Merge branch 'main' into feat/header-ssr

README.md

@@ -17,9 +17,15 @@ A single API encompassing plugin capabilities, context enhancement, and more, sa
 Visual data analysis, log review, and annotation for applications
 Dify is compatible with Langchain, meaning we'll gradually support multiple LLMs, currently supported:
 
-- GPT 3 (text-davinci-003)
-- GPT 3.5 Turbo(ChatGPT)
-- GPT-4
+* **OpenAI** ：GPT4、GPT3.5-turbo、GPT3.5-turbo-16k、text-davinci-003
+
+* **Azure OpenAI**
+
+* **Antropic**：Claude2、Claude-instant
+> We've got 1000 free trial credits available for all cloud service users to try out the Claude model.Visit [Dify.ai](https://dify.ai) and
+try it now.
+
+* **hugging face Hub**：Coming soon.
 
 ## Use Cloud Services
 

README_CN.md

@@ -17,11 +17,16 @@
 - 一套 API 即可包含插件、上下文增强等能力，替你省下了后端代码的编写工作
 - 可视化的对应用进行数据分析，查阅日志或进行标注
 
-Dify 兼容 Langchain，这意味着我们将逐步支持多种 LLMs ，目前已支持：
+Dify 兼容 Langchain，这意味着我们将逐步支持多种 LLMs ，目前支持的模型供应商：
 
-- GPT 3 (text-davinci-003)
-- GPT 3.5 Turbo(ChatGPT)
-- GPT-4
+* **OpenAI**：GPT4、GPT3.5-turbo、GPT3.5-turbo-16k、text-davinci-003 
+
+* **Azure OpenAI Service**
+* **Anthropic**：Claude2、Claude-instant
+
+> 我们为所有注册云端版的用户免费提供了 1000 次 Claude 模型的消息调用额度，登录 [dify.ai](https://cloud.dify.ai) 即可使用。
+
+* **Hugging Face Hub**（即将推出）
 
 ## 使用云服务
 

api/app.py

@@ -2,6 +2,8 @@
 import os
 from datetime import datetime
 
+from werkzeug.exceptions import Forbidden
+
 if not os.environ.get("DEBUG") or os.environ.get("DEBUG").lower() != 'true':
     from gevent import monkey
     monkey.patch_all()
@@ -27,7 +29,7 @@ from events import event_handlers
 import core
 from config import Config, CloudEditionConfig
 from commands import register_commands
-from models.account import TenantAccountJoin
+from models.account import TenantAccountJoin, AccountStatus
 from models.model import Account, EndUser, App
 
 import warnings
@@ -101,6 +103,9 @@ def load_user(user_id):
         account = db.session.query(Account).filter(Account.id == account_id).first()
 
         if account:
+            if account.status == AccountStatus.BANNED.value or account.status == AccountStatus.CLOSED.value:
+                raise Forbidden('Account is banned or closed.')
+
             workspace_id = session.get('workspace_id')
             if workspace_id:
                 tenant_account_join = db.session.query(TenantAccountJoin).filter(

api/commands.py

@@ -18,7 +18,8 @@ from models.model import Account
 import secrets
 import base64
 
-from models.provider import Provider
+from models.provider import Provider, ProviderName
+from services.provider_service import ProviderService
 
 
 @click.command('reset-password', help='Reset the account password.')
@@ -193,9 +194,40 @@ def recreate_all_dataset_indexes():
     click.echo(click.style('Congratulations! Recreate {} dataset indexes.'.format(recreate_count), fg='green'))
 
 
+@click.command('sync-anthropic-hosted-providers', help='Sync anthropic hosted providers.')
+def sync_anthropic_hosted_providers():
+    click.echo(click.style('Start sync anthropic hosted providers.', fg='green'))
+    count = 0
+
+    page = 1
+    while True:
+        try:
+            tenants = db.session.query(Tenant).order_by(Tenant.created_at.desc()).paginate(page=page, per_page=50)
+        except NotFound:
+            break
+
+        page += 1
+        for tenant in tenants:
+            try:
+                click.echo('Syncing tenant anthropic hosted provider: {}'.format(tenant.id))
+                ProviderService.create_system_provider(
+                    tenant,
+                    ProviderName.ANTHROPIC.value,
+                    current_app.config['ANTHROPIC_HOSTED_QUOTA_LIMIT'],
+                    True
+                )
+                count += 1
+            except Exception as e:
+                click.echo(click.style('Sync tenant anthropic hosted provider error: {} {}'.format(e.__class__.__name__, str(e)), fg='red'))
+                continue
+
+    click.echo(click.style('Congratulations! Synced {} anthropic hosted providers.'.format(count), fg='green'))
+
+
 def register_commands(app):
     app.cli.add_command(reset_password)
     app.cli.add_command(reset_email)
     app.cli.add_command(generate_invitation_codes)
     app.cli.add_command(reset_encrypt_key_pair)
     app.cli.add_command(recreate_all_dataset_indexes)
+    app.cli.add_command(sync_anthropic_hosted_providers)

api/config.py

@@ -50,7 +50,10 @@ DEFAULTS = {
     'PDF_PREVIEW': 'True',
     'LOG_LEVEL': 'INFO',
     'DISABLE_PROVIDER_CONFIG_VALIDATION': 'False',
-    'DEFAULT_LLM_PROVIDER': 'openai'
+    'DEFAULT_LLM_PROVIDER': 'openai',
+    'OPENAI_HOSTED_QUOTA_LIMIT': 200,
+    'ANTHROPIC_HOSTED_QUOTA_LIMIT': 1000,
+    'TENANT_DOCUMENT_COUNT': 100
 }
 
 
@@ -86,7 +89,7 @@ class Config:
         self.CONSOLE_URL = get_env('CONSOLE_URL')
         self.API_URL = get_env('API_URL')
         self.APP_URL = get_env('APP_URL')
-        self.CURRENT_VERSION = "0.3.8"
+        self.CURRENT_VERSION = "0.3.9"
         self.COMMIT_SHA = get_env('COMMIT_SHA')
         self.EDITION = "SELF_HOSTED"
         self.DEPLOY_ENV = get_env('DEPLOY_ENV')
@@ -191,6 +194,10 @@ class Config:
 
         # hosted provider credentials
         self.OPENAI_API_KEY = get_env('OPENAI_API_KEY')
+        self.ANTHROPIC_API_KEY = get_env('ANTHROPIC_API_KEY')
+
+        self.OPENAI_HOSTED_QUOTA_LIMIT = get_env('OPENAI_HOSTED_QUOTA_LIMIT')
+        self.ANTHROPIC_HOSTED_QUOTA_LIMIT = get_env('ANTHROPIC_HOSTED_QUOTA_LIMIT')
 
         # By default it is False
         # You could disable it for compatibility with certain OpenAPI providers
@@ -207,6 +214,8 @@ class Config:
         self.NOTION_INTERNAL_SECRET = get_env('NOTION_INTERNAL_SECRET')
         self.NOTION_INTEGRATION_TOKEN = get_env('NOTION_INTEGRATION_TOKEN')
 
+        self.TENANT_DOCUMENT_COUNT = get_env('TENANT_DOCUMENT_COUNT')
+
 
 class CloudEditionConfig(Config):
 

api/controllers/console/app/audio.py

@@ -50,8 +50,8 @@ class ChatMessageAudioApi(Resource):
             raise UnsupportedAudioTypeError()
         except ProviderNotSupportSpeechToTextServiceError:
             raise ProviderNotSupportSpeechToTextError()
-        except ProviderTokenNotInitError:
-            raise ProviderNotInitializeError()
+        except ProviderTokenNotInitError as ex:
+            raise ProviderNotInitializeError(ex.description)
         except QuotaExceededError:
             raise ProviderQuotaExceededError()
         except ModelCurrentlyNotSupportError:

api/controllers/console/app/completion.py

@@ -63,8 +63,8 @@ class CompletionMessageApi(Resource):
         except services.errors.app_model_config.AppModelConfigBrokenError:
             logging.exception("App model config broken.")
             raise AppUnavailableError()
-        except ProviderTokenNotInitError:
-            raise ProviderNotInitializeError()
+        except ProviderTokenNotInitError as ex:
+            raise ProviderNotInitializeError(ex.description)
         except QuotaExceededError:
             raise ProviderQuotaExceededError()
         except ModelCurrentlyNotSupportError:
@@ -133,8 +133,8 @@ class ChatMessageApi(Resource):
         except services.errors.app_model_config.AppModelConfigBrokenError:
             logging.exception("App model config broken.")
             raise AppUnavailableError()
-        except ProviderTokenNotInitError:
-            raise ProviderNotInitializeError()
+        except ProviderTokenNotInitError as ex:
+            raise ProviderNotInitializeError(ex.description)
         except QuotaExceededError:
             raise ProviderQuotaExceededError()
         except ModelCurrentlyNotSupportError:
@@ -164,8 +164,8 @@ def compact_response(response: Union[dict | Generator]) -> Response:
             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 ProviderTokenNotInitError as ex:
+                yield "data: " + json.dumps(api.handle_error(ProviderNotInitializeError(ex.description)).get_json()) + "\n\n"
             except QuotaExceededError:
                 yield "data: " + json.dumps(api.handle_error(ProviderQuotaExceededError()).get_json()) + "\n\n"
             except ModelCurrentlyNotSupportError:

api/controllers/console/app/error.py

@@ -16,7 +16,7 @@ class ProviderNotInitializeError(BaseHTTPException):
 
 class ProviderQuotaExceededError(BaseHTTPException):
     error_code = 'provider_quota_exceeded'
-    description = "Your quota for Dify Hosted OpenAI has been exhausted. " \
+    description = "Your quota for Dify Hosted Model Provider has been exhausted. " \
                   "Please go to Settings -> Model Provider to complete your own provider credentials."
     code = 400
 

api/controllers/console/app/generator.py

@@ -27,8 +27,8 @@ class IntroductionGenerateApi(Resource):
                 account.current_tenant_id,
                 args['prompt_template']
             )
-        except ProviderTokenNotInitError:
-            raise ProviderNotInitializeError()
+        except ProviderTokenNotInitError as ex:
+            raise ProviderNotInitializeError(ex.description)
         except QuotaExceededError:
             raise ProviderQuotaExceededError()
         except ModelCurrentlyNotSupportError:
@@ -58,8 +58,8 @@ class RuleGenerateApi(Resource):
                 args['audiences'],
                 args['hoping_to_solve']
             )
-        except ProviderTokenNotInitError:
-            raise ProviderNotInitializeError()
+        except ProviderTokenNotInitError as ex:
+            raise ProviderNotInitializeError(ex.description)
         except QuotaExceededError:
             raise ProviderQuotaExceededError()
         except ModelCurrentlyNotSupportError:

api/controllers/console/app/message.py

@@ -269,8 +269,8 @@ class MessageMoreLikeThisApi(Resource):
             raise NotFound("Message Not Exists.")
         except MoreLikeThisDisabledError:
             raise AppMoreLikeThisDisabledError()
-        except ProviderTokenNotInitError:
-            raise ProviderNotInitializeError()
+        except ProviderTokenNotInitError as ex:
+            raise ProviderNotInitializeError(ex.description)
         except QuotaExceededError:
             raise ProviderQuotaExceededError()
         except ModelCurrentlyNotSupportError:
@@ -297,8 +297,8 @@ def compact_response(response: Union[dict | Generator]) -> Response:
                 yield "data: " + json.dumps(api.handle_error(NotFound("Message Not Exists.")).get_json()) + "\n\n"
             except MoreLikeThisDisabledError:
                 yield "data: " + json.dumps(api.handle_error(AppMoreLikeThisDisabledError()).get_json()) + "\n\n"
-            except ProviderTokenNotInitError:
-                yield "data: " + json.dumps(api.handle_error(ProviderNotInitializeError()).get_json()) + "\n\n"
+            except ProviderTokenNotInitError as ex:
+                yield "data: " + json.dumps(api.handle_error(ProviderNotInitializeError(ex.description)).get_json()) + "\n\n"
             except QuotaExceededError:
                 yield "data: " + json.dumps(api.handle_error(ProviderQuotaExceededError()).get_json()) + "\n\n"
             except ModelCurrentlyNotSupportError:
@@ -339,8 +339,8 @@ class MessageSuggestedQuestionApi(Resource):
             raise NotFound("Message not found")
         except ConversationNotExistsError:
             raise NotFound("Conversation not found")
-        except ProviderTokenNotInitError:
-            raise ProviderNotInitializeError()
+        except ProviderTokenNotInitError as ex:
+            raise ProviderNotInitializeError(ex.description)
         except QuotaExceededError:
             raise ProviderQuotaExceededError()
         except ModelCurrentlyNotSupportError:

api/controllers/console/datasets/datasets_document.py

@@ -279,8 +279,8 @@ class DatasetDocumentListApi(Resource):
 
         try:
             documents, batch = DocumentService.save_document_with_dataset_id(dataset, args, current_user)
-        except ProviderTokenNotInitError:
-            raise ProviderNotInitializeError()
+        except ProviderTokenNotInitError as ex:
+            raise ProviderNotInitializeError(ex.description)
         except QuotaExceededError:
             raise ProviderQuotaExceededError()
         except ModelCurrentlyNotSupportError:
@@ -324,8 +324,8 @@ class DatasetInitApi(Resource):
                 document_data=args,
                 account=current_user
             )
-        except ProviderTokenNotInitError:
-            raise ProviderNotInitializeError()
+        except ProviderTokenNotInitError as ex:
+            raise ProviderNotInitializeError(ex.description)
         except QuotaExceededError:
             raise ProviderQuotaExceededError()
         except ModelCurrentlyNotSupportError:

api/controllers/console/datasets/hit_testing.py

@@ -95,8 +95,8 @@ class HitTestingApi(Resource):
             return {"query": response['query'], 'records': marshal(response['records'], hit_testing_record_fields)}
         except services.errors.index.IndexNotInitializedError:
             raise DatasetNotInitializedError()
-        except ProviderTokenNotInitError:
-            raise ProviderNotInitializeError()
+        except ProviderTokenNotInitError as ex:
+            raise ProviderNotInitializeError(ex.description)
         except QuotaExceededError:
             raise ProviderQuotaExceededError()
         except ModelCurrentlyNotSupportError:

api/controllers/console/explore/audio.py

@@ -47,8 +47,8 @@ class ChatAudioApi(InstalledAppResource):
             raise UnsupportedAudioTypeError()
         except ProviderNotSupportSpeechToTextServiceError:
             raise ProviderNotSupportSpeechToTextError()
-        except ProviderTokenNotInitError:
-            raise ProviderNotInitializeError()
+        except ProviderTokenNotInitError as ex:
+            raise ProviderNotInitializeError(ex.description)
         except QuotaExceededError:
             raise ProviderQuotaExceededError()
         except ModelCurrentlyNotSupportError:

api/controllers/console/explore/completion.py

@@ -54,8 +54,8 @@ class CompletionApi(InstalledAppResource):
         except services.errors.app_model_config.AppModelConfigBrokenError:
             logging.exception("App model config broken.")
             raise AppUnavailableError()
-        except ProviderTokenNotInitError:
-            raise ProviderNotInitializeError()
+        except ProviderTokenNotInitError as ex:
+            raise ProviderNotInitializeError(ex.description)
         except QuotaExceededError:
             raise ProviderQuotaExceededError()
         except ModelCurrentlyNotSupportError:
@@ -113,8 +113,8 @@ class ChatApi(InstalledAppResource):
         except services.errors.app_model_config.AppModelConfigBrokenError:
             logging.exception("App model config broken.")
             raise AppUnavailableError()
-        except ProviderTokenNotInitError:
-            raise ProviderNotInitializeError()
+        except ProviderTokenNotInitError as ex:
+            raise ProviderNotInitializeError(ex.description)
         except QuotaExceededError:
             raise ProviderQuotaExceededError()
         except ModelCurrentlyNotSupportError:
@@ -155,8 +155,8 @@ def compact_response(response: Union[dict | Generator]) -> Response:
             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 ProviderTokenNotInitError as ex:
+                yield "data: " + json.dumps(api.handle_error(ProviderNotInitializeError(ex.description)).get_json()) + "\n\n"
             except QuotaExceededError:
                 yield "data: " + json.dumps(api.handle_error(ProviderQuotaExceededError()).get_json()) + "\n\n"
             except ModelCurrentlyNotSupportError:

api/controllers/console/explore/message.py

@@ -107,8 +107,8 @@ class MessageMoreLikeThisApi(InstalledAppResource):
             raise NotFound("Message Not Exists.")
         except MoreLikeThisDisabledError:
             raise AppMoreLikeThisDisabledError()
-        except ProviderTokenNotInitError:
-            raise ProviderNotInitializeError()
+        except ProviderTokenNotInitError as ex:
+            raise ProviderNotInitializeError(ex.description)
         except QuotaExceededError:
             raise ProviderQuotaExceededError()
         except ModelCurrentlyNotSupportError:
@@ -135,8 +135,8 @@ def compact_response(response: Union[dict | Generator]) -> Response:
                 yield "data: " + json.dumps(api.handle_error(NotFound("Message Not Exists.")).get_json()) + "\n\n"
             except MoreLikeThisDisabledError:
                 yield "data: " + json.dumps(api.handle_error(AppMoreLikeThisDisabledError()).get_json()) + "\n\n"
-            except ProviderTokenNotInitError:
-                yield "data: " + json.dumps(api.handle_error(ProviderNotInitializeError()).get_json()) + "\n\n"
+            except ProviderTokenNotInitError as ex:
+                yield "data: " + json.dumps(api.handle_error(ProviderNotInitializeError(ex.description)).get_json()) + "\n\n"
             except QuotaExceededError:
                 yield "data: " + json.dumps(api.handle_error(ProviderQuotaExceededError()).get_json()) + "\n\n"
             except ModelCurrentlyNotSupportError:
@@ -174,8 +174,8 @@ class MessageSuggestedQuestionApi(InstalledAppResource):
             raise NotFound("Conversation not found")
         except SuggestedQuestionsAfterAnswerDisabledError:
             raise AppSuggestedQuestionsAfterAnswerDisabledError()
-        except ProviderTokenNotInitError:
-            raise ProviderNotInitializeError()
+        except ProviderTokenNotInitError as ex:
+            raise ProviderNotInitializeError(ex.description)
         except QuotaExceededError:
             raise ProviderQuotaExceededError()
         except ModelCurrentlyNotSupportError:

api/controllers/console/workspace/providers.py

@@ -3,6 +3,7 @@ import base64
 import json
 import logging
 
+from flask import current_app
 from flask_login import login_required, current_user
 from flask_restful import Resource, reqparse, abort
 from werkzeug.exceptions import Forbidden
@@ -34,7 +35,7 @@ class ProviderListApi(Resource):
         plaintext, the rest is replaced by * and the last two bits are displayed in plaintext
         """
 
-        ProviderService.init_supported_provider(current_user.current_tenant, "cloud")
+        ProviderService.init_supported_provider(current_user.current_tenant)
         providers = Provider.query.filter_by(tenant_id=tenant_id).all()
 
         provider_list = [
@@ -50,7 +51,8 @@ class ProviderListApi(Resource):
                        'quota_used': p.quota_used
                    } if p.provider_type == ProviderType.SYSTEM.value else {}),
                 'token': ProviderService.get_obfuscated_api_key(current_user.current_tenant,
-                                                                ProviderName(p.provider_name))
+                                                                ProviderName(p.provider_name), only_custom=True)
+                if p.provider_type == ProviderType.CUSTOM.value else None
             }
             for p in providers
         ]
@@ -121,9 +123,10 @@ class ProviderTokenApi(Resource):
                                       is_valid=token_is_valid)
             db.session.add(provider_model)
 
-        if provider_model.is_valid:
+        if provider in [ProviderName.OPENAI.value, ProviderName.AZURE_OPENAI.value] and provider_model.is_valid:
             other_providers = db.session.query(Provider).filter(
                 Provider.tenant_id == tenant.id,
+                Provider.provider_name.in_([ProviderName.OPENAI.value, ProviderName.AZURE_OPENAI.value]),
                 Provider.provider_name != provider,
                 Provider.provider_type == ProviderType.CUSTOM.value
             ).all()
@@ -133,7 +136,7 @@ class ProviderTokenApi(Resource):
 
         db.session.commit()
 
-        if provider in [ProviderName.ANTHROPIC.value, ProviderName.AZURE_OPENAI.value, ProviderName.COHERE.value,
+        if provider in [ProviderName.AZURE_OPENAI.value, ProviderName.COHERE.value,
                         ProviderName.HUGGINGFACEHUB.value]:
             return {'result': 'success', 'warning': 'MOCK: This provider is not supported yet.'}, 201
 
@@ -157,7 +160,7 @@ class ProviderTokenValidateApi(Resource):
         args = parser.parse_args()
 
         # todo: remove this when the provider is supported
-        if provider in [ProviderName.ANTHROPIC.value, ProviderName.COHERE.value,
+        if provider in [ProviderName.COHERE.value,
                         ProviderName.HUGGINGFACEHUB.value]:
             return {'result': 'success', 'warning': 'MOCK: This provider is not supported yet.'}
 
@@ -203,7 +206,19 @@ class ProviderSystemApi(Resource):
             provider_model.is_valid = args['is_enabled']
             db.session.commit()
         elif not provider_model:
-            ProviderService.create_system_provider(tenant, provider, args['is_enabled'])
+            if provider == ProviderName.OPENAI.value:
+                quota_limit = current_app.config['OPENAI_HOSTED_QUOTA_LIMIT']
+            elif provider == ProviderName.ANTHROPIC.value:
+                quota_limit = current_app.config['ANTHROPIC_HOSTED_QUOTA_LIMIT']
+            else:
+                quota_limit = 0
+
+            ProviderService.create_system_provider(
+                tenant,
+                provider,
+                quota_limit,
+                args['is_enabled']
+            )
         else:
             abort(403)
 

api/controllers/service_api/app/audio.py

@@ -43,8 +43,8 @@ class AudioApi(AppApiResource):
             raise UnsupportedAudioTypeError()
         except ProviderNotSupportSpeechToTextServiceError:
             raise ProviderNotSupportSpeechToTextError()
-        except ProviderTokenNotInitError:
-            raise ProviderNotInitializeError()
+        except ProviderTokenNotInitError as ex:
+            raise ProviderNotInitializeError(ex.description)
         except QuotaExceededError:
             raise ProviderQuotaExceededError()
         except ModelCurrentlyNotSupportError:

api/controllers/service_api/app/completion.py

@@ -54,8 +54,8 @@ class CompletionApi(AppApiResource):
         except services.errors.app_model_config.AppModelConfigBrokenError:
             logging.exception("App model config broken.")
             raise AppUnavailableError()
-        except ProviderTokenNotInitError:
-            raise ProviderNotInitializeError()
+        except ProviderTokenNotInitError as ex:
+            raise ProviderNotInitializeError(ex.description)
         except QuotaExceededError:
             raise ProviderQuotaExceededError()
         except ModelCurrentlyNotSupportError:
@@ -115,8 +115,8 @@ class ChatApi(AppApiResource):
         except services.errors.app_model_config.AppModelConfigBrokenError:
             logging.exception("App model config broken.")
             raise AppUnavailableError()
-        except ProviderTokenNotInitError:
-            raise ProviderNotInitializeError()
+        except ProviderTokenNotInitError as ex:
+            raise ProviderNotInitializeError(ex.description)
         except QuotaExceededError:
             raise ProviderQuotaExceededError()
         except ModelCurrentlyNotSupportError:
@@ -156,8 +156,8 @@ def compact_response(response: Union[dict | Generator]) -> Response:
             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 ProviderTokenNotInitError as ex:
+                yield "data: " + json.dumps(api.handle_error(ProviderNotInitializeError(ex.description)).get_json()) + "\n\n"
             except QuotaExceededError:
                 yield "data: " + json.dumps(api.handle_error(ProviderQuotaExceededError()).get_json()) + "\n\n"
             except ModelCurrentlyNotSupportError:

api/controllers/service_api/dataset/document.py

@@ -85,8 +85,8 @@ class DocumentListApi(DatasetApiResource):
                 dataset_process_rule=dataset.latest_process_rule,
                 created_from='api'
             )
-        except ProviderTokenNotInitError:
-            raise ProviderNotInitializeError()
+        except ProviderTokenNotInitError as ex:
+            raise ProviderNotInitializeError(ex.description)
         document = documents[0]
         if doc_type and doc_metadata:
             metadata_schema = DocumentService.DOCUMENT_METADATA_SCHEMA[doc_type]

api/controllers/web/audio.py

@@ -45,8 +45,8 @@ class AudioApi(WebApiResource):
             raise UnsupportedAudioTypeError()
         except ProviderNotSupportSpeechToTextServiceError:
             raise ProviderNotSupportSpeechToTextError()
-        except ProviderTokenNotInitError:
-            raise ProviderNotInitializeError()
+        except ProviderTokenNotInitError as ex:
+            raise ProviderNotInitializeError(ex.description)
         except QuotaExceededError:
             raise ProviderQuotaExceededError()
         except ModelCurrentlyNotSupportError:

api/controllers/web/completion.py

@@ -52,8 +52,8 @@ class CompletionApi(WebApiResource):
         except services.errors.app_model_config.AppModelConfigBrokenError:
             logging.exception("App model config broken.")
             raise AppUnavailableError()
-        except ProviderTokenNotInitError:
-            raise ProviderNotInitializeError()
+        except ProviderTokenNotInitError as ex:
+            raise ProviderNotInitializeError(ex.description)
         except QuotaExceededError:
             raise ProviderQuotaExceededError()
         except ModelCurrentlyNotSupportError:
@@ -109,8 +109,8 @@ class ChatApi(WebApiResource):
         except services.errors.app_model_config.AppModelConfigBrokenError:
             logging.exception("App model config broken.")
             raise AppUnavailableError()
-        except ProviderTokenNotInitError:
-            raise ProviderNotInitializeError()
+        except ProviderTokenNotInitError as ex:
+            raise ProviderNotInitializeError(ex.description)
         except QuotaExceededError:
             raise ProviderQuotaExceededError()
         except ModelCurrentlyNotSupportError:
@@ -150,8 +150,8 @@ def compact_response(response: Union[dict | Generator]) -> Response:
             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 ProviderTokenNotInitError as ex:
+                yield "data: " + json.dumps(api.handle_error(ProviderNotInitializeError(ex.description)).get_json()) + "\n\n"
             except QuotaExceededError:
                 yield "data: " + json.dumps(api.handle_error(ProviderQuotaExceededError()).get_json()) + "\n\n"
             except ModelCurrentlyNotSupportError:

api/controllers/web/message.py

@@ -101,8 +101,8 @@ class MessageMoreLikeThisApi(WebApiResource):
             raise NotFound("Message Not Exists.")
         except MoreLikeThisDisabledError:
             raise AppMoreLikeThisDisabledError()
-        except ProviderTokenNotInitError:
-            raise ProviderNotInitializeError()
+        except ProviderTokenNotInitError as ex:
+            raise ProviderNotInitializeError(ex.description)
         except QuotaExceededError:
             raise ProviderQuotaExceededError()
         except ModelCurrentlyNotSupportError:
@@ -129,8 +129,8 @@ def compact_response(response: Union[dict | Generator]) -> Response:
                 yield "data: " + json.dumps(api.handle_error(NotFound("Message Not Exists.")).get_json()) + "\n\n"
             except MoreLikeThisDisabledError:
                 yield "data: " + json.dumps(api.handle_error(AppMoreLikeThisDisabledError()).get_json()) + "\n\n"
-            except ProviderTokenNotInitError:
-                yield "data: " + json.dumps(api.handle_error(ProviderNotInitializeError()).get_json()) + "\n\n"
+            except ProviderTokenNotInitError as ex:
+                yield "data: " + json.dumps(api.handle_error(ProviderNotInitializeError(ex.description)).get_json()) + "\n\n"
             except QuotaExceededError:
                 yield "data: " + json.dumps(api.handle_error(ProviderQuotaExceededError()).get_json()) + "\n\n"
             except ModelCurrentlyNotSupportError:
@@ -167,8 +167,8 @@ class MessageSuggestedQuestionApi(WebApiResource):
             raise NotFound("Conversation not found")
         except SuggestedQuestionsAfterAnswerDisabledError:
             raise AppSuggestedQuestionsAfterAnswerDisabledError()
-        except ProviderTokenNotInitError:
-            raise ProviderNotInitializeError()
+        except ProviderTokenNotInitError as ex:
+            raise ProviderNotInitializeError(ex.description)
         except QuotaExceededError:
             raise ProviderQuotaExceededError()
         except ModelCurrentlyNotSupportError:

api/core/__init__.py

@@ -13,8 +13,13 @@ class HostedOpenAICredential(BaseModel):
     api_key: str
 
 
+class HostedAnthropicCredential(BaseModel):
+    api_key: str
+
+
 class HostedLLMCredentials(BaseModel):
     openai: Optional[HostedOpenAICredential] = None
+    anthropic: Optional[HostedAnthropicCredential] = None
 
 
 hosted_llm_credentials = HostedLLMCredentials()
@@ -26,3 +31,6 @@ def init_app(app: Flask):
 
     if app.config.get("OPENAI_API_KEY"):
         hosted_llm_credentials.openai = HostedOpenAICredential(api_key=app.config.get("OPENAI_API_KEY"))
+
+    if app.config.get("ANTHROPIC_API_KEY"):
+        hosted_llm_credentials.anthropic = HostedAnthropicCredential(api_key=app.config.get("ANTHROPIC_API_KEY"))

api/core/callback_handler/llm_callback_handler.py

@@ -48,7 +48,7 @@ class LLMCallbackHandler(BaseCallbackHandler):
             })
 
         self.llm_message.prompt = real_prompts
-        self.llm_message.prompt_tokens = self.llm.get_messages_tokens(messages[0])
+        self.llm_message.prompt_tokens = self.llm.get_num_tokens_from_messages(messages[0])
 
     def on_llm_start(
         self, serialized: Dict[str, Any], prompts: List[str], **kwargs: Any

api/core/completion.py

@@ -118,6 +118,7 @@ class Completion:
         prompt, stop_words = cls.get_main_llm_prompt(
             mode=mode,
             llm=final_llm,
+            model=app_model_config.model_dict,
             pre_prompt=app_model_config.pre_prompt,
             query=query,
             inputs=inputs,
@@ -129,6 +130,7 @@ class Completion:
 
         cls.recale_llm_max_tokens(
             final_llm=final_llm,
+            model=app_model_config.model_dict,
             prompt=prompt,
             mode=mode
         )
@@ -138,7 +140,8 @@ class Completion:
         return response
 
     @classmethod
-    def get_main_llm_prompt(cls, mode: str, llm: BaseLanguageModel, pre_prompt: str, query: str, inputs: dict,
+    def get_main_llm_prompt(cls, mode: str, llm: BaseLanguageModel, model: dict,
+                            pre_prompt: str, query: str, inputs: dict,
                             chain_output: Optional[str],
                             memory: Optional[ReadOnlyConversationTokenDBBufferSharedMemory]) -> \
             Tuple[Union[str | List[BaseMessage]], Optional[List[str]]]:
@@ -151,10 +154,11 @@ class Completion:
 
         if mode == 'completion':
             prompt_template = JinjaPromptTemplate.from_template(
-                template=("""Use the following CONTEXT as your learned knowledge:
-[CONTEXT]
+                template=("""Use the following context as your learned knowledge, inside <context></context> XML tags.
+
+<context>
 {{context}}
-[END CONTEXT]
+</context>
 
 When answer to user:
 - If you don't know, just say that you don't know.
@@ -204,10 +208,11 @@ And answer according to the language of the user's question.
 
             if chain_output:
                 human_inputs['context'] = chain_output
-                human_message_prompt += """Use the following CONTEXT as your learned knowledge.
-[CONTEXT]
+                human_message_prompt += """Use the following context as your learned knowledge, inside <context></context> XML tags.
+
+<context>
 {{context}}
-[END CONTEXT]
+</context>
 
 When answer to user:
 - If you don't know, just say that you don't know.
@@ -219,7 +224,7 @@ And answer according to the language of the user's question.
             if pre_prompt:
                 human_message_prompt += pre_prompt
 
-            query_prompt = "\nHuman: {{query}}\nAI: "
+            query_prompt = "\n\nHuman: {{query}}\n\nAssistant: "
 
             if memory:
                 # append chat histories
@@ -228,9 +233,11 @@ And answer according to the language of the user's question.
                     inputs=human_inputs
                 )
 
-                curr_message_tokens = memory.llm.get_messages_tokens([tmp_human_message])
-                rest_tokens = llm_constant.max_context_token_length[memory.llm.model_name] \
-                              - memory.llm.max_tokens - curr_message_tokens
+                curr_message_tokens = memory.llm.get_num_tokens_from_messages([tmp_human_message])
+                model_name = model['name']
+                max_tokens = model.get("completion_params").get('max_tokens')
+                rest_tokens = llm_constant.max_context_token_length[model_name] \
+                              - max_tokens - curr_message_tokens
                 rest_tokens = max(rest_tokens, 0)
                 histories = cls.get_history_messages_from_memory(memory, rest_tokens)
 
@@ -241,7 +248,10 @@ And answer according to the language of the user's question.
                 #         if histories_param not in human_inputs:
                 #             human_inputs[histories_param] = '{{' + histories_param + '}}'
 
-                human_message_prompt += "\n\n" + histories
+                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>"
 
             human_message_prompt += query_prompt
 
@@ -307,13 +317,15 @@ And answer according to the language of the user's question.
             model=app_model_config.model_dict
         )
 
-        model_limited_tokens = llm_constant.max_context_token_length[llm.model_name]
-        max_tokens = llm.max_tokens
+        model_name = app_model_config.model_dict.get("name")
+        model_limited_tokens = llm_constant.max_context_token_length[model_name]
+        max_tokens = app_model_config.model_dict.get("completion_params").get('max_tokens')
 
         # get prompt without memory and context
         prompt, _ = cls.get_main_llm_prompt(
             mode=mode,
             llm=llm,
+            model=app_model_config.model_dict,
             pre_prompt=app_model_config.pre_prompt,
             query=query,
             inputs=inputs,
@@ -332,16 +344,17 @@ And answer according to the language of the user's question.
         return rest_tokens
 
     @classmethod
-    def recale_llm_max_tokens(cls, final_llm: Union[StreamableOpenAI, StreamableChatOpenAI],
+    def recale_llm_max_tokens(cls, final_llm: BaseLanguageModel, model: dict,
                               prompt: Union[str, List[BaseMessage]], mode: str):
         # recalc max_tokens if sum(prompt_token +  max_tokens) over model token limit
-        model_limited_tokens = llm_constant.max_context_token_length[final_llm.model_name]
-        max_tokens = final_llm.max_tokens
+        model_name = model.get("name")
+        model_limited_tokens = llm_constant.max_context_token_length[model_name]
+        max_tokens = model.get("completion_params").get('max_tokens')
 
         if mode == 'completion' and isinstance(final_llm, BaseLLM):
             prompt_tokens = final_llm.get_num_tokens(prompt)
         else:
-            prompt_tokens = final_llm.get_messages_tokens(prompt)
+            prompt_tokens = final_llm.get_num_tokens_from_messages(prompt)
 
         if prompt_tokens + max_tokens > model_limited_tokens:
             max_tokens = max(model_limited_tokens - prompt_tokens, 16)
@@ -350,9 +363,10 @@ And answer according to the language of the user's question.
     @classmethod
     def generate_more_like_this(cls, task_id: str, app: App, message: Message, pre_prompt: str,
                                 app_model_config: AppModelConfig, user: Account, streaming: bool):
-        llm: StreamableOpenAI = LLMBuilder.to_llm(
+
+        llm = LLMBuilder.to_llm_from_model(
             tenant_id=app.tenant_id,
-            model_name='gpt-3.5-turbo',
+            model=app_model_config.model_dict,
             streaming=streaming
         )
 
@@ -360,6 +374,7 @@ And answer according to the language of the user's question.
         original_prompt, _ = cls.get_main_llm_prompt(
             mode="completion",
             llm=llm,
+            model=app_model_config.model_dict,
             pre_prompt=pre_prompt,
             query=message.query,
             inputs=message.inputs,
@@ -390,6 +405,7 @@ And answer according to the language of the user's question.
 
         cls.recale_llm_max_tokens(
             final_llm=llm,
+            model=app_model_config.model_dict,
             prompt=prompt,
             mode='completion'
         )

api/core/constant/llm_constant.py

 from _decimal import Decimal
 
 models = {
+    'claude-instant-1': 'anthropic',  # 100,000 tokens
+    'claude-2': 'anthropic',  # 100,000 tokens
     'gpt-4': 'openai',  # 8,192 tokens
     'gpt-4-32k': 'openai',  # 32,768 tokens
     'gpt-3.5-turbo': 'openai',  # 4,096 tokens
@@ -10,10 +12,13 @@ models = {
     'text-curie-001': 'openai',  # 2,049 tokens
     'text-babbage-001': 'openai',  # 2,049 tokens
     'text-ada-001': 'openai',  # 2,049 tokens
-    'text-embedding-ada-002': 'openai'  # 8191 tokens, 1536 dimensions
+    'text-embedding-ada-002': 'openai',  # 8191 tokens, 1536 dimensions
+    'whisper-1': 'openai'
 }
 
 max_context_token_length = {
+    'claude-instant-1': 100000,
+    'claude-2': 100000,
     'gpt-4': 8192,
     'gpt-4-32k': 32768,
     'gpt-3.5-turbo': 4096,
@@ -23,17 +28,21 @@ max_context_token_length = {
     'text-curie-001': 2049,
     'text-babbage-001': 2049,
     'text-ada-001': 2049,
-    'text-embedding-ada-002': 8191
+    'text-embedding-ada-002': 8191,
 }
 
 models_by_mode = {
     'chat': [
+        'claude-instant-1',  # 100,000 tokens
+        'claude-2',  # 100,000 tokens
         'gpt-4',  # 8,192 tokens
         'gpt-4-32k',  # 32,768 tokens
         'gpt-3.5-turbo',  # 4,096 tokens
         'gpt-3.5-turbo-16k',  # 16,384 tokens
     ],
     'completion': [
+        'claude-instant-1',  # 100,000 tokens
+        'claude-2',  # 100,000 tokens
         'gpt-4',  # 8,192 tokens
         'gpt-4-32k',  # 32,768 tokens
         'gpt-3.5-turbo',  # 4,096 tokens
@@ -52,6 +61,14 @@ models_by_mode = {
 model_currency = 'USD'
 
 model_prices = {
+    'claude-instant-1': {
+        'prompt': Decimal('0.00163'),
+        'completion': Decimal('0.00551'),
+    },
+    'claude-2': {
+        'prompt': Decimal('0.01102'),
+        'completion': Decimal('0.03268'),
+    },
     'gpt-4': {
         'prompt': Decimal('0.03'),
         'completion': Decimal('0.06'),

api/core/conversation_message_task.py

@@ -56,7 +56,7 @@ class ConversationMessageTask:
         )
 
     def init(self):
-        provider_name = LLMBuilder.get_default_provider(self.app.tenant_id)
+        provider_name = LLMBuilder.get_default_provider(self.app.tenant_id, self.model_name)
         self.model_dict['provider'] = provider_name
 
         override_model_configs = None
@@ -89,7 +89,7 @@ class ConversationMessageTask:
                 system_message = PromptBuilder.to_system_message(self.app_model_config.pre_prompt, self.inputs)
                 system_instruction = system_message.content
                 llm = LLMBuilder.to_llm(self.tenant_id, self.model_name)
-                system_instruction_tokens = llm.get_messages_tokens([system_message])
+                system_instruction_tokens = llm.get_num_tokens_from_messages([system_message])
 
         if not self.conversation:
             self.is_new_conversation = True
@@ -185,6 +185,7 @@ class ConversationMessageTask:
         if provider and provider.provider_type == ProviderType.SYSTEM.value:
             db.session.query(Provider).filter(
                 Provider.tenant_id == self.app.tenant_id,
+                Provider.provider_name == provider.provider_name,
                 Provider.quota_limit > Provider.quota_used
             ).update({'quota_used': Provider.quota_used + 1})
 

api/core/embedding/cached_embedding.py

@@ -4,6 +4,7 @@ from typing import List
 from langchain.embeddings.base import Embeddings
 from sqlalchemy.exc import IntegrityError
 
+from core.llm.wrappers.openai_wrapper import handle_openai_exceptions
 from extensions.ext_database import db
 from libs import helper
 from models.dataset import Embedding
@@ -49,6 +50,7 @@ class CacheEmbedding(Embeddings):
         text_embeddings.extend(embedding_results)
         return text_embeddings
 
+    @handle_openai_exceptions
     def embed_query(self, text: str) -> List[float]:
         """Embed query text."""
         # use doc embedding cache or store if not exists

api/core/generator/llm_generator.py

@@ -23,6 +23,10 @@ class LLMGenerator:
     @classmethod
     def generate_conversation_name(cls, tenant_id: str, query, answer):
         prompt = CONVERSATION_TITLE_PROMPT
+
+        if len(query) > 2000:
+            query = query[:300] + "...[TRUNCATED]..." + query[-300:]
+
         prompt = prompt.format(query=query)
         llm: StreamableOpenAI = LLMBuilder.to_llm(
             tenant_id=tenant_id,
@@ -52,7 +56,17 @@ class LLMGenerator:
             if not message.answer:
                 continue
 
-            message_qa_text = "Human:" + message.query + "\nAI:" + message.answer + "\n"
+            if len(message.query) > 2000:
+                query = message.query[:300] + "...[TRUNCATED]..." + message.query[-300:]
+            else:
+                query = message.query
+
+            if len(message.answer) > 2000:
+                answer = message.answer[:300] + "...[TRUNCATED]..." + message.answer[-300:]
+            else:
+                answer = message.answer
+
+            message_qa_text = "\n\nHuman:" + query + "\n\nAssistant:" + answer
             if rest_tokens - TokenCalculator.get_num_tokens(model, context + message_qa_text) > 0:
                 context += message_qa_text
 

api/core/index/index.py

@@ -17,7 +17,7 @@ class IndexBuilder:
 
             model_credentials = LLMBuilder.get_model_credentials(
                 tenant_id=dataset.tenant_id,
-                model_provider=LLMBuilder.get_default_provider(dataset.tenant_id),
+                model_provider=LLMBuilder.get_default_provider(dataset.tenant_id, 'text-embedding-ada-002'),
                 model_name='text-embedding-ada-002'
             )
 

api/core/llm/error.py

@@ -40,6 +40,9 @@ class ProviderTokenNotInitError(Exception):
     """
     description = "Provider Token Not Init"
 
+    def __init__(self, *args, **kwargs):
+        self.description = args[0] if args else self.description
+
 
 class QuotaExceededError(Exception):
     """

api/core/llm/llm_builder.py

@@ -8,9 +8,10 @@ from core.llm.provider.base import BaseProvider
 from core.llm.provider.llm_provider_service import LLMProviderService
 from core.llm.streamable_azure_chat_open_ai import StreamableAzureChatOpenAI
 from core.llm.streamable_azure_open_ai import StreamableAzureOpenAI
+from core.llm.streamable_chat_anthropic import StreamableChatAnthropic
 from core.llm.streamable_chat_open_ai import StreamableChatOpenAI
 from core.llm.streamable_open_ai import StreamableOpenAI
-from models.provider import ProviderType
+from models.provider import ProviderType, ProviderName
 
 
 class LLMBuilder:
@@ -32,43 +33,43 @@ class LLMBuilder:
 
     @classmethod
     def to_llm(cls, tenant_id: str, model_name: str, **kwargs) -> Union[StreamableOpenAI, StreamableChatOpenAI]:
-        provider = cls.get_default_provider(tenant_id)
+        provider = cls.get_default_provider(tenant_id, model_name)
 
         model_credentials = cls.get_model_credentials(tenant_id, provider, model_name)
 
+        llm_cls = None
         mode = cls.get_mode_by_model(model_name)
         if mode == 'chat':
-            if provider == 'openai':
+            if provider == ProviderName.OPENAI.value:
                 llm_cls = StreamableChatOpenAI
-            else:
+            elif provider == ProviderName.AZURE_OPENAI.value:
                 llm_cls = StreamableAzureChatOpenAI
+            elif provider == ProviderName.ANTHROPIC.value:
+                llm_cls = StreamableChatAnthropic
         elif mode == 'completion':
-            if provider == 'openai':
+            if provider == ProviderName.OPENAI.value:
                 llm_cls = StreamableOpenAI
-            else:
+            elif provider == ProviderName.AZURE_OPENAI.value:
                 llm_cls = StreamableAzureOpenAI
-        else:
-            raise ValueError(f"model name {model_name} is not supported.")
 
+        if not llm_cls:
+            raise ValueError(f"model name {model_name} is not supported.")
 
         model_kwargs = {
+            'model_name': model_name,
+            'temperature': kwargs.get('temperature', 0),
+            'max_tokens': kwargs.get('max_tokens', 256),
             'top_p': kwargs.get('top_p', 1),
             'frequency_penalty': kwargs.get('frequency_penalty', 0),
             'presence_penalty': kwargs.get('presence_penalty', 0),
+            'callbacks': kwargs.get('callbacks', None),
+            'streaming': kwargs.get('streaming', False),
         }
 
-        model_extras_kwargs = model_kwargs if mode == 'completion' else {'model_kwargs': model_kwargs}
+        model_kwargs.update(model_credentials)
+        model_kwargs = llm_cls.get_kwargs_from_model_params(model_kwargs)
 
-        return llm_cls(
-            model_name=model_name,
-            temperature=kwargs.get('temperature', 0),
-            max_tokens=kwargs.get('max_tokens', 256),
-            **model_extras_kwargs,
-            callbacks=kwargs.get('callbacks', None),
-            streaming=kwargs.get('streaming', False),
-            # request_timeout=None
-            **model_credentials
-        )
+        return llm_cls(**model_kwargs)
 
     @classmethod
     def to_llm_from_model(cls, tenant_id: str, model: dict, streaming: bool = False,
@@ -118,10 +119,25 @@ class LLMBuilder:
         return provider_service.get_credentials(model_name)
 
     @classmethod
-    def get_default_provider(cls, tenant_id: str) -> str:
-        provider = BaseProvider.get_valid_provider(tenant_id)
+    def get_default_provider(cls, tenant_id: str, model_name: str) -> str:
+        provider_name = llm_constant.models[model_name]
+
+        if provider_name == 'openai':
+            # get the default provider (openai / azure_openai) for the tenant
+            openai_provider = BaseProvider.get_valid_provider(tenant_id, ProviderName.OPENAI.value)
+            azure_openai_provider = BaseProvider.get_valid_provider(tenant_id, ProviderName.AZURE_OPENAI.value)
+
+            provider = None
+            if openai_provider:
+                provider = openai_provider
+            elif azure_openai_provider:
+                provider = azure_openai_provider
+
             if not provider:
-            raise ProviderTokenNotInitError()
+                raise ProviderTokenNotInitError(
+                    f"No valid {provider_name} model provider credentials found. "
+                    f"Please go to Settings -> Model Provider to complete your provider credentials."
+                )
 
             if provider.provider_type == ProviderType.SYSTEM.value:
                 provider_name = 'openai'

api/core/llm/provider/anthropic_provider.py

-from typing import Optional
+import json
+import logging
+from typing import Optional, Union
 
+import anthropic
+from langchain.chat_models import ChatAnthropic
+from langchain.schema import HumanMessage
+
+from core import hosted_llm_credentials
+from core.llm.error import ProviderTokenNotInitError
 from core.llm.provider.base import BaseProvider
-from models.provider import ProviderName
+from core.llm.provider.errors import ValidateFailedError
+from models.provider import ProviderName, ProviderType
 
 
 class AnthropicProvider(BaseProvider):
     def get_models(self, model_id: Optional[str] = None) -> list[dict]:
-        credentials = self.get_credentials(model_id)
-        # todo
-        return []
+        return [
+            {
+                'id': 'claude-instant-1',
+                'name': 'claude-instant-1',
+            },
+            {
+                'id': 'claude-2',
+                'name': 'claude-2',
+            },
+        ]
 
     def get_credentials(self, model_id: Optional[str] = None) -> dict:
+        return self.get_provider_api_key(model_id=model_id)
+
+    def get_provider_name(self):
+        return ProviderName.ANTHROPIC
+
+    def get_provider_configs(self, obfuscated: bool = False, only_custom: bool = False) -> Union[str | dict]:
         """
-        Returns the API credentials for Azure OpenAI as a dictionary, for the given tenant_id.
-        The dictionary contains keys: azure_api_type, azure_api_version, azure_api_base, and azure_api_key.
+        Returns the provider configs.
         """
-        return {
-            'anthropic_api_key': self.get_provider_api_key(model_id=model_id)
+        try:
+            config = self.get_provider_api_key(only_custom=only_custom)
+        except:
+            config = {
+                'anthropic_api_key': ''
             }
 
-    def get_provider_name(self):
-        return ProviderName.ANTHROPIC
\ No newline at end of file
+        if obfuscated:
+            if not config.get('anthropic_api_key'):
+                config = {
+                    'anthropic_api_key': ''
+                }
+
+            config['anthropic_api_key'] = self.obfuscated_token(config.get('anthropic_api_key'))
+            return config
+
+        return config
+
+    def get_encrypted_token(self, config: Union[dict | str]):
+        """
+        Returns the encrypted token.
+        """
+        return json.dumps({
+            'anthropic_api_key': self.encrypt_token(config['anthropic_api_key'])
+        })
+
+    def get_decrypted_token(self, token: str):
+        """
+        Returns the decrypted token.
+        """
+        config = json.loads(token)
+        config['anthropic_api_key'] = self.decrypt_token(config['anthropic_api_key'])
+        return config
+
+    def get_token_type(self):
+        return dict
+
+    def config_validate(self, config: Union[dict | str]):
+        """
+        Validates the given config.
+        """
+        # check OpenAI / Azure OpenAI credential is valid
+        openai_provider = BaseProvider.get_valid_provider(self.tenant_id, ProviderName.OPENAI.value)
+        azure_openai_provider = BaseProvider.get_valid_provider(self.tenant_id, ProviderName.AZURE_OPENAI.value)
+
+        provider = None
+        if openai_provider:
+            provider = openai_provider
+        elif azure_openai_provider:
+            provider = azure_openai_provider
+
+        if not provider:
+            raise ValidateFailedError(f"OpenAI or Azure OpenAI provider must be configured first.")
+
+        if provider.provider_type == ProviderType.SYSTEM.value:
+            quota_used = provider.quota_used if provider.quota_used is not None else 0
+            quota_limit = provider.quota_limit if provider.quota_limit is not None else 0
+            if quota_used >= quota_limit:
+                raise ValidateFailedError(f"Your quota for Dify Hosted OpenAI has been exhausted, "
+                                          f"please configure OpenAI or Azure OpenAI provider first.")
+
+        try:
+            if not isinstance(config, dict):
+                raise ValueError('Config must be a object.')
+
+            if 'anthropic_api_key' not in config:
+                raise ValueError('anthropic_api_key must be provided.')
+
+            chat_llm = ChatAnthropic(
+                model='claude-instant-1',
+                anthropic_api_key=config['anthropic_api_key'],
+                max_tokens_to_sample=10,
+                temperature=0,
+                default_request_timeout=60
+            )
+
+            messages = [
+                HumanMessage(
+                    content="ping"
+                )
+            ]
+
+            chat_llm(messages)
+        except anthropic.APIConnectionError as ex:
+            raise ValidateFailedError(f"Anthropic: Connection error, cause: {ex.__cause__}")
+        except (anthropic.APIStatusError, anthropic.RateLimitError) as ex:
+            raise ValidateFailedError(f"Anthropic: Error code: {ex.status_code} - "
+                                      f"{ex.body['error']['type']}: {ex.body['error']['message']}")
+        except Exception as ex:
+            logging.exception('Anthropic config validation failed')
+            raise ex
+
+    def get_hosted_credentials(self) -> Union[str | dict]:
+        if not hosted_llm_credentials.anthropic or not hosted_llm_credentials.anthropic.api_key:
+            raise ProviderTokenNotInitError(
+                f"No valid {self.get_provider_name().value} model provider credentials found. "
+                f"Please go to Settings -> Model Provider to complete your provider credentials."
+            )
+
+        return {'anthropic_api_key': hosted_llm_credentials.anthropic.api_key}

api/core/llm/provider/azure_provider.py

@@ -52,12 +52,12 @@ class AzureProvider(BaseProvider):
     def get_provider_name(self):
         return ProviderName.AZURE_OPENAI
 
-    def get_provider_configs(self, obfuscated: bool = False) -> Union[str | dict]:
+    def get_provider_configs(self, obfuscated: bool = False, only_custom: bool = False) -> Union[str | dict]:
         """
         Returns the provider configs.
         """
         try:
-            config = self.get_provider_api_key()
+            config = self.get_provider_api_key(only_custom=only_custom)
         except:
             config = {
                 'openai_api_type': 'azure',
@@ -81,7 +81,6 @@ class AzureProvider(BaseProvider):
         return config
 
     def get_token_type(self):
-        # TODO: change to dict when implemented
         return dict
 
     def config_validate(self, config: Union[dict | str]):

api/core/llm/provider/base.py

@@ -2,7 +2,7 @@ import base64
 from abc import ABC, abstractmethod
 from typing import Optional, Union
 
-from core import hosted_llm_credentials
+from core.constant import llm_constant
 from core.llm.error import QuotaExceededError, ModelCurrentlyNotSupportError, ProviderTokenNotInitError
 from extensions.ext_database import db
 from libs import rsa
@@ -14,15 +14,18 @@ class BaseProvider(ABC):
     def __init__(self, tenant_id: str):
         self.tenant_id = tenant_id
 
-    def get_provider_api_key(self, model_id: Optional[str] = None, prefer_custom: bool = True) -> Union[str | dict]:
+    def get_provider_api_key(self, model_id: Optional[str] = None, only_custom: bool = False) -> Union[str | dict]:
         """
         Returns the decrypted API key for the given tenant_id and provider_name.
         If the provider is of type SYSTEM and the quota is exceeded, raises a QuotaExceededError.
         If the provider is not found or not valid, raises a ProviderTokenNotInitError.
         """
-        provider = self.get_provider(prefer_custom)
+        provider = self.get_provider(only_custom)
         if not provider:
-            raise ProviderTokenNotInitError()
+            raise ProviderTokenNotInitError(
+                f"No valid {llm_constant.models[model_id]} model provider credentials found. "
+                f"Please go to Settings -> Model Provider to complete your provider credentials."
+            )
 
         if provider.provider_type == ProviderType.SYSTEM.value:
             quota_used = provider.quota_used if provider.quota_used is not None else 0
@@ -38,18 +41,19 @@ class BaseProvider(ABC):
         else:
             return self.get_decrypted_token(provider.encrypted_config)
 
-    def get_provider(self, prefer_custom: bool) -> Optional[Provider]:
+    def get_provider(self, only_custom: bool = False) -> Optional[Provider]:
         """
         Returns the Provider instance for the given tenant_id and provider_name.
         If both CUSTOM and System providers exist, the preferred provider will be returned based on the prefer_custom flag.
         """
-        return BaseProvider.get_valid_provider(self.tenant_id, self.get_provider_name().value, prefer_custom)
+        return BaseProvider.get_valid_provider(self.tenant_id, self.get_provider_name().value, only_custom)
 
     @classmethod
-    def get_valid_provider(cls, tenant_id: str, provider_name: str = None, prefer_custom: bool = False) -> Optional[Provider]:
+    def get_valid_provider(cls, tenant_id: str, provider_name: str = None, only_custom: bool = False) -> Optional[
+        Provider]:
         """
         Returns the Provider instance for the given tenant_id and provider_name.
-        If both CUSTOM and System providers exist, the preferred provider will be returned based on the prefer_custom flag.
+        If both CUSTOM and System providers exist.
         """
         query = db.session.query(Provider).filter(
             Provider.tenant_id == tenant_id
@@ -58,39 +62,31 @@ class BaseProvider(ABC):
         if provider_name:
             query = query.filter(Provider.provider_name == provider_name)
 
-        providers = query.order_by(Provider.provider_type.desc() if prefer_custom else Provider.provider_type).all()
+        if only_custom:
+            query = query.filter(Provider.provider_type == ProviderType.CUSTOM.value)
 
-        custom_provider = None
-        system_provider = None
+        providers = query.order_by(Provider.provider_type.asc()).all()
 
         for provider in providers:
             if provider.provider_type == ProviderType.CUSTOM.value and provider.is_valid and provider.encrypted_config:
-                custom_provider = provider
+                return provider
             elif provider.provider_type == ProviderType.SYSTEM.value and provider.is_valid:
-                system_provider = provider
+                return provider
 
-        if custom_provider:
-            return custom_provider
-        elif system_provider:
-            return system_provider
-        else:
         return None
 
-    def get_hosted_credentials(self) -> str:
-        if self.get_provider_name() != ProviderName.OPENAI:
-            raise ProviderTokenNotInitError()
-
-        if not hosted_llm_credentials.openai or not hosted_llm_credentials.openai.api_key:
-            raise ProviderTokenNotInitError()
-
-        return hosted_llm_credentials.openai.api_key
+    def get_hosted_credentials(self) -> Union[str | dict]:
+        raise ProviderTokenNotInitError(
+            f"No valid {self.get_provider_name().value} model provider credentials found. "
+            f"Please go to Settings -> Model Provider to complete your provider credentials."
+        )
 
-    def get_provider_configs(self, obfuscated: bool = False) -> Union[str | dict]:
+    def get_provider_configs(self, obfuscated: bool = False, only_custom: bool = False) -> Union[str | dict]:
         """
         Returns the provider configs.
         """
         try:
-            config = self.get_provider_api_key()
+            config = self.get_provider_api_key(only_custom=only_custom)
         except:
             config = ''
 

api/core/llm/provider/llm_provider_service.py

@@ -31,11 +31,11 @@ class LLMProviderService:
     def get_credentials(self, model_id: Optional[str] = None) -> dict:
         return self.provider.get_credentials(model_id)
 
-    def get_provider_configs(self, obfuscated: bool = False) -> Union[str | dict]:
-        return self.provider.get_provider_configs(obfuscated)
+    def get_provider_configs(self, obfuscated: bool = False, only_custom: bool = False) -> Union[str | dict]:
+        return self.provider.get_provider_configs(obfuscated=obfuscated, only_custom=only_custom)
 
-    def get_provider_db_record(self, prefer_custom: bool = False) -> Optional[Provider]:
-        return self.provider.get_provider(prefer_custom)
+    def get_provider_db_record(self) -> Optional[Provider]:
+        return self.provider.get_provider()
 
     def config_validate(self, config: Union[dict | str]):
         """

api/core/llm/provider/openai_provider.py

@@ -4,6 +4,8 @@ from typing import Optional, Union
 import openai
 from openai.error import AuthenticationError, OpenAIError
 
+from core import hosted_llm_credentials
+from core.llm.error import ProviderTokenNotInitError
 from core.llm.moderation import Moderation
 from core.llm.provider.base import BaseProvider
 from core.llm.provider.errors import ValidateFailedError
@@ -42,3 +44,12 @@ class OpenAIProvider(BaseProvider):
         except Exception as ex:
             logging.exception('OpenAI config validation failed')
             raise ex
+
+    def get_hosted_credentials(self) -> Union[str | dict]:
+        if not hosted_llm_credentials.openai or not hosted_llm_credentials.openai.api_key:
+            raise ProviderTokenNotInitError(
+                f"No valid {self.get_provider_name().value} model provider credentials found. "
+                f"Please go to Settings -> Model Provider to complete your provider credentials."
+            )
+
+        return hosted_llm_credentials.openai.api_key

api/core/llm/streamable_azure_chat_open_ai.py

-from langchain.callbacks.manager import CallbackManagerForLLMRun, AsyncCallbackManagerForLLMRun, Callbacks
-from langchain.schema import BaseMessage, ChatResult, LLMResult
+from langchain.callbacks.manager import Callbacks
+from langchain.schema import BaseMessage, LLMResult
 from langchain.chat_models import AzureChatOpenAI
 from typing import Optional, List, Dict, Any
 
 from pydantic import root_validator
 
-from core.llm.error_handle_wraps import handle_llm_exceptions, handle_llm_exceptions_async
+from core.llm.wrappers.openai_wrapper import handle_openai_exceptions
 
 
 class StreamableAzureChatOpenAI(AzureChatOpenAI):
@@ -46,30 +46,7 @@ class StreamableAzureChatOpenAI(AzureChatOpenAI):
             "organization": self.openai_organization if self.openai_organization else None,
         }
 
-    def get_messages_tokens(self, messages: List[BaseMessage]) -> int:
-        """Get the number of tokens in a list of messages.
-
-        Args:
-            messages: The messages to count the tokens of.
-
-        Returns:
-            The number of tokens in the messages.
-        """
-        tokens_per_message = 5
-        tokens_per_request = 3
-
-        message_tokens = tokens_per_request
-        message_strs = ''
-        for message in messages:
-            message_strs += message.content
-            message_tokens += tokens_per_message
-
-        # calc once
-        message_tokens += self.get_num_tokens(message_strs)
-
-        return message_tokens
-
-    @handle_llm_exceptions
+    @handle_openai_exceptions
     def generate(
             self,
             messages: List[List[BaseMessage]],
@@ -79,12 +56,18 @@ class StreamableAzureChatOpenAI(AzureChatOpenAI):
     ) -> LLMResult:
         return super().generate(messages, stop, callbacks, **kwargs)
 
-    @handle_llm_exceptions_async
-    async def agenerate(
-            self,
-            messages: List[List[BaseMessage]],
-            stop: Optional[List[str]] = None,
-            callbacks: Callbacks = None,
-            **kwargs: Any,
-    ) -> LLMResult:
-        return await super().agenerate(messages, stop, callbacks, **kwargs)
+    @classmethod
+    def get_kwargs_from_model_params(cls, params: dict):
+        model_kwargs = {
+            'top_p': params.get('top_p', 1),
+            'frequency_penalty': params.get('frequency_penalty', 0),
+            'presence_penalty': params.get('presence_penalty', 0),
+        }
+
+        del params['top_p']
+        del params['frequency_penalty']
+        del params['presence_penalty']
+
+        params['model_kwargs'] = model_kwargs
+
+        return params

api/core/llm/streamable_azure_open_ai.py

@@ -5,7 +5,7 @@ from typing import Optional, List, Dict, Mapping, Any
 
 from pydantic import root_validator
 
-from core.llm.error_handle_wraps import handle_llm_exceptions, handle_llm_exceptions_async
+from core.llm.wrappers.openai_wrapper import handle_openai_exceptions
 
 
 class StreamableAzureOpenAI(AzureOpenAI):
@@ -50,7 +50,7 @@ class StreamableAzureOpenAI(AzureOpenAI):
             "organization": self.openai_organization if self.openai_organization else None,
         }}
 
-    @handle_llm_exceptions
+    @handle_openai_exceptions
     def generate(
             self,
             prompts: List[str],
@@ -60,12 +60,6 @@ class StreamableAzureOpenAI(AzureOpenAI):
     ) -> LLMResult:
         return super().generate(prompts, stop, callbacks, **kwargs)
 
-    @handle_llm_exceptions_async
-    async def agenerate(
-            self,
-            prompts: List[str],
-            stop: Optional[List[str]] = None,
-            callbacks: Callbacks = None,
-            **kwargs: Any,
-    ) -> LLMResult:
-        return await super().agenerate(prompts, stop, callbacks, **kwargs)
+    @classmethod
+    def get_kwargs_from_model_params(cls, params: dict):
+        return params

api/core/llm/streamable_chat_anthropic.py

+from typing import List, Optional, Any, Dict
+
+from langchain.callbacks.manager import Callbacks
+from langchain.chat_models import ChatAnthropic
+from langchain.schema import BaseMessage, LLMResult
+
+from core.llm.wrappers.anthropic_wrapper import handle_anthropic_exceptions
+
+
+class StreamableChatAnthropic(ChatAnthropic):
+    """
+    Wrapper around Anthropic's large language model.
+    """
+
+    @handle_anthropic_exceptions
+    def generate(
+            self,
+            messages: List[List[BaseMessage]],
+            stop: Optional[List[str]] = None,
+            callbacks: Callbacks = None,
+            *,
+            tags: Optional[List[str]] = None,
+            metadata: Optional[Dict[str, Any]] = None,
+            **kwargs: Any,
+    ) -> LLMResult:
+        return super().generate(messages, stop, callbacks, tags=tags, metadata=metadata, **kwargs)
+
+    @classmethod
+    def get_kwargs_from_model_params(cls, params: dict):
+        params['model'] = params.get('model_name')
+        del params['model_name']
+
+        params['max_tokens_to_sample'] = params.get('max_tokens')
+        del params['max_tokens']
+
+        del params['frequency_penalty']
+        del params['presence_penalty']
+
+        return params

api/core/llm/streamable_chat_open_ai.py

@@ -7,7 +7,7 @@ from typing import Optional, List, Dict, Any
 
 from pydantic import root_validator
 
-from core.llm.error_handle_wraps import handle_llm_exceptions, handle_llm_exceptions_async
+from core.llm.wrappers.openai_wrapper import handle_openai_exceptions
 
 
 class StreamableChatOpenAI(ChatOpenAI):
@@ -48,30 +48,7 @@ class StreamableChatOpenAI(ChatOpenAI):
             "organization": self.openai_organization if self.openai_organization else None,
         }
 
-    def get_messages_tokens(self, messages: List[BaseMessage]) -> int:
-        """Get the number of tokens in a list of messages.
-
-        Args:
-            messages: The messages to count the tokens of.
-
-        Returns:
-            The number of tokens in the messages.
-        """
-        tokens_per_message = 5
-        tokens_per_request = 3
-
-        message_tokens = tokens_per_request
-        message_strs = ''
-        for message in messages:
-            message_strs += message.content
-            message_tokens += tokens_per_message
-
-        # calc once
-        message_tokens += self.get_num_tokens(message_strs)
-
-        return message_tokens
-
-    @handle_llm_exceptions
+    @handle_openai_exceptions
     def generate(
             self,
             messages: List[List[BaseMessage]],
@@ -81,12 +58,18 @@ class StreamableChatOpenAI(ChatOpenAI):
     ) -> LLMResult:
         return super().generate(messages, stop, callbacks, **kwargs)
 
-    @handle_llm_exceptions_async
-    async def agenerate(
-            self,
-            messages: List[List[BaseMessage]],
-            stop: Optional[List[str]] = None,
-            callbacks: Callbacks = None,
-            **kwargs: Any,
-    ) -> LLMResult:
-        return await super().agenerate(messages, stop, callbacks, **kwargs)
+    @classmethod
+    def get_kwargs_from_model_params(cls, params: dict):
+        model_kwargs = {
+            'top_p': params.get('top_p', 1),
+            'frequency_penalty': params.get('frequency_penalty', 0),
+            'presence_penalty': params.get('presence_penalty', 0),
+        }
+
+        del params['top_p']
+        del params['frequency_penalty']
+        del params['presence_penalty']
+
+        params['model_kwargs'] = model_kwargs
+
+        return params

api/core/llm/streamable_open_ai.py

@@ -6,7 +6,7 @@ from typing import Optional, List, Dict, Any, Mapping
 from langchain import OpenAI
 from pydantic import root_validator
 
-from core.llm.error_handle_wraps import handle_llm_exceptions, handle_llm_exceptions_async
+from core.llm.wrappers.openai_wrapper import handle_openai_exceptions
 
 
 class StreamableOpenAI(OpenAI):
@@ -49,7 +49,7 @@ class StreamableOpenAI(OpenAI):
             "organization": self.openai_organization if self.openai_organization else None,
         }}
 
-    @handle_llm_exceptions
+    @handle_openai_exceptions
     def generate(
             self,
             prompts: List[str],
@@ -59,12 +59,6 @@ class StreamableOpenAI(OpenAI):
     ) -> LLMResult:
         return super().generate(prompts, stop, callbacks, **kwargs)
 
-    @handle_llm_exceptions_async
-    async def agenerate(
-            self,
-            prompts: List[str],
-            stop: Optional[List[str]] = None,
-            callbacks: Callbacks = None,
-            **kwargs: Any,
-    ) -> LLMResult:
-        return await super().agenerate(prompts, stop, callbacks, **kwargs)
+    @classmethod
+    def get_kwargs_from_model_params(cls, params: dict):
+        return params

api/core/llm/whisper.py

 import openai
+
+from core.llm.wrappers.openai_wrapper import handle_openai_exceptions
 from models.provider import ProviderName
-from core.llm.error_handle_wraps import handle_llm_exceptions
 from core.llm.provider.base import BaseProvider
 
 
@@ -13,7 +14,7 @@ class Whisper:
             self.client = openai.Audio
             self.credentials = provider.get_credentials()
 
-    @handle_llm_exceptions
+    @handle_openai_exceptions
     def transcribe(self, file):
         return self.client.transcribe(
             model='whisper-1', 

api/core/llm/wrappers/anthropic_wrapper.py

+import logging
+from functools import wraps
+
+import anthropic
+
+from core.llm.error import LLMAPIConnectionError, LLMAPIUnavailableError, LLMRateLimitError, LLMAuthorizationError, \
+    LLMBadRequestError
+
+
+def handle_anthropic_exceptions(func):
+    @wraps(func)
+    def wrapper(*args, **kwargs):
+        try:
+            return func(*args, **kwargs)
+        except anthropic.APIConnectionError as e:
+            logging.exception("Failed to connect to Anthropic API.")
+            raise LLMAPIConnectionError(f"Anthropic: The server could not be reached, cause: {e.__cause__}")
+        except anthropic.RateLimitError:
+            raise LLMRateLimitError("Anthropic: A 429 status code was received; we should back off a bit.")
+        except anthropic.AuthenticationError as e:
+            raise LLMAuthorizationError(f"Anthropic: {e.message}")
+        except anthropic.BadRequestError as e:
+            raise LLMBadRequestError(f"Anthropic: {e.message}")
+        except anthropic.APIStatusError as e:
+            raise LLMAPIUnavailableError(f"Anthropic: code: {e.status_code}, cause: {e.message}")
+
+    return wrapper

api/core/llm/error_handle_wraps.py → api/core/llm/wrappers/openai_wrapper.py

@@ -7,7 +7,7 @@ from core.llm.error import LLMAPIConnectionError, LLMAPIUnavailableError, LLMRat
     LLMBadRequestError
 
 
-def handle_llm_exceptions(func):
+def handle_openai_exceptions(func):
     @wraps(func)
     def wrapper(*args, **kwargs):
         try:
@@ -29,27 +29,3 @@ def handle_llm_exceptions(func):
             raise LLMBadRequestError(e.__class__.__name__ + ":" + str(e))
 
     return wrapper
-
-
-def handle_llm_exceptions_async(func):
-    @wraps(func)
-    async def wrapper(*args, **kwargs):
-        try:
-            return await func(*args, **kwargs)
-        except openai.error.InvalidRequestError as e:
-            logging.exception("Invalid request to OpenAI API.")
-            raise LLMBadRequestError(str(e))
-        except openai.error.APIConnectionError as e:
-            logging.exception("Failed to connect to OpenAI API.")
-            raise LLMAPIConnectionError(e.__class__.__name__ + ":" + str(e))
-        except (openai.error.APIError, openai.error.ServiceUnavailableError, openai.error.Timeout) as e:
-            logging.exception("OpenAI service unavailable.")
-            raise LLMAPIUnavailableError(e.__class__.__name__ + ":" + str(e))
-        except openai.error.RateLimitError as e:
-            raise LLMRateLimitError(str(e))
-        except openai.error.AuthenticationError as e:
-            raise LLMAuthorizationError(str(e))
-        except openai.error.OpenAIError as e:
-            raise LLMBadRequestError(e.__class__.__name__ + ":" + str(e))
-
-    return wrapper

api/core/memory/read_only_conversation_token_db_buffer_shared_memory.py

 from typing import Any, List, Dict, Union
 
 from langchain.memory.chat_memory import BaseChatMemory
-from langchain.schema import get_buffer_string, BaseMessage, HumanMessage, AIMessage
+from langchain.schema import get_buffer_string, BaseMessage, HumanMessage, AIMessage, BaseLanguageModel
 
 from core.llm.streamable_chat_open_ai import StreamableChatOpenAI
 from core.llm.streamable_open_ai import StreamableOpenAI
@@ -12,8 +12,8 @@ from models.model import Conversation, Message
 class ReadOnlyConversationTokenDBBufferSharedMemory(BaseChatMemory):
     conversation: Conversation
     human_prefix: str = "Human"
-    ai_prefix: str = "AI"
-    llm: Union[StreamableChatOpenAI | StreamableOpenAI]
+    ai_prefix: str = "Assistant"
+    llm: BaseLanguageModel
     memory_key: str = "chat_history"
     max_token_limit: int = 2000
     message_limit: int = 10
@@ -38,12 +38,12 @@ class ReadOnlyConversationTokenDBBufferSharedMemory(BaseChatMemory):
             return chat_messages
 
         # prune the chat message if it exceeds the max token limit
-        curr_buffer_length = self.llm.get_messages_tokens(chat_messages)
+        curr_buffer_length = self.llm.get_num_tokens_from_messages(chat_messages)
         if curr_buffer_length > self.max_token_limit:
             pruned_memory = []
             while curr_buffer_length > self.max_token_limit and chat_messages:
                 pruned_memory.append(chat_messages.pop(0))
-                curr_buffer_length = self.llm.get_messages_tokens(chat_messages)
+                curr_buffer_length = self.llm.get_num_tokens_from_messages(chat_messages)
 
         return chat_messages
 

api/core/tool/dataset_index_tool.py

@@ -30,7 +30,7 @@ class DatasetTool(BaseTool):
         else:
             model_credentials = LLMBuilder.get_model_credentials(
                 tenant_id=self.dataset.tenant_id,
-                model_provider=LLMBuilder.get_default_provider(self.dataset.tenant_id),
+                model_provider=LLMBuilder.get_default_provider(self.dataset.tenant_id, 'text-embedding-ada-002'),
                 model_name='text-embedding-ada-002'
             )
 
@@ -60,7 +60,7 @@ class DatasetTool(BaseTool):
     async def _arun(self, tool_input: str) -> str:
         model_credentials = LLMBuilder.get_model_credentials(
             tenant_id=self.dataset.tenant_id,
-            model_provider=LLMBuilder.get_default_provider(self.dataset.tenant_id),
+            model_provider=LLMBuilder.get_default_provider(self.dataset.tenant_id, 'text-embedding-ada-002'),
             model_name='text-embedding-ada-002'
         )
 

api/events/event_handlers/create_provider_when_tenant_created.py

+from flask import current_app
+
 from events.tenant_event import tenant_was_updated
+from models.provider import ProviderName
 from services.provider_service import ProviderService
 
 
@@ -6,4 +9,16 @@ from services.provider_service import ProviderService
 def handle(sender, **kwargs):
     tenant = sender
     if tenant.status == 'normal':
-        ProviderService.create_system_provider(tenant)
+        ProviderService.create_system_provider(
+            tenant,
+            ProviderName.OPENAI.value,
+            current_app.config['OPENAI_HOSTED_QUOTA_LIMIT'],
+            True
+        )
+
+        ProviderService.create_system_provider(
+            tenant,
+            ProviderName.ANTHROPIC.value,
+            current_app.config['ANTHROPIC_HOSTED_QUOTA_LIMIT'],
+            True
+        )

api/events/event_handlers/create_provider_when_tenant_updated.py

+from flask import current_app
+
 from events.tenant_event import tenant_was_created
+from models.provider import ProviderName
 from services.provider_service import ProviderService
 
 
@@ -6,4 +9,16 @@ from services.provider_service import ProviderService
 def handle(sender, **kwargs):
     tenant = sender
     if tenant.status == 'normal':
-        ProviderService.create_system_provider(tenant)
+        ProviderService.create_system_provider(
+            tenant,
+            ProviderName.OPENAI.value,
+            current_app.config['OPENAI_HOSTED_QUOTA_LIMIT'],
+            True
+        )
+
+        ProviderService.create_system_provider(
+            tenant,
+            ProviderName.ANTHROPIC.value,
+            current_app.config['ANTHROPIC_HOSTED_QUOTA_LIMIT'],
+            True
+        )

api/requirements.txt

@@ -10,7 +10,7 @@ flask-session2==1.3.1
 flask-cors==3.0.10
 gunicorn~=20.1.0
 gevent~=22.10.2
-langchain==0.0.209
+langchain==0.0.230
 openai~=0.27.5
 psycopg2-binary~=2.9.6
 pycryptodome==3.17
@@ -35,3 +35,4 @@ docx2txt==0.8
 pypdfium2==4.16.0
 resend~=0.5.1
 pyjwt~=2.6.0
+anthropic~=0.3.4

api/services/app_model_config_service.py

@@ -6,6 +6,30 @@ from models.account import Account
 from services.dataset_service import DatasetService
 from core.llm.llm_builder import LLMBuilder
 
+MODEL_PROVIDERS = [
+    'openai',
+    'anthropic',
+]
+
+MODELS_BY_APP_MODE = {
+    'chat': [
+        'claude-instant-1',
+        'claude-2',
+        'gpt-4',
+        'gpt-4-32k',
+        'gpt-3.5-turbo',
+        'gpt-3.5-turbo-16k',
+    ],
+    'completion': [
+        'claude-instant-1',
+        'claude-2',
+        'gpt-4',
+        'gpt-4-32k',
+        'gpt-3.5-turbo',
+        'gpt-3.5-turbo-16k',
+        'text-davinci-003',
+    ]
+}
 
 class AppModelConfigService:
     @staticmethod
@@ -125,7 +149,7 @@ 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)
+        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")
@@ -153,14 +177,14 @@ class AppModelConfigService:
             raise ValueError("model must be of object type")
 
         # model.provider
-        if 'provider' not in config["model"] or config["model"]["provider"] != "openai":
-            raise ValueError("model.provider must be 'openai'")
+        if 'provider' not in config["model"] or config["model"]["provider"] not in MODEL_PROVIDERS:
+            raise ValueError(f"model.provider is required and must be in {str(MODEL_PROVIDERS)}")
 
         # model.name
         if 'name' not in config["model"]:
             raise ValueError("model.name is required")
 
-        if config["model"]["name"] not in llm_constant.models_by_mode[mode]:
+        if config["model"]["name"] not in MODELS_BY_APP_MODE[mode]:
             raise ValueError("model.name must be in the specified model list")
 
         # model.completion_params

api/services/audio_service.py

@@ -27,7 +27,7 @@ class AudioService:
             message = f"Audio size larger than {FILE_SIZE} mb"
             raise AudioTooLargeServiceError(message)
         
-        provider_name = LLMBuilder.get_default_provider(tenant_id)
+        provider_name = LLMBuilder.get_default_provider(tenant_id, 'whisper-1')
         if provider_name != ProviderName.OPENAI.value:
             raise ProviderNotSupportSpeechToTextServiceError()
 
@@ -37,8 +37,3 @@ class AudioService:
         buffer.name = 'temp.mp3'
 
         return Whisper(provider_service.provider).transcribe(buffer)
-
-
-
-        
-        
\ No newline at end of file

api/services/dataset_service.py

@@ -4,6 +4,9 @@ import datetime
 import time
 import random
 from typing import Optional, List
+
+from flask import current_app
+
 from extensions.ext_redis import redis_client
 from flask_login import current_user
 
@@ -374,6 +377,12 @@ class DocumentService:
     def save_document_with_dataset_id(dataset: Dataset, document_data: dict,
                                       account: Account, dataset_process_rule: Optional[DatasetProcessRule] = None,
                                       created_from: str = 'web'):
+        # check document limit
+        if current_app.config['EDITION'] == 'CLOUD':
+            documents_count = DocumentService.get_tenant_documents_count()
+            tenant_document_count = int(current_app.config['TENANT_DOCUMENT_COUNT'])
+            if documents_count > tenant_document_count:
+                raise ValueError(f"over document limit {tenant_document_count}.")
         # if dataset is empty, update dataset data_source_type
         if not dataset.data_source_type:
             dataset.data_source_type = document_data["data_source"]["type"]
@@ -521,6 +530,14 @@ class DocumentService:
         )
         return document
 
+    @staticmethod
+    def get_tenant_documents_count():
+        documents_count = Document.query.filter(Document.completed_at.isnot(None),
+                                                Document.enabled == True,
+                                                Document.archived == False,
+                                                Document.tenant_id == current_user.current_tenant_id).count()
+        return documents_count
+
     @staticmethod
     def update_document_with_dataset_id(dataset: Dataset, document_data: dict,
                                         account: Account, dataset_process_rule: Optional[DatasetProcessRule] = None,
@@ -616,6 +633,12 @@ class DocumentService:
 
     @staticmethod
     def save_document_without_dataset_id(tenant_id: str, document_data: dict, account: Account):
+        # check document limit
+        if current_app.config['EDITION'] == 'CLOUD':
+            documents_count = DocumentService.get_tenant_documents_count()
+            tenant_document_count = int(current_app.config['TENANT_DOCUMENT_COUNT'])
+            if documents_count > tenant_document_count:
+                raise ValueError(f"over document limit {tenant_document_count}.")
         # save dataset
         dataset = Dataset(
             tenant_id=tenant_id,

api/services/hit_testing_service.py

@@ -31,7 +31,7 @@ class HitTestingService:
 
         model_credentials = LLMBuilder.get_model_credentials(
             tenant_id=dataset.tenant_id,
-            model_provider=LLMBuilder.get_default_provider(dataset.tenant_id),
+            model_provider=LLMBuilder.get_default_provider(dataset.tenant_id, 'text-embedding-ada-002'),
             model_name='text-embedding-ada-002'
         )
 

api/services/provider_service.py

@@ -10,50 +10,40 @@ from models.provider import *
 class ProviderService:
 
     @staticmethod
-    def init_supported_provider(tenant, edition):
+    def init_supported_provider(tenant):
         """Initialize the model provider, check whether the supported provider has a record"""
 
-        providers = Provider.query.filter_by(tenant_id=tenant.id).all()
+        need_init_provider_names = [ProviderName.OPENAI.value, ProviderName.AZURE_OPENAI.value, ProviderName.ANTHROPIC.value]
 
-        openai_provider_exists = False
-        azure_openai_provider_exists = False
-
-        # TODO: The cloud version needs to construct the data of the SYSTEM type
+        providers = db.session.query(Provider).filter(
+            Provider.tenant_id == tenant.id,
+            Provider.provider_type == ProviderType.CUSTOM.value,
+            Provider.provider_name.in_(need_init_provider_names)
+        ).all()
 
+        exists_provider_names = []
         for provider in providers:
-            if provider.provider_name == ProviderName.OPENAI.value and provider.provider_type == ProviderType.CUSTOM.value:
-                openai_provider_exists = True
-            if provider.provider_name == ProviderName.AZURE_OPENAI.value and provider.provider_type == ProviderType.CUSTOM.value:
-                azure_openai_provider_exists = True
-
-        # Initialize the model provider, check whether the supported provider has a record
+            exists_provider_names.append(provider.provider_name)
 
-        # Create default providers if they don't exist
-        if not openai_provider_exists:
-            openai_provider = Provider(
-                tenant_id=tenant.id,
-                provider_name=ProviderName.OPENAI.value,
-                provider_type=ProviderType.CUSTOM.value,
-                is_valid=False
-            )
-            db.session.add(openai_provider)
+        not_exists_provider_names = list(set(need_init_provider_names) - set(exists_provider_names))
 
-        if not azure_openai_provider_exists:
-            azure_openai_provider = Provider(
+        if not_exists_provider_names:
+            # Initialize the model provider, check whether the supported provider has a record
+            for provider_name in not_exists_provider_names:
+                provider = Provider(
                     tenant_id=tenant.id,
-                provider_name=ProviderName.AZURE_OPENAI.value,
+                    provider_name=provider_name,
                     provider_type=ProviderType.CUSTOM.value,
                     is_valid=False
                 )
-            db.session.add(azure_openai_provider)
+                db.session.add(provider)
 
-        if not openai_provider_exists or not azure_openai_provider_exists:
             db.session.commit()
 
     @staticmethod
-    def get_obfuscated_api_key(tenant, provider_name: ProviderName):
+    def get_obfuscated_api_key(tenant, provider_name: ProviderName, only_custom: bool = False):
         llm_provider_service = LLMProviderService(tenant.id, provider_name.value)
-        return llm_provider_service.get_provider_configs(obfuscated=True)
+        return llm_provider_service.get_provider_configs(obfuscated=True, only_custom=only_custom)
 
     @staticmethod
     def get_token_type(tenant, provider_name: ProviderName):
@@ -73,7 +63,7 @@ class ProviderService:
         return llm_provider_service.get_encrypted_token(configs)
 
     @staticmethod
-    def create_system_provider(tenant: Tenant, provider_name: str = ProviderName.OPENAI.value,
+    def create_system_provider(tenant: Tenant, provider_name: str = ProviderName.OPENAI.value, quota_limit: int = 200,
                                is_valid: bool = True):
         if current_app.config['EDITION'] != 'CLOUD':
             return
@@ -90,7 +80,7 @@ class ProviderService:
                 provider_name=provider_name,
                 provider_type=ProviderType.SYSTEM.value,
                 quota_type=ProviderQuotaType.TRIAL.value,
-                quota_limit=200,
+                quota_limit=quota_limit,
                 encrypted_config='',
                 is_valid=is_valid,
             )

api/services/workspace_service.py

 from extensions.ext_database import db
 from models.account import Tenant
-from models.provider import Provider, ProviderType
+from models.provider import Provider, ProviderType, ProviderName
 
 
 class WorkspaceService:
@@ -33,7 +33,7 @@ class WorkspaceService:
                 if provider.is_valid and provider.encrypted_config:
                     custom_provider = provider
             elif provider.provider_type == ProviderType.SYSTEM.value:
-                if provider.is_valid:
+                if provider.provider_name == ProviderName.OPENAI.value and provider.is_valid:
                     system_provider = provider
 
         if system_provider and not custom_provider:

docker/docker-compose.yaml

@@ -2,7 +2,7 @@ version: '3.1'
 services:
   # API service
   api:
-    image: langgenius/dify-api:0.3.8
+    image: langgenius/dify-api:0.3.9
     restart: always
     environment:
       # Startup mode, 'api' starts the API server.
@@ -124,7 +124,7 @@ services:
   # worker service
   # The Celery worker for processing the queue.
   worker:
-    image: langgenius/dify-api:0.3.8
+    image: langgenius/dify-api:0.3.9
     restart: always
     environment:
       # Startup mode, 'worker' starts the Celery worker for processing the queue.
@@ -176,7 +176,7 @@ services:
 
   # Frontend web application.
   web:
-    image: langgenius/dify-web:0.3.8
+    image: langgenius/dify-web:0.3.9
     restart: always
     environment:
       EDITION: SELF_HOSTED

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

@@ -65,6 +65,7 @@ export type IChatProps = {
   isShowSuggestion?: boolean
   suggestionList?: string[]
   isShowSpeechToText?: boolean
+  answerIconClassName?: string
 }
 
 export type MessageMore = {
@@ -174,10 +175,11 @@ type IAnswerProps = {
   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 }) => {
+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)
@@ -292,7 +294,7 @@ const Answer: FC<IAnswerProps> = ({ item, feedbackDisabled = false, isHideFeedba
   return (
     <div key={id}>
       <div className='flex items-start'>
-        <div className={`${s.answerIcon} w-10 h-10 shrink-0`}>
+        <div className={`${s.answerIcon} ${answerIconClassName} w-10 h-10 shrink-0`}>
           {isResponsing
             && <div className={s.typeingIcon}>
               <LoadingAnim type='avatar' />
@@ -428,6 +430,7 @@ const Chat: FC<IChatProps> = ({
   isShowSuggestion,
   suggestionList,
   isShowSpeechToText,
+  answerIconClassName,
 }) => {
   const { t } = useTranslation()
   const { notify } = useContext(ToastContext)
@@ -520,6 +523,7 @@ const Chat: FC<IChatProps> = ({
               onSubmitAnnotation={onSubmitAnnotation}
               displayScene={displayScene ?? 'web'}
               isResponsing={isResponsing && isLast}
+              answerIconClassName={answerIconClassName}
             />
           }
           return <Question key={item.id} id={item.id} content={item.content} more={item.more} useCurrentUserAvatar={useCurrentUserAvatar} />

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

@@ -372,7 +372,7 @@ const Debug: FC<IDebug> = ({
         {/* Chat */}
         {mode === AppType.chat && (
           <div className="mt-[34px] h-full flex flex-col">
-            <div className={cn(doShowSuggestion ? 'pb-[140px]' : (isResponsing ? 'pb-[113px]' : 'pb-[66px]'), 'relative mt-1.5 grow h-[200px] overflow-hidden')}>
+            <div className={cn(doShowSuggestion ? 'pb-[140px]' : (isResponsing ? 'pb-[113px]' : 'pb-[76px]'), 'relative mt-1.5 grow h-[200px] overflow-hidden')}>
               <div className="h-full overflow-y-auto overflow-x-hidden" ref={chatListDomRef}>
                 <Chat
                   chatList={chatList}

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

@@ -16,6 +16,7 @@ import ConfigModel from '@/app/components/app/configuration/config-model'
 import Config from '@/app/components/app/configuration/config'
 import Debug from '@/app/components/app/configuration/debug'
 import Confirm from '@/app/components/base/confirm'
+import { ProviderType } from '@/types/app'
 import type { AppDetailResponse } from '@/models/app'
 import { ToastContext } from '@/app/components/base/toast'
 import { fetchTenantInfo } from '@/service/common'
@@ -67,7 +68,7 @@ const Configuration: FC = () => {
     frequency_penalty: 1, // -2-2
   })
   const [modelConfig, doSetModelConfig] = useState<ModelConfig>({
-    provider: 'openai',
+    provider: ProviderType.openai,
     model_id: 'gpt-3.5-turbo',
     configs: {
       prompt_template: '',
@@ -84,8 +85,9 @@ const Configuration: FC = () => {
     doSetModelConfig(newModelConfig)
   }
 
-  const setModelId = (modelId: string) => {
+  const setModelId = (modelId: string, provider: ProviderType) => {
     const newModelConfig = produce(modelConfig, (draft: any) => {
+      draft.provider = provider
       draft.model_id = modelId
     })
     setModelConfig(newModelConfig)

web/app/components/app/text-generate/item/index.tsx

@@ -184,7 +184,11 @@ const GenerationItem: FC<IGenerationItemProps> = ({
                 {taskId}
               </div>)
             }
+            <div className='flex'>
+              <div className='grow w-0'>
                 <Markdown content={content} />
+              </div>
+            </div>
             {messageId && (
               <div className='flex items-center justify-between mt-3'>
                 <div className='flex items-center'>

web/app/components/base/auto-height-textarea/index.tsx

@@ -19,6 +19,7 @@ const AutoHeightTextarea = forwardRef(
     { value, onChange, placeholder, className, minHeight = 36, maxHeight = 96, autoFocus, controlFocus, onKeyDown, onKeyUp }: IProps,
     outerRef: any,
   ) => {
+    // eslint-disable-next-line react-hooks/rules-of-hooks
     const ref = outerRef || useRef<HTMLTextAreaElement>(null)
 
     const doFocus = () => {
@@ -54,13 +55,20 @@ const AutoHeightTextarea = forwardRef(
 
     return (
       <div className='relative'>
-        <div className={cn(className, 'invisible whitespace-pre-wrap break-all  overflow-y-auto')} style={{ minHeight, maxHeight }}>
+        <div className={cn(className, 'invisible whitespace-pre-wrap break-all  overflow-y-auto')} style={{
+          minHeight,
+          maxHeight,
+          paddingRight: (value && value.trim().length > 10000) ? 140 : 130,
+        }}>
           {!value ? placeholder : value.replace(/\n$/, '\n ')}
         </div>
         <textarea
           ref={ref}
           autoFocus={autoFocus}
-          className={cn(className, 'absolute inset-0 resize-none overflow-hidden')}
+          className={cn(className, 'absolute inset-0 resize-none overflow-auto')}
+          style={{
+            paddingRight: (value && value.trim().length > 10000) ? 140 : 130,
+          }}
           placeholder={placeholder}
           onChange={onChange}
           onKeyDown={onKeyDown}

web/app/components/browser-initor.tsx

+'use client'
+
+class StorageMock {
+  data: Record<string, string>
+
+  constructor() {
+    this.data = {} as Record<string, string>
+  }
+
+  setItem(name: string, value: string) {
+    this.data[name] = value
+  }
+
+  getItem(name: string) {
+    return this.data[name] || null
+  }
+
+  removeItem(name: string) {
+    delete this.data[name]
+  }
+
+  clear() {
+    this.data = {}
+  }
+}
+
+let localStorage, sessionStorage
+
+try {
+  localStorage = globalThis.localStorage
+  sessionStorage = globalThis.sessionStorage
+}
+catch (e) {
+  localStorage = new StorageMock()
+  sessionStorage = new StorageMock()
+}
+
+Object.defineProperty(globalThis, 'localStorage', {
+  value: localStorage,
+})
+
+Object.defineProperty(globalThis, 'sessionStorage', {
+  value: sessionStorage,
+})
+
+const BrowerInitor = ({
+  children,
+}: { children: React.ReactElement }) => {
+  return children
+}
+
+export default BrowerInitor

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

@@ -13,6 +13,7 @@ import { useAppContext } from '@/context/app-context'
 import { ToastContext } from '@/app/components/base/toast'
 import AppIcon from '@/app/components/base/app-icon'
 import Avatar from '@/app/components/base/avatar'
+import { IS_CE_EDITION } from '@/config'
 
 const titleClassName = `
   text-sm font-medium text-gray-900
@@ -136,11 +137,13 @@ export default function AccountPage() {
         <div className={titleClassName}>{t('common.account.email')}</div>
         <div className={classNames(inputClassName, 'cursor-pointer')}>{userProfile.email}</div>
       </div>
+      {IS_CE_EDITION && (
         <div className='mb-8'>
           <div className='mb-1 text-sm font-medium text-gray-900'>{t('common.account.password')}</div>
           <div className='mb-2 text-xs text-gray-500'>{t('common.account.passwordTip')}</div>
           <Button className='font-medium !text-gray-700 !px-3 !py-[7px] !text-[13px]' onClick={() => setEditPasswordModalVisible(true)}>{userProfile.is_password_set ? t('common.account.resetPassword') : t('common.account.setPassword')}</Button>
         </div>
+      )}
       {!!apps.length && (
         <>
           <div className='mb-6 border-[0.5px] border-gray-100' />

web/app/components/header/account-setting/members-page/invited-modal/index.tsx

@@ -5,6 +5,8 @@ import InvitationLink from './invitation-link'
 import s from './index.module.css'
 import Modal from '@/app/components/base/modal'
 import Button from '@/app/components/base/button'
+import { IS_CE_EDITION } from '@/config'
+
 type IInvitedModalProps = {
   invitationLink: string
   onCancel: () => void
@@ -29,11 +31,18 @@ const InvitedModal = ({
           <XMarkIcon className='w-4 h-4 cursor-pointer' onClick={onCancel} />
         </div>
         <div className='mb-1 text-xl font-semibold text-gray-900'>{t('common.members.invitationSent')}</div>
+        {!IS_CE_EDITION && (
+          <div className='mb-10 text-sm text-gray-500'>{t('common.members.invitationSentTip')}</div>
+        )}
+        {IS_CE_EDITION && (
+          <>
             <div className='mb-5 text-sm text-gray-500'>{t('common.members.invitationSentTip')}</div>
             <div className='mb-9'>
               <div className='py-2 text-sm font-Medium text-gray-900'>{t('common.members.invitationLink')}</div>
               <InvitationLink value={invitationLink} />
             </div>
+          </>
+        )}
         <div className='flex justify-end'>
           <Button
             className='w-[96px] text-sm font-medium'

web/app/components/header/account-setting/provider-page/anthropic-hosted-provider/index.module.css

+.icon {
+  width: 24px;
+  height: 24px;
+  margin-right: 12px;
+  background: url(../../../assets/anthropic.svg) center center no-repeat;
+  background-size: contain;
+}
+
+.bar {
+  background: linear-gradient(90deg, rgba(41, 112, 255, 0.9) 0%, rgba(21, 94, 239, 0.9) 100%);
+}
+
+.bar-error {
+  background: linear-gradient(90deg, rgba(240, 68, 56, 0.72) 0%, rgba(217, 45, 32, 0.9) 100%);
+}
+
+.bar-item {
+  width: 10%;
+  border-right: 1px solid rgba(255, 255, 255, 0.5);
+}
+
+.bar-item:last-of-type {
+  border-right: 0;
+}
\ No newline at end of file

web/app/components/header/account-setting/provider-page/anthropic-hosted-provider/index.tsx

+import { useTranslation } from 'react-i18next'
+import cn from 'classnames'
+import s from './index.module.css'
+import type { ProviderHosted } from '@/models/common'
+
+type AnthropicHostedProviderProps = {
+  provider: ProviderHosted
+}
+const AnthropicHostedProvider = ({
+  provider,
+}: AnthropicHostedProviderProps) => {
+  const { t } = useTranslation()
+  const exhausted = provider.quota_used > provider.quota_limit
+
+  return (
+    <div className={`
+      border-[0.5px] border-gray-200 rounded-xl
+      ${exhausted ? 'bg-[#FFFBFA]' : 'bg-gray-50'}
+    `}>
+      <div className='pt-4 px-4 pb-3'>
+        <div className='flex items-center mb-3'>
+          <div className={s.icon} />
+          <div className='grow text-sm font-medium text-gray-800'>
+            {t('common.provider.anthropicHosted.anthropicHosted')}
+          </div>
+          <div className={`
+            px-2 h-[22px] flex items-center rounded-md border 
+            text-xs font-semibold 
+            ${exhausted ? 'border-[#D92D20] text-[#D92D20]' : 'border-primary-600 text-primary-600'}
+          `}>
+            {exhausted ? t('common.provider.anthropicHosted.exhausted') : t('common.provider.anthropicHosted.onTrial')}
+          </div>
+        </div>
+        <div className='text-[13px] text-gray-500'>{t('common.provider.anthropicHosted.desc')}</div>
+      </div>
+      <div className='flex items-center h-[42px] px-4 border-t-[0.5px] border-t-[rgba(0, 0, 0, 0.05)]'>
+        <div className='text-[13px] text-gray-700'>{t('common.provider.anthropicHosted.callTimes')}</div>
+        <div className='relative grow h-2 flex bg-gray-200 rounded-md mx-2 overflow-hidden'>
+          <div
+            className={cn(s.bar, exhausted && s['bar-error'], 'absolute top-0 left-0 right-0 bottom-0')}
+            style={{ width: `${(provider.quota_used / provider.quota_limit * 100).toFixed(2)}%` }}
+          />
+          {Array(10).fill(0).map((i, k) => (
+            <div key={k} className={s['bar-item']} />
+          ))}
+        </div>
+        <div className={`
+          text-[13px] font-medium ${exhausted ? 'text-[#D92D20]' : 'text-gray-700'}
+        `}>{provider.quota_used}/{provider.quota_limit}</div>
+      </div>
+      {
+        exhausted && (
+          <div className='
+            px-4 py-3 leading-[18px] flex items-center text-[13px] text-gray-700 font-medium
+            bg-[#FFFAEB] border-t border-t-[rgba(0, 0, 0, 0.05)] rounded-b-xl
+          '>
+            {t('common.provider.anthropicHosted.usedUp')}
+          </div>
+        )
+      }
+    </div>
+  )
+}
+
+export default AnthropicHostedProvider

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

+import { useEffect, useState } from 'react'
+import { useTranslation } from 'react-i18next'
+import Link from 'next/link'
+import { ArrowTopRightOnSquareIcon } from '@heroicons/react/24/outline'
+import ProviderInput from '../provider-input'
+import type { ValidatedStatusState } from '../provider-input/useValidateToken'
+import useValidateToken, { ValidatedStatus } from '../provider-input/useValidateToken'
+import {
+  ValidatedErrorIcon,
+  ValidatedErrorOnOpenaiTip,
+  ValidatedSuccessIcon,
+  ValidatingTip,
+} from '../provider-input/Validate'
+import type { Provider, ProviderAnthropicToken } from '@/models/common'
+
+type AnthropicProviderProps = {
+  provider: Provider
+  onValidatedStatus: (status?: ValidatedStatusState) => void
+  onTokenChange: (token: ProviderAnthropicToken) => void
+}
+
+const AnthropicProvider = ({
+  provider,
+  onValidatedStatus,
+  onTokenChange,
+}: AnthropicProviderProps) => {
+  const { t } = useTranslation()
+  const [token, setToken] = useState<ProviderAnthropicToken>((provider.token as ProviderAnthropicToken) || { anthropic_api_key: '' })
+  const [validating, validatedStatus, setValidatedStatus, validate] = useValidateToken(provider.provider_name)
+  const handleFocus = () => {
+    if (token.anthropic_api_key === (provider.token as ProviderAnthropicToken).anthropic_api_key) {
+      setToken({ anthropic_api_key: '' })
+      onTokenChange({ anthropic_api_key: '' })
+      setValidatedStatus({})
+    }
+  }
+  const handleChange = (v: string) => {
+    const apiKey = { anthropic_api_key: v }
+    setToken(apiKey)
+    onTokenChange(apiKey)
+    validate(apiKey, {
+      beforeValidating: () => {
+        if (!v) {
+          setValidatedStatus({})
+          return false
+        }
+        return true
+      },
+    })
+  }
+  useEffect(() => {
+    if (typeof onValidatedStatus === 'function')
+      onValidatedStatus(validatedStatus)
+  }, [validatedStatus])
+
+  const getValidatedIcon = () => {
+    if (validatedStatus?.status === ValidatedStatus.Error || validatedStatus.status === ValidatedStatus.Exceed)
+      return <ValidatedErrorIcon />
+
+    if (validatedStatus.status === ValidatedStatus.Success)
+      return <ValidatedSuccessIcon />
+  }
+  const getValidatedTip = () => {
+    if (validating)
+      return <ValidatingTip />
+
+    if (validatedStatus?.status === ValidatedStatus.Error)
+      return <ValidatedErrorOnOpenaiTip errorMessage={validatedStatus.message ?? ''} />
+  }
+
+  return (
+    <div className='px-4 pt-3 pb-4'>
+      <ProviderInput
+        value={token.anthropic_api_key}
+        name={t('common.provider.apiKey')}
+        placeholder={t('common.provider.enterYourKey')}
+        onChange={handleChange}
+        onFocus={handleFocus}
+        validatedIcon={getValidatedIcon()}
+        validatedTip={getValidatedTip()}
+      />
+      <Link className="inline-flex items-center mt-3 text-xs font-normal cursor-pointer text-primary-600 w-fit" href="https://docs.anthropic.com/claude/reference/getting-started-with-the-api" target={'_blank'}>
+        {t('common.provider.anthropic.keyFrom')}
+        <ArrowTopRightOnSquareIcon className='w-3 h-3 ml-1 text-primary-600' aria-hidden="true" />
+      </Link>
+    </div>
+  )
+}
+
+export default AnthropicProvider

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

@@ -5,6 +5,7 @@ import { useTranslation } from 'react-i18next'
 import Link from 'next/link'
 import ProviderItem from './provider-item'
 import OpenaiHostedProvider from './openai-hosted-provider'
+import AnthropicHostedProvider from './anthropic-hosted-provider'
 import type { ProviderHosted } from '@/models/common'
 import { fetchProviders } from '@/service/common'
 import { IS_CE_EDITION } from '@/config'
@@ -18,6 +19,10 @@ const providersMap: { [k: string]: any } = {
     icon: 'azure',
     name: 'Azure OpenAI Service',
   },
+  'anthropic-custom': {
+    icon: 'anthropic',
+    name: 'Anthropic',
+  },
 }
 
 // const providersList = [
@@ -65,6 +70,8 @@ const ProviderPage = () => {
     }
   })
   const providerHosted = data?.filter(provider => provider.provider_name === 'openai' && provider.provider_type === 'system')?.[0]
+  const anthropicHosted = data?.filter(provider => provider.provider_name === 'anthropic' && provider.provider_type === 'system')?.[0]
+  const providedOpenaiProvider = data?.find(provider => provider.is_enabled && (provider.provider_name === 'openai' || provider.provider_name === 'azure_openai'))
 
   return (
     <div className='pb-7'>
@@ -78,6 +85,16 @@ const ProviderPage = () => {
           </>
         )
       }
+      {
+        anthropicHosted && !IS_CE_EDITION && (
+          <>
+            <div>
+              <AnthropicHostedProvider provider={anthropicHosted as ProviderHosted} />
+            </div>
+            <div className='my-5 w-full h-0 border-[0.5px] border-gray-100' />
+          </>
+        )
+      }
       <div>
         {
           providers?.map(providerItem => (
@@ -89,11 +106,12 @@ const ProviderPage = () => {
               activeId={activeProviderId}
               onActive={aid => setActiveProviderId(aid)}
               onSave={() => mutate()}
+              providedOpenaiProvider={providedOpenaiProvider}
             />
           ))
         }
       </div>
-      <div className='absolute bottom-0 w-full h-[42px] flex items-center bg-white text-xs text-gray-500'>
+      <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

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

@@ -5,14 +5,20 @@ import { useTranslation } from 'react-i18next'
 import Indicator from '../../../indicator'
 import OpenaiProvider from '../openai-provider'
 import AzureProvider from '../azure-provider'
+import AnthropicProvider from '../anthropic-provider'
 import type { ValidatedStatusState } from '../provider-input/useValidateToken'
 import { ValidatedStatus } from '../provider-input/useValidateToken'
 import s from './index.module.css'
-import type { Provider, ProviderAzureToken } from '@/models/common'
+import type { Provider, ProviderAnthropicToken, ProviderAzureToken } from '@/models/common'
 import { ProviderName } from '@/models/common'
 import { updateProviderAIKey } from '@/service/common'
 import { ToastContext } from '@/app/components/base/toast'
+import Tooltip from '@/app/components/base/tooltip'
 
+const providerNameMap: Record<string, string> = {
+  openai: 'OpenAI',
+  azure_openai: 'Azure OpenAI Service',
+}
 type IProviderItemProps = {
   icon: string
   name: string
@@ -20,6 +26,7 @@ type IProviderItemProps = {
   activeId: string
   onActive: (v: string) => void
   onSave: () => void
+  providedOpenaiProvider?: Provider
 }
 const ProviderItem = ({
   activeId,
@@ -28,14 +35,17 @@ const ProviderItem = ({
   provider,
   onActive,
   onSave,
+  providedOpenaiProvider,
 }: IProviderItemProps) => {
   const { t } = useTranslation()
   const [validatedStatus, setValidatedStatus] = useState<ValidatedStatusState>()
   const [loading, setLoading] = useState(false)
   const { notify } = useContext(ToastContext)
-  const [token, setToken] = useState<ProviderAzureToken | string>(
+  const [token, setToken] = useState<ProviderAzureToken | string | ProviderAnthropicToken>(
     provider.provider_name === 'azure_openai'
       ? { openai_api_base: '', openai_api_key: '' }
+      : provider.provider_name === 'anthropic'
+        ? { anthropic_api_key: '' }
         : '',
   )
   const id = `${provider.provider_name}-${provider.provider_type}`
@@ -54,6 +64,8 @@ const ProviderItem = ({
     }
     if (provider.provider_name === ProviderName.OPENAI)
       return provider.token
+    if (provider.provider_name === ProviderName.ANTHROPIC)
+      return provider.token?.anthropic_api_key
   }
   const handleUpdateToken = async () => {
     if (loading)
@@ -81,7 +93,7 @@ const ProviderItem = ({
         <div className={cn(s[`icon-${icon}`], 'mr-3 w-6 h-6 rounded-md')} />
         <div className='grow text-sm font-medium text-gray-800'>{name}</div>
         {
-          providerTokenHasSetted() && !comingSoon && !isOpen && (
+          providerTokenHasSetted() && !comingSoon && !isOpen && provider.provider_name !== ProviderName.ANTHROPIC && (
             <div className='flex items-center mr-4'>
               {!isValid && <div className='text-xs text-[#D92D20]'>{t('common.provider.invalidApiKey')}</div>}
               <Indicator color={!isValid ? 'red' : 'green'} className='ml-2' />
@@ -89,7 +101,27 @@ const ProviderItem = ({
           )
         }
         {
-          !comingSoon && !isOpen && (
+          (providerTokenHasSetted() && !comingSoon && !isOpen && provider.provider_name === ProviderName.ANTHROPIC) && (
+            <div className='flex items-center mr-4'>
+              {
+                providedOpenaiProvider?.is_valid
+                  ? !isValid
+                    ? <div className='text-xs text-[#D92D20]'>{t('common.provider.invalidApiKey')}</div>
+                    : null
+                  : <div className='text-xs text-[#DC6803]'>{t('common.provider.anthropic.notEnabled')}</div>
+              }
+              <Indicator color={
+                providedOpenaiProvider?.is_valid
+                  ? isValid
+                    ? 'green'
+                    : 'red'
+                  : 'yellow'
+              } className='ml-2' />
+            </div>
+          )
+        }
+        {
+          !comingSoon && !isOpen && provider.provider_name !== ProviderName.ANTHROPIC && (
             <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
@@ -98,6 +130,34 @@ const ProviderItem = ({
             </div>
           )
         }
+        {
+          (!comingSoon && !isOpen && provider.provider_name === ProviderName.ANTHROPIC)
+            ? providedOpenaiProvider?.is_enabled
+              ? (
+                <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={() => providedOpenaiProvider.is_valid && onActive(id)}>
+                  {providerTokenHasSetted() ? t('common.provider.editKey') : t('common.provider.addKey')}
+                </div>
+              )
+              : (
+                <Tooltip
+                  htmlContent={<div className='w-[320px]'>
+                    {t('common.provider.anthropic.enableTip')}
+                  </div>}
+                  position='bottom'
+                  selector='anthropic-provider-enable-top-tooltip'>
+                  <div className='
+                    px-3 h-[28px] bg-white border border-gray-200 rounded-md cursor-not-allowed
+                    text-xs font-medium text-gray-700 flex items-center opacity-50
+                  '>
+                    {t('common.provider.addKey')}
+                  </div>
+                </Tooltip>
+              )
+            : null
+        }
         {
           comingSoon && !isOpen && (
             <div className='
@@ -147,6 +207,29 @@ const ProviderItem = ({
           />
         )
       }
+      {
+        provider.provider_name === ProviderName.ANTHROPIC && isOpen && (
+          <AnthropicProvider
+            provider={provider}
+            onValidatedStatus={v => setValidatedStatus(v)}
+            onTokenChange={v => setToken(v)}
+          />
+        )
+      }
+      {
+        provider.provider_name === ProviderName.ANTHROPIC && !isOpen && providerTokenHasSetted() && providedOpenaiProvider?.is_valid && (
+          <div className='px-4 py-3 text-[13px] font-medium text-gray-700'>
+            {t('common.provider.anthropic.using')} {providerNameMap[providedOpenaiProvider.provider_name as string]}
+          </div>
+        )
+      }
+      {
+        provider.provider_name === ProviderName.ANTHROPIC && !isOpen && providerTokenHasSetted() && !providedOpenaiProvider?.is_valid && (
+          <div className='px-4 py-3 bg-[#FFFAEB] text-[13px] font-medium text-gray-700'>
+            {t('common.provider.anthropic.enableTip')}
+          </div>
+        )
+      }
     </div>
   )
 }

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

@@ -620,7 +620,7 @@ const Main: FC<IMainProps> = ({
 
           {
             hasSetInputs && (
-              <div className={cn(doShowSuggestion ? 'pb-[140px]' : (isResponsing ? 'pb-[113px]' : 'pb-[66px]'), 'relative grow h-[200px] pc:w-[794px] max-w-full mobile:w-full mx-auto mb-3.5 overflow-hidden')}>
+              <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='h-full overflow-y-auto' ref={chatListDomRef}>
                   <Chat
                     chatList={chatList}

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

@@ -552,6 +552,10 @@ const Main: FC<IMainProps> = ({
     )
   }
 
+  const difyIcon = (
+    <div className={s.difyHeader}></div>
+  )
+
   if (appUnavailable)
     return <AppUnavailable isUnknwonReason={isUnknwonReason} />
 
@@ -562,7 +566,8 @@ const Main: FC<IMainProps> = ({
     <div>
       <Header
         title={siteInfo.title}
-        icon={siteInfo.icon || ''}
+        icon=''
+        customerIcon={difyIcon}
         icon_background={siteInfo.icon_background}
         isEmbedScene={true}
         isMobile={isMobile}
@@ -604,7 +609,7 @@ const Main: FC<IMainProps> = ({
 
           {
             hasSetInputs && (
-              <div className={cn(doShowSuggestion ? 'pb-[140px]' : (isResponsing ? 'pb-[113px]' : 'pb-[66px]'), 'relative grow h-[200px] pc:w-[794px] max-w-full mobile:w-full mx-auto mb-3.5 overflow-hidden')}>
+              <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='h-full overflow-y-auto' ref={chatListDomRef}>
                   <Chat
                     chatList={chatList}
@@ -624,6 +629,7 @@ const Main: FC<IMainProps> = ({
                     suggestionList={suggestQuestions}
                     displayScene='web'
                     isShowSpeechToText={speechToTextConfig?.enabled}
+                    answerIconClassName={s.difyIcon}
                   />
                 </div>
               </div>)

web/app/components/share/chatbot/style.module.css

 .installedApp {
   height: calc(100vh - 74px);
 }
+
+.difyIcon {
+  background-image: url(./icons/dify.svg);
+}
+
+.difyHeader {
+  width: 24px;
+  height: 24px;
+  background: url(./icons/dify-header.svg) center center no-repeat;
+  background-size: contain;
+}
\ No newline at end of file

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

@@ -307,7 +307,7 @@ const Welcome: FC<IWelcomeProps> = ({
   }
 
   return (
-    <div className='relative mobile:min-h-[48px] tablet:min-h-[64px]'>
+    <div className='relative tablet:min-h-[64px]'>
       {/* {hasSetInputs && renderHeader()} */}
       <div className='mx-auto pc:w-[794px] max-w-full mobile:w-full px-3.5'>
         {/*  Has't set inputs  */}

web/app/components/share/header.tsx

@@ -3,6 +3,7 @@ import React from 'react'
 import AppIcon from '@/app/components/base/app-icon'
 export type IHeaderProps = {
   title: string
+  customerIcon?: React.ReactNode
   icon: string
   icon_background: string
   isMobile?: boolean
@@ -11,6 +12,7 @@ export type IHeaderProps = {
 const Header: FC<IHeaderProps> = ({
   title,
   isMobile,
+  customerIcon,
   icon,
   icon_background,
   isEmbedScene = false,
@@ -25,7 +27,7 @@ const Header: FC<IHeaderProps> = ({
       >
         <div></div>
         <div className="flex items-center space-x-2">
-          <AppIcon size="small" icon={icon} background={icon_background} />
+          {customerIcon || <AppIcon size="small" icon={icon} background={icon_background} />}
           <div
             className={`text-sm text-gray-800 font-bold ${
               isEmbedScene ? 'text-white' : ''

web/app/layout.tsx

 import I18nServer from './components/i18n-server'
+import BrowerInitor from './components/browser-initor'
 import SentryInitor from './components/sentry-initor'
 import { getLocaleOnServer } from '@/i18n/server'
 
@@ -25,10 +26,12 @@ const LocaleLayout = ({
         data-public-edition={process.env.NEXT_PUBLIC_EDITION}
         data-public-sentry-dsn={process.env.NEXT_PUBLIC_SENTRY_DSN}
       >
+        <BrowerInitor>
           <SentryInitor>
             {/* @ts-expect-error Async Server Component */}
             <I18nServer locale={locale}>{children}</I18nServer>
           </SentryInitor>
+        </BrowerInitor>
       </body>
     </html>
   )

web/i18n/lang/common.en.ts

@@ -54,7 +54,7 @@ const translation = {
       maxTokenTip:
         'Max tokens depending on the model. Prompt and completion share this limit. One token is roughly 1 English character.',
       maxTokenSettingTip: 'Your max token setting is high, potentially limiting space for prompts, queries, and data. Consider setting it below 2/3.',
-      setToCurrentModelMaxTokenTip: 'Max token is updated to the maximum token of the current model 4,000.',
+      setToCurrentModelMaxTokenTip: 'Max token is updated to the maximum token of the current model {{maxToken}}.',
     },
     tone: {
       Creative: 'Creative',
@@ -180,6 +180,22 @@ const translation = {
       useYourModel: 'Currently using own Model Provider.',
       close: 'Close',
     },
+    anthropicHosted: {
+      anthropicHosted: 'Anthropic Claude',
+      onTrial: 'ON TRIAL',
+      exhausted: 'QUOTA EXHAUSTED',
+      desc: 'Powerful model, which excels at a wide range of tasks from sophisticated dialogue and creative content generation to detailed instruction.',
+      callTimes: 'Call times',
+      usedUp: 'Trial quota used up. Add own Model Provider.',
+      useYourModel: 'Currently using own Model Provider.',
+      close: 'Close',
+    },
+    anthropic: {
+      using: 'The embedding capability is using',
+      enableTip: 'To enable the Anthropic model, you need to bind to OpenAI or Azure OpenAI Service first.',
+      notEnabled: 'Not enabled',
+      keyFrom: 'Get your API key from Anthropic',
+    },
     encrypted: {
       front: 'Your API KEY will be encrypted and stored using',
       back: ' technology.',

web/i18n/lang/common.zh.ts

@@ -54,7 +54,7 @@ const translation = {
       maxTokenTip:
         '生成的最大令牌数取决于模型。提示和完成共享令牌数限制。一个令牌约等于 1 个英文或 半个中文字符。',
       maxTokenSettingTip: '您设置的最大 tokens 数较大，可能会导致 prompt、用户问题、数据集内容没有 token 空间进行处理，建议设置到 2/3 以下。',
-      setToCurrentModelMaxTokenTip: '最大令牌数更新为当前模型最大的令牌数 4,000。',
+      setToCurrentModelMaxTokenTip: '最大令牌数更新为当前模型最大的令牌数 {{maxToken}}。',
     },
     tone: {
       Creative: '创意',
@@ -180,6 +180,22 @@ const translation = {
       useYourModel: '当前正在使用你自己的模型供应商。',
       close: '关闭',
     },
+    anthropicHosted: {
+      anthropicHosted: 'Anthropic Claude',
+      onTrial: '体验',
+      exhausted: '超出限额',
+      desc: '功能强大的模型，擅长执行从复杂对话和创意内容生成到详细指导的各种任务。',
+      callTimes: '调用次数',
+      usedUp: '试用额度已用完，请在下方添加自己的模型供应商',
+      useYourModel: '当前正在使用你自己的模型供应商。',
+      close: '关闭',
+    },
+    anthropic: {
+      using: '嵌入能力正在使用',
+      enableTip: '要启用 Anthropic 模型，您需要先绑定 OpenAI 或 Azure OpenAI 服务。',
+      notEnabled: '未启用',
+      keyFrom: '从 Anthropic 获取您的 API 密钥',
+    },
     encrypted: {
       front: '密钥将使用 ',
       back: ' 技术进行加密和存储。',

web/models/common.ts

@@ -59,14 +59,19 @@ export type Member = Pick<UserProfileResponse, 'id' | 'name' | 'email' | 'last_l
 export enum ProviderName {
   OPENAI = 'openai',
   AZURE_OPENAI = 'azure_openai',
+  ANTHROPIC = 'anthropic',
 }
 export type ProviderAzureToken = {
   openai_api_base?: string
   openai_api_key?: string
 }
+export type ProviderAnthropicToken = {
+  anthropic_api_key?: string
+}
 export type ProviderTokenType = {
   [ProviderName.OPENAI]: string
   [ProviderName.AZURE_OPENAI]: ProviderAzureToken
+  [ProviderName.ANTHROPIC]: ProviderAnthropicToken
 }
 export type Provider = {
   [Name in ProviderName]: {

web/package.json

 {
   "name": "dify-web",
-  "version": "0.3.8",
+  "version": "0.3.9",
   "private": true,
   "scripts": {
     "dev": "next dev",

web/public/embed.js

@@ -54,7 +54,7 @@ async function embedChatbot () {
     iframe.title = "dify chatbot bubble window"
     iframe.id = 'dify-chatbot-bubble-window'
     iframe.src = `https://${isDev ? 'dev.' : ''}udify.app/chatbot/${difyChatbotConfig.token}`;
-    iframe.style.cssText = 'border: none; position: fixed; flex-direction: column; justify-content: space-between; box-shadow: rgba(150, 150, 150, 0.2) 0px 10px 30px 0px, rgba(150, 150, 150, 0.2) 0px 0px 0px 1px; bottom: 5rem; right: 1rem; width: 24rem; height: 40rem; border-radius: 0.75rem; display: flex; z-index: 2147483647; overflow: hidden; left: unset;'
+    iframe.style.cssText = 'border: none; position: fixed; flex-direction: column; justify-content: space-between; box-shadow: rgba(150, 150, 150, 0.2) 0px 10px 30px 0px, rgba(150, 150, 150, 0.2) 0px 0px 0px 1px; bottom: 5rem; right: 1rem; width: 24rem; height: 40rem; border-radius: 0.75rem; display: flex; z-index: 2147483647; overflow: hidden; left: unset; background-color: #F3F4F6;'
     document.body.appendChild(iframe);
   }
 

web/public/embed.min.js

@@ -27,4 +27,4 @@ async function embedChatbot(){const t=window.difyChatbotConfig;if(t&&t.token){co
             stroke-linecap="round"
             stroke-linejoin="round"
           />
-        </svg>`;if(!document.getElementById("dify-chatbot-bubble-button")){var e=document.createElement("div");e.id="dify-chatbot-bubble-button",e.style.cssText="position: fixed; bottom: 1rem; right: 1rem; width: 50px; height: 50px; border-radius: 25px; background-color: #155EEF; box-shadow: rgba(0, 0, 0, 0.2) 0px 4px 8px 0px; cursor: pointer; z-index: 2147483647; transition: all 0.2s ease-in-out 0s; left: unset; transform: scale(1); :hover {transform: scale(1.1);}";const d=document.createElement("div");d.style.cssText="display: flex; align-items: center; justify-content: center; width: 100%; height: 100%; z-index: 2147483647;",d.innerHTML=n,e.appendChild(d),document.body.appendChild(e),e.addEventListener("click",function(){var e=document.getElementById("dify-chatbot-bubble-window");e?"none"===e.style.display?(e.style.display="block",d.innerHTML=i):(e.style.display="none",d.innerHTML=n):((e=document.createElement("iframe")).allow="fullscreen;microphone",e.title="dify chatbot bubble window",e.id="dify-chatbot-bubble-window",e.src=`https://${o?"dev.":""}udify.app/chatbot/`+t.token,e.style.cssText="border: none; position: fixed; flex-direction: column; justify-content: space-between; box-shadow: rgba(150, 150, 150, 0.2) 0px 10px 30px 0px, rgba(150, 150, 150, 0.2) 0px 0px 0px 1px; bottom: 5rem; right: 1rem; width: 24rem; height: 40rem; border-radius: 0.75rem; display: flex; z-index: 2147483647; overflow: hidden; left: unset;",document.body.appendChild(e),d.innerHTML=i)})}}else console.error("difyChatbotConfig is empty or token is not provided")}document.body.onload=embedChatbot;
\ No newline at end of file
+        </svg>`;if(!document.getElementById("dify-chatbot-bubble-button")){var e=document.createElement("div");e.id="dify-chatbot-bubble-button",e.style.cssText="position: fixed; bottom: 1rem; right: 1rem; width: 50px; height: 50px; border-radius: 25px; background-color: #155EEF; box-shadow: rgba(0, 0, 0, 0.2) 0px 4px 8px 0px; cursor: pointer; z-index: 2147483647; transition: all 0.2s ease-in-out 0s; left: unset; transform: scale(1); :hover {transform: scale(1.1);}";const d=document.createElement("div");d.style.cssText="display: flex; align-items: center; justify-content: center; width: 100%; height: 100%; z-index: 2147483647;",d.innerHTML=n,e.appendChild(d),document.body.appendChild(e),e.addEventListener("click",function(){var e=document.getElementById("dify-chatbot-bubble-window");e?"none"===e.style.display?(e.style.display="block",d.innerHTML=i):(e.style.display="none",d.innerHTML=n):((e=document.createElement("iframe")).allow="fullscreen;microphone",e.title="dify chatbot bubble window",e.id="dify-chatbot-bubble-window",e.src=`https://${o?"dev.":""}udify.app/chatbot/`+t.token,e.style.cssText="border: none; position: fixed; flex-direction: column; justify-content: space-between; box-shadow: rgba(150, 150, 150, 0.2) 0px 10px 30px 0px, rgba(150, 150, 150, 0.2) 0px 0px 0px 1px; bottom: 5rem; right: 1rem; width: 24rem; height: 40rem; border-radius: 0.75rem; display: flex; z-index: 2147483647; overflow: hidden; left: unset; background-color: #F3F4F6;",document.body.appendChild(e),d.innerHTML=i)})}}else console.error("difyChatbotConfig is empty or token is not provided")}document.body.onload=embedChatbot;
\ No newline at end of file

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, ProviderAzureToken, TenantInfoResponse,
+  OauthResponse, Provider, ProviderAnthropicToken, ProviderAzureToken, TenantInfoResponse,
   UserProfileOriginResponse,
 } from '@/models/common'
 import type {
@@ -58,7 +58,7 @@ export const fetchProviders: Fetcher<Provider[] | null, { url: string; params: R
 export const validateProviderKey: Fetcher<ValidateOpenAIKeyResponse, { url: string; body: { token: string } }> = ({ url, body }) => {
   return post(url, { body }) as Promise<ValidateOpenAIKeyResponse>
 }
-export const updateProviderAIKey: Fetcher<UpdateOpenAIKeyResponse, { url: string; body: { token: string | ProviderAzureToken } }> = ({ url, body }) => {
+export const updateProviderAIKey: Fetcher<UpdateOpenAIKeyResponse, { url: string; body: { token: string | ProviderAzureToken | ProviderAnthropicToken } }> = ({ url, body }) => {
   return post(url, { body }) as Promise<UpdateOpenAIKeyResponse>
 }
 

web/types/app.ts

+export enum ProviderType {
+  openai = 'openai',
+  anthropic = 'anthropic',
+}
+
 export enum AppType {
   'chat' = 'chat',
   'completion' = 'completion',