add app convert codes

api/controllers/console/app/conversation.py

@@ -21,7 +21,7 @@ from fields.conversation_fields import (
 )
 from libs.helper import datetime_string
 from libs.login import login_required
-from models.model import Conversation, Message, MessageAnnotation, AppMode
+from models.model import AppMode, Conversation, Message, MessageAnnotation
 
 
 class CompletionConversationApi(Resource):

api/controllers/console/app/message.py

@@ -26,7 +26,7 @@ from fields.conversation_fields import annotation_fields, message_detail_fields
 from libs.helper import uuid_value
 from libs.infinite_scroll_pagination import InfiniteScrollPagination
 from libs.login import login_required
-from models.model import Conversation, Message, MessageAnnotation, MessageFeedback, AppMode
+from models.model import AppMode, Conversation, Message, MessageAnnotation, MessageFeedback
 from services.annotation_service import AppAnnotationService
 from services.errors.conversation import ConversationNotExistsError
 from services.errors.message import MessageNotExistsError

api/controllers/console/app/workflow.py

-from flask_restful import Resource, reqparse, marshal_with
+from flask_restful import Resource, marshal_with, reqparse
 
 from controllers.console import api
 from controllers.console.app.error import DraftWorkflowNotExist
@@ -6,8 +6,8 @@ from controllers.console.app.wraps import get_app_model
 from controllers.console.setup import setup_required
 from controllers.console.wraps import account_initialization_required
 from fields.workflow_fields import workflow_fields
-from libs.login import login_required, current_user
-from models.model import App, ChatbotAppEngine, AppMode
+from libs.login import current_user, login_required
+from models.model import App, AppMode, ChatbotAppEngine
 from services.workflow_service import WorkflowService
 
 

api/controllers/console/app/wraps.py

@@ -5,7 +5,7 @@ from typing import Optional, Union
 from controllers.console.app.error import AppNotFoundError
 from extensions.ext_database import db
 from libs.login import current_user
-from models.model import App, ChatbotAppEngine, AppMode
+from models.model import App, AppMode, ChatbotAppEngine
 
 
 def get_app_model(view: Optional[Callable] = None, *,

api/core/app_runner/app_runner.py

@@ -22,7 +22,7 @@ from core.model_runtime.entities.message_entities import AssistantPromptMessage,
 from core.model_runtime.entities.model_entities import ModelPropertyKey
 from core.model_runtime.errors.invoke import InvokeBadRequestError
 from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
-from core.prompt.prompt_transform import PromptTransform
+from core.prompt.simple_prompt_transform import SimplePromptTransform
 from models.model import App, Message, MessageAnnotation
 
 
@@ -140,12 +140,11 @@ class AppRunner:
         :param memory: memory
         :return:
         """
-        prompt_transform = PromptTransform()
+        prompt_transform = SimplePromptTransform()
 
         # get prompt without memory and context
         if prompt_template_entity.prompt_type == PromptTemplateEntity.PromptType.SIMPLE:
             prompt_messages, stop = prompt_transform.get_prompt(
-                app_mode=app_record.mode,
                 prompt_template_entity=prompt_template_entity,
                 inputs=inputs,
                 query=query if query else '',
@@ -155,17 +154,7 @@ class AppRunner:
                 model_config=model_config
             )
         else:
-            prompt_messages = prompt_transform.get_advanced_prompt(
-                app_mode=app_record.mode,
-                prompt_template_entity=prompt_template_entity,
-                inputs=inputs,
-                query=query,
-                files=files,
-                context=context,
-                memory=memory,
-                model_config=model_config
-            )
-            stop = model_config.stop
+            raise NotImplementedError("Advanced prompt is not supported yet.")
 
         return prompt_messages, stop
 

api/core/app_runner/basic_app_runner.py

@@ -15,7 +15,7 @@ from core.memory.token_buffer_memory import TokenBufferMemory
 from core.model_manager import ModelInstance
 from core.moderation.base import ModerationException
 from extensions.ext_database import db
-from models.model import App, Conversation, Message, AppMode
+from models.model import App, AppMode, Conversation, Message
 
 logger = logging.getLogger(__name__)
 

api/core/application_manager.py

@@ -28,7 +28,8 @@ from core.entities.application_entities import (
     ModelConfigEntity,
     PromptTemplateEntity,
     SensitiveWordAvoidanceEntity,
-    TextToSpeechEntity, VariableEntity,
+    TextToSpeechEntity,
+    VariableEntity,
 )
 from core.entities.model_entities import ModelStatus
 from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
@@ -541,8 +542,7 @@ class ApplicationManager:
                         query_variable=query_variable,
                             retrieve_strategy=DatasetRetrieveConfigEntity.RetrieveStrategy.value_of(
                             dataset_configs['retrieval_model']
-                        ),
-                        single_strategy=datasets.get('strategy', 'router')
+                        )
                     )
                 )
             else:

api/core/entities/application_entities.py

@@ -156,7 +156,6 @@ class DatasetRetrieveConfigEntity(BaseModel):
     query_variable: Optional[str] = None  # Only when app mode is completion
 
     retrieve_strategy: RetrieveStrategy
-    single_strategy: Optional[str] = None  # for temp
     top_k: Optional[int] = None
     score_threshold: Optional[float] = None
     reranking_model: Optional[dict] = None

api/core/prompt/advanced_prompt_transform.py

+from typing import Optional
+
+from core.entities.application_entities import PromptTemplateEntity, ModelConfigEntity, \
+    AdvancedCompletionPromptTemplateEntity
+from core.file.file_obj import FileObj
+from core.memory.token_buffer_memory import TokenBufferMemory
+from core.model_runtime.entities.message_entities import PromptMessage, PromptMessageRole, UserPromptMessage, \
+    SystemPromptMessage, AssistantPromptMessage, TextPromptMessageContent
+from core.prompt.prompt_template import PromptTemplateParser
+from core.prompt.prompt_transform import PromptTransform
+from core.prompt.simple_prompt_transform import ModelMode
+
+
+class AdvancePromptTransform(PromptTransform):
+    """
+    Advanced Prompt Transform for Workflow LLM Node.
+    """
+
+    def get_prompt(self, prompt_template_entity: PromptTemplateEntity,
+                   inputs: dict,
+                   query: str,
+                   files: list[FileObj],
+                   context: Optional[str],
+                   memory: Optional[TokenBufferMemory],
+                   model_config: ModelConfigEntity) -> list[PromptMessage]:
+        prompt_messages = []
+
+        model_mode = ModelMode.value_of(model_config.mode)
+        if model_mode == ModelMode.COMPLETION:
+            prompt_messages = self._get_completion_model_prompt_messages(
+                prompt_template_entity=prompt_template_entity,
+                inputs=inputs,
+                files=files,
+                context=context,
+                memory=memory,
+                model_config=model_config
+            )
+        elif model_mode == ModelMode.CHAT:
+            prompt_messages = self._get_chat_model_prompt_messages(
+                prompt_template_entity=prompt_template_entity,
+                inputs=inputs,
+                query=query,
+                files=files,
+                context=context,
+                memory=memory,
+                model_config=model_config
+            )
+
+        return prompt_messages
+
+    def _get_completion_model_prompt_messages(self,
+                                              prompt_template_entity: PromptTemplateEntity,
+                                              inputs: dict,
+                                              files: list[FileObj],
+                                              context: Optional[str],
+                                              memory: Optional[TokenBufferMemory],
+                                              model_config: ModelConfigEntity) -> list[PromptMessage]:
+        """
+        Get completion model prompt messages.
+        """
+        raw_prompt = prompt_template_entity.advanced_completion_prompt_template.prompt
+
+        prompt_messages = []
+
+        prompt_template = PromptTemplateParser(template=raw_prompt)
+        prompt_inputs = {k: inputs[k] for k in prompt_template.variable_keys if k in inputs}
+
+        self._set_context_variable(context, prompt_template, prompt_inputs)
+
+        role_prefix = prompt_template_entity.advanced_completion_prompt_template.role_prefix
+        self._set_histories_variable(
+            memory=memory,
+            raw_prompt=raw_prompt,
+            role_prefix=role_prefix,
+            prompt_template=prompt_template,
+            prompt_inputs=prompt_inputs,
+            model_config=model_config
+        )
+
+        prompt = prompt_template.format(
+            prompt_inputs
+        )
+
+        if files:
+            prompt_message_contents = [TextPromptMessageContent(data=prompt)]
+            for file in files:
+                prompt_message_contents.append(file.prompt_message_content)
+
+            prompt_messages.append(UserPromptMessage(content=prompt_message_contents))
+        else:
+            prompt_messages.append(UserPromptMessage(content=prompt))
+
+        return prompt_messages
+
+    def _get_chat_model_prompt_messages(self,
+                                        prompt_template_entity: PromptTemplateEntity,
+                                        inputs: dict,
+                                        query: str,
+                                        files: list[FileObj],
+                                        context: Optional[str],
+                                        memory: Optional[TokenBufferMemory],
+                                        model_config: ModelConfigEntity) -> list[PromptMessage]:
+        """
+        Get chat model prompt messages.
+        """
+        raw_prompt_list = prompt_template_entity.advanced_chat_prompt_template.messages
+
+        prompt_messages = []
+
+        for prompt_item in raw_prompt_list:
+            raw_prompt = prompt_item.text
+
+            prompt_template = PromptTemplateParser(template=raw_prompt)
+            prompt_inputs = {k: inputs[k] for k in prompt_template.variable_keys if k in inputs}
+
+            self._set_context_variable(context, prompt_template, prompt_inputs)
+
+            prompt = prompt_template.format(
+                prompt_inputs
+            )
+
+            if prompt_item.role == PromptMessageRole.USER:
+                prompt_messages.append(UserPromptMessage(content=prompt))
+            elif prompt_item.role == PromptMessageRole.SYSTEM and prompt:
+                prompt_messages.append(SystemPromptMessage(content=prompt))
+            elif prompt_item.role == PromptMessageRole.ASSISTANT:
+                prompt_messages.append(AssistantPromptMessage(content=prompt))
+
+        if memory:
+            self._append_chat_histories(memory, prompt_messages, model_config)
+
+            if files:
+                prompt_message_contents = [TextPromptMessageContent(data=query)]
+                for file in files:
+                    prompt_message_contents.append(file.prompt_message_content)
+
+                prompt_messages.append(UserPromptMessage(content=prompt_message_contents))
+            else:
+                prompt_messages.append(UserPromptMessage(content=query))
+        elif files:
+            # get last message
+            last_message = prompt_messages[-1] if prompt_messages else None
+            if last_message and last_message.role == PromptMessageRole.USER:
+                # get last user message content and add files
+                prompt_message_contents = [TextPromptMessageContent(data=last_message.content)]
+                for file in files:
+                    prompt_message_contents.append(file.prompt_message_content)
+
+                last_message.content = prompt_message_contents
+            else:
+                prompt_message_contents = [TextPromptMessageContent(data=query)]
+                for file in files:
+                    prompt_message_contents.append(file.prompt_message_content)
+
+                prompt_messages.append(UserPromptMessage(content=prompt_message_contents))
+
+        return prompt_messages
+
+    def _set_context_variable(self, context: str, prompt_template: PromptTemplateParser, prompt_inputs: dict) -> None:
+        if '#context#' in prompt_template.variable_keys:
+            if context:
+                prompt_inputs['#context#'] = context
+            else:
+                prompt_inputs['#context#'] = ''
+
+    def _set_query_variable(self, query: str, prompt_template: PromptTemplateParser, prompt_inputs: dict) -> None:
+        if '#query#' in prompt_template.variable_keys:
+            if query:
+                prompt_inputs['#query#'] = query
+            else:
+                prompt_inputs['#query#'] = ''
+
+    def _set_histories_variable(self, memory: TokenBufferMemory,
+                                raw_prompt: str,
+                                role_prefix: AdvancedCompletionPromptTemplateEntity.RolePrefixEntity,
+                                prompt_template: PromptTemplateParser,
+                                prompt_inputs: dict,
+                                model_config: ModelConfigEntity) -> None:
+        if '#histories#' in prompt_template.variable_keys:
+            if memory:
+                inputs = {'#histories#': '', **prompt_inputs}
+                prompt_template = PromptTemplateParser(raw_prompt)
+                prompt_inputs = {k: inputs[k] for k in prompt_template.variable_keys if k in inputs}
+                tmp_human_message = UserPromptMessage(
+                    content=prompt_template.format(prompt_inputs)
+                )
+
+                rest_tokens = self._calculate_rest_token([tmp_human_message], model_config)
+
+                histories = self._get_history_messages_from_memory(
+                    memory=memory,
+                    max_token_limit=rest_tokens,
+                    human_prefix=role_prefix.user,
+                    ai_prefix=role_prefix.assistant
+                )
+                prompt_inputs['#histories#'] = histories
+            else:
+                prompt_inputs['#histories#'] = ''

api/core/prompt/generate_prompts/baichuan_chat.json

 {
   "human_prefix": "用户",
   "assistant_prefix": "助手",
-  "context_prompt": "用户在与一个客观的助手对话。助手会尊重找到的材料，给出全面专业的解释，但不会过度演绎。同时回答中不会暴露引用的材料：\n\n```\n{{context}}\n```\n\n",
-  "histories_prompt": "用户和助手的历史对话内容如下：\n```\n{{histories}}\n```\n\n",
+  "context_prompt": "用户在与一个客观的助手对话。助手会尊重找到的材料，给出全面专业的解释，但不会过度演绎。同时回答中不会暴露引用的材料：\n\n```\n{{#context#}}\n```\n\n",
+  "histories_prompt": "用户和助手的历史对话内容如下：\n```\n{{#histories#}}\n```\n\n",
   "system_prompt_orders": [
     "context_prompt",
     "pre_prompt",
     "histories_prompt"
   ],
-  "query_prompt": "\n\n用户：{{query}}",
+  "query_prompt": "\n\n用户：{{#query#}}",
   "stops": ["用户："]
 }
\ No newline at end of file

api/core/prompt/generate_prompts/baichuan_completion.json

 {
-  "context_prompt": "用户在与一个客观的助手对话。助手会尊重找到的材料，给出全面专业的解释，但不会过度演绎。同时回答中不会暴露引用的材料：\n\n```\n{{context}}\n```\n",
+  "context_prompt": "用户在与一个客观的助手对话。助手会尊重找到的材料，给出全面专业的解释，但不会过度演绎。同时回答中不会暴露引用的材料：\n\n```\n{{#context#}}\n```\n",
   "system_prompt_orders": [
     "context_prompt",
     "pre_prompt"
   ],
-  "query_prompt": "{{query}}",
+  "query_prompt": "{{#query#}}",
   "stops": null
 }
\ No newline at end of file

api/core/prompt/generate_prompts/common_chat.json

 {
   "human_prefix": "Human",
   "assistant_prefix": "Assistant",
-  "context_prompt": "Use the following context as your learned knowledge, inside <context></context> XML tags.\n\n<context>\n{{context}}\n</context>\n\nWhen answer to user:\n- If you don't know, just say that you don't know.\n- If you don't know when you are not sure, ask for clarification.\nAvoid mentioning that you obtained the information from the context.\nAnd answer according to the language of the user's question.\n\n",
-  "histories_prompt": "Here is the chat histories between human and assistant, inside <histories></histories> XML tags.\n\n<histories>\n{{histories}}\n</histories>\n\n",
+  "context_prompt": "Use the following context as your learned knowledge, inside <context></context> XML tags.\n\n<context>\n{{#context#}}\n</context>\n\nWhen answer to user:\n- If you don't know, just say that you don't know.\n- If you don't know when you are not sure, ask for clarification.\nAvoid mentioning that you obtained the information from the context.\nAnd answer according to the language of the user's question.\n\n",
+  "histories_prompt": "Here is the chat histories between human and assistant, inside <histories></histories> XML tags.\n\n<histories>\n{{#histories#}}\n</histories>\n\n",
   "system_prompt_orders": [
     "context_prompt",
     "pre_prompt",
     "histories_prompt"
   ],
-  "query_prompt": "\n\nHuman: {{query}}\n\nAssistant: ",
+  "query_prompt": "\n\nHuman: {{#query#}}\n\nAssistant: ",
   "stops": ["\nHuman:", "</histories>"]
 }

api/core/prompt/generate_prompts/common_completion.json

 {
-  "context_prompt": "Use the following context as your learned knowledge, inside <context></context> XML tags.\n\n<context>\n{{context}}\n</context>\n\nWhen answer to user:\n- If you don't know, just say that you don't know.\n- If you don't know when you are not sure, ask for clarification.\nAvoid mentioning that you obtained the information from the context.\nAnd answer according to the language of the user's question.\n\n",
+  "context_prompt": "Use the following context as your learned knowledge, inside <context></context> XML tags.\n\n<context>\n{{#context#}}\n</context>\n\nWhen answer to user:\n- If you don't know, just say that you don't know.\n- If you don't know when you are not sure, ask for clarification.\nAvoid mentioning that you obtained the information from the context.\nAnd answer according to the language of the user's question.\n\n",
   "system_prompt_orders": [
     "context_prompt",
     "pre_prompt"
   ],
-  "query_prompt": "{{query}}",
+  "query_prompt": "{{#query#}}",
   "stops": null
 }
\ No newline at end of file

api/core/prompt/prompt_builder.py

-from core.prompt.prompt_template import PromptTemplateParser
-
-
-class PromptBuilder:
-    @classmethod
-    def parse_prompt(cls, prompt: str, inputs: dict) -> str:
-        prompt_template = PromptTemplateParser(prompt)
-        prompt_inputs = {k: inputs[k] for k in prompt_template.variable_keys if k in inputs}
-        prompt = prompt_template.format(prompt_inputs)
-        return prompt

api/core/prompt/prompt_template.py

@@ -32,7 +32,8 @@ class PromptTemplateParser:
                 return PromptTemplateParser.remove_template_variables(value)
             return value
 
-        return re.sub(REGEX, replacer, self.template)
+        prompt = re.sub(REGEX, replacer, self.template)
+        return re.sub(r'<\|.*?\|>', '', prompt)
 
     @classmethod
     def remove_template_variables(cls, text: str):

api/fields/annotation_fields.py

@@ -2,7 +2,6 @@ from flask_restful import fields
 
 from libs.helper import TimestampField
 
-
 annotation_fields = {
     "id": fields.String,
     "question": fields.String,

api/fields/workflow_fields.py

@@ -5,7 +5,6 @@ from flask_restful import fields
 from fields.member_fields import simple_account_fields
 from libs.helper import TimestampField
 
-
 workflow_fields = {
     'id': fields.String,
     'graph': fields.Raw(attribute=lambda x: json.loads(x.graph) if hasattr(x, 'graph') else None),