66d52ad020
在飞书 WS handler 中新增图片消息识别与下载：
- _get_image_key: 检测飞书 image 类型消息，提取 image_key
- download_image_from_feishu: 调用飞书 API 下载图片二进制
- 图片保存到 agent_workspaces/{agent_id}/images/ 下
- Agent 自动调用 image_ocr + image_vision 分析后回复用户
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
368 lines
14 KiB
Python
368 lines
14 KiB
Python
"""人参果1号飞书长连接 — 固定路由到 AI学习助手 Agent（行为约束版，禁止主动消息）"""
|
||
from __future__ import annotations
|
||
|
||
import asyncio
|
||
import json
|
||
import logging
|
||
from collections import deque
|
||
from typing import Optional
|
||
|
||
from app.core.config import settings
|
||
|
||
logger = logging.getLogger(__name__)
|
||
|
||
_processed_msg_ids: deque[str] = deque(maxlen=20)
|
||
|
||
|
||
def _get_message_id(data) -> Optional[str]:
|
||
try:
|
||
ev = data.event
|
||
msg = getattr(ev, "message", None)
|
||
if msg:
|
||
return getattr(msg, "message_id", None)
|
||
except Exception:
|
||
return None
|
||
return None
|
||
|
||
|
||
def _get_message_text(data) -> Optional[str]:
|
||
try:
|
||
ev = data.event
|
||
msg = getattr(ev, "message", None)
|
||
if not msg:
|
||
return None
|
||
content_str = getattr(msg, "content", None)
|
||
msg_type = getattr(msg, "message_type", "")
|
||
if not content_str:
|
||
return None
|
||
if msg_type == "text":
|
||
parsed = json.loads(content_str)
|
||
return parsed.get("text", "")
|
||
return None
|
||
except Exception as e:
|
||
logger.warning("解析人参果1号消息内容失败: %s", e)
|
||
return None
|
||
|
||
|
||
def _get_image_key(data) -> Optional[str]:
|
||
"""从图片消息中提取 image_key，返回 None 表示不是图片消息。"""
|
||
try:
|
||
ev = data.event
|
||
msg = getattr(ev, "message", None)
|
||
if not msg:
|
||
return None
|
||
msg_type = getattr(msg, "message_type", "")
|
||
if msg_type != "image":
|
||
return None
|
||
content_str = getattr(msg, "content", None)
|
||
if not content_str:
|
||
return None
|
||
parsed = json.loads(content_str)
|
||
return parsed.get("image_key", None)
|
||
except Exception:
|
||
return None
|
||
|
||
|
||
def _get_sender_open_id(data) -> Optional[str]:
|
||
try:
|
||
ev = data.event
|
||
sender = getattr(ev, "sender", None)
|
||
if not sender:
|
||
return None
|
||
sender_id = getattr(sender, "sender_id", None)
|
||
if not sender_id:
|
||
return None
|
||
return getattr(sender_id, "open_id", None)
|
||
except Exception:
|
||
return None
|
||
|
||
|
||
def _get_sender_union_id(data) -> Optional[str]:
|
||
try:
|
||
ev = data.event
|
||
sender = getattr(ev, "sender", None)
|
||
if not sender:
|
||
return None
|
||
sender_id = getattr(sender, "sender_id", None)
|
||
if not sender_id:
|
||
return None
|
||
return getattr(sender_id, "union_id", None)
|
||
except Exception:
|
||
return None
|
||
|
||
|
||
def _get_chat_type(data) -> str:
|
||
try:
|
||
ev = data.event
|
||
msg = getattr(ev, "message", None)
|
||
return getattr(msg, "chat_type", "") if msg else ""
|
||
except Exception:
|
||
return ""
|
||
|
||
|
||
def _reply_to_feishu(open_id: str, text: str):
|
||
try:
|
||
from app.services.renshenguo2_app_service import send_plain_text
|
||
send_plain_text(open_id, text)
|
||
except Exception as e:
|
||
logger.warning("人参果1号回复消息失败: %s", e)
|
||
|
||
|
||
def _reply_card(open_id: str, title: str, content: str, status: str = "info"):
|
||
try:
|
||
from app.services.renshenguo2_app_service import send_message_to_user
|
||
send_message_to_user(open_id, title, content, status=status)
|
||
except Exception as e:
|
||
logger.warning("人参果1号回复卡片失败: %s", e)
|
||
|
||
|
||
def _make_llm_logger(db, agent_id: Optional[str] = None, user_id: Optional[str] = None):
|
||
def _log(metrics: dict):
|
||
try:
|
||
from app.models.agent_llm_log import AgentLLMLog
|
||
log = AgentLLMLog(
|
||
agent_id=agent_id, session_id=metrics.get("session_id"),
|
||
user_id=user_id, model=metrics.get("model", ""),
|
||
provider=metrics.get("provider"),
|
||
prompt_tokens=metrics.get("prompt_tokens", 0),
|
||
completion_tokens=metrics.get("completion_tokens", 0),
|
||
total_tokens=metrics.get("total_tokens", 0),
|
||
latency_ms=metrics.get("latency_ms", 0),
|
||
iteration_number=metrics.get("iteration_number", 0),
|
||
step_type=metrics.get("step_type"),
|
||
tool_name=metrics.get("tool_name"),
|
||
status=metrics.get("status", "success"),
|
||
error_message=metrics.get("error_message"),
|
||
)
|
||
db.add(log)
|
||
db.commit()
|
||
except Exception as e:
|
||
logger.warning("写入 AgentLLMLog 失败: %s", e)
|
||
return _log
|
||
|
||
|
||
async def _handle_message_async(data):
|
||
open_id = _get_sender_open_id(data)
|
||
union_id = _get_sender_union_id(data)
|
||
chat_type = _get_chat_type(data)
|
||
text = _get_message_text(data)
|
||
image_key = _get_image_key(data)
|
||
message_id = _get_message_id(data)
|
||
|
||
if not open_id or chat_type != "p2p":
|
||
return
|
||
|
||
if text:
|
||
logger.info("人参果1号收到文本消息: open_id=%s text=%s", open_id[:20], text[:80])
|
||
elif image_key and message_id:
|
||
logger.info("人参果1号收到图片消息: open_id=%s image_key=%s", open_id[:20], image_key[:30])
|
||
else:
|
||
return
|
||
|
||
from sqlalchemy.orm import Session
|
||
from app.core.database import SessionLocal
|
||
from app.models.agent import Agent
|
||
from app.services.feishu_open_id_service import resolve_user_and_save
|
||
|
||
db: Optional[Session] = None
|
||
try:
|
||
db = SessionLocal()
|
||
|
||
# 自动保存/关联此应用的 open_id（跨应用识别）
|
||
resolved_uid = resolve_user_and_save(
|
||
db, app_id=settings.RENSHENGUO2_APP_ID or "",
|
||
open_id=open_id, union_id=union_id,
|
||
)
|
||
|
||
agent_id = settings.RENSHENGUO2_AGENT_ID
|
||
if not agent_id:
|
||
_reply_to_feishu(open_id, "人参果1号尚未配置，请联系管理员。")
|
||
return
|
||
|
||
agent = db.query(Agent).filter(Agent.id == agent_id).first()
|
||
if not agent:
|
||
_reply_to_feishu(open_id, "人参果1号 Agent 已不存在，请联系管理员。")
|
||
return
|
||
|
||
_reply_to_feishu(open_id, "正在思考，请稍候...")
|
||
|
||
# ─── 图片消息：下载飞书图片到工作区 ───────────────────
|
||
image_attachment_path = None
|
||
if image_key and message_id and not text:
|
||
from app.services.renshenguo2_app_service import download_image_from_feishu
|
||
from app.services.builtin_tools import _local_file_workspace_root
|
||
|
||
image_bytes = download_image_from_feishu(message_id, image_key)
|
||
if image_bytes:
|
||
ws_root = _local_file_workspace_root()
|
||
uploads_dir = ws_root / "agent_workspaces" / str(agent.id) / "images"
|
||
uploads_dir.mkdir(parents=True, exist_ok=True)
|
||
import time as _time
|
||
image_filename = f"feishu_img_{_time.strftime('%Y%m%d_%H%M%S')}.jpg"
|
||
image_path = uploads_dir / image_filename
|
||
image_path.write_bytes(image_bytes)
|
||
image_attachment_path = str(image_path.relative_to(ws_root)).replace("\\", "/")
|
||
text = (
|
||
f"用户通过飞书发来了一张图片。"
|
||
f"图片已保存到工作区路径: {image_attachment_path}\n"
|
||
f"请先用 image_ocr 提取图片中的文字，"
|
||
f"如果文字不足以理解内容，再用 image_vision 分析图片，"
|
||
f"然后根据分析结果回复用户。"
|
||
)
|
||
logger.info("人参果1号图片已保存: %s (%d bytes)", image_attachment_path, len(image_bytes))
|
||
else:
|
||
_reply_to_feishu(open_id, "图片下载失败，请稍后重试。")
|
||
return
|
||
|
||
from app.agent_runtime import AgentRuntime, AgentConfig, AgentLLMConfig, AgentToolConfig, AgentMemoryConfig
|
||
|
||
wc = agent.workflow_config or {}
|
||
nodes = wc.get("nodes", [])
|
||
system_prompt = agent.description or ""
|
||
model = "deepseek-v4-flash"
|
||
provider = "deepseek"
|
||
temperature = 0.7
|
||
max_iterations = 15
|
||
tools_whitelist = []
|
||
|
||
for n in nodes:
|
||
if n.get("type") not in ("agent", "llm", "template"):
|
||
continue
|
||
cfg = n.get("data", {}) if isinstance(n, dict) else getattr(n, "data", {})
|
||
system_prompt = cfg.get("system_prompt", "") or system_prompt
|
||
model = cfg.get("model", model)
|
||
provider = cfg.get("provider", provider)
|
||
temperature = float(cfg.get("temperature", temperature))
|
||
max_iterations = int(cfg.get("max_iterations", max_iterations))
|
||
tools_whitelist = cfg.get("tools", tools_whitelist)
|
||
break
|
||
|
||
# 人参果1号：在 system_prompt 末尾强制注入行为约束
|
||
# 无论 DB 中的 system_prompt 如何配置，这些规则始终生效
|
||
behavior_rules = (
|
||
f"\n\n## 系统信息\n"
|
||
f"你的 Agent ID 是: {agent.id}\n"
|
||
f"在调用 schedule_list、schedule_delete 等工具时，使用此 ID 作为 agent_id 参数。"
|
||
f"\n\n## 行为约束（必须严格遵守，违反将导致严重问题）\n"
|
||
f"1. **被动响应原则**：仅在用户主动发送消息时回复。不得根据时间流逝、用户在线状态或任何隐式信号主动发起对话。用户不说话，你就别说话。\n"
|
||
f"2. **单轮回复限制**：对于用户的每条消息，只回复一次。回复完毕后必须停止，不得继续追问、猜测用户状态或发送额外消息。\n"
|
||
f"3. **禁止重复关心**：如果上一轮已经表达过关心、提醒或催促（如催睡觉、催休息），不得在用户没有新输入的情况下重复类似内容。\n"
|
||
f"4. **禁止猜测用户状态**：不得主动猜测用户的行为、情绪或状态（如\"你是不是睡不着\"、\"你是不是又回来了\"、\"让我猜猜你现在\"）。只回应用户明确提出的问题或话题。\n"
|
||
f"5. **简洁直接**：回答应简洁、直接、切题。避免过度的寒暄、emoji堆砌、表格罗列猜测和冗余内容。\n"
|
||
f"6. **上下文中立**：记忆系统提供的历史信息仅供理解上下文使用，不得用于主动发起话题、回顾\"上次你如何如何\"或过度个性化回应。\n"
|
||
f"7. **禁止自言自语**：一次回复结束后，除非用户再次发送消息，否则绝对不要产生任何新输出。"
|
||
)
|
||
|
||
config = AgentConfig(
|
||
name=agent.name or "人参果1号",
|
||
system_prompt=system_prompt + behavior_rules,
|
||
llm=AgentLLMConfig(
|
||
model=model, provider=provider,
|
||
temperature=temperature, max_iterations=max_iterations,
|
||
),
|
||
tools=AgentToolConfig(include_tools=tools_whitelist),
|
||
memory=AgentMemoryConfig(
|
||
max_history_messages=int(cfg.get("memory_max_history", 40)),
|
||
vector_memory_top_k=int(cfg.get("memory_vector_top_k", 10)),
|
||
persist_to_db=bool(cfg.get("memory_persist", True)),
|
||
vector_memory_enabled=bool(cfg.get("memory_vector_enabled", True)),
|
||
learning_enabled=bool(cfg.get("memory_learning", True)),
|
||
),
|
||
user_id=resolved_uid,
|
||
memory_scope_id=str(agent.id),
|
||
)
|
||
|
||
on_llm_call = _make_llm_logger(db, agent_id=str(agent.id))
|
||
runtime = AgentRuntime(config=config, on_llm_call=on_llm_call)
|
||
result = await runtime.run(text)
|
||
|
||
if result.content:
|
||
_reply_card(open_id, f"{agent.name}", result.content.strip(), status="success")
|
||
else:
|
||
_reply_to_feishu(open_id, "Agent 未返回有效回复，请重试。")
|
||
|
||
logger.info(
|
||
"人参果1号 Agent 回复完成: open_id=%s agent=%s iterations=%d tools=%d",
|
||
open_id[:20], agent.name, result.iterations_used, result.tool_calls_made,
|
||
)
|
||
|
||
except Exception as e:
|
||
logger.error("人参果1号消息处理失败: %s", e)
|
||
try:
|
||
_reply_to_feishu(open_id, f"处理失败: {e!s}")
|
||
except Exception:
|
||
pass
|
||
finally:
|
||
if db:
|
||
db.close()
|
||
|
||
|
||
def _handle_message_internal(data):
|
||
msg_id = _get_message_id(data)
|
||
if msg_id:
|
||
if msg_id in _processed_msg_ids:
|
||
return
|
||
_processed_msg_ids.append(msg_id)
|
||
|
||
open_id = _get_sender_open_id(data)
|
||
chat_type = _get_chat_type(data)
|
||
text = _get_message_text(data)
|
||
|
||
if not open_id or chat_type != "p2p" or not text:
|
||
return
|
||
|
||
try:
|
||
loop = asyncio.get_event_loop()
|
||
if loop.is_running():
|
||
asyncio.ensure_future(_handle_message_async(data))
|
||
else:
|
||
loop.run_until_complete(_handle_message_async(data))
|
||
except Exception as e:
|
||
logger.error("人参果1号创建消息处理任务失败: %s", e)
|
||
try:
|
||
_reply_to_feishu(open_id, f"处理失败: {e!s}")
|
||
except Exception:
|
||
pass
|
||
|
||
|
||
def _build_event_handler():
|
||
from lark_oapi.event.dispatcher_handler import EventDispatcherHandler
|
||
|
||
def on_message_receive(data):
|
||
_handle_message_internal(data)
|
||
|
||
builder = EventDispatcherHandler.builder(encrypt_key="", verification_token="")
|
||
builder.register_p2_im_message_receive_v1(on_message_receive)
|
||
return builder.build()
|
||
|
||
|
||
async def start_ws_client():
|
||
if not settings.RENSHENGUO2_APP_ID or not settings.RENSHENGUO2_APP_SECRET:
|
||
logger.warning("人参果1号应用未配置，跳过人参果1号长连接启动")
|
||
return
|
||
|
||
from lark_oapi.ws import Client as WSClient
|
||
|
||
handler = _build_event_handler()
|
||
client = WSClient(
|
||
app_id=settings.RENSHENGUO2_APP_ID,
|
||
app_secret=settings.RENSHENGUO2_APP_SECRET,
|
||
event_handler=handler,
|
||
auto_reconnect=True,
|
||
)
|
||
|
||
logger.info("人参果1号长连接客户端启动中...")
|
||
|
||
while True:
|
||
try:
|
||
await client._connect()
|
||
logger.info("人参果1号长连接已建立")
|
||
asyncio.ensure_future(client._ping_loop())
|
||
while True:
|
||
await asyncio.sleep(3600)
|
||
except asyncio.CancelledError:
|
||
break
|
||
except Exception as e:
|
||
logger.warning("人参果1号长连接断开，3秒后重连: %s", e)
|
||
await asyncio.sleep(3)
|