8bc1b4e571
web 多 tab 独立会话：run_message 加 session_id，会话 key 从 channel:user_id 扩展为 channel:user_id:session_id（空则向后兼容单会话）；AgentExecutor 历史 加载/保存按 session_id 隔离，空则回退 project 级隔离。
181 lines
7.7 KiB
Python
181 lines
7.7 KiB
Python
"""
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pipeline-service: gateway — agent 网关（统一消息入口 + 会话生命周期 + 通道注册）
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gateway 的核心价值：通道无关的统一消息入口。
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Web(AgentIO) / 微信 等通道都通过 gateway.run_message() 触达 agent，
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共享同一套「解析项目上下文 → 加载产线能力 → AgentExecutor 执行」逻辑。
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标准化事件流（channel-neutral NDJSON），所有通道可消费：
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{"type":"progress","message":...}
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{"type":"tool_call","tool":...,"params":...}
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{"type":"tool_result","result":...}
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{"type":"reply","message":...}
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{"type":"ask_user","message":...}
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{"type":"error","message":...}
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安全模型（微信通道）：机构级公众号 + 用户 openid 绑定 + 匿名拒绝，
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通道身份（openid）→ 系统 user_id 的映射由各通道适配器负责，gateway 只认 user_id。
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"""
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import json
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import logging
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import time
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from dataclasses import dataclass, field
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from typing import AsyncGenerator, Dict, Optional
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logger = logging.getLogger("pipeline.gateway")
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@dataclass
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class GatewaySession:
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"""一个会话 = (channel, user_id, session_id) 的 agent 上下文（元数据，executor 每次新建）。"""
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channel: str
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user_id: str
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session_id: str = "" # 会话内唯一标识（web 多 tab 独立会话）；空 = 单会话（向后兼容）
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project_id: str = ""
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pipeline_id: str = ""
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project_name: str = ""
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created_at: float = 0.0
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updated_at: float = 0.0
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approve_all: bool = False # 会话级"全部确认"：用户评估后授权，本会话不再询问危险命令
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pending_confirm: Optional[dict] = None # 待确认工具 {"tool":..., "params":...}（危险命令等待用户确认）
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class Gateway:
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"""agent 网关。"""
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def __init__(self):
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self._sessions: Dict[str, GatewaySession] = {} # key = f"{channel}:{user_id}"
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self._channels: Dict[str, object] = {}
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# ── 通道注册 ──
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def register_channel(self, name: str, channel) -> None:
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"""注册一个通道适配器（如 web/wechat）。"""
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self._channels[name] = channel
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logger.info(f"Gateway channel registered: {name}")
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def list_channels(self) -> list:
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return list(self._channels.keys())
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# ── 会话生命周期 ──
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@staticmethod
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def _session_key(channel: str, user_id: str, session_id: str = "") -> str:
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if session_id:
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return f"{channel}:{user_id}:{session_id}"
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return f"{channel}:{user_id}"
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def get_session(self, channel: str, user_id: str, session_id: str = "") -> Optional[GatewaySession]:
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return self._sessions.get(self._session_key(channel, user_id, session_id))
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def clear_session(self, channel: str, user_id: str, session_id: str = "") -> None:
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"""清除会话（/reset 时用）。"""
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self._sessions.pop(self._session_key(channel, user_id, session_id), None)
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# ── 上下文解析 ──
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async def resolve_project(self, user_id: str) -> dict:
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"""解析用户当前项目 → {pid, pipeline_id, name, default_llm_id, default_llm_name}。
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同时读出个人选择的模型（default_llm_id → llm.name），供 run_message 覆盖 config.model_name。
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"""
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ctx = {"pid": "", "pipeline_id": "", "name": "", "default_llm_id": "", "default_llm_name": ""}
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if not user_id:
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return ctx
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try:
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from sqlor.dbpools import DBPools
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db = DBPools()
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async with db.sqlorContext("pipeline") as sor:
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recs = await sor.sqlExe(
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"SELECT current_project_id, default_llm_id FROM pipeline_agent_settings WHERE user_id=${u}$",
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{"u": user_id})
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if recs:
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ctx["pid"] = getattr(recs[0], "current_project_id", "") or ""
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ctx["default_llm_id"] = getattr(recs[0], "default_llm_id", "") or ""
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# 单独查 llm.name（避免 JOIN 触发两表字段 collation 不一致）
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if ctx["default_llm_id"]:
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llm_recs = await sor.sqlExe(
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"SELECT name FROM llm WHERE id=${id}$ AND status='active'",
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{"id": ctx["default_llm_id"]})
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if llm_recs:
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ctx["default_llm_name"] = getattr(llm_recs[0], "name", "") or ""
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if ctx["pid"]:
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proj = await sor.sqlExe(
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"SELECT name, pipeline_id FROM sd_projects WHERE id=${p}$",
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{"p": ctx["pid"]})
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if proj:
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ctx["name"] = getattr(proj[0], "name", "")
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ctx["pipeline_id"] = getattr(proj[0], "pipeline_id", "") or ""
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except Exception as e:
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logger.warning(f"gateway resolve_project failed: {e}")
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return ctx
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# ── 统一消息入口 ──
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async def run_message(self, channel: str, user_id: str, content: str,
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history=None, role: str = "", generic: bool = False,
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base_url: str = "", session_id: str = "") -> AsyncGenerator[str, None]:
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"""统一消息入口：解析上下文 → 加载产线能力 → AgentExecutor 执行 → yield 事件流。
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Args:
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channel: 通道名（web / wechat / ...）
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user_id: 系统用户 ID（通道适配器负责把 openid 映射到 user_id）
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content: 用户消息内容
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history: 可选历史消息
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role: 可选产线内角色（驾驶舱 agent 为空）
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generic: True = 纯通用会话（不解析项目、不加载产线能力，只用 GENERAL_TOOLS + 通用心智）
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session_id: 会话内唯一标识（web 多 tab 独立会话用；空 = 单会话）
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"""
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from pipeline_core.agent_config import load_agent_config
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from .agent_loop_v2 import AgentExecutor
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# 1. 解析项目上下文（纯通用模式跳过，不挂任何产线插件）
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if generic:
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ctx = {"pid": "", "pipeline_id": "", "name": ""}
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else:
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ctx = await self.resolve_project(user_id)
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# 2. 会话生命周期（跟踪 project 切换；session_id 区分多 tab 会话）
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key = self._session_key(channel, user_id, session_id)
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sess = self._sessions.get(key)
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now = time.time()
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if sess is None or sess.project_id != ctx["pid"]:
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sess = GatewaySession(
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channel=channel, user_id=user_id, session_id=session_id,
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project_id=ctx["pid"], pipeline_id=ctx["pipeline_id"],
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project_name=ctx["name"], created_at=now, updated_at=now,
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)
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self._sessions[key] = sess
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else:
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sess.project_id = ctx["pid"]
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sess.pipeline_id = ctx["pipeline_id"]
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sess.project_name = ctx["name"]
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sess.updated_at = now
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# 3. 加载产线能力 + 创建 executor（generic 时不装产线能力）
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config = await load_agent_config(
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pipeline_id=ctx["pipeline_id"], project_id=ctx["pid"], generic=generic)
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# 个人选择的模型优先（default_llm_id → llm.name，覆盖产线 default_model）
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if ctx.get("default_llm_name"):
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config.model_name = ctx["default_llm_name"]
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executor = AgentExecutor(
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config=config, project_id=ctx["pid"], user_id=user_id, role=role,
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base_url=base_url, generic=generic, session=sess, session_id=session_id)
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# 4. 转发标准化事件流
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async for chunk in executor.run(content, history=history):
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yield chunk
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# ── 全局单例 ──
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_gateway: Optional[Gateway] = None
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def get_gateway() -> Gateway:
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global _gateway
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if _gateway is None:
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_gateway = Gateway()
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return _gateway
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