201 lines
7.1 KiB
Python
201 lines
7.1 KiB
Python
import json
|
|
import time
|
|
from typing import Union
|
|
|
|
from fastapi import FastAPI
|
|
from langchain_core.messages import AIMessage, ToolMessage
|
|
from langgraph.graph.state import CompiledStateGraph
|
|
from langgraph.prebuilt import create_react_agent
|
|
from langgraph.types import Command
|
|
from pydantic import BaseModel, Field
|
|
from starlette.requests import Request
|
|
from starlette.responses import StreamingResponse
|
|
|
|
from app.model.ConversationModel import ConversationService
|
|
from app.tools.tool_list import tool_list
|
|
from app.tools.tool_project_report import tool_project_report
|
|
from app.utils.db_utils import AsyncSessionDep
|
|
from app.utils.llm_utils import create_llm
|
|
from app.utils.postgres_checkpointer import PostgresCheckpointerManager, AsyncPostgresSaverDep
|
|
|
|
|
|
class ChatMessage(BaseModel):
|
|
id: str = Field(..., description="消息id")
|
|
type: str = Field(..., description="消息类型")
|
|
content: str = Field(..., description="消息内容")
|
|
|
|
|
|
# 对话接口参数类型
|
|
class ChatParam(BaseModel):
|
|
thread_id: str = Field(..., description="线程id")
|
|
human_message: ChatMessage = Field(..., description="用户消息")
|
|
|
|
|
|
class ChatAgent:
|
|
agent: Union[CompiledStateGraph, None] = None
|
|
|
|
@staticmethod
|
|
async def get_agent() -> CompiledStateGraph:
|
|
if not ChatAgent.agent:
|
|
ChatAgent.agent = create_react_agent(
|
|
model=create_llm("huoshan-think-pro"),
|
|
tools=tool_list,
|
|
checkpointer=await PostgresCheckpointerManager.get_instance(),
|
|
prompt="""
|
|
- 你是一名擅长使用工具的智能助手，你需要根据用户问题来进行回答，请使用中文进行回答。
|
|
- 当用户问题需要调用工具时再调用工具，否则按照你的知识来回答问题。
|
|
- 你每次只能调用一个工具
|
|
- 特别注意，特别注意，特别注意，如果工具的返回结果是一个数组，你只能回复“工具已经执行完毕”
|
|
"""
|
|
)
|
|
return ChatAgent.agent
|
|
|
|
@staticmethod
|
|
async def get_chat_state(thread_id: str):
|
|
graph = await ChatAgent.get_agent()
|
|
graph_state = await graph.aget_state(config={"configurable": {"thread_id": thread_id}})
|
|
if graph_state.values.get('messages', None) is None:
|
|
graph_state.values['messages'] = []
|
|
return {
|
|
**graph_state.values,
|
|
"__interrupt__": graph_state.interrupts,
|
|
}
|
|
|
|
|
|
def add_langgraph_chat_route(app: FastAPI):
|
|
@app.post("/project/analysis")
|
|
async def project_analysis(body: dict):
|
|
|
|
return await tool_project_report.ainvoke({
|
|
"project_name": body.get('project_name'),
|
|
"start_time": body.get("start_time", None),
|
|
"end_time": body.get("end_time", None),
|
|
})
|
|
|
|
# 流式对话接口
|
|
@app.post("/langgraph/stream")
|
|
async def langgraph_stream(
|
|
body: dict,
|
|
request: Request,
|
|
):
|
|
print(":::::::::::::::::::::::::langgraph_stream:::::::::::::::::::::")
|
|
print(body)
|
|
print(request.state.user)
|
|
print(request.state.token)
|
|
|
|
stream_input = body.get('input')
|
|
stream_config = body.get('config')
|
|
stream_config['configurable']['token'] = request.state.token
|
|
stream_config['configurable']['user_id'] = request.state.user.id
|
|
|
|
print("stream_input", stream_input)
|
|
print("stream_config", stream_config)
|
|
|
|
# 暂时每次对话的时候清理掉对话历史
|
|
# await checkpointer.adelete_thread(stream_config.get('configurable').get('thread_id'))
|
|
|
|
async def generator_function():
|
|
|
|
graph = await ChatAgent.get_agent()
|
|
|
|
# chat_state = await ChatAgent.get_chat_state(thread_id)
|
|
# chat_history_list = chat_state.get('messages')
|
|
|
|
# has_emit_message_id 用来优化流式传输，避免将content为空的为AIMessageChunk发送给前端（实际上此时正在输出思考内容）
|
|
# 第一次的时候输出，后续再输出content为空的AIMessageChunk不发送给前端
|
|
has_emit_message_id = {}
|
|
|
|
async for chunk in graph.astream(
|
|
stream_input,
|
|
config=stream_config,
|
|
stream_mode=['messages', 'updates']
|
|
):
|
|
print("chunk-------->>>>>>>>>>", chunk)
|
|
|
|
result_template = {
|
|
"choices": [{"delta": {}, "index": 0}],
|
|
"created": time.time(),
|
|
"id": "",
|
|
"usage": None
|
|
}
|
|
|
|
emit_chunk = {"stream_type": chunk[0], }
|
|
|
|
if emit_chunk['stream_type'] == "messages":
|
|
# messages模式流式输出，此时 chunk[1][0] 为AIMessageChunk
|
|
chunk_message = chunk[1][0]
|
|
if not chunk_message.content:
|
|
if has_emit_message_id.get(chunk_message.id):
|
|
continue
|
|
else:
|
|
# updates模式流式输出
|
|
for k, v in chunk[1].items():
|
|
if k == 'agent' or k == 'tool':
|
|
chunk_message = v.get('messages')[0]
|
|
elif k == '__interrupt__':
|
|
chunk_message = AIMessage(content='')
|
|
emit_chunk['stream_type'] = 'interrupt'
|
|
emit_chunk['interrupt'] = v[0].value
|
|
|
|
emit_chunk = {
|
|
**emit_chunk,
|
|
"msg_id": chunk_message.id,
|
|
"msg_type": chunk_message.type,
|
|
"msg_content": chunk_message.content,
|
|
}
|
|
has_emit_message_id[chunk_message.id] = True
|
|
|
|
if isinstance(chunk_message, AIMessage):
|
|
if chunk_message.tool_calls:
|
|
emit_chunk["tool_calls"] = chunk_message.tool_calls
|
|
elif isinstance(chunk_message, ToolMessage):
|
|
emit_chunk["tool_name"] = chunk_message.name
|
|
emit_chunk["additional_kwargs"] = chunk_message.additional_kwargs
|
|
|
|
result_template["choices"][0]["delta"]['content'] = emit_chunk
|
|
result_template["choices"][0]["delta"]['role'] = 'assistant'
|
|
|
|
result_template['id'] = chunk_message.id
|
|
result_template['created'] = int(time.time())
|
|
|
|
yield f"data: {json.dumps(result_template, ensure_ascii=False)}\n\n"
|
|
# yield "data: [DONE]\n\n"
|
|
|
|
return StreamingResponse(generator_function(), media_type="text/event-stream")
|
|
|
|
# 恢复中断接口
|
|
@app.post("/langgraph/chat_resume/{thread_id}")
|
|
async def langgraph_chat(
|
|
body: dict,
|
|
thread_id: str,
|
|
request: Request,
|
|
):
|
|
graph = await ChatAgent.get_agent()
|
|
chat_state = await ChatAgent.get_chat_state(thread_id)
|
|
chat_history_list = chat_state.get('messages')
|
|
graph_state = await graph.ainvoke(
|
|
Command(resume=body.get('resume_data')),
|
|
config={"configurable": {
|
|
"thread_id": thread_id,
|
|
"token": request.state.token,
|
|
"user_id": request.state.user.id,
|
|
}}
|
|
)
|
|
return {
|
|
**graph_state,
|
|
# 这里不需要加1，因为我们并没有往messages中增加消息
|
|
"messages": graph_state.get('messages')[len(chat_history_list):],
|
|
}
|
|
|
|
# 查询聊天记录
|
|
@app.get("/langgraph/chat_state/{thread_id}")
|
|
async def langgraph_chat(thread_id: str):
|
|
return await ChatAgent.get_chat_state(thread_id) # 查询聊天记录
|
|
|
|
# 删除聊天记录
|
|
@app.post("/langgraph/chat_remove/{thread_id}")
|
|
async def langgraph_chat(thread_id: str, checkpointer: AsyncPostgresSaverDep, session: AsyncSessionDep):
|
|
await ConversationService.item_delete(session=session, row_dict={"id": thread_id})
|
|
await checkpointer.adelete_thread(thread_id)
|
|
return {"result": "success"}
|