Files
KiloStar/kilostar/api/chat.py
T
zhaoxi b61524e5d9 fix: chat stream 走 regulatory agent 支持工具调用,修复 workflow ValidationError
1. chat.py stream 端点改为调用 regulatory_node.stream_working()(pydantic-ai
   run_stream),支持工具调用 + 逐 token 流式输出
2. regulatory_node 新增 stream_working 方法,通过 asyncio.Queue 推送 token
3. ConsciousnessNodeDeps.available_skills 加默认值 None,修复 ForWorkflowInput/
   ForregulatoryInput 路径的 ValidationError

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-06-05 07:37:59 +00:00

220 lines
7.3 KiB
Python

# Copyright 2026 zhaoxi826
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import json
import asyncio
from fastapi import APIRouter, Depends, HTTPException, Request
from fastapi.responses import StreamingResponse
from pydantic import BaseModel
from kilostar.utils.ray_hook import ray_actor_hook
from kilostar.utils.access import Accessor, TokenData
from kilostar.core.individual.regulatory_node.template import (
MessageRequest,
MessageResponse,
)
chat_router = APIRouter(prefix="/api/v1/chat", tags=["chat"])
def _extract_reply(resp: MessageResponse | None) -> str | None:
"""从 RegulatoryNode.working 的输出里取出对用户的回复文本。
RegulatoryNode 现在的 output_type 只剩 ``MessageResponse``(聊天/简单任务/汇报),
没有则视为节点降级为静默——上层不写回 chat history。
"""
if resp is None:
return None
return resp.reply_message
async def _ask_regulatory(
*, user_id: str, chat_id: str, message: str
) -> str | None:
"""统一封装 chat 入口对 RegulatoryNode 的调用。"""
regulatory_node = ray_actor_hook("regulatory_node").regulatory_node
payload = MessageRequest(
platform="client",
user_name=user_id,
platform_id=chat_id,
message=message,
)
resp: MessageResponse | None = await regulatory_node.working.remote(payload)
return _extract_reply(resp)
class CreateChatRequest(BaseModel):
title: str = "新对话"
initial_message: str
class SendMessageRequest(BaseModel):
message: str
@chat_router.post("")
async def create_chat_session(
request: CreateChatRequest,
token_data: TokenData = Depends(Accessor.get_current_user),
):
postgres_database = ray_actor_hook("postgres_database").postgres_database
chat = await postgres_database.create_chat_session.remote(
user_id=token_data.user_id, title=request.title
)
# 存入用户消息
await postgres_database.add_chat_message.remote(
chat_id=chat.chat_id, message=request.initial_message, message_owner="user"
)
# 调用监管节点处理简单任务/交流
response_msg = await _ask_regulatory(
user_id=token_data.user_id,
chat_id=chat.chat_id,
message=request.initial_message,
)
# 存入回复消息
if response_msg:
await postgres_database.add_chat_message.remote(
chat_id=chat.chat_id, message=response_msg, message_owner="regulatory_node"
)
return {"chat_id": chat.chat_id, "reply": response_msg}
@chat_router.get("")
async def list_chat_sessions(
token_data: TokenData = Depends(Accessor.get_current_user),
):
postgres_database = ray_actor_hook("postgres_database").postgres_database
sessions = await postgres_database.list_chat_sessions.remote(
user_id=token_data.user_id
)
return {"sessions": sessions}
@chat_router.get("/{chat_id}")
async def get_chat_history(
chat_id: str, token_data: TokenData = Depends(Accessor.get_current_user)
):
postgres_database = ray_actor_hook("postgres_database").postgres_database
messages = await postgres_database.list_chat_messages.remote(chat_id=chat_id)
return {"messages": messages}
@chat_router.post("/{chat_id}/reply")
async def send_chat_message(
chat_id: str,
request: SendMessageRequest,
token_data: TokenData = Depends(Accessor.get_current_user),
):
postgres_database = ray_actor_hook("postgres_database").postgres_database
# 存用户消息
await postgres_database.add_chat_message.remote(
chat_id=chat_id, message=request.message, message_owner="user"
)
# 调用监管节点
response_msg = await _ask_regulatory(
user_id=token_data.user_id,
chat_id=chat_id,
message=request.message,
)
# 存回复
if response_msg:
await postgres_database.add_chat_message.remote(
chat_id=chat_id, message=response_msg, message_owner="regulatory_node"
)
return {"reply": response_msg}
@chat_router.delete("/{chat_id}")
async def delete_chat_session(
chat_id: str,
token_data: TokenData = Depends(Accessor.get_current_user),
):
postgres_database = ray_actor_hook("postgres_database").postgres_database
session = await postgres_database.get_chat_session.remote(chat_id=chat_id)
if not session:
raise HTTPException(status_code=404, detail="Chat session not found")
if session.user_id != token_data.user_id:
raise HTTPException(status_code=403, detail="Forbidden")
await postgres_database.delete_chat_session.remote(chat_id=chat_id)
return {"message": "success"}
@chat_router.post("/{chat_id}/stream")
async def stream_chat_message(
chat_id: str,
request_body: SendMessageRequest,
request: Request,
token_data: TokenData = Depends(Accessor.get_current_user),
):
"""SSE 流式聊天端点:通过 regulatory_node agent 流式输出,支持工具调用。"""
postgres_database = ray_actor_hook("postgres_database").postgres_database
# 存用户消息
await postgres_database.add_chat_message.remote(
chat_id=chat_id, message=request_body.message, message_owner="user"
)
# 构造 MessageRequest payload
payload = MessageRequest(
platform="client",
user_name=token_data.user_id,
platform_id=chat_id,
message=request_body.message,
)
regulatory_node = ray_actor_hook("regulatory_node").regulatory_node
token_queue = asyncio.Queue()
# stream_working.remote() returns an asyncio.Task in standalone mode
stream_task = regulatory_node.stream_working.remote(payload, token_queue)
async def event_generator():
full_response = ""
try:
while True:
if await request.is_disconnected():
stream_task.cancel()
break
try:
token = await asyncio.wait_for(token_queue.get(), timeout=0.5)
except asyncio.TimeoutError:
continue
if token is None:
break
full_response += token
yield f"data: {json.dumps({'token': token})}\n\n"
except Exception as e:
from kilostar.utils.logger import get_logger
get_logger("chat_stream").exception(f"Stream error: {e}")
if not full_response:
full_response = "抱歉,生成回复时出错。"
yield f"data: {json.dumps({'token': full_response})}\n\n"
# 流结束,存入数据库
if full_response:
await postgres_database.add_chat_message.remote(
chat_id=chat_id,
message=full_response,
message_owner="regulatory_node",
)
yield f"data: {json.dumps({'done': True, 'full_message': full_response})}\n\n"
return StreamingResponse(event_generator(), media_type="text/event-stream")