chengkai3
7ef266e4a0
实现AI问答的function call功能，支持调用系统接口进行查询。 改动内容： 1. 数据库扩展： - 在ai_chat_messages表增加tool_calls和tool_call_id字段 - 创建数据库迁移文件 2. 模型和Schema更新： - AiChatMessage模型增加tool_calls(JSON)和tool_call_id字段 - AiChatMessageSummary schema增加对应字段 3. Function Call实现： - 定义4个可调用函数：query_tower_models、query_lines、query_users、query_system_params - 实现_execute_function处理函数调用并返回格式化结果 - 更新_call_openai_api支持tools参数 4. 消息流程更新： - 重构send_message支持完整的function call流程 - 流程：用户消息 -> AI请求function call -> 执行函数 -> AI基于结果回复 Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> Co-authored-by: multica-agent <github@multica.ai>
60 lines
1.3 KiB
Python
60 lines
1.3 KiB
Python
from __future__ import annotations
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from datetime import datetime
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from pydantic import BaseModel, Field
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from .user import UserPublic
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class AiChatMessageSummary(BaseModel):
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id: int
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conversation_id: int
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role: str
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content: str
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tool_calls: dict | None = None
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tool_call_id: str | None = None
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created_at: datetime
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class AiChatConversationSummary(BaseModel):
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id: int
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title: str
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user_id: str
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created_at: datetime
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updated_at: datetime
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user: UserPublic | None = None
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message_count: int = 0
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class AiChatConversationDetail(BaseModel):
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id: int
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title: str
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user_id: str
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created_at: datetime
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updated_at: datetime
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user: UserPublic | None = None
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messages: list[AiChatMessageSummary] = []
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class AiChatConversationListResponse(BaseModel):
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items: list[AiChatConversationSummary]
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total: int
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class AiChatConversationCreateRequest(BaseModel):
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title: str = Field(default="新对话", min_length=1, max_length=256)
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class AiChatConversationUpdateRequest(BaseModel):
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title: str = Field(min_length=1, max_length=256)
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class AiChatMessageSendRequest(BaseModel):
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content: str = Field(min_length=1, max_length=20000)
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class AiChatMessageResponse(BaseModel):
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message: AiChatMessageSummary
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reply: AiChatMessageSummary
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