 if e.args[0] != "I/O operation on closed file.":  # ignore this error
@@ -419,6 +425,10 @@ class CompletionService:
                                 yield "data: " + json.dumps(cls.get_chain_response_data(result.get('data'))) + "\n\n"
                             elif event == 'agent_thought':
                                 yield "data: " + json.dumps(cls.get_agent_thought_response_data(result.get('data'))) + "\n\n"
+                            elif event == 'ping':
+                                yield "event: ping\n\n"
+                            else:
+                                yield "data: " + json.dumps(result) + "\n\n"
                 except ValueError as e:
                     if e.args[0] != "I/O operation on closed file.":  # ignore this error
                         logging.exception(e)
@@ -468,16 +478,14 @@ class CompletionService:
     def get_agent_thought_response_data(cls, data: dict):
         response_data = {
             'event': 'agent_thought',
-            'id': data.get('agent_thought_id'),
+            'id': data.get('id'),
             'chain_id': data.get('chain_id'),
             'task_id': data.get('task_id'),
             'message_id': data.get('message_id'),
             'position': data.get('position'),
             'thought': data.get('thought'),
-            'tool': data.get('tool'),  # todo use real dataset obj replace it
+            'tool': data.get('tool'),
             'tool_input': data.get('tool_input'),
-            'observation': data.get('observation'),
-            'answer': data.get('answer') if not data.get('thought') else '',
             'created_at': int(time.time())
         }
 

web/app/(commonLayout)/explore/chat/page.tsx

+import type { FC } from 'react'
+import React from 'react'
+import UniversalChat from '@/app/components/explore/universal-chat'
+
+const Chat: FC = () => {
+  return (
+    <div className='h-full p-2'>
+      <UniversalChat />
+    </div>
+  )
+}
+
+export default React.memo(Chat)

web/app/(commonLayout)/layout.tsx

@@ -5,6 +5,8 @@ import { AppContextProvider } from '@/context/app-context'
 import GA, { GaType } from '@/app/components/base/ga'
 import HeaderWrapper from '@/app/components/header/HeaderWrapper'
 import Header from '@/app/components/header'
+import { EventEmitterContextProvider } from '@/context/event-emitter'
+import { ProviderContextProvider } from '@/context/provider-context'
 
 const Layout = ({ children }: { children: ReactNode }) => {
   return (
@@ -12,10 +14,14 @@ const Layout = ({ children }: { children: ReactNode }) => {
       <GA gaType={GaType.admin} />
       <SwrInitor>
         <AppContextProvider>
+          <EventEmitterContextProvider>
+            <ProviderContextProvider>
               <HeaderWrapper>
                 <Header />
               </HeaderWrapper>
               {children}
+            </ProviderContextProvider>
+          </EventEmitterContextProvider>
         </AppContextProvider>
       </SwrInitor>
     </>

web/app/components/app/chat/answer/index.tsx

+'use client'
+import type { FC } from 'react'
+import React, { useState } from 'react'
+import { useTranslation } from 'react-i18next'
+import { useContext } from 'use-context-selector'
+import { UserCircleIcon } from '@heroicons/react/24/solid'
+import cn from 'classnames'
+import type { DisplayScene, FeedbackFunc, Feedbacktype, IChatItem, SubmitAnnotationFunc, ThoughtItem } from '../type'
+import { randomString } from '../../../app-sidebar/basic'
+import OperationBtn from '../operation'
+import LoadingAnim from '../loading-anim'
+import { EditIcon, EditIconSolid, OpeningStatementIcon, RatingIcon } from '../icon-component'
+import s from '../style.module.css'
+import MoreInfo from '../more-info'
+import CopyBtn from '../copy-btn'
+import Thought from '../thought'
+import type { Annotation, MessageRating } from '@/models/log'
+import AppContext from '@/context/app-context'
+import Tooltip from '@/app/components/base/tooltip'
+import { Markdown } from '@/app/components/base/markdown'
+import AutoHeightTextarea from '@/app/components/base/auto-height-textarea'
+import Button from '@/app/components/base/button'
+import type { DataSet } from '@/models/datasets'
+const Divider: FC<{ name: string }> = ({ name }) => {
+  const { t } = useTranslation()
+  return <div className='flex items-center my-2'>
+    <span className='text-xs text-gray-500 inline-flex items-center mr-2'>
+      <EditIconSolid className='mr-1' />{t('appLog.detail.annotationTip', { user: name })}
+    </span>
+    <div className='h-[1px] bg-gray-200 flex-1'></div>
+  </div>
+}
+const IconWrapper: FC<{ children: React.ReactNode | string }> = ({ children }) => {
+  return <div className={'rounded-lg h-6 w-6 flex items-center justify-center hover:bg-gray-100'}>
+    {children}
+  </div>
+}
+export type IAnswerProps = {
+  item: IChatItem
+  feedbackDisabled: boolean
+  isHideFeedbackEdit: boolean
+  onFeedback?: FeedbackFunc
+  onSubmitAnnotation?: SubmitAnnotationFunc
+  displayScene: DisplayScene
+  isResponsing?: boolean
+  answerIconClassName?: string
+  thoughts?: ThoughtItem[]
+  isThinking?: boolean
+  dataSets?: DataSet[]
+}
+// The component needs to maintain its own state to control whether to display input component
+const Answer: FC<IAnswerProps> = ({ item, feedbackDisabled = false, isHideFeedbackEdit = false, onFeedback, onSubmitAnnotation, displayScene = 'web', isResponsing, answerIconClassName, thoughts, isThinking, dataSets }) => {
+  const { id, content, more, feedback, adminFeedback, annotation: initAnnotation } = item
+  const [showEdit, setShowEdit] = useState(false)
+  const [loading, setLoading] = useState(false)
+  const [annotation, setAnnotation] = useState<Annotation | undefined | null>(initAnnotation)
+  const [inputValue, setInputValue] = useState<string>(initAnnotation?.content ?? '')
+  const [localAdminFeedback, setLocalAdminFeedback] = useState<Feedbacktype | undefined | null>(adminFeedback)
+  const { userProfile } = useContext(AppContext)
+  const { t } = useTranslation()
+
+  /**
+ * Render feedback results (distinguish between users and administrators)
+ * User reviews cannot be cancelled in Console
+ * @param rating feedback result
+ * @param isUserFeedback Whether it is user's feedback
+ * @param isWebScene Whether it is web scene
+ * @returns comp
+ */
+  const renderFeedbackRating = (rating: MessageRating | undefined, isUserFeedback = true, isWebScene = true) => {
+    if (!rating)
+      return null
+
+    const isLike = rating === 'like'
+    const ratingIconClassname = isLike ? 'text-primary-600 bg-primary-100 hover:bg-primary-200' : 'text-red-600 bg-red-100 hover:bg-red-200'
+    const UserSymbol = <UserCircleIcon className='absolute top-[-2px] left-[18px] w-3 h-3 rounded-lg text-gray-400 bg-white' />
+    // The tooltip is always displayed, but the content is different for different scenarios.
+    return (
+      <Tooltip
+        selector={`user-feedback-${randomString(16)}`}
+        content={((isWebScene || (!isUserFeedback && !isWebScene)) ? isLike ? t('appDebug.operation.cancelAgree') : t('appDebug.operation.cancelDisagree') : (!isWebScene && isUserFeedback) ? `${t('appDebug.operation.userAction')}${isLike ? t('appDebug.operation.agree') : t('appDebug.operation.disagree')}` : '') as string}
+      >
+        <div
+          className={`relative box-border flex items-center justify-center h-7 w-7 p-0.5 rounded-lg bg-white cursor-pointer text-gray-500 hover:text-gray-800 ${(!isWebScene && isUserFeedback) ? '!cursor-default' : ''}`}
+          style={{ boxShadow: '0px 4px 6px -1px rgba(0, 0, 0, 0.1), 0px 2px 4px -2px rgba(0, 0, 0, 0.05)' }}
+          {...((isWebScene || (!isUserFeedback && !isWebScene))
+            ? {
+              onClick: async () => {
+                const res = await onFeedback?.(id, { rating: null })
+                if (res && !isWebScene)
+                  setLocalAdminFeedback({ rating: null })
+              },
+            }
+            : {})}
+        >
+          <div className={`${ratingIconClassname} rounded-lg h-6 w-6 flex items-center justify-center`}>
+            <RatingIcon isLike={isLike} />
+          </div>
+          {!isWebScene && isUserFeedback && UserSymbol}
+        </div>
+      </Tooltip>
+    )
+  }
+
+  /**
+   * Different scenarios have different operation items.
+   * @param isWebScene  Whether it is web scene
+   * @returns comp
+   */
+  const renderItemOperation = (isWebScene = true) => {
+    const userOperation = () => {
+      return feedback?.rating
+        ? null
+        : <div className='flex gap-1'>
+          <Tooltip selector={`user-feedback-${randomString(16)}`} content={t('appLog.detail.operation.like') as string}>
+            {OperationBtn({ innerContent: <IconWrapper><RatingIcon isLike={true} /></IconWrapper>, onClick: () => onFeedback?.(id, { rating: 'like' }) })}
+          </Tooltip>
+          <Tooltip selector={`user-feedback-${randomString(16)}`} content={t('appLog.detail.operation.dislike') as string}>
+            {OperationBtn({ innerContent: <IconWrapper><RatingIcon isLike={false} /></IconWrapper>, onClick: () => onFeedback?.(id, { rating: 'dislike' }) })}
+          </Tooltip>
+        </div>
+    }
+
+    const adminOperation = () => {
+      return <div className='flex gap-1'>
+        <Tooltip selector={`user-feedback-${randomString(16)}`} content={t('appLog.detail.operation.addAnnotation') as string}>
+          {OperationBtn({
+            innerContent: <IconWrapper><EditIcon className='hover:text-gray-800' /></IconWrapper>,
+            onClick: () => setShowEdit(true),
+          })}
+        </Tooltip>
+        {!localAdminFeedback?.rating && <>
+          <Tooltip selector={`user-feedback-${randomString(16)}`} content={t('appLog.detail.operation.like') as string}>
+            {OperationBtn({
+              innerContent: <IconWrapper><RatingIcon isLike={true} /></IconWrapper>,
+              onClick: async () => {
+                const res = await onFeedback?.(id, { rating: 'like' })
+                if (res)
+                  setLocalAdminFeedback({ rating: 'like' })
+              },
+            })}
+          </Tooltip>
+          <Tooltip selector={`user-feedback-${randomString(16)}`} content={t('appLog.detail.operation.dislike') as string}>
+            {OperationBtn({
+              innerContent: <IconWrapper><RatingIcon isLike={false} /></IconWrapper>,
+              onClick: async () => {
+                const res = await onFeedback?.(id, { rating: 'dislike' })
+                if (res)
+                  setLocalAdminFeedback({ rating: 'dislike' })
+              },
+            })}
+          </Tooltip>
+        </>}
+      </div>
+    }
+
+    return (
+      <div className={`${s.itemOperation} flex gap-2`}>
+        {isWebScene ? userOperation() : adminOperation()}
+      </div>
+    )
+  }
+
+  return (
+    <div key={id}>
+      <div className='flex items-start'>
+        <div className={`${s.answerIcon} ${answerIconClassName} w-10 h-10 shrink-0`}>
+          {isResponsing
+            && <div className={s.typeingIcon}>
+              <LoadingAnim type='avatar' />
+            </div>
+          }
+        </div>
+        <div className={s.answerWrapWrap}>
+          <div className={`${s.answerWrap} ${showEdit ? 'w-full' : ''}`}>
+            <div className={`${s.answer} relative text-sm text-gray-900`}>
+              <div className={'ml-2 py-3 px-4 bg-gray-100 rounded-tr-2xl rounded-b-2xl'}>
+                {item.isOpeningStatement && (
+                  <div className='flex items-center mb-1 gap-1'>
+                    <OpeningStatementIcon />
+                    <div className='text-xs text-gray-500'>{t('appDebug.openingStatement.title')}</div>
+                  </div>
+                )}
+                {(thoughts && thoughts.length > 0) && (
+                  <Thought
+                    list={thoughts || []}
+                    isThinking={isThinking}
+                    dataSets={dataSets}
+                  />
+                )}
+                {(isResponsing && !content)
+                  ? (
+                    <div className='flex items-center justify-center w-6 h-5'>
+                      <LoadingAnim type='text' />
+                    </div>
+                  )
+                  : (
+                    <div>
+                      <Markdown content={content} />
+                    </div>
+                  )}
+                {!showEdit
+                  ? (annotation?.content
+                    && <>
+                      <Divider name={annotation?.account?.name || userProfile?.name} />
+                      {annotation.content}
+                    </>)
+                  : <>
+                    <Divider name={annotation?.account?.name || userProfile?.name} />
+                    <AutoHeightTextarea
+                      placeholder={t('appLog.detail.operation.annotationPlaceholder') as string}
+                      value={inputValue}
+                      onChange={e => setInputValue(e.target.value)}
+                      minHeight={58}
+                      className={`${cn(s.textArea)} !py-2 resize-none block w-full !px-3 bg-gray-50 border border-gray-200 rounded-md shadow-sm focus:outline-none focus:ring-blue-500 focus:border-blue-500 sm:text-sm text-gray-700 tracking-[0.2px]`}
+                    />
+                    <div className="mt-2 flex flex-row">
+                      <Button
+                        type='primary'
+                        className='mr-2'
+                        loading={loading}
+                        onClick={async () => {
+                          if (!inputValue)
+                            return
+                          setLoading(true)
+                          const res = await onSubmitAnnotation?.(id, inputValue)
+                          if (res)
+                            setAnnotation({ ...annotation, content: inputValue } as any)
+                          setLoading(false)
+                          setShowEdit(false)
+                        }}>{t('common.operation.confirm')}</Button>
+                      <Button
+                        onClick={() => {
+                          setInputValue(annotation?.content ?? '')
+                          setShowEdit(false)
+                        }}>{t('common.operation.cancel')}</Button>
+                    </div>
+                  </>
+                }
+              </div>
+              <div className='absolute top-[-14px] right-[-14px] flex flex-row justify-end gap-1'>
+                {!item.isOpeningStatement && (
+                  <CopyBtn
+                    value={content}
+                    className={cn(s.copyBtn, 'mr-1')}
+                  />
+                )}
+                {!feedbackDisabled && !item.feedbackDisabled && renderItemOperation(displayScene !== 'console')}
+                {/* Admin feedback is displayed only in the background. */}
+                {!feedbackDisabled && renderFeedbackRating(localAdminFeedback?.rating, false, false)}
+                {/* User feedback must be displayed */}
+                {!feedbackDisabled && renderFeedbackRating(feedback?.rating, !isHideFeedbackEdit, displayScene !== 'console')}
+              </div>
+            </div>
+            {more && <MoreInfo more={more} isQuestion={false} />}
+          </div>
+        </div>
+      </div>
+    </div>
+  )
+}
+export default React.memo(Answer)

web/app/components/app/chat/icon-component/index.tsx

+import type { FC } from 'react'
+import { HandThumbDownIcon, HandThumbUpIcon } from '@heroicons/react/24/outline'
+
+export const stopIcon = (
+  <svg width="14" height="14" viewBox="0 0 14 14" fill="none" xmlns="http://www.w3.org/2000/svg">
+    <path fillRule="evenodd" clipRule="evenodd" d="M7.00004 0.583313C3.45621 0.583313 0.583374 3.45615 0.583374 6.99998C0.583374 10.5438 3.45621 13.4166 7.00004 13.4166C10.5439 13.4166 13.4167 10.5438 13.4167 6.99998C13.4167 3.45615 10.5439 0.583313 7.00004 0.583313ZM4.73029 4.98515C4.66671 5.10993 4.66671 5.27328 4.66671 5.59998V8.39998C4.66671 8.72668 4.66671 8.89003 4.73029 9.01481C4.78621 9.12457 4.87545 9.21381 4.98521 9.26973C5.10999 9.33331 5.27334 9.33331 5.60004 9.33331H8.40004C8.72674 9.33331 8.89009 9.33331 9.01487 9.26973C9.12463 9.21381 9.21387 9.12457 9.2698 9.01481C9.33337 8.89003 9.33337 8.72668 9.33337 8.39998V5.59998C9.33337 5.27328 9.33337 5.10993 9.2698 4.98515C9.21387 4.87539 9.12463 4.78615 9.01487 4.73023C8.89009 4.66665 8.72674 4.66665 8.40004 4.66665H5.60004C5.27334 4.66665 5.10999 4.66665 4.98521 4.73023C4.87545 4.78615 4.78621 4.87539 4.73029 4.98515Z" fill="#667085" />
+  </svg>
+)
+
+export const OpeningStatementIcon: FC<{ className?: string }> = ({ className }) => (
+  <svg className={className} width="12" height="12" viewBox="0 0 12 12" fill="none" xmlns="http://www.w3.org/2000/svg">
+    <path fillRule="evenodd" clipRule="evenodd" d="M6.25002 1C3.62667 1 1.50002 3.12665 1.50002 5.75C1.50002 6.28 1.58702 6.79071 1.7479 7.26801C1.7762 7.35196 1.79285 7.40164 1.80368 7.43828L1.80722 7.45061L1.80535 7.45452C1.79249 7.48102 1.77339 7.51661 1.73766 7.58274L0.911727 9.11152C0.860537 9.20622 0.807123 9.30503 0.770392 9.39095C0.733879 9.47635 0.674738 9.63304 0.703838 9.81878C0.737949 10.0365 0.866092 10.2282 1.05423 10.343C1.21474 10.4409 1.38213 10.4461 1.475 10.4451C1.56844 10.444 1.68015 10.4324 1.78723 10.4213L4.36472 10.1549C4.406 10.1506 4.42758 10.1484 4.44339 10.1472L4.44542 10.147L4.45161 10.1492C4.47103 10.1562 4.49738 10.1663 4.54285 10.1838C5.07332 10.3882 5.64921 10.5 6.25002 10.5C8.87338 10.5 11 8.37335 11 5.75C11 3.12665 8.87338 1 6.25002 1ZM4.48481 4.29111C5.04844 3.81548 5.7986 3.9552 6.24846 4.47463C6.69831 3.9552 7.43879 3.82048 8.01211 4.29111C8.58544 4.76175 8.6551 5.562 8.21247 6.12453C7.93825 6.47305 7.24997 7.10957 6.76594 7.54348C6.58814 7.70286 6.49924 7.78255 6.39255 7.81466C6.30103 7.84221 6.19589 7.84221 6.10436 7.81466C5.99767 7.78255 5.90878 7.70286 5.73098 7.54348C5.24694 7.10957 4.55867 6.47305 4.28444 6.12453C3.84182 5.562 3.92117 4.76675 4.48481 4.29111Z" fill="#667085" />
+  </svg>
+)
+
+export const RatingIcon: FC<{ isLike: boolean }> = ({ isLike }) => {
+  return isLike ? <HandThumbUpIcon className='w-4 h-4' /> : <HandThumbDownIcon className='w-4 h-4' />
+}
+
+export const EditIcon: FC<{ className?: string }> = ({ className }) => {
+  return <svg width="16" height="16" viewBox="0 0 16 16" fill="none" xmlns="http://www.w3.org/2000/svg" className={className}>
+    <path d="M14 11.9998L13.3332 12.7292C12.9796 13.1159 12.5001 13.3332 12.0001 13.3332C11.5001 13.3332 11.0205 13.1159 10.6669 12.7292C10.3128 12.3432 9.83332 12.1265 9.33345 12.1265C8.83359 12.1265 8.35409 12.3432 7.99998 12.7292M2 13.3332H3.11636C3.44248 13.3332 3.60554 13.3332 3.75899 13.2963C3.89504 13.2637 4.0251 13.2098 4.1444 13.1367C4.27895 13.0542 4.39425 12.9389 4.62486 12.7083L13 4.33316C13.5523 3.78087 13.5523 2.88544 13 2.33316C12.4477 1.78087 11.5523 1.78087 11 2.33316L2.62484 10.7083C2.39424 10.9389 2.27894 11.0542 2.19648 11.1888C2.12338 11.3081 2.0695 11.4381 2.03684 11.5742C2 11.7276 2 11.8907 2 12.2168V13.3332Z" stroke="#6B7280" strokeLinecap="round" strokeLinejoin="round" />
+  </svg>
+}
+
+export const EditIconSolid: FC<{ className?: string }> = ({ className }) => {
+  return <svg width="12" height="12" viewBox="0 0 12 12" fill="none" xmlns="http://www.w3.org/2000/svg" className={className}>
+    <path fillRule="evenodd" clipRule="evenodd" d="M10.8374 8.63108C11.0412 8.81739 11.0554 9.13366 10.8691 9.33747L10.369 9.88449C10.0142 10.2725 9.52293 10.5001 9.00011 10.5001C8.47746 10.5001 7.98634 10.2727 7.63157 9.8849C7.45561 9.69325 7.22747 9.59515 7.00014 9.59515C6.77271 9.59515 6.54446 9.69335 6.36846 9.88517C6.18177 10.0886 5.86548 10.1023 5.66201 9.91556C5.45853 9.72888 5.44493 9.41259 5.63161 9.20911C5.98678 8.82201 6.47777 8.59515 7.00014 8.59515C7.52251 8.59515 8.0135 8.82201 8.36867 9.20911L8.36924 9.20974C8.54486 9.4018 8.77291 9.50012 9.00011 9.50012C9.2273 9.50012 9.45533 9.40182 9.63095 9.20979L10.131 8.66276C10.3173 8.45895 10.6336 8.44476 10.8374 8.63108Z" fill="#6B7280" />
+    <path fillRule="evenodd" clipRule="evenodd" d="M7.89651 1.39656C8.50599 0.787085 9.49414 0.787084 10.1036 1.39656C10.7131 2.00604 10.7131 2.99419 10.1036 3.60367L3.82225 9.88504C3.81235 9.89494 3.80254 9.90476 3.79281 9.91451C3.64909 10.0585 3.52237 10.1855 3.3696 10.2791C3.23539 10.3613 3.08907 10.4219 2.93602 10.4587C2.7618 10.5005 2.58242 10.5003 2.37897 10.5001C2.3652 10.5001 2.35132 10.5001 2.33732 10.5001H1.50005C1.22391 10.5001 1.00005 10.2763 1.00005 10.0001V9.16286C1.00005 9.14886 1.00004 9.13497 1.00003 9.1212C0.999836 8.91776 0.999669 8.73838 1.0415 8.56416C1.07824 8.4111 1.13885 8.26479 1.22109 8.13058C1.31471 7.97781 1.44166 7.85109 1.58566 7.70736C1.5954 7.69764 1.60523 7.68783 1.61513 7.67793L7.89651 1.39656Z" fill="#6B7280" />
+  </svg>
+}
+
+export const TryToAskIcon = (
+  <svg width="11" height="10" viewBox="0 0 11 10" fill="none" xmlns="http://www.w3.org/2000/svg">
+    <path d="M5.88889 0.683718C5.827 0.522805 5.67241 0.416626 5.5 0.416626C5.3276 0.416626 5.173 0.522805 5.11111 0.683718L4.27279 2.86334C4.14762 3.18877 4.10829 3.28255 4.05449 3.35821C4.00051 3.43413 3.93418 3.50047 3.85826 3.55445C3.78259 3.60825 3.68881 3.64758 3.36338 3.77275L1.18376 4.61106C1.02285 4.67295 0.916668 4.82755 0.916668 4.99996C0.916668 5.17236 1.02285 5.32696 1.18376 5.38885L3.36338 6.22717C3.68881 6.35234 3.78259 6.39167 3.85826 6.44547C3.93418 6.49945 4.00051 6.56578 4.05449 6.6417C4.10829 6.71737 4.14762 6.81115 4.27279 7.13658L5.11111 9.3162C5.173 9.47711 5.3276 9.58329 5.5 9.58329C5.67241 9.58329 5.82701 9.47711 5.8889 9.3162L6.72721 7.13658C6.85238 6.81115 6.89171 6.71737 6.94551 6.6417C6.99949 6.56578 7.06583 6.49945 7.14175 6.44547C7.21741 6.39167 7.31119 6.35234 7.63662 6.22717L9.81624 5.38885C9.97715 5.32696 10.0833 5.17236 10.0833 4.99996C10.0833 4.82755 9.97715 4.67295 9.81624 4.61106L7.63662 3.77275C7.31119 3.64758 7.21741 3.60825 7.14175 3.55445C7.06583 3.50047 6.99949 3.43413 6.94551 3.35821C6.89171 3.28255 6.85238 3.18877 6.72721 2.86334L5.88889 0.683718Z" fill="#667085" />
+  </svg>
+)

web/app/components/app/chat/index.tsx

@@ -4,43 +4,25 @@ import React, { useEffect, useLayoutEffect, useRef, useState } from 'react'
 import { useContext } from 'use-context-selector'
 import cn from 'classnames'
 import Recorder from 'js-audio-recorder'
-import { HandThumbDownIcon, HandThumbUpIcon } from '@heroicons/react/24/outline'
-import { UserCircleIcon } from '@heroicons/react/24/solid'
 import { useTranslation } from 'react-i18next'
-import { randomString } from '../../app-sidebar/basic'
 import s from './style.module.css'
-import LoadingAnim from './loading-anim'
-import CopyBtn from './copy-btn'
+import type { DisplayScene, FeedbackFunc, IChatItem, SubmitAnnotationFunc } from './type'
+import { TryToAskIcon, stopIcon } from './icon-component'
+import Answer from './answer'
+import Question from './question'
 import Tooltip from '@/app/components/base/tooltip'
 import { ToastContext } from '@/app/components/base/toast'
 import AutoHeightTextarea from '@/app/components/base/auto-height-textarea'
 import Button from '@/app/components/base/button'
-import type { Annotation, MessageRating } from '@/models/log'
-import AppContext from '@/context/app-context'
-import { Markdown } from '@/app/components/base/markdown'
-import { formatNumber } from '@/utils/format'
 import useBreakpoints, { MediaType } from '@/hooks/use-breakpoints'
 import VoiceInput from '@/app/components/base/voice-input'
 import { Microphone01 } from '@/app/components/base/icons/src/vender/line/mediaAndDevices'
 import { Microphone01 as Microphone01Solid } from '@/app/components/base/icons/src/vender/solid/mediaAndDevices'
 import { XCircle } from '@/app/components/base/icons/src/vender/solid/general'
-
-const stopIcon = (
-  <svg width="14" height="14" viewBox="0 0 14 14" fill="none" xmlns="http://www.w3.org/2000/svg">
-    <path fillRule="evenodd" clipRule="evenodd" d="M7.00004 0.583313C3.45621 0.583313 0.583374 3.45615 0.583374 6.99998C0.583374 10.5438 3.45621 13.4166 7.00004 13.4166C10.5439 13.4166 13.4167 10.5438 13.4167 6.99998C13.4167 3.45615 10.5439 0.583313 7.00004 0.583313ZM4.73029 4.98515C4.66671 5.10993 4.66671 5.27328 4.66671 5.59998V8.39998C4.66671 8.72668 4.66671 8.89003 4.73029 9.01481C4.78621 9.12457 4.87545 9.21381 4.98521 9.26973C5.10999 9.33331 5.27334 9.33331 5.60004 9.33331H8.40004C8.72674 9.33331 8.89009 9.33331 9.01487 9.26973C9.12463 9.21381 9.21387 9.12457 9.2698 9.01481C9.33337 8.89003 9.33337 8.72668 9.33337 8.39998V5.59998C9.33337 5.27328 9.33337 5.10993 9.2698 4.98515C9.21387 4.87539 9.12463 4.78615 9.01487 4.73023C8.89009 4.66665 8.72674 4.66665 8.40004 4.66665H5.60004C5.27334 4.66665 5.10999 4.66665 4.98521 4.73023C4.87545 4.78615 4.78621 4.87539 4.73029 4.98515Z" fill="#667085" />
-  </svg>
-)
-export type Feedbacktype = {
-  rating: MessageRating
-  content?: string | null
-}
-
-export type FeedbackFunc = (messageId: string, feedback: Feedbacktype) => Promise<any>
-export type SubmitAnnotationFunc = (messageId: string, content: string) => Promise<any>
-
-export type DisplayScene = 'web' | 'console'
+import type { DataSet } from '@/models/datasets'
 
 export type IChatProps = {
+  configElem?: React.ReactNode
   chatList: IChatItem[]
   /**
    * Whether to display the editing area and rating status
@@ -66,352 +48,12 @@ export type IChatProps = {
   suggestionList?: string[]
   isShowSpeechToText?: boolean
   answerIconClassName?: string
-}
-
-export type MessageMore = {
-  time: string
-  tokens: number
-  latency: number | string
-}
-
-export type IChatItem = {
-  id: string
-  content: string
-  /**
-   * Specific message type
-   */
-  isAnswer: boolean
-  /**
-   * The user feedback result of this message
-   */
-  feedback?: Feedbacktype
-  /**
-   * The admin feedback result of this message
-   */
-  adminFeedback?: Feedbacktype
-  /**
-   * Whether to hide the feedback area
-   */
-  feedbackDisabled?: boolean
-  /**
-   * More information about this message
-   */
-  more?: MessageMore
-  annotation?: Annotation
-  useCurrentUserAvatar?: boolean
-  isOpeningStatement?: boolean
-}
-
-const OperationBtn = ({ innerContent, onClick, className }: { innerContent: React.ReactNode; onClick?: () => void; className?: string }) => (
-  <div
-    className={`relative box-border flex items-center justify-center h-7 w-7 p-0.5 rounded-lg bg-white cursor-pointer text-gray-500 hover:text-gray-800 ${className ?? ''}`}
-    style={{ boxShadow: '0px 4px 6px -1px rgba(0, 0, 0, 0.1), 0px 2px 4px -2px rgba(0, 0, 0, 0.05)' }}
-    onClick={onClick && onClick}
-  >
-    {innerContent}
-  </div>
-)
-
-const MoreInfo: FC<{ more: MessageMore; isQuestion: boolean }> = ({ more, isQuestion }) => {
-  const { t } = useTranslation()
-  return (<div className={`mt-1 space-x-2 text-xs text-gray-400 ${isQuestion ? 'mr-2 text-right ' : 'ml-2 text-left float-right'}`}>
-    <span>{`${t('appLog.detail.timeConsuming')} ${more.latency}${t('appLog.detail.second')}`}</span>
-    <span>{`${t('appLog.detail.tokenCost')} ${formatNumber(more.tokens)}`}</span>
-    <span>· </span>
-    <span>{more.time} </span>
-  </div>)
-}
-
-const OpeningStatementIcon: FC<{ className?: string }> = ({ className }) => (
-  <svg width="12" height="12" viewBox="0 0 12 12" fill="none" xmlns="http://www.w3.org/2000/svg">
-    <path fillRule="evenodd" clipRule="evenodd" d="M6.25002 1C3.62667 1 1.50002 3.12665 1.50002 5.75C1.50002 6.28 1.58702 6.79071 1.7479 7.26801C1.7762 7.35196 1.79285 7.40164 1.80368 7.43828L1.80722 7.45061L1.80535 7.45452C1.79249 7.48102 1.77339 7.51661 1.73766 7.58274L0.911727 9.11152C0.860537 9.20622 0.807123 9.30503 0.770392 9.39095C0.733879 9.47635 0.674738 9.63304 0.703838 9.81878C0.737949 10.0365 0.866092 10.2282 1.05423 10.343C1.21474 10.4409 1.38213 10.4461 1.475 10.4451C1.56844 10.444 1.68015 10.4324 1.78723 10.4213L4.36472 10.1549C4.406 10.1506 4.42758 10.1484 4.44339 10.1472L4.44542 10.147L4.45161 10.1492C4.47103 10.1562 4.49738 10.1663 4.54285 10.1838C5.07332 10.3882 5.64921 10.5 6.25002 10.5C8.87338 10.5 11 8.37335 11 5.75C11 3.12665 8.87338 1 6.25002 1ZM4.48481 4.29111C5.04844 3.81548 5.7986 3.9552 6.24846 4.47463C6.69831 3.9552 7.43879 3.82048 8.01211 4.29111C8.58544 4.76175 8.6551 5.562 8.21247 6.12453C7.93825 6.47305 7.24997 7.10957 6.76594 7.54348C6.58814 7.70286 6.49924 7.78255 6.39255 7.81466C6.30103 7.84221 6.19589 7.84221 6.10436 7.81466C5.99767 7.78255 5.90878 7.70286 5.73098 7.54348C5.24694 7.10957 4.55867 6.47305 4.28444 6.12453C3.84182 5.562 3.92117 4.76675 4.48481 4.29111Z" fill="#667085" />
-  </svg>
-)
-
-const RatingIcon: FC<{ isLike: boolean }> = ({ isLike }) => {
-  return isLike ? <HandThumbUpIcon className='w-4 h-4' /> : <HandThumbDownIcon className='w-4 h-4' />
-}
-
-const EditIcon: FC<{ className?: string }> = ({ className }) => {
-  return <svg width="16" height="16" viewBox="0 0 16 16" fill="none" xmlns="http://www.w3.org/2000/svg" className={className}>
-    <path d="M14 11.9998L13.3332 12.7292C12.9796 13.1159 12.5001 13.3332 12.0001 13.3332C11.5001 13.3332 11.0205 13.1159 10.6669 12.7292C10.3128 12.3432 9.83332 12.1265 9.33345 12.1265C8.83359 12.1265 8.35409 12.3432 7.99998 12.7292M2 13.3332H3.11636C3.44248 13.3332 3.60554 13.3332 3.75899 13.2963C3.89504 13.2637 4.0251 13.2098 4.1444 13.1367C4.27895 13.0542 4.39425 12.9389 4.62486 12.7083L13 4.33316C13.5523 3.78087 13.5523 2.88544 13 2.33316C12.4477 1.78087 11.5523 1.78087 11 2.33316L2.62484 10.7083C2.39424 10.9389 2.27894 11.0542 2.19648 11.1888C2.12338 11.3081 2.0695 11.4381 2.03684 11.5742C2 11.7276 2 11.8907 2 12.2168V13.3332Z" stroke="#6B7280" strokeLinecap="round" strokeLinejoin="round" />
-  </svg>
-}
-
-export const EditIconSolid: FC<{ className?: string }> = ({ className }) => {
-  return <svg width="12" height="12" viewBox="0 0 12 12" fill="none" xmlns="http://www.w3.org/2000/svg" className={className}>
-    <path fillRule="evenodd" clipRule="evenodd" d="M10.8374 8.63108C11.0412 8.81739 11.0554 9.13366 10.8691 9.33747L10.369 9.88449C10.0142 10.2725 9.52293 10.5001 9.00011 10.5001C8.47746 10.5001 7.98634 10.2727 7.63157 9.8849C7.45561 9.69325 7.22747 9.59515 7.00014 9.59515C6.77271 9.59515 6.54446 9.69335 6.36846 9.88517C6.18177 10.0886 5.86548 10.1023 5.66201 9.91556C5.45853 9.72888 5.44493 9.41259 5.63161 9.20911C5.98678 8.82201 6.47777 8.59515 7.00014 8.59515C7.52251 8.59515 8.0135 8.82201 8.36867 9.20911L8.36924 9.20974C8.54486 9.4018 8.77291 9.50012 9.00011 9.50012C9.2273 9.50012 9.45533 9.40182 9.63095 9.20979L10.131 8.66276C10.3173 8.45895 10.6336 8.44476 10.8374 8.63108Z" fill="#6B7280" />
-    <path fillRule="evenodd" clipRule="evenodd" d="M7.89651 1.39656C8.50599 0.787085 9.49414 0.787084 10.1036 1.39656C10.7131 2.00604 10.7131 2.99419 10.1036 3.60367L3.82225 9.88504C3.81235 9.89494 3.80254 9.90476 3.79281 9.91451C3.64909 10.0585 3.52237 10.1855 3.3696 10.2791C3.23539 10.3613 3.08907 10.4219 2.93602 10.4587C2.7618 10.5005 2.58242 10.5003 2.37897 10.5001C2.3652 10.5001 2.35132 10.5001 2.33732 10.5001H1.50005C1.22391 10.5001 1.00005 10.2763 1.00005 10.0001V9.16286C1.00005 9.14886 1.00004 9.13497 1.00003 9.1212C0.999836 8.91776 0.999669 8.73838 1.0415 8.56416C1.07824 8.4111 1.13885 8.26479 1.22109 8.13058C1.31471 7.97781 1.44166 7.85109 1.58566 7.70736C1.5954 7.69764 1.60523 7.68783 1.61513 7.67793L7.89651 1.39656Z" fill="#6B7280" />
-  </svg>
-}
-
-const TryToAskIcon = (
-  <svg width="11" height="10" viewBox="0 0 11 10" fill="none" xmlns="http://www.w3.org/2000/svg">
-    <path d="M5.88889 0.683718C5.827 0.522805 5.67241 0.416626 5.5 0.416626C5.3276 0.416626 5.173 0.522805 5.11111 0.683718L4.27279 2.86334C4.14762 3.18877 4.10829 3.28255 4.05449 3.35821C4.00051 3.43413 3.93418 3.50047 3.85826 3.55445C3.78259 3.60825 3.68881 3.64758 3.36338 3.77275L1.18376 4.61106C1.02285 4.67295 0.916668 4.82755 0.916668 4.99996C0.916668 5.17236 1.02285 5.32696 1.18376 5.38885L3.36338 6.22717C3.68881 6.35234 3.78259 6.39167 3.85826 6.44547C3.93418 6.49945 4.00051 6.56578 4.05449 6.6417C4.10829 6.71737 4.14762 6.81115 4.27279 7.13658L5.11111 9.3162C5.173 9.47711 5.3276 9.58329 5.5 9.58329C5.67241 9.58329 5.82701 9.47711 5.8889 9.3162L6.72721 7.13658C6.85238 6.81115 6.89171 6.71737 6.94551 6.6417C6.99949 6.56578 7.06583 6.49945 7.14175 6.44547C7.21741 6.39167 7.31119 6.35234 7.63662 6.22717L9.81624 5.38885C9.97715 5.32696 10.0833 5.17236 10.0833 4.99996C10.0833 4.82755 9.97715 4.67295 9.81624 4.61106L7.63662 3.77275C7.31119 3.64758 7.21741 3.60825 7.14175 3.55445C7.06583 3.50047 6.99949 3.43413 6.94551 3.35821C6.89171 3.28255 6.85238 3.18877 6.72721 2.86334L5.88889 0.683718Z" fill="#667085" />
-  </svg>
-)
-
-const Divider: FC<{ name: string }> = ({ name }) => {
-  const { t } = useTranslation()
-  return <div className='flex items-center my-2'>
-    <span className='text-xs text-gray-500 inline-flex items-center mr-2'>
-      <EditIconSolid className='mr-1' />{t('appLog.detail.annotationTip', { user: name })}
-    </span>
-    <div className='h-[1px] bg-gray-200 flex-1'></div>
-  </div>
-}
-
-const IconWrapper: FC<{ children: React.ReactNode | string }> = ({ children }) => {
-  return <div className={'rounded-lg h-6 w-6 flex items-center justify-center hover:bg-gray-100'}>
-    {children}
-  </div>
-}
-
-type IAnswerProps = {
-  item: IChatItem
-  feedbackDisabled: boolean
-  isHideFeedbackEdit: boolean
-  onFeedback?: FeedbackFunc
-  onSubmitAnnotation?: SubmitAnnotationFunc
-  displayScene: DisplayScene
-  isResponsing?: boolean
-  answerIconClassName?: string
-}
-
-// The component needs to maintain its own state to control whether to display input component
-const Answer: FC<IAnswerProps> = ({ item, feedbackDisabled = false, isHideFeedbackEdit = false, onFeedback, onSubmitAnnotation, displayScene = 'web', isResponsing, answerIconClassName }) => {
-  const { id, content, more, feedback, adminFeedback, annotation: initAnnotation } = item
-  const [showEdit, setShowEdit] = useState(false)
-  const [loading, setLoading] = useState(false)
-  const [annotation, setAnnotation] = useState<Annotation | undefined | null>(initAnnotation)
-  const [inputValue, setInputValue] = useState<string>(initAnnotation?.content ?? '')
-  const [localAdminFeedback, setLocalAdminFeedback] = useState<Feedbacktype | undefined | null>(adminFeedback)
-  const { userProfile } = useContext(AppContext)
-  const { t } = useTranslation()
-
-  /**
- * Render feedback results (distinguish between users and administrators)
- * User reviews cannot be cancelled in Console
- * @param rating feedback result
- * @param isUserFeedback Whether it is user's feedback
- * @param isWebScene Whether it is web scene
- * @returns comp
- */
-  const renderFeedbackRating = (rating: MessageRating | undefined, isUserFeedback = true, isWebScene = true) => {
-    if (!rating)
-      return null
-
-    const isLike = rating === 'like'
-    const ratingIconClassname = isLike ? 'text-primary-600 bg-primary-100 hover:bg-primary-200' : 'text-red-600 bg-red-100 hover:bg-red-200'
-    const UserSymbol = <UserCircleIcon className='absolute top-[-2px] left-[18px] w-3 h-3 rounded-lg text-gray-400 bg-white' />
-    // The tooltip is always displayed, but the content is different for different scenarios.
-    return (
-      <Tooltip
-        selector={`user-feedback-${randomString(16)}`}
-        content={((isWebScene || (!isUserFeedback && !isWebScene)) ? isLike ? t('appDebug.operation.cancelAgree') : t('appDebug.operation.cancelDisagree') : (!isWebScene && isUserFeedback) ? `${t('appDebug.operation.userAction')}${isLike ? t('appDebug.operation.agree') : t('appDebug.operation.disagree')}` : '') as string}
-      >
-        <div
-          className={`relative box-border flex items-center justify-center h-7 w-7 p-0.5 rounded-lg bg-white cursor-pointer text-gray-500 hover:text-gray-800 ${(!isWebScene && isUserFeedback) ? '!cursor-default' : ''}`}
-          style={{ boxShadow: '0px 4px 6px -1px rgba(0, 0, 0, 0.1), 0px 2px 4px -2px rgba(0, 0, 0, 0.05)' }}
-          {...((isWebScene || (!isUserFeedback && !isWebScene))
-            ? {
-              onClick: async () => {
-                const res = await onFeedback?.(id, { rating: null })
-                if (res && !isWebScene)
-                  setLocalAdminFeedback({ rating: null })
-              },
-            }
-            : {})}
-        >
-          <div className={`${ratingIconClassname} rounded-lg h-6 w-6 flex items-center justify-center`}>
-            <RatingIcon isLike={isLike} />
-          </div>
-          {!isWebScene && isUserFeedback && UserSymbol}
-        </div>
-      </Tooltip>
-    )
-  }
-
-  /**
-   * Different scenarios have different operation items.
-   * @param isWebScene  Whether it is web scene
-   * @returns comp
-   */
-  const renderItemOperation = (isWebScene = true) => {
-    const userOperation = () => {
-      return feedback?.rating
-        ? null
-        : <div className='flex gap-1'>
-          <Tooltip selector={`user-feedback-${randomString(16)}`} content={t('appLog.detail.operation.like') as string}>
-            {OperationBtn({ innerContent: <IconWrapper><RatingIcon isLike={true} /></IconWrapper>, onClick: () => onFeedback?.(id, { rating: 'like' }) })}
-          </Tooltip>
-          <Tooltip selector={`user-feedback-${randomString(16)}`} content={t('appLog.detail.operation.dislike') as string}>
-            {OperationBtn({ innerContent: <IconWrapper><RatingIcon isLike={false} /></IconWrapper>, onClick: () => onFeedback?.(id, { rating: 'dislike' }) })}
-          </Tooltip>
-        </div>
-    }
-
-    const adminOperation = () => {
-      return <div className='flex gap-1'>
-        <Tooltip selector={`user-feedback-${randomString(16)}`} content={t('appLog.detail.operation.addAnnotation') as string}>
-          {OperationBtn({
-            innerContent: <IconWrapper><EditIcon className='hover:text-gray-800' /></IconWrapper>,
-            onClick: () => setShowEdit(true),
-          })}
-        </Tooltip>
-        {!localAdminFeedback?.rating && <>
-          <Tooltip selector={`user-feedback-${randomString(16)}`} content={t('appLog.detail.operation.like') as string}>
-            {OperationBtn({
-              innerContent: <IconWrapper><RatingIcon isLike={true} /></IconWrapper>,
-              onClick: async () => {
-                const res = await onFeedback?.(id, { rating: 'like' })
-                if (res)
-                  setLocalAdminFeedback({ rating: 'like' })
-              },
-            })}
-          </Tooltip>
-          <Tooltip selector={`user-feedback-${randomString(16)}`} content={t('appLog.detail.operation.dislike') as string}>
-            {OperationBtn({
-              innerContent: <IconWrapper><RatingIcon isLike={false} /></IconWrapper>,
-              onClick: async () => {
-                const res = await onFeedback?.(id, { rating: 'dislike' })
-                if (res)
-                  setLocalAdminFeedback({ rating: 'dislike' })
-              },
-            })}
-          </Tooltip>
-        </>}
-      </div>
-    }
-
-    return (
-      <div className={`${s.itemOperation} flex gap-2`}>
-        {isWebScene ? userOperation() : adminOperation()}
-      </div>
-    )
-  }
-
-  return (
-    <div key={id}>
-      <div className='flex items-start'>
-        <div className={`${s.answerIcon} ${answerIconClassName} w-10 h-10 shrink-0`}>
-          {isResponsing
-            && <div className={s.typeingIcon}>
-              <LoadingAnim type='avatar' />
-            </div>
-          }
-        </div>
-        <div className={s.answerWrapWrap}>
-          <div className={`${s.answerWrap} ${showEdit ? 'w-full' : ''}`}>
-            <div className={`${s.answer} relative text-sm text-gray-900`}>
-              <div className={'ml-2 py-3 px-4 bg-gray-100 rounded-tr-2xl rounded-b-2xl'}>
-                {item.isOpeningStatement && (
-                  <div className='flex items-center mb-1 gap-1'>
-                    <OpeningStatementIcon />
-                    <div className='text-xs text-gray-500'>{t('appDebug.openingStatement.title')}</div>
-                  </div>
-                )}
-                {(isResponsing && !content)
-                  ? (
-                    <div className='flex items-center justify-center w-6 h-5'>
-                      <LoadingAnim type='text' />
-                    </div>
-                  )
-                  : (
-                    <Markdown content={content} />
-                  )}
-                {!showEdit
-                  ? (annotation?.content
-                    && <>
-                      <Divider name={annotation?.account?.name || userProfile?.name} />
-                      {annotation.content}
-                    </>)
-                  : <>
-                    <Divider name={annotation?.account?.name || userProfile?.name} />
-                    <AutoHeightTextarea
-                      placeholder={t('appLog.detail.operation.annotationPlaceholder') as string}
-                      value={inputValue}
-                      onChange={e => setInputValue(e.target.value)}
-                      minHeight={58}
-                      className={`${cn(s.textArea)} !py-2 resize-none block w-full !px-3 bg-gray-50 border border-gray-200 rounded-md shadow-sm focus:outline-none focus:ring-blue-500 focus:border-blue-500 sm:text-sm text-gray-700 tracking-[0.2px]`}
-                    />
-                    <div className="mt-2 flex flex-row">
-                      <Button
-                        type='primary'
-                        className='mr-2'
-                        loading={loading}
-                        onClick={async () => {
-                          if (!inputValue)
-                            return
-                          setLoading(true)
-                          const res = await onSubmitAnnotation?.(id, inputValue)
-                          if (res)
-                            setAnnotation({ ...annotation, content: inputValue } as any)
-                          setLoading(false)
-                          setShowEdit(false)
-                        }}>{t('common.operation.confirm')}</Button>
-                      <Button
-                        onClick={() => {
-                          setInputValue(annotation?.content ?? '')
-                          setShowEdit(false)
-                        }}>{t('common.operation.cancel')}</Button>
-                    </div>
-                  </>
-                }
-              </div>
-              <div className='absolute top-[-14px] right-[-14px] flex flex-row justify-end gap-1'>
-                {!item.isOpeningStatement && (
-                  <CopyBtn
-                    value={content}
-                    className={cn(s.copyBtn, 'mr-1')}
-                  />
-                )}
-                {!feedbackDisabled && !item.feedbackDisabled && renderItemOperation(displayScene !== 'console')}
-                {/* Admin feedback is displayed only in the background. */}
-                {!feedbackDisabled && renderFeedbackRating(localAdminFeedback?.rating, false, false)}
-                {/* User feedback must be displayed */}
-                {!feedbackDisabled && renderFeedbackRating(feedback?.rating, !isHideFeedbackEdit, displayScene !== 'console')}
-              </div>
-            </div>
-            {more && <MoreInfo more={more} isQuestion={false} />}
-          </div>
-        </div>
-      </div>
-    </div>
-  )
-}
-
-type IQuestionProps = Pick<IChatItem, 'id' | 'content' | 'more' | 'useCurrentUserAvatar'>
-
-const Question: FC<IQuestionProps> = ({ id, content, more, useCurrentUserAvatar }) => {
-  const { userProfile } = useContext(AppContext)
-  const userName = userProfile?.name
-  return (
-    <div className='flex items-start justify-end' key={id}>
-      <div className={s.questionWrapWrap}>
-        <div className={`${s.question} relative text-sm text-gray-900`}>
-          <div
-            className={'mr-2 py-3 px-4 bg-blue-500 rounded-tl-2xl rounded-b-2xl'}
-          >
-            <Markdown content={content} />
-          </div>
-        </div>
-        {more && <MoreInfo more={more} isQuestion={true} />}
-      </div>
-      {useCurrentUserAvatar
-        ? (
-          <div className='w-10 h-10 shrink-0 leading-10 text-center mr-2 rounded-full bg-primary-600 text-white'>
-            {userName?.[0].toLocaleUpperCase()}
-          </div>
-        )
-        : (
-          <div className={`${s.questionIcon} w-10 h-10 shrink-0 `}></div>
-        )}
-    </div>
-  )
+  isShowConfigElem?: boolean
+  dataSets?: DataSet[]
 }
 
 const Chat: FC<IChatProps> = ({
+  configElem,
   chatList,
   feedbackDisabled = false,
   isHideFeedbackEdit = false,
@@ -431,6 +73,8 @@ const Chat: FC<IChatProps> = ({
   suggestionList,
   isShowSpeechToText,
   answerIconClassName,
+  isShowConfigElem,
+  dataSets,
 }) => {
   const { t } = useTranslation()
   const { notify } = useContext(ToastContext)
@@ -509,11 +153,14 @@ const Chat: FC<IChatProps> = ({
 
   return (
     <div className={cn('px-3.5', 'h-full')}>
+      {isShowConfigElem && (configElem || null)}
       {/* Chat List */}
-      <div className="h-full space-y-[30px]">
+      <div className={cn((isShowConfigElem && configElem) ? 'h-0' : 'h-full', 'space-y-[30px]')}>
         {chatList.map((item) => {
           if (item.isAnswer) {
             const isLast = item.id === chatList[chatList.length - 1].id
+            const thoughts = item.agent_thoughts?.filter(item => item.thought !== '[DONE]')
+            const isThinking = !item.content && item.agent_thoughts && item.agent_thoughts?.length > 0 && !item.agent_thoughts.some(item => item.thought === '[DONE]')
             return <Answer
               key={item.id}
               item={item}
@@ -524,6 +171,9 @@ const Chat: FC<IChatProps> = ({
               displayScene={displayScene ?? 'web'}
               isResponsing={isResponsing && isLast}
               answerIconClassName={answerIconClassName}
+              thoughts={thoughts}
+              isThinking={isThinking}
+              dataSets={dataSets}
             />
           }
           return <Question key={item.id} id={item.id} content={item.content} more={item.more} useCurrentUserAvatar={useCurrentUserAvatar} />
@@ -532,7 +182,8 @@ const Chat: FC<IChatProps> = ({
       {
         !isHideSendInput && (
           <div className={cn(!feedbackDisabled && '!left-3.5 !right-3.5', 'absolute z-10 bottom-0 left-0 right-0')}>
-            {(isResponsing && canStopResponsing) && (
+            {/* Thinking is sync and can not be stopped */}
+            {(isResponsing && canStopResponsing && !!chatList[chatList.length - 1]?.content) && (
               <div className='flex justify-center mb-4'>
                 <Button className='flex items-center space-x-1 bg-white' onClick={() => abortResponsing?.()}>
                   {stopIcon}
@@ -560,7 +211,7 @@ const Chat: FC<IChatProps> = ({
                   {/* has scrollbar would hide part of first item */}
                   <div ref={suggestionListRef} className={cn(!hasScrollbar && 'justify-center', 'flex overflow-x-auto pb-2')}>
                     {suggestionList?.map((item, index) => (
-                      <div className='shrink-0 flex justify-center mr-2'>
+                      <div key={item} className='shrink-0 flex justify-center mr-2'>
                         <Button
                           key={index}
                           onClick={() => setQuery(item)}

web/app/components/app/chat/more-info/index.tsx

+'use client'
+import type { FC } from 'react'
+import React from 'react'
+import { useTranslation } from 'react-i18next'
+import type { MessageMore } from '../type'
+import { formatNumber } from '@/utils/format'
+
+export type IMoreInfoProps = { more: MessageMore; isQuestion: boolean }
+
+const MoreInfo: FC<IMoreInfoProps> = ({ more, isQuestion }) => {
+  const { t } = useTranslation()
+  return (<div className={`mt-1 space-x-2 text-xs text-gray-400 ${isQuestion ? 'mr-2 text-right ' : 'ml-2 text-left float-right'}`}>
+    <span>{`${t('appLog.detail.timeConsuming')} ${more.latency}${t('appLog.detail.second')}`}</span>
+    <span>{`${t('appLog.detail.tokenCost')} ${formatNumber(more.tokens)}`}</span>
+    <span>· </span>
+    <span>{more.time} </span>
+  </div>)
+}
+export default React.memo(MoreInfo)

web/app/components/app/chat/operation/index.tsx

+'use client'
+import React from 'react'
+
+const OperationBtn = ({ innerContent, onClick, className }: { innerContent: React.ReactNode; onClick?: () => void; className?: string }) => (
+  <div
+    className={`relative box-border flex items-center justify-center h-7 w-7 p-0.5 rounded-lg bg-white cursor-pointer text-gray-500 hover:text-gray-800 ${className ?? ''}`}
+    style={{ boxShadow: '0px 4px 6px -1px rgba(0, 0, 0, 0.1), 0px 2px 4px -2px rgba(0, 0, 0, 0.05)' }}
+    onClick={onClick && onClick}
+  >
+    {innerContent}
+  </div>
+)
+
+export default OperationBtn

web/app/components/app/chat/question/index.tsx

+'use client'
+import type { FC } from 'react'
+import React from 'react'
+import { useContext } from 'use-context-selector'
+import s from '../style.module.css'
+import type { IChatItem } from '../type'
+import MoreInfo from '../more-info'
+import AppContext from '@/context/app-context'
+import { Markdown } from '@/app/components/base/markdown'
+
+type IQuestionProps = Pick<IChatItem, 'id' | 'content' | 'more' | 'useCurrentUserAvatar'>
+
+const Question: FC<IQuestionProps> = ({ id, content, more, useCurrentUserAvatar }) => {
+  const { userProfile } = useContext(AppContext)
+  const userName = userProfile?.name
+  return (
+    <div className='flex items-start justify-end' key={id}>
+      <div className={s.questionWrapWrap}>
+        <div className={`${s.question} relative text-sm text-gray-900`}>
+          <div
+            className={'mr-2 py-3 px-4 bg-blue-500 rounded-tl-2xl rounded-b-2xl'}
+          >
+            <Markdown content={content} />
+          </div>
+        </div>
+        {more && <MoreInfo more={more} isQuestion={true} />}
+      </div>
+      {useCurrentUserAvatar
+        ? (
+          <div className='w-10 h-10 shrink-0 leading-10 text-center mr-2 rounded-full bg-primary-600 text-white'>
+            {userName?.[0].toLocaleUpperCase()}
+          </div>
+        )
+        : (
+          <div className={`${s.questionIcon} w-10 h-10 shrink-0 `}></div>
+        )}
+    </div>
+  )
+}
+export default React.memo(Question)

web/app/components/app/chat/thought/index.tsx

+'use client'
+import type { FC } from 'react'
+import React from 'react'
+import cn from 'classnames'
+import { useTranslation } from 'react-i18next'
+import type { ThoughtItem } from '../type'
+import s from './style.module.css'
+import { DataSet as DataSetIcon, Loading as LodingIcon, Search, ThoughtList, WebReader } from '@/app/components/base/icons/src/public/thought'
+import { ChevronDown } from '@/app/components/base/icons/src/vender/line/arrows'
+import type { DataSet } from '@/models/datasets'
+
+export type IThoughtProps = {
+  list: ThoughtItem[]
+  isThinking?: boolean
+  dataSets?: DataSet[]
+}
+
+const getIcon = (toolId: string) => {
+  switch (toolId) {
+    case 'dataset':
+      return <DataSetIcon />
+    case 'web_reader':
+      return <WebReader />
+    default:
+      return <Search />
+  }
+}
+
+const Thought: FC<IThoughtProps> = ({
+  list,
+  isThinking,
+  dataSets,
+}) => {
+  const { t } = useTranslation()
+  const [isShowDetail, setIsShowDetail] = React.useState(false)
+
+  const getThoughtText = (item: ThoughtItem) => {
+    try {
+      const input = JSON.parse(item.tool_input)
+
+      switch (item.tool) {
+        case 'dataset':
+          // eslint-disable-next-line no-case-declarations
+          const datasetName = dataSets?.find(item => item.id === input.dataset_id)?.name || 'unknown dataset'
+          return t('explore.universalChat.thought.res.dataset').replace('{datasetName}', `<span class="text-gray-700">${datasetName}</span>`)
+        case 'web_reader':
+          return t(`explore.universalChat.thought.res.webReader.${!input.cursor ? 'normal' : 'hasPageInfo'}`).replace('{url}', `<a href="${input.url}" class="text-[#155EEF]">${input.url}</a>`)
+        default: // google, wikipedia
+          return t('explore.universalChat.thought.res.search', { query: input.query })
+      }
+    }
+    catch (error) {
+      console.error(error)
+      return item
+    }
+  }
+  const renderItem = (item: ThoughtItem) => (
+    <div className='flex space-x-1 py-[3px] leading-[18px]' key={item.id}>
+      <div className='flex items-center h-[18px] shrink-0'>{getIcon(item.tool)}</div>
+      <div dangerouslySetInnerHTML={{
+        __html: getThoughtText(item),
+        // item.thought.replace(urlRegex, (url) => {
+        //   return `<a href="${url}" class="text-[#155EEF]">${url}</a>`
+        // }),
+      }}></div>
+    </div>
+  )
+  return (
+    <div className={cn(s.wrap, !isShowDetail && s.wrapHoverEffect, 'inline-block mb-2 px-2 py-0.5 rounded-md text-xs text-gray-500 font-medium')} >
+      <div className='flex items-center h-6 space-x-1 cursor-pointer' onClick={() => setIsShowDetail(!isShowDetail)} >
+        {!isThinking ? <ThoughtList /> : <div className='animate-spin'><LodingIcon /></div>}
+        <div dangerouslySetInnerHTML= {{
+          __html: isThinking ? getThoughtText(list[list.length - 1]) : (t(`explore.universalChat.thought.${isShowDetail ? 'hide' : 'show'}`) + t('explore.universalChat.thought.processOfThought')),
+        }}
+        ></div>
+        <ChevronDown className={isShowDetail ? 'rotate-180' : '' } />
+      </div>
+      {isShowDetail && (
+        <div>
+          {list.map(item => renderItem(item))}
+        </div>
+      )}
+    </div>
+  )
+}
+export default React.memo(Thought)

web/app/components/app/chat/thought/style.module.css

+.wrap {
+  background-color: rgba(255, 255, 255, 0.92);
+}
+
+.wrapHoverEffect:hover{
+  box-shadow: 0px 1px 2px 0px rgba(16, 24, 40, 0.06), 0px 1px 3px 0px rgba(16, 24, 40, 0.1);
+}
\ No newline at end of file

web/app/components/app/chat/type.ts

+import type { Annotation, MessageRating } from '@/models/log'
+
+export type MessageMore = {
+  time: string
+  tokens: number
+  latency: number | string
+}
+
+export type Feedbacktype = {
+  rating: MessageRating
+  content?: string | null
+}
+
+export type FeedbackFunc = (messageId: string, feedback: Feedbacktype) => Promise<any>
+export type SubmitAnnotationFunc = (messageId: string, content: string) => Promise<any>
+
+export type DisplayScene = 'web' | 'console'
+
+export type ThoughtItem = {
+  id: string
+  tool: string // plugin or dataset
+  thought: string
+  tool_input: string
+  message_id: string
+}
+export type IChatItem = {
+  id: string
+  content: string
+  agent_thoughts?: ThoughtItem[]
+  /**
+   * Specific message type
+   */
+  isAnswer: boolean
+  /**
+   * The user feedback result of this message
+   */
+  feedback?: Feedbacktype
+  /**
+   * The admin feedback result of this message
+   */
+  adminFeedback?: Feedbacktype
+  /**
+   * Whether to hide the feedback area
+   */
+  feedbackDisabled?: boolean
+  /**
+   * More information about this message
+   */
+  more?: MessageMore
+  annotation?: Annotation
+  useCurrentUserAvatar?: boolean
+  isOpeningStatement?: boolean
+}

web/app/components/app/configuration/base/feature-panel/index.tsx

 'use client'
-import React, { FC, ReactNode } from 'react'
+import type { FC, ReactNode } from 'react'
+import React from 'react'
 import cn from 'classnames'
 
-export interface IFeaturePanelProps {
+export type IFeaturePanelProps = {
   className?: string
-  headerIcon: ReactNode
+  headerIcon?: ReactNode
   title: ReactNode
-  headerRight: ReactNode
+  headerRight?: ReactNode
   hasHeaderBottomBorder?: boolean
   isFocus?: boolean
   noBodySpacing?: boolean
@@ -26,15 +27,17 @@ const FeaturePanel: FC<IFeaturePanelProps> = ({
   return (
     <div
       className={cn(className, isFocus && 'border border-[#2D0DEE]', 'rounded-xl bg-gray-50 pt-2 pb-3', noBodySpacing && '!pb-0')}
-      style={isFocus ? {
+      style={isFocus
+        ? {
           boxShadow: '0px 4px 8px -2px rgba(16, 24, 40, 0.1), 0px 2px 4px -2px rgba(16, 24, 40, 0.06)',
-      } : {}}
+        }
+        : {}}
     >
       {/* Header */}
       <div className={cn('pb-2 px-3', hasHeaderBottomBorder && 'border-b border-gray-100')}>
         <div className='flex justify-between items-center h-8'>
           <div className='flex items-center space-x-1 shrink-0'>
-            <div className='flex items-center justify-center w-4 h-4'>{headerIcon}</div>
+            {headerIcon && <div className='flex items-center justify-center w-4 h-4'>{headerIcon}</div>}
             <div className='text-sm font-semibold text-gray-800'>{title}</div>
           </div>
           <div>

web/app/components/app/configuration/config-model/index.tsx

@@ -6,15 +6,15 @@ import { useTranslation } from 'react-i18next'
 import { useBoolean, useClickAway } from 'ahooks'
 import { ChevronDownIcon, Cog8ToothIcon, InformationCircleIcon } from '@heroicons/react/24/outline'
 import ParamItem from './param-item'
+import ModelIcon from './model-icon'
 import Radio from '@/app/components/base/radio'
 import Panel from '@/app/components/base/panel'
 import type { CompletionParams } from '@/models/debug'
 import { AppType, ProviderType } from '@/types/app'
-import { TONE_LIST } from '@/config'
+import { MODEL_LIST, TONE_LIST } from '@/config'
 import Toast from '@/app/components/base/toast'
 import { AlertTriangle } from '@/app/components/base/icons/src/vender/solid/alertsAndFeedback'
 import { formatNumber } from '@/utils/format'
-
 export type IConifgModelProps = {
   mode: string
   modelId: string
@@ -26,19 +26,7 @@ export type IConifgModelProps = {
   onShowUseGPT4Confirm: () => void
 }
 
-const options = [
-  { id: 'gpt-3.5-turbo', name: 'gpt-3.5-turbo', type: AppType.chat },
-  { id: 'gpt-3.5-turbo-16k', name: 'gpt-3.5-turbo-16k', type: AppType.chat },
-  { id: 'gpt-4', name: 'gpt-4', type: AppType.chat }, // 8k version
-  { id: 'claude-instant-1', name: 'claude-instant-1', type: AppType.chat, provider: ProviderType.anthropic }, // set 30k
-  { id: 'claude-2', name: 'claude-2', type: AppType.chat, provider: ProviderType.anthropic }, // set 30k
-  { id: 'gpt-3.5-turbo', name: 'gpt-3.5-turbo', type: AppType.completion },
-  { id: 'gpt-3.5-turbo-16k', name: 'gpt-3.5-turbo-16k', type: AppType.completion },
-  { id: 'text-davinci-003', name: 'text-davinci-003', type: AppType.completion },
-  { id: 'gpt-4', name: 'gpt-4', type: AppType.completion }, // 8k version
-  { id: 'claude-instant-1', name: 'claude-instant-1', type: AppType.completion, provider: ProviderType.anthropic }, // set 30k
-  { id: 'claude-2', name: 'claude-2', type: AppType.completion, provider: ProviderType.anthropic }, // set 30k
-]
+const options = MODEL_LIST
 
 const getMaxToken = (modelId: string) => {
   if (['claude-instant-1', 'claude-2'].includes(modelId))
@@ -50,30 +38,6 @@ const getMaxToken = (modelId: string) => {
   return 4000
 }
 
-const ModelIcon = ({ provider, className }: { provider?: ProviderType; className?: string }) => {
-  if (provider === ProviderType.anthropic) {
-    return (
-      <svg className={`w-4 h-4 ${className}`} width="24" height="24" viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg">
-        <rect width="24" height="24" rx="6" fill="#CA9F7B"/>
-        <g clip-path="url(#clip0_3907_39360)">
-          <path d="M14.9613 7.13043H12.8476L16.7022 16.8696H18.8159L14.9613 7.13043ZM8.85457 7.13043L5 16.8696H7.15539L7.94365 14.8243H11.9763L12.7645 16.8696H14.9199L11.0653 7.13043H8.85457ZM8.64091 13.0156L9.95996 9.59291L11.279 13.0156H8.64091Z" fill="#191918"/>
-        </g>
-        <defs>
-          <clipPath id="clip0_3907_39360">
-            <rect width="14" height="9.73913" fill="white" transform="translate(5 7.13043)"/>
-          </clipPath>
-        </defs>
-      </svg>
-    )
-  }
-  return (
-    <svg className={`w-4 h-4 ${className}`} width="20" height="20" viewBox="0 0 20 20" fill="none" xmlns="http://www.w3.org/2000/svg">
-      <rect width="20" height="20" rx="6" fill="black" />
-      <path d="M16.5963 9.65729C16.748 9.99569 16.8443 10.3574 16.8836 10.7265C16.9216 11.0955 16.9026 11.4689 16.8238 11.8321C16.7465 12.1953 16.6123 12.5439 16.4256 12.8648C16.3031 13.0793 16.1587 13.2805 15.9924 13.4658C15.8276 13.6496 15.6438 13.8159 15.444 13.9617C15.2427 14.1076 15.0283 14.2301 14.8007 14.3308C14.5746 14.4299 14.3383 14.5058 14.0962 14.5554C13.9824 14.9084 13.8132 15.2424 13.5944 15.5429C13.3771 15.8434 13.1131 16.1074 12.8126 16.3247C12.5121 16.5435 12.1795 16.7127 11.8266 16.8265C11.4736 16.9417 11.1045 16.9986 10.7326 16.9986C10.4861 17.0001 10.2381 16.9738 9.99596 16.9242C9.75529 16.8732 9.51899 16.7959 9.2929 16.6952C9.06681 16.5946 8.85239 16.4691 8.65256 16.3233C8.45418 16.1774 8.2704 16.0097 8.10703 15.8244C7.74237 15.9032 7.36896 15.9221 6.99992 15.8842C6.63089 15.8448 6.26914 15.7486 5.92928 15.5969C5.59088 15.4466 5.27727 15.2424 5.00159 14.993C4.72591 14.7436 4.49107 14.4518 4.30582 14.1309C4.18184 13.9165 4.07973 13.6904 4.00242 13.4556C3.92511 13.2207 3.87406 12.9786 3.84781 12.7321C3.82155 12.487 3.82301 12.2391 3.84927 11.9926C3.87552 11.7475 3.92949 11.5054 4.0068 11.2705C3.75883 10.9949 3.55462 10.6813 3.40292 10.3428C3.25268 10.003 3.15495 9.6427 3.11703 9.27367C3.07765 8.90463 3.09807 8.53122 3.17538 8.16802C3.25268 7.80482 3.38688 7.4562 3.57358 7.1353C3.69611 6.92088 3.84051 6.71813 4.00534 6.53434C4.17017 6.35056 4.35541 6.18427 4.55525 6.03841C4.75508 5.89254 4.97096 5.76856 5.19705 5.66937C5.42459 5.56873 5.66089 5.49434 5.90303 5.44474C6.0168 5.09029 6.186 4.75772 6.40334 4.45725C6.62213 4.15677 6.88615 3.89275 7.18663 3.67396C7.48711 3.45662 7.81968 3.28742 8.17267 3.17219C8.52566 3.05841 8.89469 3.00007 9.26664 3.00153C9.51315 3.00007 9.76112 3.02486 10.0033 3.07592C10.2454 3.12697 10.4817 3.20282 10.7078 3.30346C10.9339 3.40557 11.1483 3.52955 11.3481 3.67542C11.548 3.82274 11.7317 3.98902 11.8951 4.17427C12.2583 4.09696 12.6317 4.078 13.0008 4.11592C13.3698 4.15385 13.7301 4.25158 14.0699 4.40182C14.4083 4.55352 14.7219 4.75627 14.9976 5.00569C15.2733 5.25366 15.5082 5.54393 15.6934 5.86629C15.8174 6.07925 15.9195 6.30534 15.9968 6.54164C16.0741 6.77648 16.1266 7.01861 16.1514 7.26512C16.1777 7.51163 16.1777 7.7596 16.15 8.00611C16.1237 8.25262 16.0697 8.49475 15.9924 8.72959C16.2418 9.00528 16.4446 9.31742 16.5963 9.65729ZM11.7361 15.8842C12.0541 15.7529 12.3429 15.5589 12.5865 15.3153C12.8301 15.0717 13.0241 14.7829 13.1554 14.4635C13.2866 14.1455 13.3552 13.8042 13.3552 13.46V10.2072C13.3542 10.2043 13.3533 10.2009 13.3523 10.197C13.3513 10.1941 13.3499 10.1911 13.3479 10.1882C13.346 10.1853 13.3435 10.1829 13.3406 10.1809C13.3377 10.178 13.3348 10.1761 13.3319 10.1751L12.1547 9.49538V13.4249C12.1547 13.4643 12.1489 13.5052 12.1387 13.5431C12.1285 13.5825 12.1139 13.6189 12.0935 13.654C12.0731 13.689 12.0497 13.7211 12.0206 13.7488C11.9922 13.777 11.9603 13.8015 11.9257 13.8217L9.13828 15.4306C9.11495 15.4452 9.07556 15.4656 9.05514 15.4772C9.17037 15.575 9.29582 15.661 9.42709 15.7369C9.55983 15.8127 9.69694 15.8769 9.83989 15.9294C9.98284 15.9805 10.1302 16.0199 10.2789 16.0461C10.4292 16.0724 10.5809 16.0855 10.7326 16.0855C11.0768 16.0855 11.4181 16.0169 11.7361 15.8842ZM5.09786 13.6758C5.27144 13.9749 5.50044 14.2345 5.77321 14.4445C6.04743 14.6546 6.35812 14.8077 6.69069 14.8967C7.02326 14.9857 7.37042 15.009 7.71174 14.9638C8.05306 14.9186 8.38125 14.8077 8.68027 14.6356L11.4984 13.0092L11.5057 13.0019C11.5076 13 11.5091 12.9971 11.51 12.9932C11.512 12.9903 11.5134 12.9874 11.5144 12.9844V11.6133L8.11286 13.581C8.07786 13.6014 8.04139 13.616 8.00346 13.6277C7.96408 13.6379 7.9247 13.6423 7.88386 13.6423C7.84447 13.6423 7.80509 13.6379 7.76571 13.6277C7.72778 13.616 7.68986 13.6014 7.65485 13.581L4.86739 11.9707C4.8426 11.9561 4.80613 11.9342 4.78571 11.9211C4.75946 12.0713 4.74633 12.223 4.74633 12.3747C4.74633 12.5264 4.76091 12.6781 4.78717 12.8284C4.81342 12.9771 4.85427 13.1245 4.90532 13.2674C4.95783 13.4104 5.02201 13.5475 5.09786 13.6788V13.6758ZM4.36562 7.59332C4.1935 7.89234 4.08265 8.22199 4.03743 8.56331C3.99221 8.90463 4.01555 9.25033 4.10453 9.58436C4.1935 9.91692 4.34666 10.2276 4.5567 10.5018C4.76675 10.7746 5.02784 11.0036 5.32541 11.1757L8.14204 12.8036C8.14495 12.8045 8.14836 12.8055 8.15225 12.8065H8.16246C8.16635 12.8065 8.16975 12.8055 8.17267 12.8036C8.17558 12.8026 8.1785 12.8011 8.18142 12.7992L9.36291 12.1165L5.96137 10.1532C5.92782 10.1328 5.89573 10.108 5.86656 10.0803C5.8383 10.0519 5.81379 10.0201 5.79363 9.98548C5.77467 9.95047 5.75862 9.91401 5.74841 9.87462C5.7382 9.8367 5.73237 9.79732 5.73383 9.75647V6.44391C5.59088 6.49642 5.45231 6.5606 5.32103 6.63645C5.18975 6.71376 5.06577 6.80128 4.94908 6.899C4.83385 6.99673 4.72591 7.10467 4.62818 7.22136C4.53045 7.3366 4.44439 7.46204 4.36854 7.59332H4.36562ZM14.0408 9.84545C14.0758 9.86587 14.1079 9.88921 14.137 9.91838C14.1647 9.9461 14.1895 9.97819 14.21 10.0132C14.2289 10.0482 14.245 10.0861 14.2552 10.1241C14.2639 10.1634 14.2698 10.2028 14.2683 10.2437V13.5562C14.7365 13.3841 15.145 13.0822 15.4469 12.6854C15.7503 12.2887 15.9326 11.8146 15.9749 11.3187C16.0172 10.8227 15.918 10.3239 15.6876 9.88192C15.4571 9.43995 15.1056 9.07237 14.6738 8.82441L11.8572 7.19657C11.8543 7.19559 11.8509 7.19462 11.847 7.19365H11.8368C11.8338 7.19462 11.8304 7.19559 11.8266 7.19657C11.8236 7.19754 11.8207 7.199 11.8178 7.20094L10.6421 7.88067L14.0437 9.84545H14.0408ZM15.215 8.0805H15.2135V8.08196L15.215 8.0805ZM15.2135 8.07904C15.2981 7.58894 15.2412 7.08425 15.0487 6.62478C14.8576 6.16531 14.5382 5.77002 14.1297 5.48413C13.7213 5.19969 13.24 5.03632 12.7426 5.01445C12.2437 4.99402 11.7507 5.11509 11.3189 5.36306L8.50232 6.98944C8.4994 6.99138 8.49697 6.99382 8.49503 6.99673L8.48919 7.00549C8.48822 7.0084 8.48725 7.01181 8.48627 7.0157C8.4853 7.01861 8.48482 7.02202 8.48482 7.02591V8.38536L11.8864 6.42057C11.9214 6.40015 11.9593 6.38556 11.9972 6.37389C12.0366 6.36368 12.076 6.35931 12.1154 6.35931C12.1562 6.35931 12.1956 6.36368 12.235 6.37389C12.2729 6.38556 12.3094 6.40015 12.3444 6.42057L15.1318 8.03091C15.1566 8.04549 15.1931 8.06591 15.2135 8.07904ZM7.84301 6.57373C7.84301 6.53434 7.84885 6.49496 7.85906 6.45558C7.86927 6.41765 7.88386 6.37973 7.90428 6.34472C7.9247 6.31117 7.94804 6.27908 7.97721 6.24991C8.00492 6.2222 8.03701 6.1974 8.07202 6.17844L10.8595 4.56956C10.8857 4.55352 10.9222 4.53309 10.9426 4.52288C10.5605 4.20344 10.0937 3.99923 9.59921 3.93651C9.10474 3.87233 8.60296 3.9511 8.15225 4.1626C7.70007 4.3741 7.3179 4.71105 7.05097 5.13114C6.78404 5.55268 6.64256 6.03987 6.64256 6.53872V9.79148C6.64353 9.79537 6.6445 9.79878 6.64547 9.80169C6.64645 9.80461 6.6479 9.80753 6.64985 9.81044C6.65179 9.81336 6.65422 9.81628 6.65714 9.8192C6.65909 9.82114 6.662 9.82309 6.66589 9.82503L7.84301 10.5048V6.57373ZM8.4819 10.8723L9.99742 11.7475L11.5129 10.8723V9.12343L9.99888 8.24824L8.48336 9.12343L8.4819 10.8723Z" fill="white" />
-    </svg>
-  )
-}
-
 const ConifgModel: FC<IConifgModelProps> = ({
   mode,
   modelId,
@@ -227,7 +191,7 @@ const ConifgModel: FC<IConifgModelProps> = ({
         className={cn('flex items-center border h-8 px-2.5 space-x-2 rounded-lg', disabled ? diabledStyle : ableStyle)}
         onClick={() => !disabled && toogleShowConfig()}
       >
-        <ModelIcon provider={currModel?.provider} />
+        <ModelIcon modelId={currModel?.id as string} />
         <div className='text-[13px] text-gray-900 font-medium'>{selectedModel.name}</div>
         {disabled ? <InformationCircleIcon className='w-3.5 h-3.5 text-[#F79009]' /> : <Cog8ToothIcon className='w-3.5 h-3.5 text-gray-500' />}
       </div>
@@ -254,7 +218,7 @@ const ConifgModel: FC<IConifgModelProps> = ({
               {/* model selector */}
               <div className="relative" style={{ zIndex: 30 }}>
                 <div ref={triggerRef} onClick={() => !selectModelDisabled && toogleOption()} className={cn(selectModelDisabled ? 'cursor-not-allowed' : 'cursor-pointer', 'flex items-center h-9 px-3 space-x-2 rounded-lg bg-gray-50 ')}>
-                  <ModelIcon provider={currModel?.provider} />
+                  <ModelIcon modelId={currModel?.id as string} />
                   <div className="text-sm gray-900">{selectedModel?.name}</div>
                   {!selectModelDisabled && <ChevronDownIcon className={cn(isShowOption && 'rotate-180', 'w-[14px] h-[14px] text-gray-500')} />}
                 </div>
@@ -262,7 +226,7 @@ const ConifgModel: FC<IConifgModelProps> = ({
                   <div className={cn(isChatApp ? 'min-w-[159px]' : 'w-[179px]', 'absolute right-0 bg-gray-50 rounded-lg shadow')}>
                     {availableModels.map(item => (
                       <div key={item.id} onClick={handleSelectModel(item.id, item.provider)} className="flex items-center h-9 px-3 rounded-lg cursor-pointer hover:bg-gray-100">
-                        <ModelIcon className='shrink-0 mr-2' provider={item?.provider} />
+                        <ModelIcon className='shrink-0 mr-2' modelId={item?.id} />
                         <div className="text-sm gray-900 whitespace-nowrap">{item.name}</div>
                       </div>
                     ))}

web/app/components/app/configuration/config-model/model-icon.tsx

+'use client'
+import type { FC } from 'react'
+import React from 'react'
+import { ProviderType } from '@/types/app'
+import { MODEL_LIST } from '@/config'
+import { Anthropic, Gpt3, Gpt4 } from '@/app/components/base/icons/src/public/llm'
+
+export type IModelIconProps = { modelId: string; className?: string }
+
+const ModelIcon: FC<IModelIconProps> = ({ modelId, className }) => {
+  const resClassName = `w-4 h-4 ${className}`
+  const model = MODEL_LIST.find(item => item.id === modelId)
+  if (model?.id === 'gpt-4')
+    return <Gpt4 className={resClassName} />
+
+  if (model?.provider === ProviderType.anthropic) {
+    return (
+      <Anthropic className={resClassName} />
+    )
+  }
+  return (
+    <Gpt3 className={resClassName} />
+  )
+}
+
+export default React.memo(ModelIcon)

web/app/components/app/configuration/config/index.tsx

@@ -4,7 +4,6 @@ import React from 'react'
 import { useContext } from 'use-context-selector'
 import produce from 'immer'
 import { useBoolean } from 'ahooks'
-import useSWR from 'swr'
 import DatasetConfig from '../dataset-config'
 import ChatGroup from '../features/chat-group'
 import ExperienceEnchanceGroup from '../features/experience-enchance-group'
@@ -20,7 +19,7 @@ import ConfigPrompt from '@/app/components/app/configuration/config-prompt'
 import ConfigVar from '@/app/components/app/configuration/config-var'
 import type { PromptVariable } from '@/models/debug'
 import { AppType } from '@/types/app'
-import { fetchTenantInfo } from '@/service/common'
+import { useProviderContext } from '@/context/provider-context'
 
 const Config: FC = () => {
   const {
@@ -39,8 +38,7 @@ const Config: FC = () => {
     setSpeechToTextConfig,
   } = useContext(ConfigContext)
   const isChatApp = mode === AppType.chat
-  const { data: userInfo } = useSWR({ url: '/info' }, fetchTenantInfo)
-  const openaiProvider = userInfo?.providers?.find(({ token_is_set, is_valid, provider_name }) => token_is_set && is_valid && provider_name === 'openai')
+  const { currentProvider } = useProviderContext()
 
   const promptTemplate = modelConfig.configs.prompt_template
   const promptVariables = modelConfig.configs.prompt_variables
@@ -92,7 +90,7 @@ const Config: FC = () => {
     },
   })
 
-  const hasChatConfig = isChatApp && (featureConfig.openingStatement || featureConfig.suggestedQuestionsAfterAnswer || (featureConfig.speechToText && openaiProvider))
+  const hasChatConfig = isChatApp && (featureConfig.openingStatement || featureConfig.suggestedQuestionsAfterAnswer || (featureConfig.speechToText && currentProvider?.provider_name === 'openai'))
   const hasToolbox = false
 
   const [showAutomatic, { setTrue: showAutomaticTrue, setFalse: showAutomaticFalse }] = useBoolean(false)
@@ -122,7 +120,7 @@ const Config: FC = () => {
             isChatApp={isChatApp}
             config={featureConfig}
             onChange={handleFeatureChange}
-            showSpeechToTextItem={!!openaiProvider}
+            showSpeechToTextItem={currentProvider?.provider_name === 'openai'}
           />
         )}
         {showAutomatic && (
@@ -162,7 +160,7 @@ const Config: FC = () => {
                 }
               }
               isShowSuggestedQuestionsAfterAnswer={featureConfig.suggestedQuestionsAfterAnswer}
-              isShowSpeechText={featureConfig.speechToText}
+              isShowSpeechText={featureConfig.speechToText && currentProvider?.provider_name === 'openai'}
             />
           )
         }

web/app/components/app/configuration/dataset-config/card-item/index.tsx

 'use client'
-import React, { FC } from 'react'
+import type { FC } from 'react'
+import React from 'react'
 import cn from 'classnames'
-import TypeIcon from '../type-icon'
 import { useTranslation } from 'react-i18next'
-import { formatNumber } from '@/utils/format'
+import TypeIcon from '../type-icon'
 import RemoveIcon from '../../base/icons/remove-icon'
 import s from './style.module.css'
+import { formatNumber } from '@/utils/format'
 
-export interface ICardItemProps {
+export type ICardItemProps = {
   className?: string
   config: any
   onRemove: (id: string) => void
+  readonly?: boolean
 }
 
-
-
 // const RemoveIcon = ({ className, onClick }: { className: string, onClick: () => void }) => (
 //   <svg className={className} onClick={onClick} width="24" height="24" viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg">
 //     <path d="M10 6H14M6 8H18M16.6667 8L16.1991 15.0129C16.129 16.065 16.0939 16.5911 15.8667 16.99C15.6666 17.3412 15.3648 17.6235 15.0011 17.7998C14.588 18 14.0607 18 13.0062 18H10.9938C9.93927 18 9.41202 18 8.99889 17.7998C8.63517 17.6235 8.33339 17.3412 8.13332 16.99C7.90607 16.5911 7.871 16.065 7.80086 15.0129L7.33333 8M10.6667 11V14.3333M13.3333 11V14.3333" stroke="#667085" strokeWidth="1.5" strokeLinecap="round" strokeLinejoin="round" />
@@ -24,7 +24,8 @@ export interface ICardItemProps {
 const CardItem: FC<ICardItemProps> = ({
   className,
   config,
-  onRemove
+  onRemove,
+  readonly,
 }) => {
   const { t } = useTranslation()
 
@@ -44,7 +45,7 @@ const CardItem: FC<ICardItemProps> = ({
         </div>
       </div>
 
-      <RemoveIcon className={`${s.deleteBtn} shrink-0`} onClick={() => onRemove(config.id)} />
+      {!readonly && <RemoveIcon className={`${s.deleteBtn} shrink-0`} onClick={() => onRemove(config.id)} />}
     </div>
   )
 }

web/app/components/app/configuration/dataset-config/select-dataset/index.tsx

@@ -128,8 +128,12 @@ const SelectDataSet: FC<ISelectDataSetProps> = ({
                   <div className='max-w-[200px] text-[13px] font-medium text-gray-800 overflow-hidden text-ellipsis whitespace-nowrap'>{item.name}</div>
                 </div>
 
-                <div className='max-w-[140px] flex text-xs text-gray-500  overflow-hidden text-ellipsis whitespace-nowrap'>
-                  {formatNumber(item.word_count)} {t('appDebug.feature.dataSet.words')} · {formatNumber(item.document_count)} {t('appDebug.feature.dataSet.textBlocks')}
+                <div className='flex text-xs text-gray-500 overflow-hidden whitespace-nowrap'>
+                  <span className='max-w-[100px] overflow-hidden text-ellipsis whitespace-nowrap'>{formatNumber(item.word_count)}</span>
+                  {t('appDebug.feature.dataSet.words')}
+                  <span className='px-0.5'>·</span>
+                  <span className='max-w-[100px] min-w-[8px] overflow-hidden text-ellipsis whitespace-nowrap'>{formatNumber(item.document_count)} </span>
+                  {t('appDebug.feature.dataSet.textBlocks')}
                 </div>
               </div>
             ))}

web/app/components/app/configuration/debug/index.tsx

@@ -22,6 +22,7 @@ import type { ModelConfig as BackendModelConfig } from '@/types/app'
 import { promptVariablesToUserInputsForm } from '@/utils/model-config'
 import TextGeneration from '@/app/components/app/text-generate/item'
 import { IS_CE_EDITION } from '@/config'
+import { useProviderContext } from '@/context/provider-context'
 
 type IDebug = {
   hasSetAPIKEY: boolean
@@ -51,7 +52,7 @@ const Debug: FC<IDebug> = ({
     modelConfig,
     completionParams,
   } = useContext(ConfigContext)
-
+  const { currentProvider } = useProviderContext()
   const [chatList, setChatList, getChatList] = useGetState<IChatItem[]>([])
   const chatListDomRef = useRef<HTMLDivElement>(null)
   useEffect(() => {
@@ -389,7 +390,7 @@ const Debug: FC<IDebug> = ({
                   }}
                   isShowSuggestion={doShowSuggestion}
                   suggestionList={suggestQuestions}
-                  isShowSpeechToText={speechToTextConfig.enabled}
+                  isShowSpeechToText={speechToTextConfig.enabled && currentProvider?.provider_name === 'openai'}
                 />
               </div>
             </div>

web/app/components/app/configuration/prompt-value-panel/index.tsx

 'use client'
 import type { FC } from 'react'
-import React from 'react'
+import React, { useState } from 'react'
 import { useTranslation } from 'react-i18next'
 import { useContext } from 'use-context-selector'
 import {
@@ -13,6 +13,7 @@ import { AppType } from '@/types/app'
 import Select from '@/app/components/base/select'
 import { DEFAULT_VALUE_MAX_LEN } from '@/config'
 import Button from '@/app/components/base/button'
+import { ChevronDown, ChevronRight } from '@/app/components/base/icons/src/vender/line/arrows'
 
 export type IPromptValuePanelProps = {
   appType: AppType
@@ -37,6 +38,8 @@ const PromptValuePanel: FC<IPromptValuePanelProps> = ({
 }) => {
   const { t } = useTranslation()
   const { modelConfig, inputs, setInputs } = useContext(ConfigContext)
+  const [promptPreviewCollapse, setPromptPreviewCollapse] = useState(false)
+  const [userInputFieldCollapse, setUserInputFieldCollapse] = useState(false)
   const promptTemplate = modelConfig.configs.prompt_template
   const promptVariables = modelConfig.configs.prompt_variables.filter(({ key, name }) => {
     return key && key?.trim() && name && name?.trim()
@@ -63,12 +66,19 @@ const PromptValuePanel: FC<IPromptValuePanelProps> = ({
   }
 
   const promptPreview = (
-    <div className='pt-3 pb-4 rounded-t-xl bg-indigo-25'>
+    <div className='py-3 rounded-t-xl bg-indigo-25'>
       <div className="px-4">
-        <div className="flex items-center space-x-1">
+        <div className="flex items-center space-x-1 cursor-pointer" onClick={() => setPromptPreviewCollapse(!promptPreviewCollapse)}>
           {starIcon}
           <div className="text-xs font-medium text-indigo-600 uppercase">{t('appDebug.inputs.previewTitle')}</div>
+          {
+            promptPreviewCollapse
+              ? <ChevronRight className='w-3 h-3 text-gray-700' />
+              : <ChevronDown className='w-3 h-3 text-gray-700' />
+          }
         </div>
+        {
+          !promptPreviewCollapse && (
             <div className='mt-2  leading-normal'>
               {
                 (promptTemplate && promptTemplate?.trim())
@@ -86,26 +96,38 @@ const PromptValuePanel: FC<IPromptValuePanelProps> = ({
                   )
               }
             </div>
+          )
+        }
       </div>
     </div>
   )
 
   return (
-    <div className="pb-5 border border-gray-200 bg-white rounded-xl" style={{
+    <div className="pb-3 border border-gray-200 bg-white rounded-xl" style={{
       boxShadow: '0px 4px 8px -2px rgba(16, 24, 40, 0.1), 0px 2px 4px -2px rgba(16, 24, 40, 0.06)',
     }}>
       {promptPreview}
 
-      <div className="mt-5 px-4">
-        <div className='mb-4 '>
-          <div className='flex items-center space-x-1'>
+      <div className={'mt-3 px-4 bg-white'}>
+        <div className={
+          `${!userInputFieldCollapse && 'mb-2'}`
+        }>
+          <div className='flex items-center space-x-1 cursor-pointer' onClick={() => setUserInputFieldCollapse(!userInputFieldCollapse)}>
             <div className='flex items-center justify-center w-4 h-4'><VarIcon /></div>
-            <div className='text-sm font-semibold text-gray-800'>{t('appDebug.inputs.userInputField')}</div>
+            <div className='text-xs font-medium text-gray-800'>{t('appDebug.inputs.userInputField')}</div>
+            {
+              userInputFieldCollapse
+                ? <ChevronRight className='w-3 h-3 text-gray-700' />
+                : <ChevronDown className='w-3 h-3 text-gray-700' />
+            }
           </div>
-          {appType === AppType.completion && promptVariables.length > 0 && (
+          {appType === AppType.completion && promptVariables.length > 0 && !userInputFieldCollapse && (
             <div className="mt-1 text-xs leading-normal text-gray-500">{t('appDebug.inputs.completionVarTip')}</div>
           )}
         </div>
+        {
+          !userInputFieldCollapse && (
+            <>
               {
                 promptVariables.length > 0
                   ? (
@@ -144,12 +166,15 @@ const PromptValuePanel: FC<IPromptValuePanelProps> = ({
                     <div className='text-xs text-gray-500'>{t('appDebug.inputs.noVar')}</div>
                   )
               }
+            </>
+          )
+        }
       </div>
 
       {
         appType === AppType.completion && (
           <div className='px-4'>
-            <div className="mt-5 border-b border-gray-100"></div>
+            <div className="mt-3 border-b border-gray-100"></div>
             <div className="mt-4">
               <div>
                 <div className="text-[13px] text-gray-900 font-medium">{t('appDebug.inputs.queryTitle')}</div>

web/app/components/app/log/list.tsx

@@ -16,10 +16,10 @@ import dayjs from 'dayjs'
 import { createContext, useContext } from 'use-context-selector'
 import classNames from 'classnames'
 import { useTranslation } from 'react-i18next'
-import { EditIconSolid } from '../chat'
 import { randomString } from '../../app-sidebar/basic'
 import s from './style.module.css'
-import type { FeedbackFunc, Feedbacktype, IChatItem, SubmitAnnotationFunc } from '@/app/components/app/chat'
+import { EditIconSolid } from '@/app/components/app/chat/icon-component'
+import type { FeedbackFunc, Feedbacktype, IChatItem, SubmitAnnotationFunc } from '@/app/components/app/chat/type'
 import type { Annotation, ChatConversationFullDetailResponse, ChatConversationGeneralDetail, ChatConversationsResponse, ChatMessage, ChatMessagesRequest, CompletionConversationFullDetailResponse, CompletionConversationGeneralDetail, CompletionConversationsResponse } from '@/models/log'
 import type { App } from '@/types/app'
 import Loading from '@/app/components/base/loading'
@@ -412,7 +412,7 @@ const ConversationList: FC<IConversationList> = ({ logs, appDetail, onRefresh })
         </thead>
         <tbody className="text-gray-500">
           {logs.data.map((log) => {
-            const endUser = log.from_end_user_id?.slice(0, 8)
+            const endUser = log.from_end_user_session_id
             const leftValue = get(log, isChatMode ? 'summary' : 'message.query')
             const rightValue = get(log, isChatMode ? 'message_count' : 'message.answer')
             return <tr

web/app/components/base/icons/assets/public/llm/anthropic.svg

+<svg width="24" height="24" viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg">
+<rect width="24" height="24" rx="6" fill="#CA9F7B"/>
+<g clip-path="url(#clip0_7672_55906)">
+<path d="M15.3843 6.43457H12.9687L17.3739 17.565H19.7896L15.3843 6.43457ZM8.40522 6.43457L4 17.565H6.4633L7.36417 15.2276H11.9729L12.8737 17.565H15.337L10.9318 6.43457H8.40522ZM8.16104 13.1605L9.66852 9.24883L11.176 13.1605H8.16104Z" fill="#191918"/>
+</g>
+<rect x="0.5" y="0.5" width="23" height="23" rx="5.5" stroke="black" stroke-opacity="0.05"/>
+<defs>
+<clipPath id="clip0_7672_55906">
+<rect width="16" height="11.1304" fill="white" transform="translate(4 6.43457)"/>
+</clipPath>
+</defs>
+</svg>

web/app/components/base/icons/assets/public/llm/gpt-3.svg

+<svg width="24" height="24" viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg">
+<rect width="24" height="24" rx="6" fill="#19C37D"/>
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+<rect x="0.5" y="0.5" width="23" height="23" rx="5.5" stroke="black" stroke-opacity="0.05"/>
+</svg>

web/app/components/base/icons/assets/public/llm/gpt-4.svg

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+<path d="M4.5 1.75V1M2.53033 2.53033L2 2M2.53033 6.5L2 7.03033M6.5 2.53033L7.03033 2M1.75 4.5H1M7.93224 8.09479L6.68637 10.4085C6.54404 10.6728 6.47287 10.805 6.38725 10.8384C6.31295 10.8674 6.22926 10.8592 6.16199 10.8164C6.08447 10.767 6.04028 10.6235 5.95191 10.3366L4.22259 4.72263C4.1504 4.48825 4.1143 4.37107 4.14335 4.29192C4.16865 4.22298 4.22298 4.16865 4.29192 4.14335C4.37107 4.1143 4.48825 4.1504 4.72262 4.2226L10.3366 5.95192C10.6235 6.0403 10.767 6.08449 10.8164 6.16201C10.8592 6.22928 10.8674 6.31297 10.8384 6.38727C10.805 6.47289 10.6728 6.54406 10.4085 6.68639L8.09479 7.93224C8.05551 7.95339 8.03587 7.96396 8.01868 7.97755C8.00341 7.98961 7.98961 8.00341 7.97755 8.01868C7.96396 8.03587 7.95339 8.05551 7.93224 8.09479Z" stroke="#667085" stroke-width="1.25" stroke-linecap="round" stroke-linejoin="round"/>
+</g>
+<defs>
+<clipPath id="clip0_7847_32887">
+<rect width="12" height="12" fill="white"/>
+</clipPath>
+</defs>
+</svg>

web/app/components/base/icons/assets/vender/line/general/link-external-02.svg

+<svg width="12" height="12" viewBox="0 0 12 12" fill="none" xmlns="http://www.w3.org/2000/svg">
+<g id="link-external-02">
+<path id="Icon" d="M10.5 4.5L10.5 1.5M10.5 1.5H7.49999M10.5 1.5L6 6M5 1.5H3.9C3.05992 1.5 2.63988 1.5 2.31901 1.66349C2.03677 1.8073 1.8073 2.03677 1.66349 2.31901C1.5 2.63988 1.5 3.05992 1.5 3.9V8.1C1.5 8.94008 1.5 9.36012 1.66349 9.68099C1.8073 9.96323 2.03677 10.1927 2.31901 10.3365C2.63988 10.5 3.05992 10.5 3.9 10.5H8.1C8.94008 10.5 9.36012 10.5 9.68099 10.3365C9.96323 10.1927 10.1927 9.96323 10.3365 9.68099C10.5 9.36012 10.5 8.94008 10.5 8.1V7" stroke="#155EEF" stroke-linecap="round" stroke-linejoin="round"/>
+</g>
+</svg>

web/app/components/base/icons/assets/vender/solid/alertsAndFeedback/alert-circle.svg

+<svg width="16" height="16" viewBox="0 0 16 16" fill="none" xmlns="http://www.w3.org/2000/svg">
+<g id="alert-circle">
+<path id="Solid" fill-rule="evenodd" clip-rule="evenodd" d="M8 0.666626C3.94992 0.666626 0.666672 3.94987 0.666672 7.99996C0.666672 12.05 3.94992 15.3333 8 15.3333C12.0501 15.3333 15.3333 12.05 15.3333 7.99996C15.3333 3.94987 12.0501 0.666626 8 0.666626ZM8.66667 5.33329C8.66667 4.9651 8.36819 4.66663 8 4.66663C7.63181 4.66663 7.33334 4.9651 7.33334 5.33329V7.99996C7.33334 8.36815 7.63181 8.66663 8 8.66663C8.36819 8.66663 8.66667 8.36815 8.66667 7.99996V5.33329ZM8 9.99996C7.63181 9.99996 7.33334 10.2984 7.33334 10.6666C7.33334 11.0348 7.63181 11.3333 8 11.3333H8.00667C8.37486 11.3333 8.67334 11.0348 8.67334 10.6666C8.67334 10.2984 8.37486 9.99996 8.00667 9.99996H8Z" fill="#D92D20"/>
+</g>
+</svg>

web/app/components/base/icons/assets/vender/solid/general/check-circle.svg

+<svg width="16" height="16" viewBox="0 0 16 16" fill="none" xmlns="http://www.w3.org/2000/svg">
+<g id="check-circle">
+<path id="Solid" fill-rule="evenodd" clip-rule="evenodd" d="M8 0.666626C3.94992 0.666626 0.666672 3.94987 0.666672 7.99996C0.666672 12.05 3.94992 15.3333 8 15.3333C12.0501 15.3333 15.3333 12.05 15.3333 7.99996C15.3333 3.94987 12.0501 0.666626 8 0.666626ZM11.4714 6.47136C11.7318 6.21101 11.7318 5.7889 11.4714 5.52855C11.2111 5.26821 10.7889 5.26821 10.5286 5.52855L7 9.05715L5.47141 7.52855C5.21106 7.2682 4.78895 7.2682 4.5286 7.52855C4.26825 7.7889 4.26825 8.21101 4.5286 8.47136L6.5286 10.4714C6.78895 10.7317 7.21106 10.7317 7.47141 10.4714L11.4714 6.47136Z" fill="#039855"/>
+</g>
+</svg>

web/app/components/base/icons/src/public/llm/Anthropic.json

+{
+	"icon": {
+		"type": "element",
+		"isRootNode": true,
+		"name": "svg",
+		"attributes": {
+			"width": "24",
+			"height": "24",
+			"viewBox": "0 0 24 24",
+			"fill": "none",
+			"xmlns": "http://www.w3.org/2000/svg"
+		},
+		"children": [
+			{
+				"type": "element",
+				"name": "rect",
+				"attributes": {
+					"width": "24",
+					"height": "24",
+					"rx": "6",
+					"fill": "#CA9F7B"
+				},
+				"children": []
+			},
+			{
+				"type": "element",
+				"name": "g",
+				"attributes": {
+					"clip-path": "url(#clip0_7672_55906)"
+				},
+				"children": [
+					{
+						"type": "element",
+						"name": "path",
+						"attributes": {
+							"d": "M15.3843 6.43457H12.9687L17.3739 17.565H19.7896L15.3843 6.43457ZM8.40522 6.43457L4 17.565H6.4633L7.36417 15.2276H11.9729L12.8737 17.565H15.337L10.9318 6.43457H8.40522ZM8.16104 13.1605L9.66852 9.24883L11.176 13.1605H8.16104Z",
+							"fill": "#191918"
+						},
+						"children": []
+					}
+				]
+			},
+			{
+				"type": "element",
+				"name": "rect",
+				"attributes": {
+					"x": "0.5",
+					"y": "0.5",
+					"width": "23",
+					"height": "23",
+					"rx": "5.5",
+					"stroke": "black",
+					"stroke-opacity": "0.05"
+				},
+				"children": []
+			},
+			{
+				"type": "element",
+				"name": "defs",
+				"attributes": {},
+				"children": [
+					{
+						"type": "element",
+						"name": "clipPath",
+						"attributes": {
+							"id": "clip0_7672_55906"
+						},
+						"children": [
+							{
+								"type": "element",
+								"name": "rect",
+								"attributes": {
+									"width": "16",
+									"height": "11.1304",
+									"fill": "white",
+									"transform": "translate(4 6.43457)"
+								},
+								"children": []
+							}
+						]
+					}
+				]
+			}
+		]
+	},
+	"name": "Anthropic"
+}
\ No newline at end of file

web/app/components/base/icons/src/public/llm/Anthropic.tsx

+// GENERATE BY script
+// DON NOT EDIT IT MANUALLY
+
+import * as React from 'react'
+import data from './Anthropic.json'
+import IconBase from '@/app/components/base/icons/IconBase'
+import type { IconBaseProps, IconData } from '@/app/components/base/icons/IconBase'
+
+const Icon = React.forwardRef<React.MutableRefObject<SVGElement>, Omit<IconBaseProps, 'data'>>((
+  props,
+  ref,
+) => <IconBase {...props} ref={ref} data={data as IconData} />)
+
+export default Icon

web/app/components/base/icons/src/public/llm/Gpt3.json

+{
+	"icon": {
+		"type": "element",
+		"isRootNode": true,
+		"name": "svg",
+		"attributes": {
+			"width": "24",
+			"height": "24",
+			"viewBox": "0 0 24 24",
+			"fill": "none",
+			"xmlns": "http://www.w3.org/2000/svg"
+		},
+		"children": [
+			{
+				"type": "element",
+				"name": "rect",
+				"attributes": {
+					"width": "24",
+					"height": "24",
+					"rx": "6",
+					"fill": "#19C37D"
+				},
+				"children": []
+			},
+			{
+				"type": "element",
+				"name": "path",
+				"attributes": {
+					"d": "M19.6451 11.6028C19.8209 11.995 19.9325 12.4142 19.9781 12.8419C20.0221 13.2696 20.0001 13.7024 19.9088 14.1234C19.8192 14.5443 19.6637 14.9484 19.4473 15.3203C19.3053 15.5688 19.1379 15.8021 18.9452 16.0168C18.7542 16.2298 18.5412 16.4225 18.3096 16.5916C18.0763 16.7606 17.8278 16.9027 17.564 17.0193C17.302 17.1343 17.0281 17.2222 16.7475 17.2796C16.6156 17.6888 16.4195 18.0759 16.1659 18.4242C15.914 18.7724 15.6081 19.0784 15.2598 19.3303C14.9115 19.5839 14.5261 19.78 14.117 19.9118C13.7079 20.0454 13.2802 20.1113 12.8491 20.1113C12.5634 20.113 12.276 20.0826 11.9953 20.0251C11.7164 19.9659 11.4425 19.8763 11.1805 19.7597C10.9184 19.643 10.6699 19.4977 10.4383 19.3286C10.2084 19.1595 9.99541 18.9651 9.80606 18.7504C9.38342 18.8417 8.95064 18.8637 8.52293 18.8197C8.09522 18.7741 7.67596 18.6625 7.28206 18.4867C6.88985 18.3126 6.52638 18.0759 6.20687 17.7868C5.88735 17.4977 5.61517 17.1596 5.40047 16.7877C5.25677 16.5392 5.13843 16.2771 5.04883 16.005C4.95924 15.7328 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17.4727 5.92248 17.7923 6.21157C18.1118 6.49896 18.384 6.83538 18.5987 7.209C18.7423 7.45582 18.8607 7.71786 18.9503 7.99173C19.0399 8.26391 19.1007 8.54454 19.1295 8.83024C19.1599 9.11595 19.1599 9.40334 19.1278 9.68905C19.0974 9.97475 19.0348 10.2554 18.9452 10.5276C19.2343 10.8471 19.4693 11.2089 19.6451 11.6028ZM14.0122 18.8197C14.3807 18.6676 14.7154 18.4428 14.9978 18.1604C15.2801 17.8781 15.5049 17.5434 15.6571 17.1731C15.8092 16.8046 15.8887 16.409 15.8887 16.01V12.2401C15.8876 12.2367 15.8864 12.2328 15.8853 12.2283C15.8842 12.2249 15.8825 12.2215 15.8802 12.2181C15.878 12.2147 15.8752 12.2119 15.8718 12.2097C15.8684 12.2063 15.865 12.204 15.8616 12.2029L14.4974 11.4151V15.9695C14.4974 16.0151 14.4906 16.0624 14.4788 16.1064C14.4669 16.152 14.45 16.1943 14.4264 16.2349C14.4027 16.2755 14.3756 16.3126 14.3418 16.3448C14.309 16.3775 14.272 16.4059 14.2319 16.4293L11.0013 18.294C10.9742 18.3109 10.9286 18.3346 10.9049 18.3481C11.0385 18.4613 11.1839 18.5611 11.336 18.649C11.4899 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9.21062C5.2703 9.55718 5.14182 9.93925 5.08941 10.3348C5.037 10.7304 5.06405 11.1311 5.16717 11.5182C5.2703 11.9037 5.44781 12.2638 5.69125 12.5816C5.93469 12.8977 6.2373 13.1631 6.58217 13.3626L9.84664 15.2493C9.85002 15.2504 9.85396 15.2515 9.85847 15.2527H9.8703C9.87481 15.2527 9.87876 15.2515 9.88214 15.2493C9.88552 15.2482 9.8889 15.2465 9.89228 15.2442L11.2616 14.453L7.31925 12.1775C7.28037 12.1539 7.24318 12.1251 7.20937 12.093C7.17661 12.0602 7.1482 12.0232 7.12484 11.9831C7.10286 11.9426 7.08427 11.9003 7.07243 11.8547C7.0606 11.8107 7.05384 11.7651 7.05553 11.7177V7.87846C6.88985 7.93932 6.72925 8.0137 6.5771 8.10161C6.42495 8.19121 6.28125 8.29265 6.14601 8.40591C6.01245 8.51918 5.88735 8.64428 5.77408 8.77953C5.66082 8.91308 5.56107 9.05847 5.47316 9.21062H5.46978ZM16.6832 11.8208C16.7238 11.8445 16.761 11.8716 16.7948 11.9054C16.8269 11.9375 16.8557 11.9747 16.8794 12.0153C16.9013 12.0558 16.9199 12.0998 16.9318 12.1437C16.9419 12.1894 16.9487 12.235 16.947 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+					"fill": "white"
+				},
+				"children": []
+			},
+			{
+				"type": "element",
+				"name": "rect",
+				"attributes": {
+					"x": "0.5",
+					"y": "0.5",
+					"width": "23",
+					"height": "23",
+					"rx": "5.5",
+					"stroke": "black",
+					"stroke-opacity": "0.05"
+				},
+				"children": []
+			}
+		]
+	},
+	"name": "Gpt3"
+}
\ No newline at end of file

web/app/components/base/icons/src/public/llm/Gpt3.tsx

+// GENERATE BY script
+// DON NOT EDIT IT MANUALLY
+
+import * as React from 'react'
+import data from './Gpt3.json'
+import IconBase from '@/app/components/base/icons/IconBase'
+import type { IconBaseProps, IconData } from '@/app/components/base/icons/IconBase'
+
+const Icon = React.forwardRef<React.MutableRefObject<SVGElement>, Omit<IconBaseProps, 'data'>>((
+  props,
+  ref,
+) => <IconBase {...props} ref={ref} data={data as IconData} />)
+
+export default Icon

web/app/components/base/icons/src/public/llm/Gpt4.json

+{
+	"icon": {
+		"type": "element",
+		"isRootNode": true,
+		"name": "svg",
+		"attributes": {
+			"width": "24",
+			"height": "24",
+			"viewBox": "0 0 24 24",
+			"fill": "none",
+			"xmlns": "http://www.w3.org/2000/svg"
+		},
+		"children": [
+			{
+				"type": "element",
+				"name": "rect",
+				"attributes": {
+					"width": "24",
+					"height": "24",
+					"rx": "6",
+					"fill": "#AB68FF"
+				},
+				"children": []
+			},
+			{
+				"type": "element",
+				"name": "path",
+				"attributes": {
+					"d": "M19.6451 11.6028C19.8209 11.995 19.9325 12.4142 19.9781 12.8419C20.0221 13.2696 20.0001 13.7024 19.9088 14.1234C19.8192 14.5443 19.6637 14.9484 19.4473 15.3203C19.3053 15.5688 19.1379 15.8021 18.9452 16.0168C18.7542 16.2298 18.5412 16.4225 18.3096 16.5916C18.0763 16.7606 17.8278 16.9027 17.564 17.0193C17.302 17.1343 17.0281 17.2222 16.7475 17.2796C16.6156 17.6888 16.4195 18.0759 16.1659 18.4242C15.914 18.7724 15.6081 19.0784 15.2598 19.3303C14.9115 19.5839 14.5261 19.78 14.117 19.9118C13.7079 20.0454 13.2802 20.1113 12.8491 20.1113C12.5634 20.113 12.276 20.0826 11.9953 20.0251C11.7164 19.9659 11.4425 19.8763 11.1805 19.7597C10.9184 19.643 10.6699 19.4977 10.4383 19.3286C10.2084 19.1595 9.99541 18.9651 9.80606 18.7504C9.38342 18.8417 8.95064 18.8637 8.52293 18.8197C8.09522 18.7741 7.67596 18.6625 7.28206 18.4867C6.88985 18.3126 6.52638 18.0759 6.20687 17.7868C5.88735 17.4977 5.61517 17.1596 5.40047 16.7877C5.25677 16.5392 5.13843 16.2771 5.04883 16.005C4.95924 15.7328 4.90007 15.4522 4.86964 15.1665C4.83921 14.8824 4.8409 14.595 4.87133 14.3093C4.90176 14.0253 4.96431 13.7447 5.05391 13.4725C4.76651 13.153 4.52983 12.7895 4.35402 12.3973C4.17989 12.0034 4.06662 11.5859 4.02267 11.1581C3.97702 10.7304 4.00069 10.2976 4.09029 9.8767C4.17989 9.45575 4.33542 9.05171 4.55181 8.67978C4.69382 8.43127 4.86118 8.19628 5.05222 7.98327C5.24325 7.77026 5.45795 7.57754 5.68956 7.40848C5.92116 7.23943 6.17136 7.09573 6.4334 6.98077C6.69713 6.86412 6.971 6.77791 7.25163 6.72043C7.38349 6.30962 7.5796 5.92417 7.83149 5.57592C8.08508 5.22766 8.39107 4.92167 8.73932 4.66809C9.08758 4.4162 9.47302 4.22009 9.88214 4.08654C10.2913 3.95467 10.719 3.88705 11.1501 3.88874C11.4358 3.88705 11.7232 3.91579 12.0038 3.97496C12.2844 4.03413 12.5583 4.12204 12.8203 4.23869C13.0824 4.35703 13.3309 4.50072 13.5625 4.66978C13.7941 4.84053 14.0071 5.03325 14.1964 5.24795C14.6174 5.15835 15.0502 5.13637 15.4779 5.18033C15.9056 5.22428 16.3232 5.33755 16.7171 5.51168C17.1093 5.6875 17.4727 5.92248 17.7923 6.21157C18.1118 6.49896 18.384 6.83538 18.5987 7.209C18.7423 7.45582 18.8607 7.71786 18.9503 7.99173C19.0399 8.26391 19.1007 8.54454 19.1295 8.83024C19.1599 9.11595 19.1599 9.40334 19.1278 9.68905C19.0974 9.97475 19.0348 10.2554 18.9452 10.5276C19.2343 10.8471 19.4693 11.2089 19.6451 11.6028ZM14.0122 18.8197C14.3807 18.6676 14.7154 18.4428 14.9978 18.1604C15.2801 17.8781 15.5049 17.5434 15.6571 17.1731C15.8092 16.8046 15.8887 16.409 15.8887 16.01V12.2401C15.8876 12.2367 15.8864 12.2328 15.8853 12.2283C15.8842 12.2249 15.8825 12.2215 15.8802 12.2181C15.878 12.2147 15.8752 12.2119 15.8718 12.2097C15.8684 12.2063 15.865 12.204 15.8616 12.2029L14.4974 11.4151V15.9695C14.4974 16.0151 14.4906 16.0624 14.4788 16.1064C14.4669 16.152 14.45 16.1943 14.4264 16.2349C14.4027 16.2755 14.3756 16.3126 14.3418 16.3448C14.309 16.3775 14.272 16.4059 14.2319 16.4293L11.0013 18.294C10.9742 18.3109 10.9286 18.3346 10.9049 18.3481C11.0385 18.4613 11.1839 18.5611 11.336 18.649C11.4899 18.7369 11.6488 18.8113 11.8144 18.8722C11.9801 18.9313 12.1509 18.977 12.3233 19.0074C12.4974 19.0378 12.6732 19.053 12.8491 19.053C13.248 19.053 13.6436 18.9736 14.0122 18.8197ZM6.31844 16.2602C6.51962 16.6068 6.78504 16.9077 7.10117 17.1512C7.419 17.3946 7.77908 17.5721 8.16453 17.6752C8.54998 17.7784 8.95233 17.8054 9.34792 17.753C9.74351 17.7006 10.1239 17.5721 10.4705 17.3726L13.7366 15.4877L13.7451 15.4792C13.7473 15.477 13.749 15.4736 13.7501 15.4691C13.7524 15.4657 13.7541 15.4623 13.7552 15.4589V13.8698L9.81283 16.1504C9.77225 16.174 9.72999 16.1909 9.68603 16.2045C9.64039 16.2163 9.59474 16.2214 9.54741 16.2214C9.50176 16.2214 9.45612 16.2163 9.41047 16.2045C9.36652 16.1909 9.32256 16.174 9.28199 16.1504L6.05133 14.284C6.0226 14.2671 5.98033 14.2417 5.95666 14.2265C5.92623 14.4006 5.91102 14.5764 5.91102 14.7523C5.91102 14.9281 5.92792 15.1039 5.95835 15.278C5.98878 15.4505 6.03612 15.6212 6.09529 15.7869C6.15615 15.9526 6.23053 16.1115 6.31844 16.2636V16.2602ZM5.46978 9.21062C5.2703 9.55718 5.14182 9.93925 5.08941 10.3348C5.037 10.7304 5.06405 11.1311 5.16717 11.5182C5.2703 11.9037 5.44781 12.2638 5.69125 12.5816C5.93469 12.8977 6.2373 13.1631 6.58217 13.3626L9.84664 15.2493C9.85002 15.2504 9.85396 15.2515 9.85847 15.2527H9.8703C9.87481 15.2527 9.87876 15.2515 9.88214 15.2493C9.88552 15.2482 9.8889 15.2465 9.89228 15.2442L11.2616 14.453L7.31925 12.1775C7.28037 12.1539 7.24318 12.1251 7.20937 12.093C7.17661 12.0602 7.1482 12.0232 7.12484 11.9831C7.10286 11.9426 7.08427 11.9003 7.07243 11.8547C7.0606 11.8107 7.05384 11.7651 7.05553 11.7177V7.87846C6.88985 7.93932 6.72925 8.0137 6.5771 8.10161C6.42495 8.19121 6.28125 8.29265 6.14601 8.40591C6.01245 8.51918 5.88735 8.64428 5.77408 8.77953C5.66082 8.91308 5.56107 9.05847 5.47316 9.21062H5.46978ZM16.6832 11.8208C16.7238 11.8445 16.761 11.8716 16.7948 11.9054C16.8269 11.9375 16.8557 11.9747 16.8794 12.0153C16.9013 12.0558 16.9199 12.0998 16.9318 12.1437C16.9419 12.1894 16.9487 12.235 16.947 12.2824V16.1216C17.4896 15.9221 17.963 15.5722 18.3129 15.1124C18.6646 14.6525 18.8759 14.1031 18.9249 13.5283C18.974 12.9535 18.859 12.3753 18.5919 11.8631C18.3248 11.3509 17.9174 10.9248 17.417 10.6374L14.1525 8.75079C14.1491 8.74966 14.1452 8.74853 14.1407 8.74741H14.1288C14.1254 8.74853 14.1215 8.74966 14.117 8.75079C14.1136 8.75191 14.1102 8.7536 14.1068 8.75586L12.7443 9.54366L16.6866 11.8208H16.6832ZM18.0441 9.77526H18.0425V9.77695L18.0441 9.77526ZM18.0425 9.77357C18.1405 9.20555 18.0746 8.62061 17.8514 8.08809C17.63 7.55556 17.2597 7.09742 16.7864 6.76607C16.313 6.43641 15.7551 6.24707 15.1787 6.22171C14.6005 6.19804 14.0291 6.33836 13.5287 6.62575L10.2642 8.51073C10.2608 8.51298 10.258 8.5158 10.2558 8.51918L10.249 8.52932C10.2479 8.5327 10.2467 8.53665 10.2456 8.54116C10.2445 8.54454 10.2439 8.54848 10.2439 8.55299V10.1286L14.1863 7.85141C14.2269 7.82774 14.2708 7.81084 14.3148 7.79731C14.3604 7.78548 14.4061 7.78041 14.4517 7.78041C14.499 7.78041 14.5447 7.78548 14.5903 7.79731C14.6343 7.81084 14.6766 7.82774 14.7171 7.85141L17.9478 9.71778C17.9765 9.73469 18.0188 9.75836 18.0425 9.77357ZM9.50007 8.02892C9.50007 7.98327 9.50683 7.93763 9.51867 7.89198C9.5305 7.84803 9.54741 7.80407 9.57108 7.7635C9.59474 7.72462 9.62179 7.68743 9.6556 7.65361C9.68772 7.62149 9.72492 7.59275 9.76549 7.57078L12.9961 5.70609C13.0266 5.6875 13.0688 5.66383 13.0925 5.65199C12.6496 5.28176 12.1086 5.04508 11.5355 4.97239C10.9624 4.89801 10.3809 4.9893 9.85847 5.23443C9.3344 5.47956 8.89147 5.87008 8.5821 6.35696C8.27273 6.84553 8.10874 7.41017 8.10874 7.98834V11.7583C8.10987 11.7628 8.111 11.7667 8.11212 11.7701C8.11325 11.7735 8.11494 11.7769 8.1172 11.7803C8.11945 11.7836 8.12227 11.787 8.12565 11.7904C8.1279 11.7927 8.13128 11.7949 8.13579 11.7972L9.50007 12.585V8.02892ZM10.2405 13.011L11.997 14.0253L13.7535 13.011V10.984L11.9987 9.96968L10.2422 10.984L10.2405 13.011Z",
+					"fill": "white"
+				},
+				"children": []
+			},
+			{
+				"type": "element",
+				"name": "rect",
+				"attributes": {
+					"x": "0.5",
+					"y": "0.5",
+					"width": "23",
+					"height": "23",
+					"rx": "5.5",
+					"stroke": "black",
+					"stroke-opacity": "0.05"
+				},
+				"children": []
+			}
+		]
+	},
+	"name": "Gpt4"
+}
\ No newline at end of file

web/app/components/base/icons/src/public/llm/Gpt4.tsx

+// GENERATE BY script
+// DON NOT EDIT IT MANUALLY
+
+import * as React from 'react'
+import data from './Gpt4.json'
+import IconBase from '@/app/components/base/icons/IconBase'
+import type { IconBaseProps, IconData } from '@/app/components/base/icons/IconBase'
+
+const Icon = React.forwardRef<React.MutableRefObject<SVGElement>, Omit<IconBaseProps, 'data'>>((
+  props,
+  ref,
+) => <IconBase {...props} ref={ref} data={data as IconData} />)
+
+export default Icon

web/app/components/base/icons/src/public/llm/index.ts

+export { default as Anthropic } from './Anthropic'
+export { default as Gpt3 } from './Gpt3'
+export { default as Gpt4 } from './Gpt4'

web/app/components/base/icons/src/public/model/Checked.json

+{
+	"icon": {
+		"type": "element",
+		"isRootNode": true,
+		"name": "svg",
+		"attributes": {
+			"width": "16",
+			"height": "16",
+			"viewBox": "0 0 16 16",
+			"fill": "none",
+			"xmlns": "http://www.w3.org/2000/svg"
+		},
+		"children": [
+			{
+				"type": "element",
+				"name": "path",
+				"attributes": {
+					"d": "M13.3332 4L5.99984 11.3333L2.6665 8",
+					"stroke": "#155EEF",
+					"stroke-width": "2",
+					"stroke-linecap": "round",
+					"stroke-linejoin": "round"
+				},
+				"children": []
+			}
+		]
+	},
+	"name": "Checked"
+}
\ No newline at end of file

web/app/components/base/icons/src/public/model/Checked.tsx

+// GENERATE BY script
+// DON NOT EDIT IT MANUALLY
+
+import * as React from 'react'
+import data from './Checked.json'
+import IconBase from '@/app/components/base/icons/IconBase'
+import type { IconBaseProps, IconData } from '@/app/components/base/icons/IconBase'
+
+const Icon = React.forwardRef<React.MutableRefObject<SVGElement>, Omit<IconBaseProps, 'data'>>((
+  props,
+  ref,
+) => <IconBase {...props} ref={ref} data={data as IconData} />)
+
+export default Icon

web/app/components/base/icons/src/public/model/index.ts

+export { default as Checked } from './Checked'

web/app/components/base/icons/src/public/plugins/Google.json

+{
+	"icon": {
+		"type": "element",
+		"isRootNode": true,
+		"name": "svg",
+		"attributes": {
+			"width": "24",
+			"height": "24",
+			"viewBox": "0 0 24 24",
+			"fill": "none",
+			"xmlns": "http://www.w3.org/2000/svg"
+		},
+		"children": [
+			{
+				"type": "element",
+				"name": "path",
+				"attributes": {
+					"d": "M22.501 12.2331C22.501 11.3698 22.4296 10.7398 22.2748 10.0864H12.2153V13.983H18.12C18.001 14.9514 17.3582 16.4097 15.9296 17.3897L15.9096 17.5202L19.0902 19.9349L19.3106 19.9564C21.3343 18.1247 22.501 15.4297 22.501 12.2331Z",
+					"fill": "#4285F4"
+				},
+				"children": []
+			},
+			{
+				"type": "element",
+				"name": "path",
+				"attributes": {
+					"d": "M12.2147 22.5001C15.1075 22.5001 17.5361 21.5667 19.3099 19.9567L15.929 17.39C15.0242 18.0083 13.8099 18.44 12.2147 18.44C9.38142 18.44 6.97669 16.6083 6.11947 14.0767L5.99382 14.0871L2.68656 16.5955L2.64331 16.7133C4.40519 20.1433 8.02423 22.5001 12.2147 22.5001Z",
+					"fill": "#34A853"
+				},
+				"children": []
+			},
+			{
+				"type": "element",
+				"name": "path",
+				"attributes": {
+					"d": "M6.11997 14.0765C5.89379 13.4232 5.76289 12.7231 5.76289 11.9998C5.76289 11.2764 5.89379 10.5765 6.10807 9.92313L6.10208 9.78398L2.75337 7.23535L2.64381 7.28642C1.91765 8.70977 1.50098 10.3081 1.50098 11.9998C1.50098 13.6915 1.91765 15.2897 2.64381 16.7131L6.11997 14.0765Z",
+					"fill": "#FBBC05"
+				},
+				"children": []
+			},
+			{
+				"type": "element",
+				"name": "path",
+				"attributes": {
+					"d": "M12.2148 5.55997C14.2267 5.55997 15.5838 6.41163 16.3576 7.12335L19.3814 4.23C17.5243 2.53834 15.1076 1.5 12.2148 1.5C8.02426 1.5 4.4052 3.85665 2.64331 7.28662L6.10759 9.92332C6.97672 7.39166 9.38146 5.55997 12.2148 5.55997Z",
+					"fill": "#EB4335"
+				},
+				"children": []
+			}
+		]
+	},
+	"name": "Google"
+}
\ No newline at end of file

web/app/components/base/icons/src/public/plugins/Google.tsx

+// GENERATE BY script
+// DON NOT EDIT IT MANUALLY
+
+import * as React from 'react'
+import data from './Google.json'
+import IconBase from '@/app/components/base/icons/IconBase'
+import type { IconBaseProps, IconData } from '@/app/components/base/icons/IconBase'
+
+const Icon = React.forwardRef<React.MutableRefObject<SVGElement>, Omit<IconBaseProps, 'data'>>((
+  props,
+  ref,
+) => <IconBase {...props} ref={ref} data={data as IconData} />)
+
+export default Icon

web/app/components/base/icons/src/public/plugins/WebReader.json

+{
+	"icon": {
+		"type": "element",
+		"isRootNode": true,
+		"name": "svg",
+		"attributes": {
+			"width": "24",
+			"height": "24",
+			"viewBox": "0 0 24 24",
+			"fill": "none",
+			"xmlns": "http://www.w3.org/2000/svg"
+		},
+		"children": [
+			{
+				"type": "element",
+				"name": "path",
+				"attributes": {
+					"fill-rule": "evenodd",
+					"clip-rule": "evenodd",
+					"d": "M9.59235 3.32566C10.3587 3.11341 11.1661 3 12 3C13.962 3 15.7773 3.62779 17.2561 4.69345C16.4693 5.21349 15.8824 5.77819 15.4756 6.38193C14.854 7.30445 14.6947 8.25844 14.8234 9.12887C14.9484 9.97416 15.3366 10.696 15.7446 11.2301C16.1402 11.7479 16.6256 12.181 17.0531 12.3946C18.1294 12.9327 19.3714 13.2022 20.2999 13.341C21.1399 13.4667 22.9206 13.8871 22.9865 12.5492C22.9955 12.3672 23 12.1841 23 12C23 5.92487 18.0751 1 12 1C5.92487 1 1 5.92487 1 12C1 18.0751 5.92487 23 12 23C12.1841 23 12.3672 22.9955 12.5492 22.9865C13.1008 22.9593 13.526 22.4902 13.4988 21.9385C13.4716 21.3869 13.0024 20.9618 12.4508 20.9889C12.3015 20.9963 12.1512 21 12 21C8.49063 21 5.45038 18.9914 3.96619 16.0611L4.93474 15.502L8.50745 16.1706C9.43309 16.3439 10.2876 15.6313 10.2834 14.6896L10.2694 11.5365L12.0952 8.41051C12.3911 7.90404 12.3646 7.27161 12.0274 6.79167L9.59235 3.32566Z",
+					"fill": "#444CE7"
+				},
+				"children": []
+			},
+			{
+				"type": "element",
+				"name": "path",
+				"attributes": {
+					"fill-rule": "evenodd",
+					"clip-rule": "evenodd",
+					"d": "M13.9456 12.6561C13.5777 12.5165 13.1621 12.6057 12.8839 12.884C12.6056 13.1623 12.5164 13.5778 12.656 13.9458L15.8228 22.2945C15.969 22.68 16.3367 22.9362 16.7489 22.9399C17.1611 22.9435 17.5333 22.6938 17.6863 22.3111L19.007 19.0071L22.311 17.6865C22.6937 17.5334 22.9434 17.1612 22.9397 16.749C22.9361 16.3368 22.6799 15.9691 22.2944 15.8229L13.9456 12.6561Z",
+					"fill": "#444CE7"
+				},
+				"children": []
+			}
+		]
+	},
+	"name": "WebReader"
+}
\ No newline at end of file

web/app/components/base/icons/src/public/plugins/WebReader.tsx

+// GENERATE BY script
+// DON NOT EDIT IT MANUALLY
+
+import * as React from 'react'
+import data from './WebReader.json'
+import IconBase from '@/app/components/base/icons/IconBase'
+import type { IconBaseProps, IconData } from '@/app/components/base/icons/IconBase'
+
+const Icon = React.forwardRef<React.MutableRefObject<SVGElement>, Omit<IconBaseProps, 'data'>>((
+  props,
+  ref,
+) => <IconBase {...props} ref={ref} data={data as IconData} />)
+
+export default Icon

web/app/components/base/icons/src/public/plugins/Wikipedia.json

+{
+	"icon": {
+		"type": "element",
+		"isRootNode": true,
+		"name": "svg",
+		"attributes": {
+			"width": "24",
+			"height": "24",
+			"viewBox": "0 0 24 24",
+			"fill": "none",
+			"xmlns": "http://www.w3.org/2000/svg"
+		},
+		"children": [
+			{
+				"type": "element",
+				"name": "path",
+				"attributes": {
+					"d": "M23.8431 5.0001H19.2179H19.0609V5.15706V5.66001V5.81696H19.2179H19.5393C19.9131 5.81696 20.2502 6.00882 20.4411 6.33021C20.632 6.65161 20.6392 7.0394 20.4603 7.36765L15.3174 16.8077L12.9751 11.2238L15.1813 7.17527C15.6379 6.33743 16.5143 5.81696 17.4684 5.81696H17.5726H17.7296V5.66001V5.15706V5.0001H17.5726H12.9474H12.7905V5.15706V5.66001V5.81696H12.9474H13.2688C13.6426 5.81696 13.9797 6.00882 14.1706 6.33021C14.3615 6.65161 14.3687 7.0394 14.1899 7.36765L12.5896 10.305L11.1634 6.9051C11.0601 6.65867 11.0856 6.38965 11.2336 6.16714C11.3816 5.94462 11.6197 5.81696 11.887 5.81696H12.2526H12.4095V5.66001V5.15706V5.0001H12.2526H6.72092H6.56396V5.15706V5.66001V5.81696H6.72092H6.79699C7.88821 5.81696 8.866 6.46719 9.28817 7.47344L11.3954 12.497L9.04698 16.8077L4.89304 6.9051C4.78966 6.65867 4.81525 6.38965 4.9632 6.16714C5.11116 5.94462 5.34932 5.81696 5.61657 5.81696H6.17832H6.33527V5.66001V5.15706V5.0001H6.17832H0.156957H0V5.15706V5.66001V5.81696H0.156957H0.52654C1.61776 5.81696 2.59561 6.46719 3.01772 7.47344L7.80628 18.889C7.89004 19.0887 8.08425 19.2177 8.30111 19.2177C8.50014 19.2177 8.67588 19.1131 8.77125 18.9381L9.39589 17.7918L11.7807 13.4155L14.0767 18.889C14.1604 19.0886 14.3547 19.2176 14.5715 19.2176C14.7705 19.2176 14.9463 19.1131 15.0417 18.938L15.6663 17.7917L21.4517 7.17517C21.9083 6.33733 22.7847 5.81686 23.7388 5.81686H23.843H24V5.6599V5.15696V5H23.8431V5.0001Z",
+					"fill": "#222A30"
+				},
+				"children": []
+			}
+		]
+	},
+	"name": "Wikipedia"
+}
\ No newline at end of file

web/app/components/base/icons/src/public/plugins/Wikipedia.tsx

+// GENERATE BY script
+// DON NOT EDIT IT MANUALLY
+
+import * as React from 'react'
+import data from './Wikipedia.json'
+import IconBase from '@/app/components/base/icons/IconBase'
+import type { IconBaseProps, IconData } from '@/app/components/base/icons/IconBase'
+
+const Icon = React.forwardRef<React.MutableRefObject<SVGElement>, Omit<IconBaseProps, 'data'>>((
+  props,
+  ref,
+) => <IconBase {...props} ref={ref} data={data as IconData} />)
+
+export default Icon

web/app/components/base/icons/src/public/plugins/index.ts

+export { default as Google } from './Google'
+export { default as WebReader } from './WebReader'
+export { default as Wikipedia } from './Wikipedia'

web/app/components/base/icons/src/public/thought/DataSet.json

+{
+	"icon": {
+		"type": "element",
+		"isRootNode": true,
+		"name": "svg",
+		"attributes": {
+			"width": "12",
+			"height": "12",
+			"viewBox": "0 0 12 12",
+			"fill": "none",
+			"xmlns": "http://www.w3.org/2000/svg"
+		},
+		"children": [
+			{
+				"type": "element",
+				"name": "g",
+				"attributes": {
+					"clip-path": "url(#clip0_7847_32895)"
+				},
+				"children": [
+					{
+						"type": "element",
+						"name": "path",
+						"attributes": {
+							"d": "M10.5 2.5C10.5 3.32843 8.48528 4 6 4C3.51472 4 1.5 3.32843 1.5 2.5M10.5 2.5C10.5 1.67157 8.48528 1 6 1C3.51472 1 1.5 1.67157 1.5 2.5M10.5 2.5V9.5C10.5 10.33 8.5 11 6 11C3.5 11 1.5 10.33 1.5 9.5V2.5M10.5 6C10.5 6.83 8.5 7.5 6 7.5C3.5 7.5 1.5 6.83 1.5 6",
+							"stroke": "#667085",
+							"stroke-width": "1.25",
+							"stroke-linecap": "round",
+							"stroke-linejoin": "round"
+						},
+						"children": []
+					}
+				]
+			},
+			{
+				"type": "element",
+				"name": "defs",
+				"attributes": {},
+				"children": [
+					{
+						"type": "element",
+						"name": "clipPath",
+						"attributes": {
+							"id": "clip0_7847_32895"
+						},
+						"children": [
+							{
+								"type": "element",
+								"name": "rect",
+								"attributes": {
+									"width": "12",
+									"height": "12",
+									"fill": "white"
+								},
+								"children": []
+							}
+						]
+					}
+				]
+			}
+		]
+	},
+	"name": "DataSet"
+}
\ No newline at end of file

web/app/components/base/icons/src/public/thought/DataSet.tsx

+// GENERATE BY script
+// DON NOT EDIT IT MANUALLY
+
+import * as React from 'react'
+import data from './DataSet.json'
+import IconBase from '@/app/components/base/icons/IconBase'
+import type { IconBaseProps, IconData } from '@/app/components/base/icons/IconBase'
+
+const Icon = React.forwardRef<React.MutableRefObject<SVGElement>, Omit<IconBaseProps, 'data'>>((
+  props,
+  ref,
+) => <IconBase {...props} ref={ref} data={data as IconData} />)
+
+export default Icon

web/app/components/base/icons/src/public/thought/Loading.json

+{
+	"icon": {
+		"type": "element",
+		"isRootNode": true,
+		"name": "svg",
+		"attributes": {
+			"width": "12",
+			"height": "12",
+			"viewBox": "0 0 12 12",
+			"fill": "none",
+			"xmlns": "http://www.w3.org/2000/svg"
+		},
+		"children": [
+			{
+				"type": "element",
+				"name": "g",
+				"attributes": {
+					"clip-path": "url(#clip0_7998_4025)"
+				},
+				"children": [
+					{
+						"type": "element",
+						"name": "path",
+						"attributes": {
+							"d": "M6 1.125V2.375M6 9V11M2.875 6H1.125M10.625 6H9.875M9.22855 9.22855L8.875 8.875M9.33211 2.70789L8.625 3.415M2.46079 9.53921L3.875 8.125M2.56434 2.60434L3.625 3.665",
+							"stroke": "#667085",
+							"stroke-width": "1.25",
+							"stroke-linecap": "round",
+							"stroke-linejoin": "round"
+						},
+						"children": []
+					}
+				]
+			},
+			{
+				"type": "element",
+				"name": "defs",
+				"attributes": {},
+				"children": [
+					{
+						"type": "element",
+						"name": "clipPath",
+						"attributes": {
+							"id": "clip0_7998_4025"
+						},
+						"children": [
+							{
+								"type": "element",
+								"name": "rect",
+								"attributes": {
+									"width": "12",
+									"height": "12",
+									"fill": "white"
+								},
+								"children": []
+							}
+						]
+					}
+				]
+			}
+		]
+	},
+	"name": "Loading"
+}
\ No newline at end of file

web/app/components/base/icons/src/public/thought/Loading.tsx

+// GENERATE BY script
+// DON NOT EDIT IT MANUALLY
+
+import * as React from 'react'
+import data from './Loading.json'
+import IconBase from '@/app/components/base/icons/IconBase'
+import type { IconBaseProps, IconData } from '@/app/components/base/icons/IconBase'
+
+const Icon = React.forwardRef<React.MutableRefObject<SVGElement>, Omit<IconBaseProps, 'data'>>((
+  props,
+  ref,
+) => <IconBase {...props} ref={ref} data={data as IconData} />)
+
+export default Icon

web/app/components/base/icons/src/public/thought/Search.json

+{
+	"icon": {
+		"type": "element",
+		"isRootNode": true,
+		"name": "svg",
+		"attributes": {
+			"width": "12",
+			"height": "12",
+			"viewBox": "0 0 12 12",
+			"fill": "none",
+			"xmlns": "http://www.w3.org/2000/svg"
+		},
+		"children": [
+			{
+				"type": "element",
+				"name": "g",
+				"attributes": {
+					"clip-path": "url(#clip0_7847_32899)"
+				},
+				"children": [
+					{
+						"type": "element",
+						"name": "path",
+						"attributes": {
+							"d": "M10.5 10.5L8.75005 8.75M10 5.75C10 8.09721 8.09721 10 5.75 10C3.40279 10 1.5 8.09721 1.5 5.75C1.5 3.40279 3.40279 1.5 5.75 1.5C8.09721 1.5 10 3.40279 10 5.75Z",
+							"stroke": "#667085",
+							"stroke-width": "1.25",
+							"stroke-linecap": "round",
+							"stroke-linejoin": "round"
+						},
+						"children": []
+					}
+				]
+			},
+			{
+				"type": "element",
+				"name": "defs",
+				"attributes": {},
+				"children": [
+					{
+						"type": "element",
+						"name": "clipPath",
+						"attributes": {
+							"id": "clip0_7847_32899"
+						},
+						"children": [
+							{
+								"type": "element",
+								"name": "rect",
+								"attributes": {
+									"width": "12",
+									"height": "12",
+									"fill": "white"
+								},
+								"children": []
+							}
+						]
+					}
+				]
+			}
+		]
+	},
+	"name": "Search"
+}
\ No newline at end of file

web/app/components/base/icons/src/public/thought/Search.tsx

+// GENERATE BY script
+// DON NOT EDIT IT MANUALLY
+
+import * as React from 'react'
+import data from './Search.json'
+import IconBase from '@/app/components/base/icons/IconBase'
+import type { IconBaseProps, IconData } from '@/app/components/base/icons/IconBase'
+
+const Icon = React.forwardRef<React.MutableRefObject<SVGElement>, Omit<IconBaseProps, 'data'>>((
+  props,
+  ref,
+) => <IconBase {...props} ref={ref} data={data as IconData} />)
+
+export default Icon

web/app/components/base/icons/src/public/thought/ThoughtList.json

+{
+	"icon": {
+		"type": "element",
+		"isRootNode": true,
+		"name": "svg",
+		"attributes": {
+			"width": "12",
+			"height": "12",
+			"viewBox": "0 0 12 12",
+			"fill": "none",
+			"xmlns": "http://www.w3.org/2000/svg"
+		},
+		"children": [
+			{
+				"type": "element",
+				"name": "path",
+				"attributes": {
+					"fill-rule": "evenodd",
+					"clip-rule": "evenodd",
+					"d": "M4 6C4 5.72386 4.22386 5.5 4.5 5.5L10.5 5.5C10.7761 5.5 11 5.72386 11 6C11 6.27614 10.7761 6.5 10.5 6.5L4.5 6.5C4.22386 6.5 4 6.27614 4 6Z",
+					"fill": "#667085"
+				},
+				"children": []
+			},
+			{
+				"type": "element",
+				"name": "path",
+				"attributes": {
+					"fill-rule": "evenodd",
+					"clip-rule": "evenodd",
+					"d": "M4 3C4 2.72386 4.22386 2.5 4.5 2.5L10.5 2.5C10.7761 2.5 11 2.72386 11 3C11 3.27614 10.7761 3.5 10.5 3.5L4.5 3.5C4.22386 3.5 4 3.27614 4 3Z",
+					"fill": "#667085"
+				},
+				"children": []
+			},
+			{
+				"type": "element",
+				"name": "path",
+				"attributes": {
+					"fill-rule": "evenodd",
+					"clip-rule": "evenodd",
+					"d": "M4 9C4 8.72386 4.22386 8.5 4.5 8.5L10.5 8.5C10.7761 8.5 11 8.72386 11 9C11 9.27614 10.7761 9.5 10.5 9.5L4.5 9.5C4.22386 9.5 4 9.27614 4 9Z",
+					"fill": "#667085"
+				},
+				"children": []
+			},
+			{
+				"type": "element",
+				"name": "path",
+				"attributes": {
+					"fill-rule": "evenodd",
+					"clip-rule": "evenodd",
+					"d": "M1 6C1 5.44772 1.44772 5 2 5C2.55228 5 3 5.44772 3 6C3 6.55228 2.55228 7 2 7C1.44772 7 1 6.55228 1 6Z",
+					"fill": "#667085"
+				},
+				"children": []
+			},
+			{
+				"type": "element",
+				"name": "path",
+				"attributes": {
+					"fill-rule": "evenodd",
+					"clip-rule": "evenodd",
+					"d": "M1 3C1 2.44772 1.44772 2 2 2C2.55228 2 3 2.44772 3 3C3 3.55228 2.55228 4 2 4C1.44772 4 1 3.55228 1 3Z",
+					"fill": "#667085"
+				},
+				"children": []
+			},
+			{
+				"type": "element",
+				"name": "path",
+				"attributes": {
+					"fill-rule": "evenodd",
+					"clip-rule": "evenodd",
+					"d": "M1 9C1 8.44772 1.44772 8 2 8C2.55228 8 3 8.44772 3 9C3 9.55228 2.55228 10 2 10C1.44772 10 1 9.55228 1 9Z",
+					"fill": "#667085"
+				},
+				"children": []
+			}
+		]
+	},
+	"name": "ThoughtList"
+}
\ No newline at end of file

web/app/components/base/icons/src/public/thought/ThoughtList.tsx

+// GENERATE BY script
+// DON NOT EDIT IT MANUALLY
+
+import * as React from 'react'
+import data from './ThoughtList.json'
+import IconBase from '@/app/components/base/icons/IconBase'
+import type { IconBaseProps, IconData } from '@/app/components/base/icons/IconBase'
+
+const Icon = React.forwardRef<React.MutableRefObject<SVGElement>, Omit<IconBaseProps, 'data'>>((
+  props,
+  ref,
+) => <IconBase {...props} ref={ref} data={data as IconData} />)
+
+export default Icon

web/app/components/base/icons/src/public/thought/WebReader.json

+{
+	"icon": {
+		"type": "element",
+		"isRootNode": true,
+		"name": "svg",
+		"attributes": {
+			"width": "12",
+			"height": "12",
+			"viewBox": "0 0 12 12",
+			"fill": "none",
+			"xmlns": "http://www.w3.org/2000/svg"
+		},
+		"children": [
+			{
+				"type": "element",
+				"name": "g",
+				"attributes": {
+					"clip-path": "url(#clip0_7847_32887)"
+				},
+				"children": [
+					{
+						"type": "element",
+						"name": "path",
+						"attributes": {
+							"d": "M4.5 1.75V1M2.53033 2.53033L2 2M2.53033 6.5L2 7.03033M6.5 2.53033L7.03033 2M1.75 4.5H1M7.93224 8.09479L6.68637 10.4085C6.54404 10.6728 6.47287 10.805 6.38725 10.8384C6.31295 10.8674 6.22926 10.8592 6.16199 10.8164C6.08447 10.767 6.04028 10.6235 5.95191 10.3366L4.22259 4.72263C4.1504 4.48825 4.1143 4.37107 4.14335 4.29192C4.16865 4.22298 4.22298 4.16865 4.29192 4.14335C4.37107 4.1143 4.48825 4.1504 4.72262 4.2226L10.3366 5.95192C10.6235 6.0403 10.767 6.08449 10.8164 6.16201C10.8592 6.22928 10.8674 6.31297 10.8384 6.38727C10.805 6.47289 10.6728 6.54406 10.4085 6.68639L8.09479 7.93224C8.05551 7.95339 8.03587 7.96396 8.01868 7.97755C8.00341 7.98961 7.98961 8.00341 7.97755 8.01868C7.96396 8.03587 7.95339 8.05551 7.93224 8.09479Z",
+							"stroke": "#667085",
+							"stroke-width": "1.25",
+							"stroke-linecap": "round",
+							"stroke-linejoin": "round"
+						},
+						"children": []
+					}
+				]
+			},
+			{
+				"type": "element",
+				"name": "defs",
+				"attributes": {},
+				"children": [
+					{
+						"type": "element",
+						"name": "clipPath",
+						"attributes": {
+							"id": "clip0_7847_32887"
+						},
+						"children": [
+							{
+								"type": "element",
+								"name": "rect",
+								"attributes": {
+									"width": "12",
+									"height": "12",
+									"fill": "white"
+								},
+								"children": []
+							}
+						]
+					}
+				]
+			}
+		]
+	},
+	"name": "WebReader"
+}
\ No newline at end of file

web/app/components/base/icons/src/public/thought/WebReader.tsx

+// GENERATE BY script
+// DON NOT EDIT IT MANUALLY
+
+import * as React from 'react'
+import data from './WebReader.json'
+import IconBase from '@/app/components/base/icons/IconBase'
+import type { IconBaseProps, IconData } from '@/app/components/base/icons/IconBase'
+
+const Icon = React.forwardRef<React.MutableRefObject<SVGElement>, Omit<IconBaseProps, 'data'>>((
+  props,
+  ref,
+) => <IconBase {...props} ref={ref} data={data as IconData} />)
+
+export default Icon

web/app/components/base/icons/src/public/thought/index.ts

+export { default as DataSet } from './DataSet'
+export { default as Loading } from './Loading'
+export { default as Search } from './Search'
+export { default as ThoughtList } from './ThoughtList'
+export { default as WebReader } from './WebReader'

web/app/components/base/icons/src/vender/line/general/LinkExternal02.json

+{
+	"icon": {
+		"type": "element",
+		"isRootNode": true,
+		"name": "svg",
+		"attributes": {
+			"width": "12",
+			"height": "12",
+			"viewBox": "0 0 12 12",
+			"fill": "none",
+			"xmlns": "http://www.w3.org/2000/svg"
+		},
+		"children": [
+			{
+				"type": "element",
+				"name": "g",
+				"attributes": {
+					"id": "link-external-02"
+				},
+				"children": [
+					{
+						"type": "element",
+						"name": "path",
+						"attributes": {
+							"id": "Icon",
+							"d": "M10.5 4.5L10.5 1.5M10.5 1.5H7.49999M10.5 1.5L6 6M5 1.5H3.9C3.05992 1.5 2.63988 1.5 2.31901 1.66349C2.03677 1.8073 1.8073 2.03677 1.66349 2.31901C1.5 2.63988 1.5 3.05992 1.5 3.9V8.1C1.5 8.94008 1.5 9.36012 1.66349 9.68099C1.8073 9.96323 2.03677 10.1927 2.31901 10.3365C2.63988 10.5 3.05992 10.5 3.9 10.5H8.1C8.94008 10.5 9.36012 10.5 9.68099 10.3365C9.96323 10.1927 10.1927 9.96323 10.3365 9.68099C10.5 9.36012 10.5 8.94008 10.5 8.1V7",
+							"stroke": "currentColor",
+							"stroke-linecap": "round",
+							"stroke-linejoin": "round"
+						},
+						"children": []
+					}
+				]
+			}
+		]
+	},
+	"name": "LinkExternal02"
+}
\ No newline at end of file

web/app/components/base/icons/src/vender/line/general/LinkExternal02.tsx

+// GENERATE BY script
+// DON NOT EDIT IT MANUALLY
+
+import * as React from 'react'
+import data from './LinkExternal02.json'
+import IconBase from '@/app/components/base/icons/IconBase'
+import type { IconBaseProps, IconData } from '@/app/components/base/icons/IconBase'
+
+const Icon = React.forwardRef<React.MutableRefObject<SVGElement>, Omit<IconBaseProps, 'data'>>((
+  props,
+  ref,
+) => <IconBase {...props} ref={ref} data={data as IconData} />)
+
+export default Icon

web/app/components/base/icons/src/vender/line/general/index.ts

 export { default as Check } from './Check'
 export { default as Edit03 } from './Edit03'
 export { default as Hash02 } from './Hash02'
+export { default as LinkExternal02 } from './LinkExternal02'
 export { default as Loading02 } from './Loading02'
 export { default as LogOut01 } from './LogOut01'
 export { default as Trash03 } from './Trash03'

web/app/components/base/icons/src/vender/solid/alertsAndFeedback/AlertCircle.json

+{
+	"icon": {
+		"type": "element",
+		"isRootNode": true,
+		"name": "svg",
+		"attributes": {
+			"width": "16",
+			"height": "16",
+			"viewBox": "0 0 16 16",
+			"fill": "none",
+			"xmlns": "http://www.w3.org/2000/svg"
+		},
+		"children": [
+			{
+				"type": "element",
+				"name": "g",
+				"attributes": {
+					"id": "alert-circle"
+				},
+				"children": [
+					{
+						"type": "element",
+						"name": "path",
+						"attributes": {
+							"id": "Solid",
+							"fill-rule": "evenodd",
+							"clip-rule": "evenodd",
+							"d": "M8 0.666626C3.94992 0.666626 0.666672 3.94987 0.666672 7.99996C0.666672 12.05 3.94992 15.3333 8 15.3333C12.0501 15.3333 15.3333 12.05 15.3333 7.99996C15.3333 3.94987 12.0501 0.666626 8 0.666626ZM8.66667 5.33329C8.66667 4.9651 8.36819 4.66663 8 4.66663C7.63181 4.66663 7.33334 4.9651 7.33334 5.33329V7.99996C7.33334 8.36815 7.63181 8.66663 8 8.66663C8.36819 8.66663 8.66667 8.36815 8.66667 7.99996V5.33329ZM8 9.99996C7.63181 9.99996 7.33334 10.2984 7.33334 10.6666C7.33334 11.0348 7.63181 11.3333 8 11.3333H8.00667C8.37486 11.3333 8.67334 11.0348 8.67334 10.6666C8.67334 10.2984 8.37486 9.99996 8.00667 9.99996H8Z",
+							"fill": "currentColor"
+						},
+						"children": []
+					}
+				]
+			}
+		]
+	},
+	"name": "AlertCircle"
+}
\ No newline at end of file

web/app/components/base/icons/src/vender/solid/alertsAndFeedback/AlertCircle.tsx

+// GENERATE BY script
+// DON NOT EDIT IT MANUALLY
+
+import * as React from 'react'
+import data from './AlertCircle.json'
+import IconBase from '@/app/components/base/icons/IconBase'
+import type { IconBaseProps, IconData } from '@/app/components/base/icons/IconBase'
+
+const Icon = React.forwardRef<React.MutableRefObject<SVGElement>, Omit<IconBaseProps, 'data'>>((
+  props,
+  ref,
+) => <IconBase {...props} ref={ref} data={data as IconData} />)
+
+export default Icon

web/app/components/base/icons/src/vender/solid/alertsAndFeedback/index.ts

+export { default as AlertCircle } from './AlertCircle'
 export { default as AlertTriangle } from './AlertTriangle'

web/app/components/base/icons/src/vender/solid/general/CheckCircle.json

+{
+	"icon": {
+		"type": "element",
+		"isRootNode": true,
+		"name": "svg",
+		"attributes": {
+			"width": "16",
+			"height": "16",
+			"viewBox": "0 0 16 16",
+			"fill": "none",
+			"xmlns": "http://www.w3.org/2000/svg"
+		},
+		"children": [
+			{
+				"type": "element",
+				"name": "g",
+				"attributes": {
+					"id": "check-circle"
+				},
+				"children": [
+					{
+						"type": "element",
+						"name": "path",
+						"attributes": {
+							"id": "Solid",
+							"fill-rule": "evenodd",
+							"clip-rule": "evenodd",
+							"d": "M8 0.666626C3.94992 0.666626 0.666672 3.94987 0.666672 7.99996C0.666672 12.05 3.94992 15.3333 8 15.3333C12.0501 15.3333 15.3333 12.05 15.3333 7.99996C15.3333 3.94987 12.0501 0.666626 8 0.666626ZM11.4714 6.47136C11.7318 6.21101 11.7318 5.7889 11.4714 5.52855C11.2111 5.26821 10.7889 5.26821 10.5286 5.52855L7 9.05715L5.47141 7.52855C5.21106 7.2682 4.78895 7.2682 4.5286 7.52855C4.26825 7.7889 4.26825 8.21101 4.5286 8.47136L6.5286 10.4714C6.78895 10.7317 7.21106 10.7317 7.47141 10.4714L11.4714 6.47136Z",
+							"fill": "currentColor"
+						},
+						"children": []
+					}
+				]
+			}
+		]
+	},
+	"name": "CheckCircle"
+}
\ No newline at end of file

web/app/components/base/icons/src/vender/solid/general/CheckCircle.tsx

+// GENERATE BY script
+// DON NOT EDIT IT MANUALLY
+
+import * as React from 'react'
+import data from './CheckCircle.json'
+import IconBase from '@/app/components/base/icons/IconBase'
+import type { IconBaseProps, IconData } from '@/app/components/base/icons/IconBase'
+
+const Icon = React.forwardRef<React.MutableRefObject<SVGElement>, Omit<IconBaseProps, 'data'>>((
+  props,
+  ref,
+) => <IconBase {...props} ref={ref} data={data as IconData} />)
+
+export default Icon

web/app/components/base/icons/src/vender/solid/general/index.ts

+export { default as CheckCircle } from './CheckCircle'
 export { default as Download02 } from './Download02'
 export { default as XCircle } from './XCircle'

web/app/components/base/markdown.tsx

-import ReactMarkdown from "react-markdown";
-import "katex/dist/katex.min.css";
-import RemarkMath from "remark-math";
-import RemarkBreaks from "remark-breaks";
-import RehypeKatex from "rehype-katex";
-import RemarkGfm from "remark-gfm";
+import ReactMarkdown from 'react-markdown'
+import 'katex/dist/katex.min.css'
+import RemarkMath from 'remark-math'
+import RemarkBreaks from 'remark-breaks'
+import RehypeKatex from 'rehype-katex'
+import RemarkGfm from 'remark-gfm'
 import SyntaxHighlighter from 'react-syntax-highlighter'
 import { atelierHeathLight } from 'react-syntax-highlighter/dist/esm/styles/hljs'
-import { useRef, useState, RefObject, useEffect } from "react";
+import type { RefObject } from 'react'
+import { useEffect, useRef, useState } from 'react'
 // import { copyToClipboard } from "../utils";
+// https://txtfiddle.com/~hlshwya/extract-urls-from-text
+// const urlRegex = /\b((https?|ftp|file):\/\/|(www|ftp)\.)[-A-Z0-9+&@#\/%?=~_|$!:,.;]*[A-Z0-9+&@#\/%=~_|$]/ig
 
+// function highlightURL(content: string) {
+//   return content.replace(urlRegex, (url) => {
+//     // fix http:// in [] will be parsed to link agin
+//     const res = `[${url.replace('://', '://')}](${url})`
+//     return res
+//   })
+// }
 export function PreCode(props: { children: any }) {
-  const ref = useRef<HTMLPreElement>(null);
+  const ref = useRef<HTMLPreElement>(null)
 
   return (
     <pre ref={ref}>
@@ -18,38 +28,37 @@ export function PreCode(props: { children: any }) {
         className="copy-code-button"
         onClick={() => {
           if (ref.current) {
-            const code = ref.current.innerText;
+            const code = ref.current.innerText
             // copyToClipboard(code);
           }
         }}
       ></span>
       {props.children}
     </pre>
-  );
+  )
 }
 
 const useLazyLoad = (ref: RefObject<Element>): boolean => {
-  const [isIntersecting, setIntersecting] = useState<boolean>(false);
+  const [isIntersecting, setIntersecting] = useState<boolean>(false)
 
   useEffect(() => {
     const observer = new IntersectionObserver(([entry]) => {
       if (entry.isIntersecting) {
-        setIntersecting(true);
-        observer.disconnect();
+        setIntersecting(true)
+        observer.disconnect()
       }
-    });
+    })
 
-    if (ref.current) {
-      observer.observe(ref.current);
-    }
+    if (ref.current)
+      observer.observe(ref.current)
 
     return () => {
-      observer.disconnect();
-    };
-  }, [ref]);
+      observer.disconnect()
+    }
+  }, [ref])
 
-  return isIntersecting;
-};
+  return isIntersecting
+}
 
 export function Markdown(props: { content: string }) {
   return (
@@ -62,7 +71,8 @@ export function Markdown(props: { content: string }) {
         components={{
           code({ node, inline, className, children, ...props }) {
             const match = /language-(\w+)/.exec(className || '')
-            return !inline && match ? (
+            return (!inline && match)
+              ? (
                 <SyntaxHighlighter
                   {...props}
                   children={String(children).replace(/\n$/, '')}
@@ -71,17 +81,19 @@ export function Markdown(props: { content: string }) {
                   showLineNumbers
                   PreTag="div"
                 />
-            ) : (
+              )
+              : (
                 <code {...props} className={className}>
                   {children}
                 </code>
               )
-          }
+          },
         }}
-        linkTarget={"_blank"}
+        linkTarget={'_blank'}
       >
+        {/* Markdown detect has problem. */}
         {props.content}
       </ReactMarkdown>
     </div>
-  );
+  )
 }

web/app/components/base/toast/index.tsx

@@ -9,7 +9,7 @@ import {
   InformationCircleIcon,
   XCircleIcon,
 } from '@heroicons/react/20/solid'
-import { createContext } from 'use-context-selector'
+import { createContext, useContext } from 'use-context-selector'
 
 export type IToastProps = {
   type?: 'success' | 'error' | 'warning' | 'info'
@@ -24,6 +24,7 @@ type IToastContext = {
 const defaultDuring = 3000
 
 export const ToastContext = createContext<IToastContext>({} as IToastContext)
+export const useToastContext = () => useContext(ToastContext)
 const Toast = ({
   type = 'info',
   duration,
@@ -31,9 +32,9 @@ const Toast = ({
   children,
 }: IToastProps) => {
   // sometimes message is react node array. Not handle it.
-  if (typeof message !== 'string') {
+  if (typeof message !== 'string')
     return null
-  }
+
   return <div className={classNames(
     'fixed rounded-md p-4 my-4 mx-8 z-50',
     'top-0',

web/app/components/base/voice-input/index.tsx

@@ -86,7 +86,7 @@ const VoiceInput = ({
     const formData = new FormData()
     formData.append('file', mp3File)
 
-    let url = ''
+    let url = '/universal-chat/audio-to-text'
     let isPublic = false
 
     if (params.token) {

web/app/components/develop/template/template_chat.en.mdx

@@ -380,6 +380,48 @@ For versatile conversational apps using a Q&A format, call the chat-messages API
   </Col>
 </Row>
 
+---
+
+<Heading
+  url='/audio-to-text'
+  method='POST'
+  title='speech to text'
+  name='#audio'
+/>
+<Row>
+  <Col>
+    Speech to text, only supports openai model.
+
+    ### Request Body
+
+    <Properties>
+      <Property name='file' type='file' key='file'>
+        Audio file.    
+        File uploads are currently limited to 15 MB and the following input file types are supported: mp3, mp4, mpeg, mpga, m4a, wav, and webm.
+      </Property>
+    </Properties>
+  </Col>
+  <Col sticky>
+
+    <CodeGroup title="Request" tag="POST" label="/audio-to-text" targetCode={`curl --location --request POST '${props.appDetail.api_base_url}/audio-to-text' \\\n--header 'Authorization: Bearer ENTER-YOUR-SECRET-KEY' \\\n--form 'file=@localfile;type=audio/[mp3|mp4|mpeg|mpga|m4a|wav|webm]'`}>
+
+    ```bash {{ title: 'cURL' }}
+    curl --location --request POST 'https://cloud.langgenius.dev/api/conversations/name' \
+    --header 'Authorization: Bearer ENTER-YOUR-SECRET-KEY' \
+    --form 'file=@localfile;type=audio/mp3'
+    ```
+
+    </CodeGroup>
+
+    <CodeGroup title="Response">
+    ```json {{ title: 'Response' }}
+    {
+      "text": ""
+    }
+    ```
+    </CodeGroup>
+  </Col>
+</Row>
 
 ---
 

web/app/components/develop/template/template_chat.zh.mdx

@@ -379,6 +379,48 @@ import { Row, Col, Properties, Property, Heading, SubProperty } from '../md.tsx'
   </Col>
 </Row>
 
+---
+
+<Heading
+  url='/audio-to-text'
+  method='POST'
+  title='语音转文字'
+  name='#audio'
+/>
+<Row>
+  <Col>
+    语音转文字，仅支持 openai 模型。
+
+    ### Request Body
+
+    <Properties>
+      <Property name='file' type='file' key='file'>
+        语音文件。    
+        文件上传当前限制为 15 MB，并且支持以下输入文件类型：mp3、mp4、mpeg、mpga、m4a、wav 和 webm。
+      </Property>
+    </Properties>
+  </Col>
+  <Col sticky>
+
+    <CodeGroup title="Request" tag="POST" label="/audio-to-text" targetCode={`curl --location --request POST '${props.appDetail.api_base_url}/audio-to-text' \\\n--header 'Authorization: Bearer ENTER-YOUR-SECRET-KEY' \\\n--form 'file=@localfile;type=audio/[mp3|mp4|mpeg|mpga|m4a|wav|webm]`}>
+
+    ```bash {{ title: 'cURL' }}
+    curl --location --request POST 'https://cloud.langgenius.dev/api/conversations/name' \
+    --header 'Authorization: Bearer ENTER-YOUR-SECRET-KEY' \
+    --form 'file=@localfile;type=audio/mp3'
+    ```
+
+    </CodeGroup>
+
+    <CodeGroup title="Response">
+    ```json {{ title: 'Response' }}
+    {
+      "text": ""
+    }
+    ```
+    </CodeGroup>
+  </Col>
+</Row>
 
 ---
 

web/app/components/explore/sidebar/index.tsx

@@ -14,13 +14,25 @@ import Confirm from '@/app/components/base/confirm'
 
 const SelectedDiscoveryIcon = () => (
   <svg width="16" height="16" viewBox="0 0 16 16" fill="none" xmlns="http://www.w3.org/2000/svg">
-    <path fillRule="evenodd" clipRule="evenodd" d="M13.4135 1.11725C13.5091 1.09983 13.6483 1.08355 13.8078 1.11745C14.0143 1.16136 14.2017 1.26953 14.343 1.42647C14.4521 1.54766 14.5076 1.67634 14.5403 1.76781C14.5685 1.84673 14.593 1.93833 14.6136 2.01504L15.5533 5.5222C15.5739 5.5989 15.5985 5.69049 15.6135 5.77296C15.6309 5.86852 15.6472 6.00771 15.6133 6.16722C15.5694 6.37378 15.4612 6.56114 15.3043 6.70245C15.1831 6.81157 15.0544 6.86706 14.9629 6.89975C14.884 6.92796 14.7924 6.95247 14.7157 6.97299L14.676 6.98364C14.3365 7.07461 14.0437 7.15309 13.7972 7.19802C13.537 7.24543 13.2715 7.26736 12.9946 7.20849C12.7513 7.15677 12.5213 7.06047 12.3156 6.92591L9.63273 7.64477C9.86399 7.97104 9.99992 8.36965 9.99992 8.80001C9.99992 9.2424 9.85628 9.65124 9.6131 9.98245L12.5508 14.291C12.7582 14.5952 12.6797 15.01 12.3755 15.2174C12.0713 15.4248 11.6566 15.3464 11.4492 15.0422L8.51171 10.7339C8.34835 10.777 8.17682 10.8 7.99992 10.8C7.82305 10.8 7.65155 10.777 7.48823 10.734L4.5508 15.0422C4.34338 15.3464 3.92863 15.4248 3.62442 15.2174C3.32021 15.01 3.24175 14.5952 3.44916 14.291L6.3868 9.98254C6.14358 9.65132 5.99992 9.24244 5.99992 8.80001C5.99992 8.73795 6.00274 8.67655 6.00827 8.61594L4.59643 8.99424C4.51973 9.01483 4.42813 9.03941 4.34567 9.05444C4.25011 9.07185 4.11092 9.08814 3.95141 9.05423C3.74485 9.01033 3.55748 8.90215 3.41618 8.74522C3.38535 8.71097 3.3588 8.67614 3.33583 8.64171L2.49206 8.8678C2.41536 8.88838 2.32376 8.91296 2.2413 8.92799C2.14574 8.94541 2.00655 8.96169 1.84704 8.92779C1.64048 8.88388 1.45311 8.77571 1.31181 8.61877C1.20269 8.49759 1.1472 8.3689 1.1145 8.27744C1.08629 8.1985 1.06177 8.10689 1.04125 8.03018L0.791701 7.09885C0.771119 7.02215 0.746538 6.93055 0.731508 6.84809C0.714092 6.75253 0.697808 6.61334 0.731712 6.45383C0.775619 6.24726 0.883793 6.0599 1.04073 5.9186C1.16191 5.80948 1.2906 5.75399 1.38206 5.72129C1.461 5.69307 1.55261 5.66856 1.62932 5.64804L2.47318 5.42193C2.47586 5.38071 2.48143 5.33735 2.49099 5.29237C2.5349 5.08581 2.64307 4.89844 2.80001 4.75714C2.92119 4.64802 3.04988 4.59253 3.14134 4.55983C3.22027 4.53162 3.31189 4.50711 3.3886 4.48658L11.1078 2.41824C11.2186 2.19888 11.3697 2.00049 11.5545 1.83406C11.7649 1.64462 12.0058 1.53085 12.2548 1.44183C12.4907 1.35749 12.7836 1.27904 13.123 1.18809L13.1628 1.17744C13.2395 1.15686 13.3311 1.13228 13.4135 1.11725ZM13.3642 2.5039C13.0648 2.58443 12.8606 2.64126 12.7036 2.69735C12.5325 2.75852 12.4742 2.80016 12.4467 2.82492C12.3421 2.91912 12.2699 3.04403 12.2407 3.18174C12.233 3.21793 12.2261 3.28928 12.2587 3.46805C12.2927 3.6545 12.3564 3.89436 12.4559 4.26563L12.5594 4.652C12.6589 5.02328 12.7236 5.26287 12.7874 5.44133C12.8486 5.61244 12.8902 5.67079 12.915 5.69829C13.0092 5.80291 13.1341 5.87503 13.2718 5.9043C13.308 5.91199 13.3793 5.91887 13.5581 5.88629C13.7221 5.85641 13.9273 5.80352 14.2269 5.72356L13.3642 2.5039Z" fill="#155EEF"/>
+    <path fillRule="evenodd" clipRule="evenodd" d="M13.4135 1.11725C13.5091 1.09983 13.6483 1.08355 13.8078 1.11745C14.0143 1.16136 14.2017 1.26953 14.343 1.42647C14.4521 1.54766 14.5076 1.67634 14.5403 1.76781C14.5685 1.84673 14.593 1.93833 14.6136 2.01504L15.5533 5.5222C15.5739 5.5989 15.5985 5.69049 15.6135 5.77296C15.6309 5.86852 15.6472 6.00771 15.6133 6.16722C15.5694 6.37378 15.4612 6.56114 15.3043 6.70245C15.1831 6.81157 15.0544 6.86706 14.9629 6.89975C14.884 6.92796 14.7924 6.95247 14.7157 6.97299L14.676 6.98364C14.3365 7.07461 14.0437 7.15309 13.7972 7.19802C13.537 7.24543 13.2715 7.26736 12.9946 7.20849C12.7513 7.15677 12.5213 7.06047 12.3156 6.92591L9.63273 7.64477C9.86399 7.97104 9.99992 8.36965 9.99992 8.80001C9.99992 9.2424 9.85628 9.65124 9.6131 9.98245L12.5508 14.291C12.7582 14.5952 12.6797 15.01 12.3755 15.2174C12.0713 15.4248 11.6566 15.3464 11.4492 15.0422L8.51171 10.7339C8.34835 10.777 8.17682 10.8 7.99992 10.8C7.82305 10.8 7.65155 10.777 7.48823 10.734L4.5508 15.0422C4.34338 15.3464 3.92863 15.4248 3.62442 15.2174C3.32021 15.01 3.24175 14.5952 3.44916 14.291L6.3868 9.98254C6.14358 9.65132 5.99992 9.24244 5.99992 8.80001C5.99992 8.73795 6.00274 8.67655 6.00827 8.61594L4.59643 8.99424C4.51973 9.01483 4.42813 9.03941 4.34567 9.05444C4.25011 9.07185 4.11092 9.08814 3.95141 9.05423C3.74485 9.01033 3.55748 8.90215 3.41618 8.74522C3.38535 8.71097 3.3588 8.67614 3.33583 8.64171L2.49206 8.8678C2.41536 8.88838 2.32376 8.91296 2.2413 8.92799C2.14574 8.94541 2.00655 8.96169 1.84704 8.92779C1.64048 8.88388 1.45311 8.77571 1.31181 8.61877C1.20269 8.49759 1.1472 8.3689 1.1145 8.27744C1.08629 8.1985 1.06177 8.10689 1.04125 8.03018L0.791701 7.09885C0.771119 7.02215 0.746538 6.93055 0.731508 6.84809C0.714092 6.75253 0.697808 6.61334 0.731712 6.45383C0.775619 6.24726 0.883793 6.0599 1.04073 5.9186C1.16191 5.80948 1.2906 5.75399 1.38206 5.72129C1.461 5.69307 1.55261 5.66856 1.62932 5.64804L2.47318 5.42193C2.47586 5.38071 2.48143 5.33735 2.49099 5.29237C2.5349 5.08581 2.64307 4.89844 2.80001 4.75714C2.92119 4.64802 3.04988 4.59253 3.14134 4.55983C3.22027 4.53162 3.31189 4.50711 3.3886 4.48658L11.1078 2.41824C11.2186 2.19888 11.3697 2.00049 11.5545 1.83406C11.7649 1.64462 12.0058 1.53085 12.2548 1.44183C12.4907 1.35749 12.7836 1.27904 13.123 1.18809L13.1628 1.17744C13.2395 1.15686 13.3311 1.13228 13.4135 1.11725ZM13.3642 2.5039C13.0648 2.58443 12.8606 2.64126 12.7036 2.69735C12.5325 2.75852 12.4742 2.80016 12.4467 2.82492C12.3421 2.91912 12.2699 3.04403 12.2407 3.18174C12.233 3.21793 12.2261 3.28928 12.2587 3.46805C12.2927 3.6545 12.3564 3.89436 12.4559 4.26563L12.5594 4.652C12.6589 5.02328 12.7236 5.26287 12.7874 5.44133C12.8486 5.61244 12.8902 5.67079 12.915 5.69829C13.0092 5.80291 13.1341 5.87503 13.2718 5.9043C13.308 5.91199 13.3793 5.91887 13.5581 5.88629C13.7221 5.85641 13.9273 5.80352 14.2269 5.72356L13.3642 2.5039Z" fill="#155EEF" />
   </svg>
 )
 
 const DiscoveryIcon = () => (
   <svg width="16" height="16" viewBox="0 0 16 16" fill="none" xmlns="http://www.w3.org/2000/svg">
-    <path d="M8.74786 9.89676L12.0003 14.6669M7.25269 9.89676L4.00027 14.6669M9.3336 8.80031C9.3336 9.53669 8.73665 10.1336 8.00027 10.1336C7.26389 10.1336 6.66694 9.53669 6.66694 8.80031C6.66694 8.06393 7.26389 7.46698 8.00027 7.46698C8.73665 7.46698 9.3336 8.06393 9.3336 8.80031ZM11.4326 3.02182L3.57641 5.12689C3.39609 5.1752 3.30593 5.19936 3.24646 5.25291C3.19415 5.30001 3.15809 5.36247 3.14345 5.43132C3.12681 5.5096 3.15097 5.59976 3.19929 5.78008L3.78595 7.96951C3.83426 8.14984 3.85842 8.24 3.91197 8.29947C3.95907 8.35178 4.02153 8.38784 4.09038 8.40248C4.16866 8.41911 4.25882 8.39496 4.43914 8.34664L12.2953 6.24158L11.4326 3.02182ZM14.5285 6.33338C13.8072 6.52665 13.4466 6.62328 13.1335 6.55673C12.8581 6.49819 12.6082 6.35396 12.4198 6.14471C12.2056 5.90682 12.109 5.54618 11.9157 4.82489L11.8122 4.43852C11.6189 3.71722 11.5223 3.35658 11.5889 3.04347C11.6474 2.76805 11.7916 2.51823 12.0009 2.32982C12.2388 2.11563 12.5994 2.019 13.3207 1.82573C13.501 1.77741 13.5912 1.75325 13.6695 1.76989C13.7383 1.78452 13.8008 1.82058 13.8479 1.87289C13.9014 1.93237 13.9256 2.02253 13.9739 2.20285L14.9057 5.68018C14.954 5.86051 14.9781 5.95067 14.9615 6.02894C14.9469 6.0978 14.9108 6.16025 14.8585 6.20736C14.799 6.2609 14.7088 6.28506 14.5285 6.33338ZM2.33475 8.22033L3.23628 7.97876C3.4166 7.93044 3.50676 7.90628 3.56623 7.85274C3.61854 7.80563 3.6546 7.74318 3.66924 7.67433C3.68588 7.59605 3.66172 7.50589 3.6134 7.32556L3.37184 6.42403C3.32352 6.24371 3.29936 6.15355 3.24581 6.09408C3.19871 6.04176 3.13626 6.00571 3.0674 5.99107C2.98912 5.97443 2.89896 5.99859 2.71864 6.04691L1.81711 6.28847C1.63678 6.33679 1.54662 6.36095 1.48715 6.4145C1.43484 6.4616 1.39878 6.52405 1.38415 6.59291C1.36751 6.67119 1.39167 6.76135 1.43998 6.94167L1.68155 7.8432C1.72987 8.02352 1.75402 8.11369 1.80757 8.17316C1.85467 8.22547 1.91713 8.26153 1.98598 8.27616C2.06426 8.2928 2.15442 8.26864 2.33475 8.22033Z" stroke="#344054" strokeWidth="1.25" strokeLinecap="round" strokeLinejoin="round"/>
+    <path d="M8.74786 9.89676L12.0003 14.6669M7.25269 9.89676L4.00027 14.6669M9.3336 8.80031C9.3336 9.53669 8.73665 10.1336 8.00027 10.1336C7.26389 10.1336 6.66694 9.53669 6.66694 8.80031C6.66694 8.06393 7.26389 7.46698 8.00027 7.46698C8.73665 7.46698 9.3336 8.06393 9.3336 8.80031ZM11.4326 3.02182L3.57641 5.12689C3.39609 5.1752 3.30593 5.19936 3.24646 5.25291C3.19415 5.30001 3.15809 5.36247 3.14345 5.43132C3.12681 5.5096 3.15097 5.59976 3.19929 5.78008L3.78595 7.96951C3.83426 8.14984 3.85842 8.24 3.91197 8.29947C3.95907 8.35178 4.02153 8.38784 4.09038 8.40248C4.16866 8.41911 4.25882 8.39496 4.43914 8.34664L12.2953 6.24158L11.4326 3.02182ZM14.5285 6.33338C13.8072 6.52665 13.4466 6.62328 13.1335 6.55673C12.8581 6.49819 12.6082 6.35396 12.4198 6.14471C12.2056 5.90682 12.109 5.54618 11.9157 4.82489L11.8122 4.43852C11.6189 3.71722 11.5223 3.35658 11.5889 3.04347C11.6474 2.76805 11.7916 2.51823 12.0009 2.32982C12.2388 2.11563 12.5994 2.019 13.3207 1.82573C13.501 1.77741 13.5912 1.75325 13.6695 1.76989C13.7383 1.78452 13.8008 1.82058 13.8479 1.87289C13.9014 1.93237 13.9256 2.02253 13.9739 2.20285L14.9057 5.68018C14.954 5.86051 14.9781 5.95067 14.9615 6.02894C14.9469 6.0978 14.9108 6.16025 14.8585 6.20736C14.799 6.2609 14.7088 6.28506 14.5285 6.33338ZM2.33475 8.22033L3.23628 7.97876C3.4166 7.93044 3.50676 7.90628 3.56623 7.85274C3.61854 7.80563 3.6546 7.74318 3.66924 7.67433C3.68588 7.59605 3.66172 7.50589 3.6134 7.32556L3.37184 6.42403C3.32352 6.24371 3.29936 6.15355 3.24581 6.09408C3.19871 6.04176 3.13626 6.00571 3.0674 5.99107C2.98912 5.97443 2.89896 5.99859 2.71864 6.04691L1.81711 6.28847C1.63678 6.33679 1.54662 6.36095 1.48715 6.4145C1.43484 6.4616 1.39878 6.52405 1.38415 6.59291C1.36751 6.67119 1.39167 6.76135 1.43998 6.94167L1.68155 7.8432C1.72987 8.02352 1.75402 8.11369 1.80757 8.17316C1.85467 8.22547 1.91713 8.26153 1.98598 8.27616C2.06426 8.2928 2.15442 8.26864 2.33475 8.22033Z" stroke="#344054" strokeWidth="1.25" strokeLinecap="round" strokeLinejoin="round" />
+  </svg>
+)
+
+const SelectedChatIcon = () => (
+  <svg width="16" height="16" viewBox="0 0 16 16" fill="none" xmlns="http://www.w3.org/2000/svg">
+    <path fillRule="evenodd" clipRule="evenodd" d="M8.00016 1.3335C4.31826 1.3335 1.3335 4.31826 1.3335 8.00016C1.3335 8.88571 1.50651 9.7325 1.8212 10.5074C1.84962 10.5773 1.86597 10.6178 1.87718 10.6476L1.88058 10.6568L1.88016 10.66C1.87683 10.6846 1.87131 10.7181 1.86064 10.7821L1.46212 13.1732C1.44424 13.2803 1.42423 13.4001 1.41638 13.5041C1.40782 13.6176 1.40484 13.7981 1.48665 13.9888C1.58779 14.2246 1.77569 14.4125 2.0115 14.5137C2.20224 14.5955 2.38274 14.5925 2.49619 14.5839C2.60025 14.5761 2.72006 14.5561 2.82715 14.5382L5.2182 14.1397C5.28222 14.129 5.31576 14.1235 5.34036 14.1202L5.34353 14.1197L5.35274 14.1231C5.38258 14.1344 5.42298 14.1507 5.49297 14.1791C6.26783 14.4938 7.11462 14.6668 8.00016 14.6668C11.6821 14.6668 14.6668 11.6821 14.6668 8.00016C14.6668 4.31826 11.6821 1.3335 8.00016 1.3335ZM4.00016 8.00016C4.00016 7.44788 4.44788 7.00016 5.00016 7.00016C5.55245 7.00016 6.00016 7.44788 6.00016 8.00016C6.00016 8.55245 5.55245 9.00016 5.00016 9.00016C4.44788 9.00016 4.00016 8.55245 4.00016 8.00016ZM7.00016 8.00016C7.00016 7.44788 7.44788 7.00016 8.00016 7.00016C8.55245 7.00016 9.00016 7.44788 9.00016 8.00016C9.00016 8.55245 8.55245 9.00016 8.00016 9.00016C7.44788 9.00016 7.00016 8.55245 7.00016 8.00016ZM11.0002 7.00016C10.4479 7.00016 10.0002 7.44788 10.0002 8.00016C10.0002 8.55245 10.4479 9.00016 11.0002 9.00016C11.5524 9.00016 12.0002 8.55245 12.0002 8.00016C12.0002 7.44788 11.5524 7.00016 11.0002 7.00016Z" fill="#155EEF"/>
+  </svg>
+)
+
+const ChatIcon = () => (
+  <svg width="16" height="16" viewBox="0 0 16 16" fill="none" xmlns="http://www.w3.org/2000/svg">
+    <path d="M5 8H5.00667M8 8H8.00667M11 8H11.0067M8 14C11.3137 14 14 11.3137 14 8C14 4.68629 11.3137 2 8 2C4.68629 2 2 4.68629 2 8C2 8.7981 2.15582 9.5598 2.43871 10.2563C2.49285 10.3897 2.51992 10.4563 2.532 10.5102C2.54381 10.5629 2.54813 10.6019 2.54814 10.6559C2.54814 10.7111 2.53812 10.7713 2.51807 10.8916L2.12275 13.2635C2.08135 13.5119 2.06065 13.6361 2.09917 13.7259C2.13289 13.8045 2.19552 13.8671 2.27412 13.9008C2.36393 13.9393 2.48812 13.9186 2.73651 13.8772L5.10843 13.4819C5.22872 13.4619 5.28887 13.4519 5.34409 13.4519C5.3981 13.4519 5.43711 13.4562 5.48981 13.468C5.54369 13.4801 5.61035 13.5072 5.74366 13.5613C6.4402 13.8442 7.2019 14 8 14ZM5.33333 8C5.33333 8.1841 5.1841 8.33333 5 8.33333C4.81591 8.33333 4.66667 8.1841 4.66667 8C4.66667 7.81591 4.81591 7.66667 5 7.66667C5.1841 7.66667 5.33333 7.81591 5.33333 8ZM8.33333 8C8.33333 8.1841 8.1841 8.33333 8 8.33333C7.81591 8.33333 7.66667 8.1841 7.66667 8C7.66667 7.81591 7.81591 7.66667 8 7.66667C8.1841 7.66667 8.33333 7.81591 8.33333 8ZM11.3333 8C11.3333 8.1841 11.1841 8.33333 11 8.33333C10.8159 8.33333 10.6667 8.1841 10.6667 8C10.6667 7.81591 10.8159 7.66667 11 7.66667C11.1841 7.66667 11.3333 7.81591 11.3333 8Z" stroke="#344054" stroke-width="1.25" stroke-linecap="round" stroke-linejoin="round"/>
   </svg>
 )
 
@@ -33,6 +45,7 @@ const SideBar: FC<{
   const segments = useSelectedLayoutSegments()
   const lastSegment = segments.slice(-1)[0]
   const isDiscoverySelected = lastSegment === 'apps'
+  const isChatSelected = lastSegment === 'chat'
   const { installedApps, setInstalledApps } = useContext(ExploreContext)
 
   const fetchInstalledAppList = async () => {
@@ -81,6 +94,14 @@ const SideBar: FC<{
           {isDiscoverySelected ? <SelectedDiscoveryIcon /> : <DiscoveryIcon />}
           <div className='text-sm'>{t('explore.sidebar.discovery')}</div>
         </Link>
+        <Link
+          href='/explore/chat'
+          className={cn(isChatSelected ? 'text-primary-600  bg-white font-semibold' : 'text-gray-700 font-medium', 'flex items-center h-9 pl-3 space-x-2 rounded-lg')}
+          style={isChatSelected ? { boxShadow: '0px 1px 2px rgba(16, 24, 40, 0.05)' } : {}}
+        >
+          {isChatSelected ? <SelectedChatIcon /> : <ChatIcon />}
+          <div className='text-sm'>{t('explore.sidebar.chat')}</div>
+        </Link>
       </div>
       {installedApps.length > 0 && (
         <div className='mt-10'>

web/app/components/explore/universal-chat/config-view/detail/index.tsx

+'use client'
+import type { FC } from 'react'
+import React from 'react'
+import cn from 'classnames'
+import { useTranslation } from 'react-i18next'
+import s from './style.module.css'
+import Config from '@/app/components/explore/universal-chat/config'
+
+type Props = {
+  modelId: string
+  plugins: Record<string, boolean>
+  dataSets: any[]
+}
+const ConfigViewPanel: FC<Props> = ({
+  modelId,
+  plugins,
+  dataSets,
+}) => {
+  const { t } = useTranslation()
+  return (
+    <div className={cn('absolute top-9 right-0 z-20 p-4 bg-white rounded-2xl shadow-md', s.panelBorder)}>
+      <div className='w-[368px]'>
+        <Config
+          readonly
+          modelId={modelId}
+          plugins={plugins}
+          dataSets={dataSets}
+        />
+        <div className='mt-3 text-xs leading-[18px] text-500 font-normal'>{t('explore.universalChat.viewConfigDetailTip')}</div>
+      </div>
+    </div>
+  )
+}
+export default React.memo(ConfigViewPanel)

web/app/components/explore/universal-chat/config-view/detail/style.module.css

+.btn {
+  background: url(~@/app/components/datasets/documents/assets/action.svg) center center no-repeat transparent;
+  background-size: 16px 16px;
+  /* mask-image: ; */
+}
+
+.panelBorder {
+  border: 0.5px solid rgba(0, 0, 0, .05);
+}
\ No newline at end of file

web/app/components/explore/universal-chat/config-view/summary/index.tsx

+'use client'
+import type { FC } from 'react'
+import React from 'react'
+import cn from 'classnames'
+import { useBoolean, useClickAway } from 'ahooks'
+import s from './style.module.css'
+import ModelIcon from '@/app/components/app/configuration/config-model/model-icon'
+import { Google, WebReader, Wikipedia } from '@/app/components/base/icons/src/public/plugins'
+import ConfigDetail from '@/app/components/explore/universal-chat/config-view/detail'
+
+export type ISummaryProps = {
+  modelId: string
+  plugins: Record<string, boolean>
+  dataSets: any[]
+}
+
+const getColorInfo = (modelId: string) => {
+  if (modelId === 'gpt-4')
+    return s.gpt4
+
+  if (modelId === 'claude-2')
+    return s.claude
+
+  return s.gpt3
+}
+
+const getPlugIcon = (pluginId: string) => {
+  const className = 'w-4 h-4'
+  switch (pluginId) {
+    case 'google_search':
+      return <Google className={className} />
+    case 'web_reader':
+      return <WebReader className={className} />
+    case 'wikipedia':
+      return <Wikipedia className={className} />
+    default:
+      return null
+  }
+}
+
+const Summary: FC<ISummaryProps> = ({
+  modelId,
+  plugins,
+  dataSets,
+}) => {
+  const pluginIds = Object.keys(plugins).filter(key => plugins[key])
+  const [isShowConfig, { setFalse: hideConfig, toggle: toggleShowConfig }] = useBoolean(false)
+  const configContentRef = React.useRef(null)
+
+  useClickAway(() => {
+    hideConfig()
+  }, configContentRef)
+  return (
+    <div ref={configContentRef} className='relative'>
+      <div onClick={toggleShowConfig} className={cn(getColorInfo(modelId), 'flex items-center px-1 h-8 rounded-lg border cursor-pointer')}>
+        <ModelIcon modelId={modelId} className='!w-6 !h-6' />
+        <div className='ml-2 text-[13px] font-medium text-gray-900'>{modelId}</div>
+        {
+          pluginIds.length > 0 && (
+            <div className='ml-1.5 flex items-center'>
+              <div className='mr-1 h-3 w-[1px] bg-[#000] opacity-[0.05]'></div>
+              <div className='flex space-x-1'>
+                {pluginIds.map(pluginId => (
+                  <div
+                    key={pluginId}
+                    className={`flex items-center justify-center w-6 h-6 rounded-md ${s.border} bg-white`}
+                  >
+                    {getPlugIcon(pluginId)}</div>
+                ))}
+              </div>
+            </div>
+          )
+        }
+      </div>
+      {isShowConfig && (
+        <ConfigDetail
+          modelId={modelId} plugins={plugins} dataSets={dataSets}
+        />
+      )}
+    </div>
+
+  )
+}
+export default React.memo(Summary)

web/app/components/explore/universal-chat/config-view/summary/style.module.css

+.border {
+  border: 1px solid rgba(0, 0, 0, 0.05);
+}
+
+.gpt3 {
+  background: linear-gradient(0deg, #D3F8DF, #D3F8DF),
+linear-gradient(0deg, #EDFCF2, #EDFCF2);
+  border: 1px solid rgba(211, 248, 223, 1)
+}
+
+.gpt4 {
+  background: linear-gradient(0deg, #EBE9FE, #EBE9FE),
+  linear-gradient(0deg, #F4F3FF, #F4F3FF);
+  border: 1px solid rgba(235, 233, 254, 1)
+}
+
+.claude {
+  background: linear-gradient(0deg, #F9EBDF, #F9EBDF),
+linear-gradient(0deg, #FCF3EB, #FCF3EB);
+  border: 1px solid rgba(249, 235, 223, 1)
+}
\ No newline at end of file

web/app/components/explore/universal-chat/config/data-config/index.tsx

+'use client'
+import type { FC } from 'react'
+import React from 'react'
+import { useTranslation } from 'react-i18next'
+import { useBoolean } from 'ahooks'
+import { isEqual } from 'lodash-es'
+import produce from 'immer'
+import FeaturePanel from '@/app/components/app/configuration/base/feature-panel'
+import OperationBtn from '@/app/components/app/configuration/base/operation-btn'
+import CardItem from '@/app/components/app/configuration/dataset-config/card-item'
+import SelectDataSet from '@/app/components/app/configuration/dataset-config/select-dataset'
+import type { DataSet } from '@/models/datasets'
+
+type Props = {
+  readonly?: boolean
+  dataSets: DataSet[]
+  onChange?: (data: DataSet[]) => void
+}
+
+const DatasetConfig: FC<Props> = ({
+  readonly,
+  dataSets,
+  onChange,
+}) => {
+  const { t } = useTranslation()
+
+  const selectedIds = dataSets.map(item => item.id)
+
+  const hasData = dataSets.length > 0
+  const [isShowSelectDataSet, { setTrue: showSelectDataSet, setFalse: hideSelectDataSet }] = useBoolean(false)
+  const handleSelect = (data: DataSet[]) => {
+    if (isEqual(data.map(item => item.id), dataSets.map(item => item.id))) {
+      hideSelectDataSet()
+      return
+    }
+
+    if (data.find(item => !item.name)) { // has not loaded selected dataset
+      const newSelected = produce(data, (draft) => {
+        data.forEach((item, index) => {
+          if (!item.name) { // not fetched database
+            const newItem = dataSets.find(i => i.id === item.id)
+            if (newItem)
+              draft[index] = newItem
+          }
+        })
+      })
+      onChange?.(newSelected)
+    }
+    else {
+      onChange?.(data)
+    }
+    hideSelectDataSet()
+  }
+  const onRemove = (id: string) => {
+    onChange?.(dataSets.filter(item => item.id !== id))
+  }
+
+  return (
+    <FeaturePanel
+      className='mt-3'
+      title={t('appDebug.feature.dataSet.title')}
+      headerRight={!readonly && <OperationBtn type="add" onClick={showSelectDataSet} />}
+      hasHeaderBottomBorder={!hasData}
+    >
+      {hasData
+        ? (
+          <div className='max-h-[220px] overflow-y-auto'>
+            {dataSets.map(item => (
+              <CardItem
+                className="mb-2 !w-full"
+                key={item.id}
+                config={item}
+                onRemove={onRemove}
+                readonly={readonly}
+                // TODO: readonly remove btn
+              />
+            ))}
+          </div>
+        )
+        : (
+          <div className='pt-2 pb-1 text-xs text-gray-500'>{t('appDebug.feature.dataSet.noData')}</div>
+        )}
+
+      {isShowSelectDataSet && (
+        <SelectDataSet
+          isShow={isShowSelectDataSet}
+          onClose={hideSelectDataSet}
+          selectedIds={selectedIds}
+          onSelect={handleSelect}
+        />
+      )}
+    </FeaturePanel>
+  )
+}
+export default React.memo(DatasetConfig)

web/app/components/explore/universal-chat/config/index.tsx

+'use client'
+import type { FC } from 'react'
+import React from 'react'
+import ModelConfig from './model-config'
+import DataConfig from './data-config'
+import PluginConfig from './plugins-config'
+
+export type IConfigProps = {
+  className?: string
+  readonly?: boolean
+  modelId: string
+  onModelChange?: (modelId: string) => void
+  plugins: Record<string, boolean>
+  onPluginChange?: (key: string, value: boolean) => void
+  dataSets: any[]
+  onDataSetsChange?: (contexts: any[]) => void
+}
+
+const Config: FC<IConfigProps> = ({
+  className,
+  readonly,
+  modelId,
+  onModelChange,
+  plugins,
+  onPluginChange,
+  dataSets,
+  onDataSetsChange,
+}) => {
+  return (
+    <div className={className}>
+      <ModelConfig
+        readonly={readonly}
+        modelId={modelId}
+        onChange={onModelChange}
+      />
+      <PluginConfig
+        readonly={readonly}
+        config={plugins}
+        onChange={onPluginChange}
+      />
+      {(!readonly || (readonly && dataSets.length > 0)) && (
+        <DataConfig
+          readonly={readonly}
+          dataSets={dataSets}
+          onChange={onDataSetsChange}
+        />
+      )}
+    </div>
+  )
+}
+export default React.memo(Config)

web/app/components/explore/universal-chat/config/model-config/index.tsx

+'use client'
+import type { FC } from 'react'
+import React from 'react'
+import cn from 'classnames'
+import { useBoolean, useClickAway } from 'ahooks'
+import { ChevronDownIcon } from '@heroicons/react/24/outline'
+import { useTranslation } from 'react-i18next'
+import ModelIcon from '@/app/components/app/configuration/config-model/model-icon'
+import { UNIVERSAL_CHAT_MODEL_LIST as MODEL_LIST } from '@/config'
+import { Checked as CheckedIcon } from '@/app/components/base/icons/src/public/model'
+export type IModelConfigProps = {
+  modelId: string
+  onChange?: (model: string) => void
+  readonly?: boolean
+}
+
+const ModelConfig: FC<IModelConfigProps> = ({
+  modelId,
+  onChange,
+  readonly,
+}) => {
+  const { t } = useTranslation()
+
+  const currModel = MODEL_LIST.find(item => item.id === modelId)
+  const [isShowOption, { setFalse: hideOption, toggle: toogleOption }] = useBoolean(false)
+  const triggerRef = React.useRef(null)
+  useClickAway(() => {
+    hideOption()
+  }, triggerRef)
+
+  return (
+    <div className='flex items-center justify-between h-[52px] px-3 rounded-xl bg-gray-50'>
+      <div className='text-sm font-semibold text-gray-800'>{t('explore.universalChat.model')}</div>
+      <div className="relative z-10">
+        <div
+          ref={triggerRef}
+          onClick={() => !readonly && toogleOption()}
+          className={cn(
+            readonly ? 'cursor-not-allowed' : 'cursor-pointer', 'flex items-center h-9 px-3 space-x-2 rounded-lg',
+            isShowOption && 'bg-gray-100',
+          )}>
+          <ModelIcon modelId={currModel?.id as string} />
+          <div className="text-sm gray-900">{currModel?.name}</div>
+          {!readonly && <ChevronDownIcon className={cn(isShowOption && 'rotate-180', 'w-[14px] h-[14px] text-gray-500')} />}
+        </div>
+        {isShowOption && (
+          <div className={cn('absolute top-10 right-0 bg-white rounded-lg shadow')}>
+            {MODEL_LIST.map(item => (
+              <div key={item.id} onClick={() => onChange?.(item.id)} className="w-[232px] flex items-center h-9 px-4 rounded-lg cursor-pointer hover:bg-gray-100">
+                <ModelIcon className='shrink-0 mr-2' modelId={item?.id} />
+                <div className="text-sm gray-900 whitespace-nowrap">{item.name}</div>
+                {(item.id === currModel?.id) && <CheckedIcon className='absolute right-4' />}
+              </div>
+            ))}
+          </div>
+        )}
+      </div>
+    </div>
+  )
+}
+export default React.memo(ModelConfig)

web/app/components/explore/universal-chat/config/plugins-config/index.tsx

+'use client'
+import type { FC } from 'react'
+import React, { useEffect } from 'react'
+import { useTranslation } from 'react-i18next'
+import Item from './item'
+import FeaturePanel from '@/app/components/app/configuration/base/feature-panel'
+import { Google, WebReader, Wikipedia } from '@/app/components/base/icons/src/public/plugins'
+import { getToolProviders } from '@/service/explore'
+import Loading from '@/app/components/base/loading'
+import AccountSetting from '@/app/components/header/account-setting'
+
+export type IPluginsProps = {
+  readonly?: boolean
+  config: Record<string, boolean>
+  onChange?: (key: string, value: boolean) => void
+}
+
+const plugins = [
+  { key: 'google_search', icon: <Google /> },
+  { key: 'web_reader', icon: <WebReader /> },
+  { key: 'wikipedia', icon: <Wikipedia /> },
+]
+const Plugins: FC<IPluginsProps> = ({
+  readonly,
+  config,
+  onChange,
+}) => {
+  const { t } = useTranslation()
+  const [isLoading, setIsLoading] = React.useState(!readonly)
+  const [isSerpApiValid, setIsSerpApiValid] = React.useState(false)
+  const checkSerpApiKey = async () => {
+    if (readonly)
+      return
+
+    const provides: any = await getToolProviders()
+    const isSerpApiValid = !!provides.find((v: any) => v.tool_name === 'serpapi' && v.is_enabled)
+    setIsSerpApiValid(isSerpApiValid)
+    setIsLoading(false)
+  }
+  useEffect(() => {
+    checkSerpApiKey()
+  }, [])
+
+  const [showSetSerpAPIKeyModal, setShowSetAPIKeyModal] = React.useState(false)
+
+  const itemConfigs = plugins.map((plugin) => {
+    const res: Record<string, any> = { ...plugin }
+    const { key } = plugin
+    res.name = t(`explore.universalChat.plugins.${key}.name`)
+    if (key === 'web_reader')
+      res.description = t(`explore.universalChat.plugins.${key}.description`)
+
+    if (key === 'google_search' && !isSerpApiValid && !readonly) {
+      res.readonly = true
+      res.more = (
+        <div className='border-t border-[#FEF0C7] flex items-center h-[34px] pl-2 bg-[#FFFAEB] text-gray-700 text-xs '>
+          <span className='whitespace-pre'>{t('explore.universalChat.plugins.google_search.more.left')}</span>
+          <span className='cursor-pointer text-[#155EEF]' onClick={() => setShowSetAPIKeyModal(true)}>{t('explore.universalChat.plugins.google_search.more.link')}</span>
+          <span className='whitespace-pre'>{t('explore.universalChat.plugins.google_search.more.right')}</span>
+        </div>
+      )
+    }
+    return res
+  })
+
+  const enabledPluginNum = Object.values(config).filter(v => v).length
+
+  return (
+    <>
+      <FeaturePanel
+        className='mt-3'
+        title={
+          <div className='flex space-x-1'>
+            <div>{t('explore.universalChat.plugins.name')}</div>
+            <div className='text-[13px] font-normal text-gray-500'>({enabledPluginNum}/{plugins.length})</div>
+          </div>}
+        hasHeaderBottomBorder={false}
+      >
+        {isLoading
+          ? (
+            <div className='flex items-center h-[166px]'>
+              <Loading type='area' />
+            </div>
+          )
+          : (<div className='space-y-2'>
+            {itemConfigs.map(item => (
+              <Item
+                key={item.key}
+                icon={item.icon}
+                name={item.name}
+                description={item.description}
+                more={item.more}
+                enabled={config[item.key]}
+                onChange={enabled => onChange?.(item.key, enabled)}
+                readonly={readonly || item.readonly}
+              />
+            ))}
+          </div>)}
+      </FeaturePanel>
+      {
+        showSetSerpAPIKeyModal && (
+          <AccountSetting activeTab="plugin" onCancel={async () => {
+            setShowSetAPIKeyModal(false)
+            await checkSerpApiKey()
+          }} />
+        )
+      }
+    </>
+  )
+}
+export default React.memo(Plugins)

web/app/components/explore/universal-chat/config/plugins-config/item.module.css

+.shadow {
+  box-shadow: 0px 1px 2px 0px rgba(16, 24, 40, 0.05);
+}
\ No newline at end of file

web/app/components/explore/universal-chat/config/plugins-config/item.tsx

+'use client'
+import type { FC } from 'react'
+import React from 'react'
+import cn from 'classnames'
+import s from './item.module.css'
+import Switch from '@/app/components/base/switch'
+
+export type IItemProps = {
+  icon: React.ReactNode
+  name: string
+  description?: string
+  more?: React.ReactNode
+  enabled: boolean
+  onChange: (enabled: boolean) => void
+  readonly?: boolean
+}
+
+const Item: FC<IItemProps> = ({
+  icon,
+  name,
+  description,
+  more,
+  enabled,
+  onChange,
+  readonly,
+}) => {
+  return (
+    <div className={cn('bg-white rounded-xl border border-gray-200 overflow-hidden', s.shadow)}>
+      <div className='flex justify-between items-center min-h-[48px] px-2'>
+        <div className='flex items-center space-x-2'>
+          {icon}
+          <div className='leading-[18px]'>
+            <div className='text-[13px] font-medium text-gray-800'>{name}</div>
+            {description && <div className='text-xs leading-[18px] text-gray-500'>{description}</div>}
+          </div>
+        </div>
+        <Switch size='md' defaultValue={enabled} onChange={onChange} disabled={readonly} />
+      </div>
+      {more}
+    </div>
+  )
+}
+export default React.memo(Item)

web/app/components/explore/universal-chat/hooks/use-conversation.ts

+import { useState } from 'react'
+import produce from 'immer'
+import { useGetState } from 'ahooks'
+import type { ConversationItem } from '@/models/share'
+
+const storageConversationIdKey = 'conversationIdInfo'
+
+type ConversationInfoType = Omit<ConversationItem, 'inputs' | 'id'>
+function useConversation() {
+  const [conversationList, setConversationList] = useState<ConversationItem[]>([])
+  const [pinnedConversationList, setPinnedConversationList] = useState<ConversationItem[]>([])
+  const [currConversationId, doSetCurrConversationId, getCurrConversationId] = useGetState<string>('-1')
+  // when set conversation id, we do not have set appId
+  const setCurrConversationId = (id: string, appId: string, isSetToLocalStroge = true, newConversationName = '') => {
+    doSetCurrConversationId(id)
+    if (isSetToLocalStroge && id !== '-1') {
+      // conversationIdInfo: {[appId1]: conversationId1, [appId2]: conversationId2}
+      const conversationIdInfo = globalThis.localStorage?.getItem(storageConversationIdKey) ? JSON.parse(globalThis.localStorage?.getItem(storageConversationIdKey) || '') : {}
+      conversationIdInfo[appId] = id
+      globalThis.localStorage?.setItem(storageConversationIdKey, JSON.stringify(conversationIdInfo))
+    }
+  }
+
+  const getConversationIdFromStorage = (appId: string) => {
+    const conversationIdInfo = globalThis.localStorage?.getItem(storageConversationIdKey) ? JSON.parse(globalThis.localStorage?.getItem(storageConversationIdKey) || '') : {}
+    const id = conversationIdInfo[appId]
+    return id
+  }
+
+  const isNewConversation = currConversationId === '-1'
+  // input can be updated by user
+  const [newConversationInputs, setNewConversationInputs] = useState<Record<string, any> | null>(null)
+  const resetNewConversationInputs = () => {
+    if (!newConversationInputs)
+      return
+    setNewConversationInputs(produce(newConversationInputs, (draft) => {
+      Object.keys(draft).forEach((key) => {
+        draft[key] = ''
+      })
+    }))
+  }
+  const [existConversationInputs, setExistConversationInputs] = useState<Record<string, any> | null>(null)
+  const currInputs = isNewConversation ? newConversationInputs : existConversationInputs
+  const setCurrInputs = isNewConversation ? setNewConversationInputs : setExistConversationInputs
+
+  // info is muted
+  const [newConversationInfo, setNewConversationInfo] = useState<ConversationInfoType | null>(null)
+  const [existConversationInfo, setExistConversationInfo] = useState<ConversationInfoType | null>(null)
+  const currConversationInfo = isNewConversation ? newConversationInfo : existConversationInfo
+
+  return {
+    conversationList,
+    setConversationList,
+    pinnedConversationList,
+    setPinnedConversationList,
+    currConversationId,
+    getCurrConversationId,
+    setCurrConversationId,
+    getConversationIdFromStorage,
+    isNewConversation,
+    currInputs,
+    newConversationInputs,
+    existConversationInputs,
+    resetNewConversationInputs,
+    setCurrInputs,
+    currConversationInfo,
+    setNewConversationInfo,
+    setExistConversationInfo,
+  }
+}
+
+export default useConversation

web/app/components/explore/universal-chat/index.tsx

+/* eslint-disable react-hooks/exhaustive-deps */
+/* eslint-disable @typescript-eslint/no-use-before-define */
+'use client'
+import type { FC } from 'react'
+import React, { useEffect, useRef, useState } from 'react'
+import cn from 'classnames'
+import { useTranslation } from 'react-i18next'
+import { useContext } from 'use-context-selector'
+import produce from 'immer'
+import { useBoolean, useGetState } from 'ahooks'
+import AppUnavailable from '../../base/app-unavailable'
+import useConversation from './hooks/use-conversation'
+import s from './style.module.css'
+import Init from './init'
+import { ToastContext } from '@/app/components/base/toast'
+import Sidebar from '@/app/components/share/chat/sidebar'
+import {
+  delConversation,
+  fetchAppParams,
+  fetchChatList,
+  fetchConversations,
+  fetchSuggestedQuestions,
+  pinConversation,
+  sendChatMessage,
+  stopChatMessageResponding,
+  unpinConversation,
+  updateFeedback,
+} from '@/service/universal-chat'
+import type { ConversationItem, SiteInfo } from '@/models/share'
+import type { PromptConfig, SuggestedQuestionsAfterAnswerConfig } from '@/models/debug'
+import type { Feedbacktype, IChatItem } from '@/app/components/app/chat/type'
+import Chat from '@/app/components/app/chat'
+import useBreakpoints, { MediaType } from '@/hooks/use-breakpoints'
+import Loading from '@/app/components/base/loading'
+import { replaceStringWithValues } from '@/app/components/app/configuration/prompt-value-panel'
+import { userInputsFormToPromptVariables } from '@/utils/model-config'
+import Confirm from '@/app/components/base/confirm'
+import type { DataSet } from '@/models/datasets'
+import ConfigSummary from '@/app/components/explore/universal-chat/config-view/summary'
+import { fetchDatasets } from '@/service/datasets'
+import ItemOperation from '@/app/components/explore/item-operation'
+
+const APP_ID = 'universal-chat'
+const DEFAULT_MODEL_ID = 'gpt-3.5-turbo' // gpt-4, claude-2
+const DEFAULT_PLUGIN = {
+  google_search: false,
+  web_reader: true,
+  wikipedia: true,
+}
+export type IMainProps = {}
+
+const Main: FC<IMainProps> = () => {
+  const { t } = useTranslation()
+  const media = useBreakpoints()
+  const isMobile = media === MediaType.mobile
+
+  /*
+  * app info
+  */
+  const [appUnavailable, setAppUnavailable] = useState<boolean>(false)
+  const [isUnknwonReason, setIsUnknwonReason] = useState<boolean>(false)
+  const siteInfo: SiteInfo = (
+    {
+      title: 'universal Chatbot',
+      icon: '',
+      icon_background: '',
+      description: '',
+      default_language: 'en', // TODO
+      prompt_public: true,
+    }
+  )
+  const [promptConfig, setPromptConfig] = useState<PromptConfig | null>(null)
+  const [inited, setInited] = useState<boolean>(false)
+  // in mobile, show sidebar by click button
+  const [isShowSidebar, { setTrue: showSidebar, setFalse: hideSidebar }] = useBoolean(false)
+  /*
+  * conversation info
+  */
+  const [allConversationList, setAllConversationList] = useState<ConversationItem[]>([])
+  const [isClearConversationList, { setTrue: clearConversationListTrue, setFalse: clearConversationListFalse }] = useBoolean(false)
+  const [isClearPinnedConversationList, { setTrue: clearPinnedConversationListTrue, setFalse: clearPinnedConversationListFalse }] = useBoolean(false)
+  const {
+    conversationList,
+    setConversationList,
+    pinnedConversationList,
+    setPinnedConversationList,
+    currConversationId,
+    getCurrConversationId,
+    setCurrConversationId,
+    getConversationIdFromStorage,
+    isNewConversation,
+    currConversationInfo,
+    currInputs,
+    newConversationInputs,
+    // existConversationInputs,
+    resetNewConversationInputs,
+    setCurrInputs,
+    setNewConversationInfo,
+    setExistConversationInfo,
+  } = useConversation()
+  const [hasMore, setHasMore] = useState<boolean>(true)
+  const [hasPinnedMore, setHasPinnedMore] = useState<boolean>(true)
+  const onMoreLoaded = ({ data: conversations, has_more }: any) => {
+    setHasMore(has_more)
+    if (isClearConversationList) {
+      setConversationList(conversations)
+      clearConversationListFalse()
+    }
+    else {
+      setConversationList([...conversationList, ...conversations])
+    }
+  }
+  const onPinnedMoreLoaded = ({ data: conversations, has_more }: any) => {
+    setHasPinnedMore(has_more)
+    if (isClearPinnedConversationList) {
+      setPinnedConversationList(conversations)
+      clearPinnedConversationListFalse()
+    }
+    else {
+      setPinnedConversationList([...pinnedConversationList, ...conversations])
+    }
+  }
+  const [controlUpdateConversationList, setControlUpdateConversationList] = useState(0)
+  const noticeUpdateList = () => {
+    setHasMore(true)
+    clearConversationListTrue()
+
+    setHasPinnedMore(true)
+    clearPinnedConversationListTrue()
+
+    setControlUpdateConversationList(Date.now())
+  }
+  const handlePin = async (id: string) => {
+    await pinConversation(id)
+    setControlItemOpHide(Date.now())
+    notify({ type: 'success', message: t('common.api.success') })
+    noticeUpdateList()
+  }
+
+  const handleUnpin = async (id: string) => {
+    await unpinConversation(id)
+    setControlItemOpHide(Date.now())
+    notify({ type: 'success', message: t('common.api.success') })
+    noticeUpdateList()
+  }
+  const [isShowConfirm, { setTrue: showConfirm, setFalse: hideConfirm }] = useBoolean(false)
+  const [toDeleteConversationId, setToDeleteConversationId] = useState('')
+  const handleDelete = (id: string) => {
+    setToDeleteConversationId(id)
+    hideSidebar() // mobile
+    showConfirm()
+  }
+
+  const didDelete = async () => {
+    await delConversation(toDeleteConversationId)
+    setControlItemOpHide(Date.now())
+    notify({ type: 'success', message: t('common.api.success') })
+    hideConfirm()
+    if (currConversationId === toDeleteConversationId)
+      handleConversationIdChange('-1')
+
+    noticeUpdateList()
+  }
+
+  const [suggestedQuestionsAfterAnswerConfig, setSuggestedQuestionsAfterAnswerConfig] = useState<SuggestedQuestionsAfterAnswerConfig | null>(null)
+  const [speechToTextConfig, setSpeechToTextConfig] = useState<SuggestedQuestionsAfterAnswerConfig | null>(null)
+
+  const [conversationIdChangeBecauseOfNew, setConversationIdChangeBecauseOfNew, getConversationIdChangeBecauseOfNew] = useGetState(false)
+
+  const conversationName = currConversationInfo?.name || t('share.chat.newChatDefaultName') as string
+  const conversationIntroduction = currConversationInfo?.introduction || ''
+
+  const handleConversationSwitch = async () => {
+    if (!inited)
+      return
+
+    // update inputs of current conversation
+    let notSyncToStateIntroduction = ''
+    let notSyncToStateInputs: Record<string, any> | undefined | null = {}
+    // debugger
+    if (!isNewConversation) {
+      const item = allConversationList.find(item => item.id === currConversationId) as any
+      notSyncToStateInputs = item?.inputs || {}
+      // setCurrInputs(notSyncToStateInputs)
+      notSyncToStateIntroduction = item?.introduction || ''
+      setExistConversationInfo({
+        name: item?.name || '',
+        introduction: notSyncToStateIntroduction,
+      })
+      const modelConfig = item?.model_config
+      if (modelConfig) {
+        setModeId(modelConfig.model_id)
+        const pluginConfig: Record<string, boolean> = {}
+        const datasetIds: string[] = []
+        modelConfig.agent_mode.tools.forEach((item: any) => {
+          const pluginName = Object.keys(item)[0]
+          if (pluginName === 'dataset')
+            datasetIds.push(item.dataset.id)
+          else
+            pluginConfig[pluginName] = item[pluginName].enabled
+        })
+        setPlugins(pluginConfig)
+        if (datasetIds.length > 0) {
+          const { data } = await fetchDatasets({ url: '/datasets', params: { page: 1, ids: datasetIds } })
+          setDateSets(data)
+        }
+        else {
+          setDateSets([])
+        }
+      }
+      else {
+        configSetDefaultValue()
+      }
+    }
+    else {
+      configSetDefaultValue()
+      notSyncToStateInputs = newConversationInputs
+      setCurrInputs(notSyncToStateInputs)
+    }
+
+    // update chat list of current conversation
+    if (!isNewConversation && !conversationIdChangeBecauseOfNew) {
+      fetchChatList(currConversationId).then((res: any) => {
+        const { data } = res
+        const newChatList: IChatItem[] = generateNewChatListWithOpenstatement(notSyncToStateIntroduction, notSyncToStateInputs)
+
+        data.forEach((item: any) => {
+          newChatList.push({
+            id: `question-${item.id}`,
+            content: item.query,
+            isAnswer: false,
+          })
+          newChatList.push({
+            ...item,
+            id: item.id,
+            content: item.answer,
+            feedback: item.feedback,
+            isAnswer: true,
+          })
+        })
+        setChatList(newChatList)
+        setErrorHappened(false)
+      })
+    }
+
+    if (isNewConversation) {
+      setChatList(generateNewChatListWithOpenstatement())
+      setErrorHappened(false)
+    }
+
+    setControlFocus(Date.now())
+  }
+
+  useEffect(() => {
+    handleConversationSwitch()
+  }, [currConversationId, inited])
+
+  const handleConversationIdChange = (id: string) => {
+    if (id === '-1') {
+      createNewChat()
+      setConversationIdChangeBecauseOfNew(true)
+    }
+    else {
+      setConversationIdChangeBecauseOfNew(false)
+    }
+    // trigger handleConversationSwitch
+    setCurrConversationId(id, APP_ID)
+    setIsShowSuggestion(false)
+    hideSidebar()
+  }
+
+  /*
+  * chat info. chat is under conversation.
+  */
+  const [chatList, setChatList, getChatList] = useGetState<IChatItem[]>([])
+  const chatListDomRef = useRef<HTMLDivElement>(null)
+  useEffect(() => {
+    // scroll to bottom
+    if (chatListDomRef.current)
+      chatListDomRef.current.scrollTop = chatListDomRef.current.scrollHeight
+  }, [chatList, currConversationId])
+
+  // user can not edit inputs if user had send message
+  const createNewChat = async () => {
+    // if new chat is already exist, do not create new chat
+    abortController?.abort()
+    setResponsingFalse()
+    if (conversationList.some(item => item.id === '-1'))
+      return
+
+    setConversationList(produce(conversationList, (draft) => {
+      draft.unshift({
+        id: '-1',
+        name: t('share.chat.newChatDefaultName'),
+        inputs: newConversationInputs,
+        introduction: conversationIntroduction,
+      })
+    }))
+    configSetDefaultValue()
+  }
+
+  // sometime introduction is not applied to state
+  const generateNewChatListWithOpenstatement = (introduction?: string, inputs?: Record<string, any> | null) => {
+    let caculatedIntroduction = introduction || conversationIntroduction || ''
+    const caculatedPromptVariables = inputs || currInputs || null
+    if (caculatedIntroduction && caculatedPromptVariables)
+      caculatedIntroduction = replaceStringWithValues(caculatedIntroduction, promptConfig?.prompt_variables || [], caculatedPromptVariables)
+
+    const openstatement = {
+      id: `${Date.now()}`,
+      content: caculatedIntroduction,
+      isAnswer: true,
+      feedbackDisabled: true,
+      isOpeningStatement: true,
+    }
+    if (caculatedIntroduction)
+      return [openstatement]
+
+    return []
+  }
+
+  const fetchAllConversations = () => {
+    return fetchConversations(undefined, undefined, 100)
+  }
+
+  const fetchInitData = async () => {
+    return Promise.all([fetchAllConversations(), fetchAppParams()])
+  }
+
+  // init
+  useEffect(() => {
+    (async () => {
+      try {
+        const [conversationData, appParams]: any = await fetchInitData()
+        const prompt_template = ''
+        // handle current conversation id
+        const { data: allConversations } = conversationData as { data: ConversationItem[]; has_more: boolean }
+        const _conversationId = getConversationIdFromStorage(APP_ID)
+        const isNotNewConversation = allConversations.some(item => item.id === _conversationId)
+        setAllConversationList(allConversations)
+        // fetch new conversation info
+        const { user_input_form, opening_statement: introduction, suggested_questions_after_answer, speech_to_text }: any = appParams
+        const prompt_variables = userInputsFormToPromptVariables(user_input_form)
+
+        setNewConversationInfo({
+          name: t('share.chat.newChatDefaultName'),
+          introduction,
+        })
+        setPromptConfig({
+          prompt_template,
+          prompt_variables,
+        } as PromptConfig)
+        setSuggestedQuestionsAfterAnswerConfig(suggested_questions_after_answer)
+        setSpeechToTextConfig(speech_to_text)
+
+        if (isNotNewConversation)
+          setCurrConversationId(_conversationId, APP_ID, false)
+
+        setInited(true)
+      }
+      catch (e: any) {
+        if (e.status === 404) {
+          setAppUnavailable(true)
+        }
+        else {
+          setIsUnknwonReason(true)
+          setAppUnavailable(true)
+        }
+      }
+    })()
+  }, [])
+
+  const [isResponsing, { setTrue: setResponsingTrue, setFalse: setResponsingFalse }] = useBoolean(false)
+  const [abortController, setAbortController] = useState<AbortController | null>(null)
+  const { notify } = useContext(ToastContext)
+  const logError = (message: string) => {
+    notify({ type: 'error', message })
+  }
+
+  const checkCanSend = () => {
+    if (currConversationId !== '-1')
+      return true
+
+    const prompt_variables = promptConfig?.prompt_variables
+    const inputs = currInputs
+    if (!inputs || !prompt_variables || prompt_variables?.length === 0)
+      return true
+
+    let hasEmptyInput = false
+    const requiredVars = prompt_variables?.filter(({ key, name, required }) => {
+      const res = (!key || !key.trim()) || (!name || !name.trim()) || (required || required === undefined || required === null)
+      return res
+    }) || [] // compatible with old version
+    requiredVars.forEach(({ key }) => {
+      if (hasEmptyInput)
+        return
+
+      if (!inputs?.[key])
+        hasEmptyInput = true
+    })
+
+    if (hasEmptyInput) {
+      logError(t('appDebug.errorMessage.valueOfVarRequired'))
+      return false
+    }
+    return !hasEmptyInput
+  }
+
+  const [controlFocus, setControlFocus] = useState(0)
+  const [isShowSuggestion, setIsShowSuggestion] = useState(false)
+  const doShowSuggestion = isShowSuggestion && !isResponsing
+  const [suggestQuestions, setSuggestQuestions] = useState<string[]>([])
+  const [messageTaskId, setMessageTaskId] = useState('')
+  const [hasStopResponded, setHasStopResponded, getHasStopResponded] = useGetState(false)
+  const [errorHappened, setErrorHappened] = useState(false)
+  const [isResponsingConIsCurrCon, setIsResponsingConCurrCon, getIsResponsingConIsCurrCon] = useGetState(true)
+  const handleSend = async (message: string) => {
+    if (isResponsing) {
+      notify({ type: 'info', message: t('appDebug.errorMessage.waitForResponse') })
+      return
+    }
+    const formattedPlugins = Object.keys(plugins).map(key => ({
+      [key]: {
+        enabled: plugins[key],
+      },
+    }))
+    const formattedDataSets = dataSets.map(({ id }) => {
+      return {
+        dataset: {
+          enabled: true,
+          id,
+        },
+      }
+    })
+    const data = {
+      query: message,
+      conversation_id: isNewConversation ? null : currConversationId,
+      model: modelId,
+      tools: [...formattedPlugins, ...formattedDataSets],
+    }
+
+    // qustion
+    const questionId = `question-${Date.now()}`
+    const questionItem = {
+      id: questionId,
+      content: message,
+      agent_thoughts: [],
+      isAnswer: false,
+    }
+
+    const placeholderAnswerId = `answer-placeholder-${Date.now()}`
+    const placeholderAnswerItem = {
+      id: placeholderAnswerId,
+      content: '',
+      isAnswer: true,
+    }
+
+    const newList = [...getChatList(), questionItem, placeholderAnswerItem]
+    setChatList(newList)
+
+    // answer
+    const responseItem: IChatItem = {
+      id: `${Date.now()}`,
+      content: '',
+      agent_thoughts: [],
+      isAnswer: true,
+    }
+
+    const prevTempNewConversationId = getCurrConversationId() || '-1'
+    let tempNewConversationId = prevTempNewConversationId
+
+    setHasStopResponded(false)
+    setResponsingTrue()
+    setErrorHappened(false)
+    setIsShowSuggestion(false)
+    setIsResponsingConCurrCon(true)
+
+    sendChatMessage(data, {
+      getAbortController: (abortController) => {
+        setAbortController(abortController)
+      },
+      onData: (message: string, isFirstMessage: boolean, { conversationId: newConversationId, messageId, taskId }: any) => {
+        responseItem.content = responseItem.content + message
+        responseItem.id = messageId
+        if (isFirstMessage && newConversationId)
+          tempNewConversationId = newConversationId
+
+        setMessageTaskId(taskId)
+        // has switched to other conversation
+        if (prevTempNewConversationId !== getCurrConversationId()) {
+          setIsResponsingConCurrCon(false)
+          return
+        }
+
+        // closesure new list is outdated.
+        const newListWithAnswer = produce(
+          getChatList().filter(item => item.id !== responseItem.id && item.id !== placeholderAnswerId),
+          (draft) => {
+            if (!draft.find(item => item.id === questionId))
+              draft.push({ ...questionItem } as any)
+
+            draft.push({ ...responseItem })
+          })
+
+        setChatList(newListWithAnswer)
+      },
+      async onCompleted(hasError?: boolean) {
+        if (hasError) {
+          setResponsingFalse()
+          return
+        }
+
+        if (getConversationIdChangeBecauseOfNew()) {
+          const { data: allConversations }: any = await fetchAllConversations()
+          setAllConversationList(allConversations)
+          noticeUpdateList()
+        }
+        setConversationIdChangeBecauseOfNew(false)
+        resetNewConversationInputs()
+        setCurrConversationId(tempNewConversationId, APP_ID, true)
+        if (getIsResponsingConIsCurrCon() && suggestedQuestionsAfterAnswerConfig?.enabled && !getHasStopResponded()) {
+          const { data }: any = await fetchSuggestedQuestions(responseItem.id)
+          setSuggestQuestions(data)
+          setIsShowSuggestion(true)
+        }
+        setResponsingFalse()
+      },
+      onThought(thought) {
+        // thought finished then start to return message. Warning: use push agent_thoughts.push would caused problem when the thought is more then 2
+        responseItem.id = thought.message_id;
+        (responseItem as any).agent_thoughts = [...(responseItem as any).agent_thoughts, thought] // .push(thought)
+        // has switched to other conversation
+
+        if (prevTempNewConversationId !== getCurrConversationId()) {
+          setIsResponsingConCurrCon(false)
+          return
+        }
+        const newListWithAnswer = produce(
+          getChatList().filter(item => item.id !== responseItem.id && item.id !== placeholderAnswerId),
+          (draft) => {
+            if (!draft.find(item => item.id === questionId))
+              draft.push({ ...questionItem })
+            draft.push({ ...responseItem })
+          })
+        setChatList(newListWithAnswer)
+      },
+      onError() {
+        setErrorHappened(true)
+        // role back placeholder answer
+        setChatList(produce(getChatList(), (draft) => {
+          draft.splice(draft.findIndex(item => item.id === placeholderAnswerId), 1)
+        }))
+        setResponsingFalse()
+      },
+    })
+  }
+
+  const handleFeedback = async (messageId: string, feedback: Feedbacktype) => {
+    await updateFeedback({ url: `/messages/${messageId}/feedbacks`, body: { rating: feedback.rating } })
+    const newChatList = chatList.map((item) => {
+      if (item.id === messageId) {
+        return {
+          ...item,
+          feedback,
+        }
+      }
+      return item
+    })
+    setChatList(newChatList)
+    notify({ type: 'success', message: t('common.api.success') })
+  }
+
+  const renderSidebar = () => {
+    if (!APP_ID || !promptConfig)
+      return null
+    return (
+      <Sidebar
+        list={conversationList}
+        isClearConversationList={isClearConversationList}
+        pinnedList={pinnedConversationList}
+        isClearPinnedConversationList={isClearPinnedConversationList}
+        onMoreLoaded={onMoreLoaded}
+        onPinnedMoreLoaded={onPinnedMoreLoaded}
+        isNoMore={!hasMore}
+        isPinnedNoMore={!hasPinnedMore}
+        onCurrentIdChange={handleConversationIdChange}
+        currentId={currConversationId}
+        copyRight={''}
+        isInstalledApp={false}
+        isUniversalChat
+        installedAppId={''}
+        siteInfo={siteInfo}
+        onPin={handlePin}
+        onUnpin={handleUnpin}
+        controlUpdateList={controlUpdateConversationList}
+        onDelete={handleDelete}
+      />
+    )
+  }
+
+  const [modelId, setModeId] = useState(DEFAULT_MODEL_ID)
+  // const currModel = MODEL_LIST.find(item => item.id === modelId)
+
+  const [plugins, setPlugins] = useState<Record<string, boolean>>(DEFAULT_PLUGIN)
+  const handlePluginsChange = (key: string, value: boolean) => {
+    setPlugins({
+      ...plugins,
+      [key]: value,
+    })
+  }
+  const [dataSets, setDateSets] = useState<DataSet[]>([])
+  const configSetDefaultValue = () => {
+    setModeId(DEFAULT_MODEL_ID)
+    setPlugins(DEFAULT_PLUGIN)
+    setDateSets([])
+  }
+  const isCurrConversationPinned = !!pinnedConversationList.find(item => item.id === currConversationId)
+  const [controlItemOpHide, setControlItemOpHide] = useState(0)
+  if (appUnavailable)
+    return <AppUnavailable isUnknwonReason={isUnknwonReason} />
+
+  if (!promptConfig)
+    return <Loading type='app' />
+
+  return (
+    <div className='bg-gray-100'>
+      <div
+        className={cn(
+          'flex rounded-t-2xl bg-white overflow-hidden rounded-b-2xl',
+        )}
+        style={{
+          boxShadow: '0px 12px 16px -4px rgba(16, 24, 40, 0.08), 0px 4px 6px -2px rgba(16, 24, 40, 0.03)',
+        }}
+      >
+        {/* sidebar */}
+        {!isMobile && renderSidebar()}
+        {isMobile && isShowSidebar && (
+          <div className='fixed inset-0 z-50'
+            style={{ backgroundColor: 'rgba(35, 56, 118, 0.2)' }}
+            onClick={hideSidebar}
+          >
+            <div className='inline-block' onClick={e => e.stopPropagation()}>
+              {renderSidebar()}
+            </div>
+          </div>
+        )}
+        {/* main */}
+        <div className={cn(
+          s.installedApp,
+          'flex-grow flex flex-col overflow-y-auto',
+        )
+        }>
+          {(!isNewConversation || isResponsing || errorHappened) && (
+            <div className='mb-5 antialiased font-sans shrink-0 relative mobile:min-h-[48px] tablet:min-h-[64px]'>
+              <div className='absolute z-10 top-0 left-0 right-0 flex items-center justify-between border-b border-gray-100 mobile:h-12 tablet:h-16 px-8 bg-white'>
+                <div className='text-gray-900'>{conversationName}</div>
+                <div className='flex items-center shrink-0 ml-2 space-x-2'>
+                  <ConfigSummary
+                    modelId={modelId}
+                    plugins={plugins}
+                    dataSets={dataSets}
+                  />
+                  <div className={cn('flex w-8 h-8 justify-center items-center shrink-0 rounded-lg border border-gray-200')} onClick={e => e.stopPropagation()}>
+                    <ItemOperation
+                      key={controlItemOpHide}
+                      className='!w-8 !h-8'
+                      isPinned={isCurrConversationPinned}
+                      togglePin={() => isCurrConversationPinned ? handleUnpin(currConversationId) : handlePin(currConversationId)}
+                      isShowDelete
+                      onDelete={() => handleDelete(currConversationId)}
+                    />
+                  </div>
+                </div>
+              </div>
+            </div>
+          )}
+          <div className={cn(doShowSuggestion ? 'pb-[140px]' : (isResponsing ? 'pb-[113px]' : 'pb-[76px]'), 'relative grow h-[200px] pc:w-[794px] max-w-full mobile:w-full mx-auto  mb-3.5 overflow-hidden')}>
+            <div className={cn('pc:w-[794px] max-w-full mobile:w-full mx-auto h-full overflow-y-auto')} ref={chatListDomRef}>
+              <Chat
+                isShowConfigElem={isNewConversation && chatList.length === 0}
+                configElem={<Init
+                  modelId={modelId}
+                  onModelChange={setModeId}
+                  plugins={plugins}
+                  onPluginChange={handlePluginsChange}
+                  dataSets={dataSets}
+                  onDataSetsChange={setDateSets}
+                />}
+                chatList={chatList}
+                onSend={handleSend}
+                isHideFeedbackEdit
+                onFeedback={handleFeedback}
+                isResponsing={isResponsing}
+                canStopResponsing={!!messageTaskId && isResponsingConIsCurrCon}
+                abortResponsing={async () => {
+                  await stopChatMessageResponding(messageTaskId)
+                  setHasStopResponded(true)
+                  setResponsingFalse()
+                }}
+                checkCanSend={checkCanSend}
+                controlFocus={controlFocus}
+                isShowSuggestion={doShowSuggestion}
+                suggestionList={suggestQuestions}
+                isShowSpeechToText={speechToTextConfig?.enabled}
+                dataSets={dataSets}
+              />
+            </div>
+          </div>
+
+          {isShowConfirm && (
+            <Confirm
+              title={t('share.chat.deleteConversation.title')}
+              content={t('share.chat.deleteConversation.content')}
+              isShow={isShowConfirm}
+              onClose={hideConfirm}
+              onConfirm={didDelete}
+              onCancel={hideConfirm}
+            />
+          )}
+        </div>
+      </div>
+    </div>
+  )
+}
+export default React.memo(Main)

web/app/components/explore/universal-chat/init/index.tsx

+'use client'
+import type { FC } from 'react'
+import React from 'react'
+import { useTranslation } from 'react-i18next'
+import cn from 'classnames'
+import type { IConfigProps } from '../config'
+import Config from '../config'
+import s from './style.module.css'
+
+const Line = (
+  <svg width="720" height="1" viewBox="0 0 720 1" fill="none" xmlns="http://www.w3.org/2000/svg">
+    <line y1="0.5" x2="720" y2="0.5" stroke="url(#paint0_linear_6845_53470)"/>
+    <defs>
+      <linearGradient id="paint0_linear_6845_53470" x1="0" y1="1" x2="720" y2="1" gradientUnits="userSpaceOnUse">
+        <stop stopColor="#F2F4F7" stopOpacity="0"/>
+        <stop offset="0.491667" stopColor="#F2F4F7"/>
+        <stop offset="1" stopColor="#F2F4F7" stopOpacity="0"/>
+      </linearGradient>
+    </defs>
+  </svg>
+)
+
+const Init: FC<IConfigProps> = ({
+  ...configProps
+}) => {
+  const { t } = useTranslation()
+
+  return (
+    <div className='h-full flex items-center'>
+      <div>
+        <div className='w-[480px] mx-auto text-center'>
+          <div className={cn(s.textGradient, 'mb-2 leading-[32px] font-semibold text-[24px]')}>{t('explore.universalChat.welcome')}</div>
+          <div className='mb-2 font-normal text-sm text-gray-500'>{t('explore.universalChat.welcomeDescribe')}</div>
+        </div>
+        <div className='flex mb-2 mx-auto h-8 items-center'>
+          {Line}
+        </div>
+        <Config className='w-[480px] mx-auto' {...configProps} />
+      </div>
+    </div>
+  )
+}
+export default React.memo(Init)

web/app/components/explore/universal-chat/init/style.module.css

+.textGradient {
+  background: linear-gradient(to right, rgba(16, 74, 225, 1) 0, rgba(0, 152, 238, 1) 100%);
+  -webkit-background-clip: text;
+  -webkit-text-fill-color: transparent;
+  background-clip: text;
+  text-fill-color: transparent;
+}
+
+

web/app/components/explore/universal-chat/style.module.css

+.installedApp {
+  height: calc(100vh - 74px);
+}
\ No newline at end of file

web/app/components/header/account-dropdown/workplace-selector/index.tsx

 import { Fragment } from 'react'
 import { useContext } from 'use-context-selector'
 import { useTranslation } from 'react-i18next'
-import { useRouter } from 'next/navigation'
 import { Menu, Transition } from '@headlessui/react'
 import cn from 'classnames'
 import s from './index.module.css'
@@ -26,7 +25,6 @@ const itemCheckClassName = `
 
 const WorkplaceSelector = () => {
   const { t } = useTranslation()
-  const router = useRouter()
   const { notify } = useContext(ToastContext)
   const { workspaces } = useWorkspacesContext()
   const currentWrokspace = workspaces.filter(item => item.current)?.[0]
@@ -35,7 +33,7 @@ const WorkplaceSelector = () => {
     try {
       await switchWorkspace({ url: '/workspaces/switch', body: { tenant_id } })
       notify({ type: 'success', message: t('common.actionMsg.modifiedSuccessfully') })
-      router.replace('/apps')
+      location.assign(`${location.origin}`)
     }
     catch (e) {
       notify({ type: 'error', message: t('common.provider.saveFailed') })

web/app/components/header/account-setting/index.tsx

@@ -9,11 +9,12 @@ import MembersPage from './members-page'
 import IntegrationsPage from './Integrations-page'
 import LanguagePage from './language-page'
 import ProviderPage from './provider-page'
+import PluginPage from './plugin-page'
 import DataSourcePage from './data-source-page'
 import s from './index.module.css'
 import Modal from '@/app/components/base/modal'
-import { Database03 } from '@/app/components/base/icons/src/vender/line/development'
-import { Database03 as Database03Solid } from '@/app/components/base/icons/src/vender/solid/development'
+import { Database03, PuzzlePiece01 } from '@/app/components/base/icons/src/vender/line/development'
+import { Database03 as Database03Solid, PuzzlePiece01 as PuzzlePiece01Solid } from '@/app/components/base/icons/src/vender/solid/development'
 
 const iconClassName = `
   w-4 h-4 ml-3 mr-2
@@ -80,6 +81,12 @@ export default function AccountSetting({
           icon: <Database03 className={iconClassName} />,
           activeIcon: <Database03Solid className={iconClassName} />,
         },
+        {
+          key: 'plugin',
+          name: t('common.settings.plugin'),
+          icon: <PuzzlePiece01 className={iconClassName} />,
+          activeIcon: <PuzzlePiece01Solid className={iconClassName} />,
+        },
       ],
     },
   ]
@@ -148,6 +155,7 @@ export default function AccountSetting({
             {activeMenu === 'language' && <LanguagePage />}
             {activeMenu === 'provider' && <ProviderPage />}
             {activeMenu === 'data-source' && <DataSourcePage />}
+            {activeMenu === 'plugin' && <PluginPage />}
           </div>
         </div>
       </div>

web/app/components/header/account-setting/key-validator/KeyInput.tsx

+import type { ChangeEvent } from 'react'
+import {
+  ValidatedErrorIcon,
+  ValidatedErrorMessage,
+  ValidatedSuccessIcon,
+  ValidatingTip,
+} from './ValidateStatus'
+import { ValidatedStatus } from './declarations'
+import type { ValidatedStatusState } from './declarations'
+
+type KeyInputProps = {
+  value?: string
+  name: string
+  placeholder: string
+  className?: string
+  onChange: (v: string) => void
+  onFocus?: () => void
+  validating: boolean
+  validatedStatusState: ValidatedStatusState
+}
+
+const KeyInput = ({
+  value,
+  name,
+  placeholder,
+  className,
+  onChange,
+  onFocus,
+  validating,
+  validatedStatusState,
+}: KeyInputProps) => {
+  const handleChange = (e: ChangeEvent<HTMLInputElement>) => {
+    const inputValue = e.target.value
+    onChange(inputValue)
+  }
+
+  const getValidatedIcon = () => {
+    if (validatedStatusState.status === ValidatedStatus.Error || validatedStatusState.status === ValidatedStatus.Exceed)
+      return <ValidatedErrorIcon />
+
+    if (validatedStatusState.status === ValidatedStatus.Success)
+      return <ValidatedSuccessIcon />
+  }
+  const getValidatedTip = () => {
+    if (validating)
+      return <ValidatingTip />
+
+    if (validatedStatusState.status === ValidatedStatus.Error)
+      return <ValidatedErrorMessage errorMessage={validatedStatusState.message ?? ''} />
+  }
+
+  return (
+    <div className={className}>
+      <div className="mb-2 text-[13px] font-medium text-gray-800">{name}</div>
+      <div className='
+        flex items-center px-3 bg-white rounded-lg
+        shadow-[0_1px_2px_rgba(16,24,40,0.05)]
+      '>
+        <input
+          className='
+            w-full py-[9px] mr-2
+            text-xs font-medium text-gray-700 leading-[18px]
+            appearance-none outline-none bg-transparent
+          '
+          value={value}
+          placeholder={placeholder}
+          onChange={handleChange}
+          onFocus={onFocus}
+        />
+        {getValidatedIcon()}
+      </div>
+      {getValidatedTip()}
+    </div>
+  )
+}
+
+export default KeyInput

web/app/components/header/account-setting/key-validator/Operate.tsx

+import { useTranslation } from 'react-i18next'
+import Indicator from '../../indicator'
+import type { Status } from './declarations'
+
+type OperateProps = {
+  isOpen: boolean
+  status: Status
+  onCancel: () => void
+  onSave: () => void
+  onAdd: () => void
+  onEdit: () => void
+}
+
+const Operate = ({
+  isOpen,
+  status,
+  onCancel,
+  onSave,
+  onAdd,
+  onEdit,
+}: OperateProps) => {
+  const { t } = useTranslation()
+
+  if (isOpen) {
+    return (
+      <div className='flex items-center'>
+        <div className='
+          flex items-center
+          mr-[5px] px-3 h-7 rounded-md cursor-pointer
+          text-xs font-medium text-gray-700
+        ' onClick={onCancel} >
+          {t('common.operation.cancel')}
+        </div>
+        <div className='
+          flex items-center
+          px-3 h-7 rounded-md cursor-pointer bg-primary-700
+          text-xs font-medium text-white
+        ' onClick={onSave}>
+          {t('common.operation.save')}
+        </div>
+      </div>
+    )
+  }
+
+  if (status === 'add') {
+    return (
+      <div className='
+        px-3 h-[28px] bg-white border border-gray-200 rounded-md cursor-pointer
+        text-xs font-medium text-gray-700 flex items-center
+      ' onClick={onAdd}>
+        {t('common.provider.addKey')}
+      </div>
+    )
+  }
+
+  if (status === 'fail' || status === 'success') {
+    return (
+      <div className='flex items-center'>
+        {
+          status === 'fail' && (
+            <div className='flex items-center mr-4'>
+              <div className='text-xs text-[#D92D20]'>{t('common.provider.invalidApiKey')}</div>
+              <Indicator color='red' className='ml-2' />
+            </div>
+          )
+        }
+        {
+          status === 'success' && (
+            <Indicator color='green' className='mr-4' />
+          )
+        }
+        <div className='
+          px-3 h-[28px] bg-white border border-gray-200 rounded-md cursor-pointer
+          text-xs font-medium text-gray-700 flex items-center
+        ' onClick={onEdit}>
+          {t('common.provider.editKey')}
+        </div>
+      </div>
+    )
+  }
+
+  return null
+}
+
+export default Operate

web/app/components/header/account-setting/key-validator/ValidateStatus.tsx

+import { useTranslation } from 'react-i18next'
+import { AlertCircle } from '@/app/components/base/icons/src/vender/solid/alertsAndFeedback'
+import { CheckCircle } from '@/app/components/base/icons/src/vender/solid/general'
+
+export const ValidatedErrorIcon = () => {
+  return <AlertCircle className='w-4 h-4 text-[#D92D20]' />
+}
+
+export const ValidatedSuccessIcon = () => {
+  return <CheckCircle className='w-4 h-4 text-[#039855]' />
+}
+
+export const ValidatingTip = () => {
+  const { t } = useTranslation()
+  return (
+    <div className={'mt-2 text-primary-600 text-xs font-normal'}>
+      {t('common.provider.validating')}
+    </div>
+  )
+}
+
+export const ValidatedErrorMessage = ({ errorMessage }: { errorMessage: string }) => {
+  const { t } = useTranslation()
+
+  return (
+    <div className={'mt-2 text-[#D92D20] text-xs font-normal'}>
+      {t('common.provider.validatedError')}{errorMessage}
+    </div>
+  )
+}

web/app/components/header/account-setting/key-validator/declarations.ts

+import type { Dispatch, SetStateAction } from 'react'
+
+export enum ValidatedStatus {
+  Success = 'success',
+  Error = 'error',
+  Exceed = 'exceed',
+}
+
+export type ValidatedStatusState = {
+  status?: ValidatedStatus
+  message?: string
+}
+
+export type Status = 'add' | 'fail' | 'success'
+
+export type ValidateValue = Record<string, string | undefined>
+
+export type ValidateCallback = {
+  before: (v?: ValidateValue) => boolean | undefined
+  run?: (v?: ValidateValue) => Promise<ValidatedStatusState>
+}
+
+export type Form = {
+  key: string
+  title: string
+  placeholder: string
+  value?: string
+  validate?: ValidateCallback
+  handleFocus?: (v: ValidateValue, dispatch: Dispatch<SetStateAction<ValidateValue>>) => void
+}
+
+export type KeyFrom = {
+  text: string
+  link: string
+}
+
+export type KeyValidatorProps = {
+  type: string
+  title: React.ReactNode
+  status: Status
+  forms: Form[]
+  keyFrom: KeyFrom
+}

web/app/components/header/account-setting/key-validator/hooks.ts

+import { useState } from 'react'
+import { useDebounceFn } from 'ahooks'
+import type { DebouncedFunc } from 'lodash-es'
+import { ValidatedStatus } from './declarations'
+import type { ValidateCallback, ValidateValue, ValidatedStatusState } from './declarations'
+
+export const useValidate: (value: ValidateValue) => [DebouncedFunc<(validateCallback: ValidateCallback) => Promise<void>>, boolean, ValidatedStatusState] = (value) => {
+  const [validating, setValidating] = useState(false)
+  const [validatedStatus, setValidatedStatus] = useState<ValidatedStatusState>({})
+
+  const { run } = useDebounceFn(async (validateCallback: ValidateCallback) => {
+    if (!validateCallback.before(value)) {
+      setValidating(false)
+      setValidatedStatus({})
+      return
+    }
+
+    setValidating(true)
+
+    if (validateCallback.run) {
+      const res = await validateCallback?.run(value)
+      setValidatedStatus(
+        res.status === 'success'
+          ? { status: ValidatedStatus.Success }
+          : { status: ValidatedStatus.Error, message: res.message })
+
+      setValidating(false)
+    }
+  }, { wait: 500 })
+
+  return [run, validating, validatedStatus]
+}

web/app/components/header/account-setting/key-validator/index.tsx

+import { useState } from 'react'
+import Operate from './Operate'
+import KeyInput from './KeyInput'
+import { useValidate } from './hooks'
+import type { Form, KeyFrom, Status, ValidateValue } from './declarations'
+import { useEventEmitterContextContext } from '@/context/event-emitter'
+import { LinkExternal02 } from '@/app/components/base/icons/src/vender/line/general'
+
+export type KeyValidatorProps = {
+  type: string
+  title: React.ReactNode
+  status: Status
+  forms: Form[]
+  keyFrom: KeyFrom
+  onSave: (v: ValidateValue) => Promise<boolean | undefined>
+}
+
+const KeyValidator = ({
+  type,
+  title,
+  status,
+  forms,
+  keyFrom,
+  onSave,
+}: KeyValidatorProps) => {
+  const triggerKey = `plugins/${type}`
+  const { eventEmitter } = useEventEmitterContextContext()
+  const [isOpen, setIsOpen] = useState(false)
+  const prevValue = forms.reduce((prev: ValidateValue, next: Form) => {
+    prev[next.key] = next.value
+    return prev
+  }, {})
+  const [value, setValue] = useState(prevValue)
+  const [validate, validating, validatedStatusState] = useValidate(value)
+
+  eventEmitter?.useSubscription((v) => {
+    if (v !== triggerKey) {
+      setIsOpen(false)
+      setValue(prevValue)
+      validate({ before: () => false })
+    }
+  })
+
+  const handleCancel = () => {
+    eventEmitter?.emit('')
+  }
+
+  const handleSave = async () => {
+    if (await onSave(value))
+      eventEmitter?.emit('')
+  }
+
+  const handleAdd = () => {
+    setIsOpen(true)
+    eventEmitter?.emit(triggerKey)
+  }
+
+  const handleEdit = () => {
+    setIsOpen(true)
+    eventEmitter?.emit(triggerKey)
+  }
+
+  const handleChange = (form: Form, val: string) => {
+    setValue({ ...value, [form.key]: val })
+
+    if (form.validate)
+      validate(form.validate)
+  }
+
+  const handleFocus = (form: Form) => {
+    if (form.handleFocus)
+      form.handleFocus(value, setValue)
+  }
+
+  return (
+    <div className='mb-2 border-[0.5px] border-gray-200 bg-gray-50 rounded-md'>
+      <div className={
+        `flex items-center justify-between px-4 h-[52px] cursor-pointer ${isOpen && 'border-b-[0.5px] border-b-gray-200'}`
+      }>
+        {title}
+        <Operate
+          isOpen={isOpen}
+          status={status}
+          onCancel={handleCancel}
+          onSave={handleSave}
+          onAdd={handleAdd}
+          onEdit={handleEdit}
+        />
+      </div>
+      {
+        isOpen && (
+          <div className='px-4 py-3'>
+            {
+              forms.map(form => (
+                <KeyInput
+                  key={form.key}
+                  className='mb-4'
+                  name={form.title}
+                  placeholder={form.placeholder}
+                  value={value[form.key] || ''}
+                  onChange={v => handleChange(form, v)}
+                  onFocus={() => handleFocus(form)}
+                  validating={validating}
+                  validatedStatusState={validatedStatusState}
+                />
+              ))
+            }
+            <a className="flex items-center text-xs cursor-pointer text-primary-600" href={keyFrom.link} target={'_blank'}>
+              {keyFrom.text}
+              <LinkExternal02 className='w-3 h-3 ml-1 text-primary-600' />
+            </a>
+          </div>
+        )
+      }
+    </div>
+  )
+}
+
+export default KeyValidator

web/app/components/header/account-setting/plugin-page/SerpapiPlugin.tsx

+import { useTranslation } from 'react-i18next'
+import Image from 'next/image'
+import SerpapiLogo from '../../assets/serpapi.png'
+import KeyValidator from '../key-validator'
+import type { Form, ValidateValue } from '../key-validator/declarations'
+import { updatePluginKey, validatePluginKey } from './utils'
+import { useToastContext } from '@/app/components/base/toast'
+import type { PluginProvider } from '@/models/common'
+
+type SerpapiPluginProps = {
+  plugin: PluginProvider
+  onUpdate: () => void
+}
+const SerpapiPlugin = ({
+  plugin,
+  onUpdate,
+}: SerpapiPluginProps) => {
+  const { t } = useTranslation()
+  const { notify } = useToastContext()
+
+  const forms: Form[] = [{
+    key: 'api_key',
+    title: t('common.plugin.serpapi.apiKey'),
+    placeholder: t('common.plugin.serpapi.apiKeyPlaceholder'),
+    value: plugin.credentials?.api_key,
+    validate: {
+      before: (v) => {
+        if (v?.api_key)
+          return true
+      },
+      run: async (v) => {
+        return validatePluginKey('serpapi', {
+          credentials: {
+            api_key: v?.api_key,
+          },
+        })
+      },
+    },
+    handleFocus: (v, dispatch) => {
+      if (v.api_key === plugin.credentials?.api_key)
+        dispatch({ ...v, api_key: '' })
+    },
+  }]
+
+  const handleSave = async (v: ValidateValue) => {
+    if (!v?.api_key || v?.api_key === plugin.credentials?.api_key)
+      return
+
+    const res = await updatePluginKey('serpapi', {
+      credentials: {
+        api_key: v?.api_key,
+      },
+    })
+
+    if (res.status === 'success') {
+      notify({ type: 'success', message: t('common.actionMsg.modifiedSuccessfully') })
+      onUpdate()
+      return true
+    }
+  }
+
+  return (
+    <KeyValidator
+      type='serpapi'
+      title={<Image alt='serpapi logo' src={SerpapiLogo} width={64} />}
+      status={plugin.credentials?.api_key ? 'success' : 'add'}
+      forms={forms}
+      keyFrom={{
+        text: t('common.plugin.serpapi.keyFrom'),
+        link: 'https://serpapi.com/manage-api-key',
+      }}
+      onSave={handleSave}
+    />
+  )
+}
+
+export default SerpapiPlugin

web/app/components/header/account-setting/plugin-page/index.tsx

+import useSWR from 'swr'
+import { LockClosedIcon } from '@heroicons/react/24/solid'
+import { useTranslation } from 'react-i18next'
+import Link from 'next/link'
+import SerpapiPlugin from './SerpapiPlugin'
+import { fetchPluginProviders } from '@/service/common'
+import type { PluginProvider } from '@/models/common'
+
+const PluginPage = () => {
+  const { t } = useTranslation()
+  const { data: plugins, mutate } = useSWR('/workspaces/current/tool-providers', fetchPluginProviders)
+
+  const Plugin_MAP: Record<string, any> = {
+    serpapi: (plugin: PluginProvider) => <SerpapiPlugin key='serpapi' plugin={plugin} onUpdate={() => mutate()} />,
+  }
+
+  return (
+    <div className='pb-7'>
+      <div>
+        {plugins?.map(plugin => Plugin_MAP[plugin.tool_name](plugin))}
+      </div>
+      <div className='fixed bottom-0 w-[472px] h-[42px] flex items-center bg-white text-xs text-gray-500'>
+        <LockClosedIcon className='w-3 h-3 mr-1' />
+        {t('common.provider.encrypted.front')}
+        <Link
+          className='text-primary-600 mx-1'
+          target={'_blank'}
+          href='https://pycryptodome.readthedocs.io/en/latest/src/cipher/oaep.html'
+        >
+          PKCS1_OAEP
+        </Link>
+        {t('common.provider.encrypted.back')}
+      </div>
+    </div>
+  )
+}
+
+export default PluginPage

web/app/components/header/account-setting/plugin-page/utils.ts

+import { ValidatedStatus } from '../key-validator/declarations'
+import { updatePluginProviderAIKey, validatePluginProviderKey } from '@/service/common'
+
+export const validatePluginKey = async (pluginType: string, body: any) => {
+  try {
+    const res = await validatePluginProviderKey({
+      url: `/workspaces/current/tool-providers/${pluginType}/credentials-validate`,
+      body,
+    })
+    if (res.result === 'success')
+      return Promise.resolve({ status: ValidatedStatus.Success })
+    else
+      return Promise.resolve({ status: ValidatedStatus.Error, message: res.error })
+  }
+  catch (e: any) {
+    return Promise.resolve({ status: ValidatedStatus.Error, message: e.message })
+  }
+}
+
+export const updatePluginKey = async (pluginType: string, body: any) => {
+  try {
+    const res = await updatePluginProviderAIKey({
+      url: `/workspaces/current/tool-providers/${pluginType}/credentials`,
+      body,
+    })
+    if (res.result === 'success')
+      return Promise.resolve({ status: ValidatedStatus.Success })
+    else
+      return Promise.resolve({ status: ValidatedStatus.Error, message: res.error })
+  }
+  catch (e: any) {
+    return Promise.resolve({ status: ValidatedStatus.Error, message: e.message })
+  }
+}

web/app/components/share/chat/hooks/use-conversation.ts

 import { useState } from 'react'
 import produce from 'immer'
+import { useGetState } from 'ahooks'
 import type { ConversationItem } from '@/models/share'
 
 const storageConversationIdKey = 'conversationIdInfo'
@@ -8,7 +9,7 @@ type ConversationInfoType = Omit<ConversationItem, 'inputs' | 'id'>
 function useConversation() {
   const [conversationList, setConversationList] = useState<ConversationItem[]>([])
   const [pinnedConversationList, setPinnedConversationList] = useState<ConversationItem[]>([])
-  const [currConversationId, doSetCurrConversationId] = useState<string>('-1')
+  const [currConversationId, doSetCurrConversationId, getCurrConversationId] = useGetState<string>('-1')
   // when set conversation id, we do not have set appId
   const setCurrConversationId = (id: string, appId: string, isSetToLocalStroge = true, newConversationName = '') => {
     doSetCurrConversationId(id)
@@ -53,6 +54,7 @@ function useConversation() {
     pinnedConversationList,
     setPinnedConversationList,
     currConversationId,
+    getCurrConversationId,
     setCurrConversationId,
     getConversationIdFromStorage,
     isNewConversation,

web/app/components/share/chat/index.tsx

@@ -43,6 +43,8 @@ import Confirm from '@/app/components/base/confirm'
 export type IMainProps = {
   isInstalledApp?: boolean
   installedAppInfo?: InstalledApp
+  isSupportPlugin?: boolean
+  isUniversalChat?: boolean
 }
 
 const Main: FC<IMainProps> = ({
@@ -88,6 +90,7 @@ const Main: FC<IMainProps> = ({
     pinnedConversationList,
     setPinnedConversationList,
     currConversationId,
+    getCurrConversationId,
     setCurrConversationId,
     getConversationIdFromStorage,
     isNewConversation,
@@ -212,7 +215,7 @@ const Main: FC<IMainProps> = ({
     }
 
     // update chat list of current conversation
-    if (!isNewConversation && !conversationIdChangeBecauseOfNew && !isResponsing) {
+    if (!isNewConversation && !conversationIdChangeBecauseOfNew) {
       fetchChatList(currConversationId, isInstalledApp, installedAppInfo?.id).then((res: any) => {
         const { data } = res
         const newChatList: IChatItem[] = generateNewChatListWithOpenstatement(notSyncToStateIntroduction, notSyncToStateInputs)
@@ -421,6 +424,7 @@ const Main: FC<IMainProps> = ({
   const [suggestQuestions, setSuggestQuestions] = useState<string[]>([])
   const [messageTaskId, setMessageTaskId] = useState('')
   const [hasStopResponded, setHasStopResponded, getHasStopResponded] = useGetState(false)
+  const [isResponsingConIsCurrCon, setIsResponsingConCurrCon, getIsResponsingConIsCurrCon] = useGetState(true)
 
   const handleSend = async (message: string) => {
     if (isResponsing) {
@@ -457,12 +461,13 @@ const Main: FC<IMainProps> = ({
       content: '',
       isAnswer: true,
     }
-
-    let tempNewConversationId = ''
+    const prevTempNewConversationId = getCurrConversationId() || '-1'
+    let tempNewConversationId = prevTempNewConversationId
 
     setHasStopResponded(false)
     setResponsingTrue()
     setIsShowSuggestion(false)
+    setIsResponsingConCurrCon(true)
     sendChatMessage(data, {
       getAbortController: (abortController) => {
         setAbortController(abortController)
@@ -474,6 +479,11 @@ const Main: FC<IMainProps> = ({
           tempNewConversationId = newConversationId
 
         setMessageTaskId(taskId)
+        // has switched to other conversation
+        if (prevTempNewConversationId !== getCurrConversationId()) {
+          setIsResponsingConCurrCon(false)
+          return
+        }
         // closesure new list is outdated.
         const newListWithAnswer = produce(
           getChatList().filter(item => item.id !== responseItem.id && item.id !== placeholderAnswerId),
@@ -499,7 +509,7 @@ const Main: FC<IMainProps> = ({
         resetNewConversationInputs()
         setChatNotStarted()
         setCurrConversationId(tempNewConversationId, appId, true)
-        if (suggestedQuestionsAfterAnswerConfig?.enabled && !getHasStopResponded()) {
+        if (getIsResponsingConIsCurrCon() && suggestedQuestionsAfterAnswerConfig?.enabled && !getHasStopResponded()) {
           const { data }: any = await fetchSuggestedQuestions(responseItem.id, isInstalledApp, installedAppInfo?.id)
           setSuggestQuestions(data)
           setIsShowSuggestion(true)
@@ -628,7 +638,7 @@ const Main: FC<IMainProps> = ({
                     isHideFeedbackEdit
                     onFeedback={handleFeedback}
                     isResponsing={isResponsing}
-                    canStopResponsing={!!messageTaskId}
+                    canStopResponsing={!!messageTaskId && isResponsingConIsCurrCon}
                     abortResponsing={async () => {
                       await stopChatMessageResponding(appId, messageTaskId, isInstalledApp, installedAppInfo?.id)
                       setHasStopResponded(true)

web/app/components/share/chat/sidebar/index.tsx

@@ -11,6 +11,7 @@ import AppInfo from '@/app/components/share/chat/sidebar/app-info'
 // import Card from './card'
 import type { ConversationItem, SiteInfo } from '@/models/share'
 import { fetchConversations } from '@/service/share'
+import { fetchConversations as fetchUniversalConversations } from '@/service/universal-chat'
 
 export type ISidebarProps = {
   copyRight: string
@@ -22,6 +23,7 @@ export type ISidebarProps = {
   isClearPinnedConversationList: boolean
   isInstalledApp: boolean
   installedAppId?: string
+  isUniversalChat?: boolean
   siteInfo: SiteInfo
   onMoreLoaded: (res: { data: ConversationItem[]; has_more: boolean }) => void
   onPinnedMoreLoaded: (res: { data: ConversationItem[]; has_more: boolean }) => void
@@ -43,6 +45,7 @@ const Sidebar: FC<ISidebarProps> = ({
   isClearPinnedConversationList,
   isInstalledApp,
   installedAppId,
+  isUniversalChat,
   siteInfo,
   onMoreLoaded,
   onPinnedMoreLoaded,
@@ -57,8 +60,14 @@ const Sidebar: FC<ISidebarProps> = ({
   const [hasPinned, setHasPinned] = useState(false)
 
   const checkHasPinned = async () => {
-    const { data }: any = await fetchConversations(isInstalledApp, installedAppId, undefined, true)
-    setHasPinned(data.length > 0)
+    let res: any
+    if (isUniversalChat)
+      res = await fetchUniversalConversations(undefined, true)
+
+    else
+      res = await fetchConversations(isInstalledApp, installedAppId, undefined, true)
+
+    setHasPinned(res.data.length > 0)
   }
 
   useEffect(() => {
@@ -70,13 +79,13 @@ const Sidebar: FC<ISidebarProps> = ({
       checkHasPinned()
   }, [controlUpdateList])
 
-  const maxListHeight = isInstalledApp ? 'max-h-[30vh]' : 'max-h-[40vh]'
+  const maxListHeight = (isInstalledApp || isUniversalChat) ? 'max-h-[30vh]' : 'max-h-[40vh]'
 
   return (
     <div
       className={
         cn(
-          isInstalledApp ? 'tablet:h-[calc(100vh_-_74px)]' : 'tablet:h-[calc(100vh_-_3rem)]',
+          (isInstalledApp || isUniversalChat) ? 'tablet:h-[calc(100vh_-_74px)]' : 'tablet:h-[calc(100vh_-_3rem)]',
           'shrink-0 flex flex-col bg-white pc:w-[244px] tablet:w-[192px] mobile:w-[240px]  border-r border-gray-200 mobile:h-screen',
         )
       }
@@ -109,6 +118,7 @@ const Sidebar: FC<ISidebarProps> = ({
               isClearConversationList={isClearPinnedConversationList}
               isInstalledApp={isInstalledApp}
               installedAppId={installedAppId}
+              isUniversalChat={isUniversalChat}
               onMoreLoaded={onPinnedMoreLoaded}
               isNoMore={isPinnedNoMore}
               isPinned={true}
@@ -119,18 +129,19 @@ const Sidebar: FC<ISidebarProps> = ({
           </div>
         )}
         {/* unpinned list */}
-        <div className={cn('mt-4 px-4', !hasPinned && 'flex flex-col flex-grow')}>
+        <div className={cn('grow flex flex-col mt-4 px-4', !hasPinned && 'flex flex-col flex-grow')}>
           {(hasPinned && list.length > 0) && (
             <div className='mb-1.5 leading-[18px] text-xs text-gray-500 font-medium uppercase'>{t('share.chat.unpinnedTitle')}</div>
           )}
           <List
-            className={cn(hasPinned ? maxListHeight : 'flex-grow')}
+            className={cn('flex-grow h-0')}
             currentId={currentId}
             onCurrentIdChange={onCurrentIdChange}
             list={list}
             isClearConversationList={isClearConversationList}
             isInstalledApp={isInstalledApp}
             installedAppId={installedAppId}
+            isUniversalChat={isUniversalChat}
             onMoreLoaded={onMoreLoaded}
             isNoMore={isNoMore}
             isPinned={false}
@@ -141,9 +152,11 @@ const Sidebar: FC<ISidebarProps> = ({
         </div>
 
       </div>
+      {!isUniversalChat && (
         <div className="flex flex-shrink-0 pr-4 pb-4 pl-4">
           <div className="text-gray-400 font-normal text-xs">© {copyRight} {(new Date()).getFullYear()}</div>
         </div>
+      )}
     </div>
   )
 }

web/app/components/share/chat/sidebar/list/index.tsx

@@ -10,6 +10,7 @@ import cn from 'classnames'
 import s from './style.module.css'
 import type { ConversationItem } from '@/models/share'
 import { fetchConversations } from '@/service/share'
+import { fetchConversations as fetchUniversalConversations } from '@/service/universal-chat'
 import ItemOperation from '@/app/components/explore/item-operation'
 
 export type IListProps = {
@@ -19,6 +20,7 @@ export type IListProps = {
   list: ConversationItem[]
   isClearConversationList: boolean
   isInstalledApp: boolean
+  isUniversalChat?: boolean
   installedAppId?: string
   onMoreLoaded: (res: { data: ConversationItem[]; has_more: boolean }) => void
   isNoMore: boolean
@@ -35,6 +37,7 @@ const List: FC<IListProps> = ({
   list,
   isClearConversationList,
   isInstalledApp,
+  isUniversalChat,
   installedAppId,
   onMoreLoaded,
   isNoMore,
@@ -51,8 +54,12 @@ const List: FC<IListProps> = ({
         let lastId = !isClearConversationList ? list[list.length - 1]?.id : undefined
         if (lastId === '-1')
           lastId = undefined
-
-        const { data: conversations, has_more }: any = await fetchConversations(isInstalledApp, installedAppId, lastId, isPinned)
+        let res: any
+        if (isUniversalChat)
+          res = await fetchUniversalConversations(lastId, isPinned)
+        else
+          res = await fetchConversations(isInstalledApp, installedAppId, lastId, isPinned)
+        const { data: conversations, has_more }: any = res
         onMoreLoaded({ data: conversations, has_more })
       }
       return { list: [] }
@@ -68,7 +75,7 @@ const List: FC<IListProps> = ({
   return (
     <nav
       ref={listRef}
-      className={cn(className, 'shrink-0 space-y-1 bg-white pb-[85px] overflow-y-auto')}
+      className={cn(className, 'shrink-0 space-y-1 bg-white overflow-y-auto overflow-x-hidden')}
     >
       {list.map((item) => {
         const isCurrent = item.id === currentId

web/app/components/share/chat/welcome/index.tsx

@@ -25,7 +25,7 @@ export type IWelcomeProps = {
   canEidtInpus: boolean
   savedInputs: Record<string, any>
   onInputsChange: (inputs: Record<string, any>) => void
-  plan: string
+  plan?: string
 }
 
 const Welcome: FC<IWelcomeProps> = ({

web/app/components/share/chatbot/sidebar/list/index.tsx

@@ -65,7 +65,7 @@ const List: FC<IListProps> = ({
   return (
     <nav
       ref={listRef}
-      className={cn(className, 'shrink-0 space-y-1 bg-white pb-[85px] overflow-y-auto')}
+      className={cn(className, 'shrink-0 space-y-1 bg-white overflow-y-auto')}
     >
       {list.map((item) => {
         const isCurrent = item.id === currentId

web/app/styles/markdown.scss

@@ -109,7 +109,7 @@
 
 .markdown-body a {
   background-color: transparent;
-  color: var(--color-accent-fg);
+  color: #155EEF;
   text-decoration: none;
 }
 

web/config/index.ts

 /* eslint-disable import/no-mutable-exports */
+import { AppType, ProviderType } from '@/types/app'
+
 const isDevelopment = process.env.NODE_ENV === 'development'
 
 export let apiPrefix = ''
@@ -37,6 +39,21 @@ export const PUBLIC_API_PREFIX: string = publicApiPrefix
 const EDITION = process.env.NEXT_PUBLIC_EDITION || globalThis.document?.body?.getAttribute('data-public-edition')
 export const IS_CE_EDITION = EDITION === 'SELF_HOSTED'
 
+export const MODEL_LIST = [
+  { id: 'gpt-3.5-turbo', name: 'gpt-3.5-turbo', type: AppType.chat },
+  { id: 'gpt-3.5-turbo-16k', name: 'gpt-3.5-turbo-16k', type: AppType.chat },
+  { id: 'gpt-4', name: 'gpt-4', type: AppType.chat }, // 8k version
+  { id: 'claude-instant-1', name: 'claude-instant-1', type: AppType.chat, provider: ProviderType.anthropic }, // set 30k
+  { id: 'claude-2', name: 'claude-2', type: AppType.chat, provider: ProviderType.anthropic }, // set 30k
+  { id: 'gpt-3.5-turbo', name: 'gpt-3.5-turbo', type: AppType.completion },
+  { id: 'gpt-3.5-turbo-16k', name: 'gpt-3.5-turbo-16k', type: AppType.completion },
+  { id: 'text-davinci-003', name: 'text-davinci-003', type: AppType.completion },
+  { id: 'gpt-4', name: 'gpt-4', type: AppType.completion }, // 8k version
+  { id: 'claude-instant-1', name: 'claude-instant-1', type: AppType.completion, provider: ProviderType.anthropic }, // set 30k
+  { id: 'claude-2', name: 'claude-2', type: AppType.completion, provider: ProviderType.anthropic }, // set 30k
+]
+const UNIVERSAL_CHAT_MODEL_ID_LIST = ['gpt-3.5-turbo', 'gpt-3.5-turbo-16k', 'gpt-4', 'claude-2']
+export const UNIVERSAL_CHAT_MODEL_LIST = MODEL_LIST.filter(({ id, type }) => UNIVERSAL_CHAT_MODEL_ID_LIST.includes(id) && (type === AppType.chat))
 export const TONE_LIST = [
   {
     id: 1,

web/context/event-emitter.tsx

+'use client'
+
+import { createContext, useContext } from 'use-context-selector'
+import { useEventEmitter } from 'ahooks'
+import type { EventEmitter } from 'ahooks/lib/useEventEmitter'
+
+const EventEmitterContext = createContext<{ eventEmitter: EventEmitter<string> | null }>({
+  eventEmitter: null,
+})
+
+export const useEventEmitterContextContext = () => useContext(EventEmitterContext)
+
+type EventEmitterContextProviderProps = {
+  children: React.ReactNode
+}
+export const EventEmitterContextProvider = ({
+  children,
+}: EventEmitterContextProviderProps) => {
+  const eventEmitter = useEventEmitter<string>()
+
+  return (
+    <EventEmitterContext.Provider value={{ eventEmitter }}>
+      {children}
+    </EventEmitterContext.Provider>
+  )
+}
+
+export default EventEmitterContext

web/context/provider-context.tsx

+'use client'
+
+import { createContext, useContext } from 'use-context-selector'
+import useSWR from 'swr'
+import { fetchTenantInfo } from '@/service/common'
+
+const ProviderContext = createContext<{ currentProvider: {
+  provider: string
+  provider_name: string
+  token_is_set: boolean
+  is_valid: boolean
+  token_is_valid: boolean
+} | null | undefined }>({
+  currentProvider: null,
+})
+
+export const useProviderContext = () => useContext(ProviderContext)
+
+type ProviderContextProviderProps = {
+  children: React.ReactNode
+}
+export const ProviderContextProvider = ({
+  children,
+}: ProviderContextProviderProps) => {
+  const { data: userInfo } = useSWR({ url: '/info' }, fetchTenantInfo)
+  const currentProvider = userInfo?.providers?.find(({ token_is_set, is_valid }) => token_is_set && is_valid)
+
+  return (
+    <ProviderContext.Provider value={{ currentProvider }}>
+      {children}
+    </ProviderContext.Provider>
+  )
+}
+
+export default ProviderContext

web/i18n/lang/common.en.ts

@@ -91,6 +91,7 @@ const translation = {
     language: 'Language',
     provider: 'Model Provider',
     dataSource: 'Data Source',
+    plugin: 'Plugins',
   },
   account: {
     avatar: 'Avatar',
@@ -224,6 +225,13 @@ const translation = {
       },
     },
   },
+  plugin: {
+    serpapi: {
+      apiKey: 'API Key',
+      apiKeyPlaceholder: 'Enter your API key',
+      keyFrom: 'Get your SerpAPI key from SerpAPI Account Page',
+    },
+  },
   about: {
     changeLog: 'Changlog',
     updateNow: 'Update now',

web/i18n/lang/common.zh.ts

@@ -91,6 +91,7 @@ const translation = {
     language: '语言',
     provider: '模型供应商',
     dataSource: '数据来源',
+    plugin: '插件',
   },
   account: {
     avatar: '头像',
@@ -224,6 +225,13 @@ const translation = {
       },
     },
   },
+  plugin: {
+    serpapi: {
+      apiKey: 'API Key',
+      apiKeyPlaceholder: '输入你的 API 密钥',
+      keyFrom: '从 SerpAPI 帐户页面获取您的 SerpAPI 密钥',
+    },
+  },
   about: {
     changeLog: '更新日志',
     updateNow: '现在更新',

web/i18n/lang/explore.en.ts

@@ -2,6 +2,7 @@ const translation = {
   title: 'My Apps',
   sidebar: {
     discovery: 'Discovery',
+    chat: 'Chat',
     workspace: 'Workspace',
     action: {
       pin: 'Pin',
@@ -34,6 +35,43 @@ const translation = {
     Programming: 'Programming',
     HR: 'HR',
   },
+  universalChat: {
+    welcome: 'Start chat with Dify',
+    welcomeDescribe: 'Your AI conversation companion for personalized assistance',
+    model: 'Model',
+    plugins: {
+      name: 'Plugins',
+      google_search: {
+        name: 'Google Search',
+        more: {
+          left: 'Enable the plugin, ',
+          link: 'set up your SerpAPI key',
+          right: ' first.',
+        },
+      },
+      web_reader: {
+        name: 'Web Reader',
+        description: 'Get needed information from any web link',
+      },
+      wikipedia: {
+        name: 'Wikipedia',
+      },
+    },
+    thought: {
+      show: 'Show',
+      hide: 'Hide',
+      processOfThought: ' the process of thinking',
+      res: {
+        webReader: {
+          normal: 'Reading {url}',
+          hasPageInfo: 'Reading next page of {url}',
+        },
+        search: 'Searching {{query}}',
+        dataset: 'Retrieving dataset {datasetName}',
+      },
+    },
+    viewConfigDetailTip: 'In conversation, cannot change above settings',
+  },
 }
 
 export default translation

web/i18n/lang/explore.zh.ts

@@ -2,6 +2,7 @@ const translation = {
   title: '我的应用',
   sidebar: {
     discovery: '发现',
+    chat: '智聊',
     workspace: '工作区',
     action: {
       pin: '置顶',
@@ -34,6 +35,43 @@ const translation = {
     Programming: '编程',
     HR: '人力资源',
   },
+  universalChat: {
+    welcome: '开始和 Dify 聊天吧',
+    welcomeDescribe: '您的 AI 对话伴侣，为您提供个性化的帮助',
+    model: '模型',
+    plugins: {
+      name: '插件',
+      google_search: {
+        name: '谷歌搜索',
+        more: {
+          left: '启用插件，首先',
+          link: '设置您的 SerpAPI 密钥',
+          right: '',
+        },
+      },
+      web_reader: {
+        name: '解析链接',
+        description: '从任何网页链接获取所需信息',
+      },
+      wikipedia: {
+        name: '维基百科',
+      },
+    },
+    thought: {
+      show: '显示',
+      hide: '隐藏',
+      processOfThought: '思考过程',
+      res: {
+        webReader: {
+          normal: '解析链接 {url}',
+          hasPageInfo: '解析链接 {url} 的下一页',
+        },
+        search: '搜索 {{query}}',
+        dataset: '检索数据集 {datasetName}',
+      },
+    },
+    viewConfigDetailTip: '在对话中，无法更改上述设置',
+  },
 }
 
 export default translation

web/models/common.ts

@@ -142,3 +142,11 @@ export type DataSourceNotion = {
 export type GithubRepo = {
   stargazers_count: number
 }
+
+export type PluginProvider = {
+  tool_name: string
+  is_enabled: boolean
+  credentials: {
+    api_key: string
+  } | null
+}

web/models/log.ts

@@ -79,6 +79,7 @@ export type CompletionConversationGeneralDetail = {
   status: 'normal' | 'finished'
   from_source: 'api' | 'console'
   from_end_user_id: string
+  from_end_user_session_id: string
   from_account_id: string
   read_at: Date
   created_at: number

web/service/base.ts

 /* eslint-disable no-new, prefer-promise-reject-errors */
 import { API_PREFIX, IS_CE_EDITION, PUBLIC_API_PREFIX } from '@/config'
 import Toast from '@/app/components/base/toast'
+import type { ThoughtItem } from '@/app/components/app/chat/type'
 
 const TIME_OUT = 100000
 
@@ -30,6 +31,7 @@ export type IOnDataMoreInfo = {
 }
 
 export type IOnData = (message: string, isFirstMessage: boolean, moreInfo: IOnDataMoreInfo) => void
+export type IOnThought = (though: ThoughtItem) => void
 export type IOnCompleted = (hasError?: boolean) => void
 export type IOnError = (msg: string) => void
 
@@ -39,12 +41,16 @@ type IOtherOptions = {
   needAllResponseContent?: boolean
   deleteContentType?: boolean
   onData?: IOnData // for stream
+  onThought?: IOnThought
   onError?: IOnError
   onCompleted?: IOnCompleted // for stream
   getAbortController?: (abortController: AbortController) => void
 }
 
 function unicodeToChar(text: string) {
+  if (!text)
+    return ''
+
   return text.replace(/\\u[0-9a-f]{4}/g, (_match, p1) => {
     return String.fromCharCode(parseInt(p1, 16))
   })
@@ -58,7 +64,7 @@ export function format(text: string) {
   return res.replaceAll('\n', '<br/>').replaceAll('```', '')
 }
 
-const handleStream = (response: any, onData: IOnData, onCompleted?: IOnCompleted) => {
+const handleStream = (response: any, onData: IOnData, onCompleted?: IOnCompleted, onThought?: IOnThought) => {
   if (!response.ok)
     throw new Error('Network response was not ok')
 
@@ -101,6 +107,7 @@ const handleStream = (response: any, onData: IOnData, onCompleted?: IOnCompleted
               onCompleted && onCompleted(true)
               return
             }
+            if (bufferObj.event === 'message') {
               // can not use format here. Because message is splited.
               onData(unicodeToChar(bufferObj.answer), isFirstMessage, {
                 conversationId: bufferObj.conversation_id,
@@ -109,6 +116,10 @@ const handleStream = (response: any, onData: IOnData, onCompleted?: IOnCompleted
               })
               isFirstMessage = false
             }
+            else if (bufferObj.event === 'agent_thought') {
+              onThought?.(bufferObj as any)
+            }
+          }
         })
         buffer = lines[lines.length - 1]
       }
@@ -298,7 +309,7 @@ export const upload = (options: any): Promise<any> => {
   })
 }
 
-export const ssePost = (url: string, fetchOptions: any, { isPublicAPI = false, onData, onCompleted, onError, getAbortController }: IOtherOptions) => {
+export const ssePost = (url: string, fetchOptions: any, { isPublicAPI = false, onData, onCompleted, onThought, onError, getAbortController }: IOtherOptions) => {
   const abortController = new AbortController()
 
   const options = Object.assign({}, baseOptions, {
@@ -333,17 +344,17 @@ export const ssePost = (url: string, fetchOptions: any, { isPublicAPI = false, o
       }
       return handleStream(res, (str: string, isFirstMessage: boolean, moreInfo: IOnDataMoreInfo) => {
         if (moreInfo.errorMessage) {
+          // debugger
           onError?.(moreInfo.errorMessage)
           if (moreInfo.errorMessage !== 'AbortError: The user aborted a request.')
             Toast.notify({ type: 'error', message: moreInfo.errorMessage })
           return
         }
         onData?.(str, isFirstMessage, moreInfo)
-      }, onCompleted)
+      }, onCompleted, onThought)
     }).catch((e) => {
       if (e.toString() !== 'AbortError: The user aborted a request.')
         Toast.notify({ type: 'error', message: e })
-
       onError?.(e)
     })
 }

web/service/common.ts

@@ -3,7 +3,7 @@ import { del, get, patch, post, put } from './base'
 import type {
   AccountIntegrate, CommonResponse, DataSourceNotion,
   IWorkspace, LangGeniusVersionResponse, Member,
-  OauthResponse, Provider, ProviderAnthropicToken, ProviderAzureToken, TenantInfoResponse,
+  OauthResponse, PluginProvider, Provider, ProviderAnthropicToken, ProviderAzureToken, TenantInfoResponse,
   UserProfileOriginResponse,
 } from '@/models/common'
 import type {
@@ -102,6 +102,17 @@ export const updateDataSourceNotionAction: Fetcher<CommonResponse, { url: string
   return patch(url) as Promise<CommonResponse>
 }
 
+export const fetchPluginProviders: Fetcher<PluginProvider[] | null, string> = (url) => {
+  return get(url) as Promise<PluginProvider[] | null>
+}
+
+export const validatePluginProviderKey: Fetcher<ValidateOpenAIKeyResponse, { url: string; body: { credentials: any } }> = ({ url, body }) => {
+  return post(url, { body }) as Promise<ValidateOpenAIKeyResponse>
+}
+export const updatePluginProviderAIKey: Fetcher<UpdateOpenAIKeyResponse, { url: string; body: { credentials: any } }> = ({ url, body }) => {
+  return post(url, { body }) as Promise<UpdateOpenAIKeyResponse>
+}
+
 export const invitationCheck: Fetcher<CommonResponse & { is_valid: boolean; workspace_name: string }, { url: string; params: { workspace_id: string; email: string; token: string } }> = ({ url, params }) => {
   return get(url, { params }) as Promise<CommonResponse & { is_valid: boolean; workspace_name: string }>
 }

web/service/explore.ts

@@ -31,3 +31,7 @@ export const updatePinStatus = (id: string, isPinned: boolean) => {
     },
   })
 }
+
+export const getToolProviders = () => {
+  return get('/workspaces/current/tool-providers')
+}

web/service/share.ts

@@ -3,7 +3,7 @@ import {
   del as consoleDel, get as consoleGet, patch as consolePatch, post as consolePost,
   delPublic as del, getPublic as get, patchPublic as patch, postPublic as post, ssePost,
 } from './base'
-import type { Feedbacktype } from '@/app/components/app/chat'
+import type { Feedbacktype } from '@/app/components/app/chat/type'
 
 function getAction(action: 'get' | 'post' | 'del' | 'patch', isInstalledApp: boolean) {
   switch (action) {

web/service/universal-chat.ts

+import type { IOnCompleted, IOnData, IOnError, IOnThought } from './base'
+import {
+  del, get, patch, post, ssePost,
+} from './base'
+import type { Feedbacktype } from '@/app/components/app/chat/type'
+
+const baseUrl = 'universal-chat'
+
+function getUrl(url: string) {
+  return `${baseUrl}/${url.startsWith('/') ? url.slice(1) : url}`
+}
+
+export const sendChatMessage = async (body: Record<string, any>, { onData, onCompleted, onError, onThought, getAbortController }: {
+  onData: IOnData
+  onCompleted: IOnCompleted
+  onError: IOnError
+  onThought: IOnThought
+  getAbortController?: (abortController: AbortController) => void
+}) => {
+  return ssePost(getUrl('messages'), {
+    body: {
+      ...body,
+      response_mode: 'streaming',
+    },
+  }, { onData, onCompleted, onThought, onError, getAbortController })
+}
+
+export const stopChatMessageResponding = async (taskId: string) => {
+  return post(getUrl(`messages/${taskId}/stop`))
+}
+
+export const fetchConversations = async (last_id?: string, pinned?: boolean, limit?: number) => {
+  return get(getUrl('conversations'), { params: { ...{ limit: limit || 20 }, ...(last_id ? { last_id } : {}), ...(pinned !== undefined ? { pinned } : {}) } })
+}
+
+export const pinConversation = async (id: string) => {
+  return patch(getUrl(`conversations/${id}/pin`))
+}
+
+export const unpinConversation = async (id: string) => {
+  return patch(getUrl(`conversations/${id}/unpin`))
+}
+
+export const delConversation = async (id: string) => {
+  return del(getUrl(`conversations/${id}`))
+}
+
+export const fetchChatList = async (conversationId: string) => {
+  return get(getUrl('messages'), { params: { conversation_id: conversationId, limit: 20, last_id: '' } })
+}
+
+// init value. wait for server update
+export const fetchAppParams = async () => {
+  return get(getUrl('parameters'))
+}
+
+export const updateFeedback = async ({ url, body }: { url: string; body: Feedbacktype }) => {
+  return post(getUrl(url), { body })
+}
+
+export const fetchMoreLikeThis = async (messageId: string) => {
+  return get(getUrl(`/messages/${messageId}/more-like-this`), {
+    params: {
+      response_mode: 'blocking',
+    },
+  })
+}
+
+export const fetchSuggestedQuestions = (messageId: string) => {
+  return get(getUrl(`/messages/${messageId}/suggested-questions`))
+}
+
+export const audioToText = (url: string, body: FormData) => {
+  return post(url, { body }, { bodyStringify: false, deleteContentType: true }) as Promise<{ text: string }>
+}