651 lines
24 KiB
Python
651 lines
24 KiB
Python
"""会话服务"""
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import os
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import uuid
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from datetime import datetime, timedelta
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from typing import Annotated
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from typing import Optional, List, Tuple
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import json_repair
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from fastapi import Depends
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from jinja2 import Template
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from sqlalchemy.orm import Session
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from app.core.error_codes import BizCode
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from app.core.exceptions import BusinessException
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from app.core.exceptions import ResourceNotFoundException
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from app.core.logging_config import get_business_logger
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from app.core.models import RedBearLLM, RedBearModelConfig
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from app.db import get_db
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from app.models import Conversation, Message, User, ModelType
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from app.models.conversation_model import ConversationDetail
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from app.models.prompt_optimizer_model import RoleType
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from app.repositories.conversation_repository import ConversationRepository, MessageRepository
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from app.schemas.conversation_schema import ConversationOut
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from app.schemas.model_schema import ModelInfo
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from app.services import workspace_service
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from app.services.model_service import ModelConfigService
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logger = get_business_logger()
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class ConversationService:
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"""
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Service layer for managing conversations and messages.
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Provides methods to create, retrieve, list, and manipulate conversations and messages.
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Delegates database operations to repositories.
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"""
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def __init__(self, db: Session):
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self.db = db
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self.conversation_repo = ConversationRepository(db)
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self.message_repo = MessageRepository(db)
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def create_conversation(
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self,
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app_id: uuid.UUID,
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workspace_id: uuid.UUID,
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user_id: Optional[str] = None,
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title: Optional[str] = None,
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is_draft: bool = False,
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config_snapshot: Optional[dict] = None
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) -> Conversation:
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"""
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Create a new conversation in the system.
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Args:
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app_id (uuid.UUID): The application ID the conversation belongs to.
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workspace_id (uuid.UUID): Workspace ID for context.
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user_id (Optional[str]): Optional user ID for the conversation owner.
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title (Optional[str]): Conversation title. Defaults to 'New Conversation' if not provided.
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is_draft (bool): Whether the conversation is a draft.
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config_snapshot (Optional[dict]): Optional configuration snapshot.
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Returns:
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Conversation: Newly created Conversation instance.
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"""
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try:
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conversation = self.conversation_repo.create_conversation(
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app_id=app_id,
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workspace_id=workspace_id,
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user_id=user_id,
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title=title or "New Conversation",
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is_draft=is_draft,
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config_snapshot=config_snapshot
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)
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self.db.commit()
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self.db.refresh(conversation)
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logger.info(
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"Create Conversation Success",
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extra={
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"conversation_id": str(conversation.id),
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"app_id": str(app_id),
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"workspace_id": str(workspace_id),
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"is_draft": is_draft
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}
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)
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except Exception as e:
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logger.error(
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f"Create Conversation Failed - {str(e)}"
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)
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self.db.rollback()
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raise BusinessException(f"Error create Convsersation", code=BizCode.DB_ERROR)
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return conversation
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def get_conversation(
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self,
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conversation_id: uuid.UUID,
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workspace_id: Optional[uuid.UUID] = None
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) -> Conversation:
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"""
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Retrieve a conversation by its ID.
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Args:
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conversation_id (uuid.UUID): The conversation UUID.
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workspace_id (Optional[uuid.UUID]): Optional workspace UUID to restrict the query.
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Raises:
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ResourceNotFoundException: If the conversation does not exist.
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Returns:
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Conversation: The requested Conversation instance.
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"""
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conversation = self.conversation_repo.get_conversation_by_conversation_id(
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conversation_id=conversation_id,
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workspace_id=workspace_id
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)
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return conversation
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def get_user_conversations(
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self,
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user_id: uuid.UUID,
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page: int = 1,
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page_size: int = 20
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) -> tuple[list[Conversation], int]:
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"""
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Retrieve recent conversations for a specific user with pagination.
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Args:
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user_id (uuid.UUID): Unique identifier of the user.
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page (int): Page number (1-based). Defaults to 1.
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page_size (int): Number of items per page. Defaults to 20.
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Returns:
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tuple[list[Conversation], int]: A list of recent conversation entities and total count.
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"""
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conversations, total = self.conversation_repo.get_conversation_by_user_id(
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user_id,
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page=page,
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page_size=page_size
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)
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return conversations, total
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def list_conversations(
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self,
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app_id: uuid.UUID,
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workspace_id: uuid.UUID,
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user_id: Optional[str] = None,
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is_draft: Optional[bool] = None,
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page: int = 1,
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pagesize: int = 20
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) -> Tuple[List[Conversation], int]:
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"""
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List conversations with optional filters and pagination.
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Args:
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app_id (uuid.UUID): Application ID filter.
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workspace_id (uuid.UUID): Workspace ID filter.
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user_id (Optional[str]): Optional user ID filter.
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is_draft (Optional[bool]): Optional draft status filter.
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page (int): Page number, 1-based.
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pagesize (int): Number of items per page.
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Returns:
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Tuple[List[Conversation], int]: A list of Conversation instances and the total count.
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"""
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conversations, total = self.conversation_repo.list_conversations(
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app_id=app_id,
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workspace_id=workspace_id,
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user_id=user_id,
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is_draft=is_draft,
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page=page,
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pagesize=pagesize
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)
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return conversations, total
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def add_message(
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self,
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conversation_id: uuid.UUID,
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role: str,
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content: str,
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meta_data: Optional[dict] = None,
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message_id: Optional[uuid.UUID] = None,
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) -> Message:
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"""
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Add a message to a conversation using UnitOfWork.
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Args:
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conversation_id (uuid.UUID): Conversation UUID.
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role (str): Role of the message sender ('user' or 'assistant').
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content (str): Message content.
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meta_data (Optional[dict]): Optional metadata.
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message_id (Optional[uuid.UUID]): Optional custom message UUID.
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Returns:
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Message: Newly created Message instance.
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"""
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try:
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conversation = self.conversation_repo.get_conversation_by_conversation_id(
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conversation_id
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)
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message = Message(
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id=message_id if message_id else uuid.uuid4(),
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conversation_id=conversation_id,
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role=role,
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content=content,
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meta_data=meta_data,
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)
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self.message_repo.add_message(message)
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conversation.message_count += 1
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if conversation.message_count == 1 and role == "user":
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conversation.title = (
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content[:50] + ("..." if len(content) > 50 else "")
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)
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self.db.commit()
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self.db.refresh(message)
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logger.info(
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"Message added successfully",
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extra={
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"conversation_id": str(conversation_id),
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"message_id": str(message.id),
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"role": role,
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"content_length": len(content),
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},
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)
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return message
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except Exception as e:
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logger.error(
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f"Message added error, db roll back - {str(e)}",
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extra={
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"conversation_id": str(conversation_id),
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"role": role,
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"content_length": len(content),
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},
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)
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self.db.rollback()
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raise BusinessException(
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f"Error adding message, conversation_id={conversation_id}",
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code=BizCode.DB_ERROR
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)
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def get_messages(
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self,
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conversation_id: uuid.UUID,
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limit: Optional[int] = None
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) -> List[Message]:
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"""
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Retrieve messages for a conversation.
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Args:
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conversation_id (uuid.UUID): Conversation UUID.
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limit (Optional[int]): Optional maximum number of messages.
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Returns:
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List[Message]: List of messages ordered by creation time.
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"""
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messages = self.message_repo.get_message_by_conversation_id(
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conversation_id,
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limit
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)
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return messages
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async def get_conversation_history(
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self,
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conversation_id: uuid.UUID,
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max_history: Optional[int] = None,
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current_provider: Optional[str] = None,
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current_is_omni: Optional[bool] = None
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) -> List[dict]:
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"""
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Retrieve historical conversation messages formatted as dictionaries.
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Args:
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conversation_id (uuid.UUID): Conversation UUID.
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max_history (Optional[int]): Maximum number of messages to retrieve.
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current_provider (Optional[str]): Current provider for file handling.
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current_is_omni (Optional[bool]): Current omni flag for file handling.
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Returns:
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List[dict]: List of message dictionaries with keys 'role' and 'content'.
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"""
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messages = self.message_repo.get_message_by_conversation_id(
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conversation_id,
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limit=max_history
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)
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history = []
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for msg in messages:
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msg_dict = {
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"role": msg.role,
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"content": [{"type": "text", "text": msg.content}]
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}
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# 处理用户消息中的多模态文件
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if msg.role == "user" and msg.meta_data:
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history_files = msg.meta_data.get("history_files", {})
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if history_files and current_provider and current_is_omni is not None:
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# 检查是否需要重新处理文件
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stored_provider = history_files.get("provider")
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stored_is_omni = history_files.get("is_omni")
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# 如果provider或is_omni不匹配，需要重新处理
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if stored_provider != current_provider or stored_is_omni != current_is_omni:
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continue
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# provider和is_omni匹配，直接使用存储的内容
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msg_dict["content"].extend(history_files.get("content"))
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history.append(msg_dict)
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return history
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def save_conversation_messages(
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self,
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conversation_id: uuid.UUID,
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user_message: str,
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assistant_message: str,
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meta_data: Optional[dict] = None
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):
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"""
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Save a pair of user and assistant messages to the conversation.
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Args:
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conversation_id (uuid.UUID): Conversation UUID.
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user_message (str): User's message content.
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assistant_message (str): Assistant's response content.
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meta_data (Optional[dict]): Optional metadata for the messages.
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"""
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self.add_message(
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conversation_id=conversation_id,
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role="user",
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content=user_message
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)
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ai_message = self.add_message(
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conversation_id=conversation_id,
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role="assistant",
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content=assistant_message,
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meta_data=meta_data
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)
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logger.debug(
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"Saved conversation messages successfully",
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extra={
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"conversation_id": str(conversation_id),
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"user_message_length": len(user_message),
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"assistant_message_length": len(assistant_message)
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}
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)
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return ai_message.id
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def delete_conversation(
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self,
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conversation_id: uuid.UUID,
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workspace_id: uuid.UUID
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):
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"""
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Soft delete a conversation.
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Args:
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conversation_id (uuid.UUID): Conversation UUID.
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workspace_id (uuid.UUID): Workspace UUID for validation.
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"""
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try:
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self.conversation_repo.soft_delete_conversation_by_conversation_id(
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conversation_id,
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workspace_id
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)
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self.db.commit()
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logger.info(
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"Soft deleted conversation successfully",
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extra={
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"conversation_id": str(conversation_id),
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"workspace_id": str(workspace_id)
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}
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)
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except Exception as e:
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self.db.rollback()
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logger.error(
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f"Error deleting conversation, conversation_id={conversation_id} - {str(e)}",
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)
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raise BusinessException("Error deleting conversation", code=BizCode.DB_ERROR)
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def create_or_get_conversation(
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self,
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app_id: uuid.UUID,
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workspace_id: uuid.UUID,
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is_draft: bool = False,
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conversation_id: Optional[uuid.UUID] = None,
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user_id: Optional[str] = None,
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) -> Conversation:
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"""
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Retrieve an existing conversation by ID or create a new one.
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Args:
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app_id (uuid.UUID): Application ID.
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workspace_id (uuid.UUID): Workspace ID.
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is_draft (bool): Whether the conversation should be a draft.
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conversation_id (Optional[uuid.UUID]): Optional conversation ID to retrieve.
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user_id (Optional[str]): Optional user ID.
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Returns:
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Conversation: Existing or newly created conversation.
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"""
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if conversation_id:
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try:
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conversation = self.get_conversation(
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conversation_id=conversation_id,
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workspace_id=workspace_id
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)
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# 验证会话是否属于该应用
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if conversation.app_id != app_id:
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raise BusinessException(
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"Conversation does not belong to this app",
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BizCode.INVALID_CONVERSATION
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)
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return conversation
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except ResourceNotFoundException:
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logger.warning(
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"Conversation not found. A new conversation will be created.",
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extra={"conversation_id": str(conversation_id)}
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)
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# 创建新会话（使用发布版本的配置）
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conversation = self.create_conversation(
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app_id=app_id,
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workspace_id=workspace_id,
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user_id=user_id,
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is_draft=is_draft
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)
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logger.info(
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"Created a new conversation for shared link usage",
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extra={
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"conversation_id": str(conversation_id),
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}
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)
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return conversation
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async def get_conversation_detail(
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self,
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user: User,
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conversation_id: uuid.UUID,
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workspace_id: uuid.UUID,
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language: str = "zh"
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) -> ConversationOut:
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"""
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Retrieve or generate the summary and theme of a conversation.
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This method first attempts to fetch the conversation detail from the repository.
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If no detail exists or the conversation is outdated (>1 day), it generates a new
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summary using the configured LLM model, stores it, and returns it.
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Args:
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user (User): The user requesting the conversation summary.
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conversation_id (UUID): Unique identifier of the conversation.
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workspace_id (UUID): Identifier of the workspace where the conversation belongs.
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language (str, optional): Language for the summary generation. Defaults to "zh".
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Returns:
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ConversationOut: An object containing the conversation's theme, summary,
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takeaways, and information score.
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Raises:
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BusinessException: If the workspace model is not configured, the model does
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not exist, API keys are missing, or the LLM output is invalid.
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Notes:
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- If conversation details exist and are recent, they are returned directly.
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- LLM generation uses system and user prompt templates from the filesystem.
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- JSON repair is applied to ensure model outputs can be safely parsed.
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- Commits the new conversation detail only if it is generated or outdated.
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"""
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logger.info(f"Fetching conversation detail for conversation_id={conversation_id}, workspace_id={workspace_id}")
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conversation_detail = self.conversation_repo.get_conversation_detail(
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conversation_id=conversation_id,
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)
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conversation = self.get_conversation(
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conversation_id=conversation_id,
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)
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if not conversation:
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raise BusinessException("Conversation not found", BizCode.INVALID_CONVERSATION)
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is_stable = (
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conversation.updated_at
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and datetime.now() - conversation.updated_at > timedelta(days=1)
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)
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if conversation_detail and is_stable:
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logger.info(f"Conversation detail found in repository for conversation_id={conversation_id}")
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return ConversationOut(
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theme=conversation_detail.theme,
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question=conversation_detail.question if conversation_detail.question else [],
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summary=conversation_detail.summary,
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takeaways=conversation_detail.takeaways,
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info_score=conversation_detail.info_score,
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)
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logger.info("Conversation detail not found, generating new summary using LLM")
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configs = workspace_service.get_workspace_models_configs(
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db=self.db,
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workspace_id=workspace_id,
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user=user
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)
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model_id = configs.get('llm')
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if not model_id:
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logger.error(f"Workspace model configuration not found for workspace_id={workspace_id}")
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raise BusinessException("Workspace model configuration not found. Please configure a model first.", code=BizCode.MODEL_NOT_FOUND)
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config = ModelConfigService.get_model_by_id(db=self.db, model_id=model_id)
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if not config:
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logger.error("Configured model not found for model_id={model_id}")
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raise BusinessException("Configured model does not exist.", BizCode.NOT_FOUND)
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if not config.api_keys or len(config.api_keys) == 0:
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logger.error(f"Model API keys missing for model_id={model_id}", )
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raise BusinessException("Model configuration missing API keys.", BizCode.INVALID_PARAMETER)
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api_config = config.api_keys[0]
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model_name = api_config.model_name
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provider = api_config.provider
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api_key = api_config.api_key
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api_base = api_config.api_base
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is_omni = api_config.is_omni
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model_type = config.type
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llm = RedBearLLM(
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RedBearModelConfig(
|
||
model_name=model_name,
|
||
provider=provider,
|
||
api_key=api_key,
|
||
base_url=api_base,
|
||
is_omni=is_omni
|
||
),
|
||
type=ModelType(model_type)
|
||
)
|
||
|
||
conversation_messages = await self.get_conversation_history(
|
||
conversation_id=conversation_id,
|
||
max_history=20,
|
||
current_provider=provider,
|
||
current_is_omni=is_omni
|
||
)
|
||
if len(conversation_messages) == 0:
|
||
return ConversationOut(
|
||
theme="",
|
||
question=[],
|
||
summary="",
|
||
takeaways=[],
|
||
info_score=0,
|
||
)
|
||
prompt_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'prompt')
|
||
with open(os.path.join(prompt_path, 'conversation_summary_system.jinja2'), 'r', encoding='utf-8') as f:
|
||
system_prompt = f.read()
|
||
rendered_system_message = Template(system_prompt).render()
|
||
|
||
with open(os.path.join(prompt_path, 'conversation_summary_user.jinja2'), 'r', encoding='utf-8') as f:
|
||
user_prompt = f.read()
|
||
rendered_user_message = Template(user_prompt).render(
|
||
language=language,
|
||
conversation=str(conversation_messages)
|
||
)
|
||
|
||
messages = [
|
||
(RoleType.SYSTEM, rendered_system_message),
|
||
(RoleType.USER, rendered_user_message),
|
||
]
|
||
logger.info(f"Invoking LLM for conversation_id={conversation_id}")
|
||
model_resp = await llm.ainvoke(messages)
|
||
|
||
try:
|
||
if isinstance(model_resp.content, str):
|
||
result = json_repair.repair_json(model_resp.content, return_objects=True)
|
||
elif isinstance(model_resp.content, list):
|
||
result = json_repair.repair_json(model_resp.content[0].get("text"), return_objects=True)
|
||
elif isinstance(model_resp.content, dict):
|
||
result = model_resp.content
|
||
else:
|
||
raise BusinessException("Unexpect model output", code=BizCode.LLM_ERROR)
|
||
except Exception as e:
|
||
logger.exception(f"Failed to parse LLM response for conversation_id={conversation_id}")
|
||
raise BusinessException("Failed to parse LLM response", code=BizCode.LLM_ERROR) from e
|
||
|
||
summary = result.get('summary', "")
|
||
theme = result.get('theme', "")
|
||
question = result.get("question") or []
|
||
takeaways = result.get("takeaways") or []
|
||
info_score = result.get("info_score", 50)
|
||
|
||
if not is_stable:
|
||
if not conversation_detail:
|
||
logger.info(f"Creating conversation detail in DB for conversation_id={conversation_id}")
|
||
conversation_detail = ConversationDetail(
|
||
conversation_id=conversation.id,
|
||
summary=summary,
|
||
theme=theme,
|
||
question=question,
|
||
takeaways=takeaways,
|
||
info_score=info_score
|
||
)
|
||
self.conversation_repo.add_conversation_detail(conversation_detail)
|
||
else:
|
||
logger.info(f"Updating conversation detail in DB for conversation_id={conversation_id}")
|
||
conversation_detail.summary = summary
|
||
conversation_detail.theme = theme
|
||
conversation_detail.question = question
|
||
conversation_detail.takeaways = takeaways
|
||
conversation_detail.info_score = info_score
|
||
|
||
self.db.commit()
|
||
self.db.refresh(conversation_detail)
|
||
|
||
logger.info(f"Returning conversation summary for conversation_id={conversation_id}")
|
||
conversation_out = ConversationOut(
|
||
theme=theme,
|
||
question=question,
|
||
summary=summary,
|
||
takeaways=takeaways,
|
||
info_score=info_score
|
||
)
|
||
return conversation_out
|
||
|
||
|
||
# ==================== Dependency Injection ====================
|
||
|
||
def get_conversation_service(
|
||
db: Annotated[Session, Depends(get_db)]
|
||
) -> ConversationService:
|
||
"""
|
||
Dependency injection function to provide ConversationService instance.
|
||
|
||
Args:
|
||
db (Session): Database session provided by FastAPI dependency.
|
||
|
||
Returns:
|
||
ConversationService: Service instance.
|
||
"""
|
||
return ConversationService(db)
|