fix(wechat-bot): ①对话时间统一北京时间 ②媒体内联发送(微信直看图片/视频) ③媒体生成计入Token驾驶舱 ④清空技能市场
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@@ -459,6 +459,9 @@ async def _generate_media_task(ai_msg_id: str, ai_model_id: str, prompt: str, us
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msg.token_used = len(result) // 2
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db.commit()
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logger.info(f"[_generate_media_task] 消息 {ai_msg_id} 已回写内容")
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# 媒体 Token 记账:把图片/视频真实消耗写入 TokenUsageLog,供驾驶舱统计。
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# 主流程对媒体请求只写了占位文本的几 token,此处补写真实媒体消耗(模型名正确、数值合理)。
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_write_media_token_log(db, ai_model, user_id, msg.conversation_id if msg else None, prompt)
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except Exception as e:
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logger.warning(f"[_generate_media_task] 后台生成异常: {e}")
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finally:
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@@ -468,6 +471,38 @@ async def _generate_media_task(ai_msg_id: str, ai_model_id: str, prompt: str, us
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pass
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def _write_media_token_log(db, ai_model, user_id: str, conversation_id: str, prompt: str):
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"""媒体生成完成后补写 TokenUsageLog(图片/视频),修正此前只记占位文本的偏差。
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媒体 API 不返回 token 用量,采用与 IM Bot 路径一致的估算:
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视频基线 1200、图片基线 400,再加 prompt 长度的 1/4 作为提示词开销。
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"""
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if not user_id or not ai_model:
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return
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try:
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is_video = "video" in (ai_model.capabilities or [])
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base = 1200 if is_video else 400
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est = base + (len(prompt or "") // 4)
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db.add(TokenUsageLog(
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id=gen_uuid(),
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user_id=user_id,
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model_id=ai_model.id,
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model_name=ai_model.name,
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conversation_id=conversation_id,
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prompt_tokens=est,
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completion_tokens=0,
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total_tokens=est,
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created_at=cst_now(),
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))
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db.commit()
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except Exception as e:
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logger.warning(f"[_write_media_token_log] 写入失败(忽略): {e}")
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try:
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db.rollback()
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except Exception:
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pass
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# ============================================================
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# 外部 Agent 远程调用 (Dify / n8n / Coze)
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# ============================================================
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@@ -2062,19 +2097,20 @@ async def send_message(
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conv.knowledge_graph_count = (conv.knowledge_graph_count or 0) + 1
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conv.updated_at = cst_now()
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# 记录Token使用
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token_usage = TokenUsageLog(
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id=gen_uuid(),
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user_id=current_user.id,
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model_id=ai_model.id if ai_model else (req.model_id or conv.model_id),
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model_name=ai_model.name if ai_model else None,
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conversation_id=conv_id,
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prompt_tokens=prompt_tokens or len(req.content) // 2,
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completion_tokens=completion_tokens or ai_token_count,
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total_tokens=total_tokens or (len(req.content) // 2 + ai_token_count),
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created_at=cst_now(),
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)
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db.add(token_usage)
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# 记录Token使用(媒体生成走 _generate_media_task 异步补写真实消耗,此处跳过避免占位文本重复记账)
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if not media_generating:
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token_usage = TokenUsageLog(
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id=gen_uuid(),
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user_id=current_user.id,
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model_id=ai_model.id if ai_model else (req.model_id or conv.model_id),
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model_name=ai_model.name if ai_model else None,
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conversation_id=conv_id,
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prompt_tokens=prompt_tokens or len(req.content) // 2,
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completion_tokens=completion_tokens or ai_token_count,
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total_tokens=total_tokens or (len(req.content) // 2 + ai_token_count),
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created_at=cst_now(),
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)
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db.add(token_usage)
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# 进化轨迹记录
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try:
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@@ -17,7 +17,7 @@ import json
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import random
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import threading
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import time
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from datetime import datetime, timedelta
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from datetime import datetime, timedelta, timezone
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from typing import Optional
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import requests
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@@ -31,6 +31,15 @@ from ..models import User
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router = APIRouter()
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# 北京时间(UTC+8)。容器系统时区为 UTC,所有对外展示/持久化的时间戳必须按北京时间存储,
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# 否则前台微信 Bot 对话窗会显示成 UTC(比系统时间早 8 小时)。
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TZ_BEIJING = timezone(timedelta(hours=8))
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def _beijing_now() -> datetime:
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"""返回北京时间的 naive datetime(去掉 tzinfo 以便直接存入 MySQL DATETIME)。"""
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return datetime.now(TZ_BEIJING).replace(tzinfo=None)
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# ============================================================
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# iLink 协议常量(腾讯官方 iLink Bot HTTP API,直连免 AppID)
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# ============================================================
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@@ -136,7 +145,7 @@ def _qihua_reply(text: str, user_id: str = None) -> str:
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try:
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from app.api.im_llm import _call_real_llm
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db = SessionLocal()
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return _call_real_llm(db, None, prompt, "个人微信")
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return _call_real_llm(db, None, prompt, "个人微信", user_id=user_id)
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except Exception as e:
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return f"(AI 回复生成失败:{e})"
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finally:
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@@ -164,9 +173,9 @@ def _wechat_get_updates(baseurl: str, bot_token: str, cursor: str):
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return [], cursor
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def _wechat_send_message(baseurl: str, bot_token: str, to_user_id: str, context_token: str, text: str):
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"""发送文本回复(必须带 context_token 关联到正确的对话窗口)。
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返回 (ok, ret, body)。ret=-14=会话过期需重扫;ret=-2=token 失效。"""
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def _wechat_post_msg(baseurl: str, bot_token: str, to_user_id: str, context_token: str, item_list: list):
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"""向 iLink 发送一条消息(item_list 可含文本/图片/视频等)。返回 (ok, ret, body)。
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ret=-14=会话过期需重扫;ret=-2=token 失效。"""
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import uuid as _uuid
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payload = {
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"msg": {
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@@ -176,7 +185,7 @@ def _wechat_send_message(baseurl: str, bot_token: str, to_user_id: str, context_
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"message_type": 2,
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"message_state": 2,
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"context_token": context_token,
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"item_list": [{"type": 1, "text_item": {"text": text}}],
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"item_list": item_list,
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},
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"base_info": {"channel_version": "1.0.2"},
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}
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@@ -197,7 +206,7 @@ def _wechat_send_message(baseurl: str, bot_token: str, to_user_id: str, context_
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ret = body.get("ret") if isinstance(body, dict) else None
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try:
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with open("/tmp/wechat_send.log", "a", encoding="utf-8") as _f:
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_f.write(datetime.now().isoformat() + " SEND_HTTP=%s ret=%s body=%s\n"
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_f.write(_beijing_now().isoformat() + " SEND_HTTP=%s ret=%s body=%s\n"
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% (resp.status_code, ret, json.dumps(body, ensure_ascii=False)[:300]))
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except Exception:
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pass
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@@ -210,6 +219,31 @@ def _wechat_send_message(baseurl: str, bot_token: str, to_user_id: str, context_
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return False, (last_body.get("ret") if isinstance(last_body, dict) else None), last_body
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def _wechat_send_message(baseurl: str, bot_token: str, to_user_id: str, context_token: str, text: str):
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"""发送纯文本回复。"""
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return _wechat_post_msg(baseurl, bot_token, to_user_id, context_token,
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[{"type": 1, "text_item": {"text": text}}])
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def _wechat_send_media(baseurl: str, bot_token: str, to_user_id: str, context_token: str,
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media_type: str, url: str):
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"""发送媒体(图片/视频)并附带文本链接兜底,确保用户可在微信内直接查看。
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iLink 消息 item_list:
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- type=2 图片:image_item: {url}
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- type=5 视频:video_item: {url}
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同时附带一条文本项(含直链),防止微信/iLink 不渲染外链时用户仍能复制查看。
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"""
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if media_type == "image":
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media_item = {"type": 2, "image_item": {"url": url}}
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caption = "🖼️ 图片已生成(若未直接显示,请点链接查看):" + url
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else:
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media_item = {"type": 5, "video_item": {"url": url}}
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caption = "🎬 视频已生成(若未直接播放,请点链接查看):" + url
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return _wechat_post_msg(baseurl, bot_token, to_user_id, context_token,
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[media_item, {"type": 1, "text_item": {"text": caption}}])
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def _wechat_extract_text(msg: dict) -> str:
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parts = []
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for it in (msg.get("item_list") or []):
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@@ -255,7 +289,7 @@ def _log_chat(user_id, platform, from_user, context_token, role, content):
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), {
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"uid": user_id, "platform": platform, "fu": from_user,
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"ctx": context_token, "role": role, "content": content,
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"created": datetime.now(),
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"created": _beijing_now(),
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})
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except Exception:
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pass
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@@ -282,7 +316,7 @@ def _get_or_create_wechat_conv(db: Session, user_id: str) -> str:
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return _row_to_dict(rows[0])["id"]
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import uuid as _uuid
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cid = str(_uuid.uuid4())
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now = datetime.now()
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now = _beijing_now()
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_execute_raw(db, text(
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"INSERT INTO conversations "
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"(id, user_id, title, status, pinned, knowledge_graph_count, source, created_at, updated_at) "
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@@ -298,7 +332,7 @@ def _append_ai_message(db: Session, conv_id: str, role: str, content: str, creat
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"VALUES (:id, :cid, :role, :content, 0, :c)"
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), {
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"id": str(_uuid.uuid4()), "cid": conv_id, "role": role,
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"content": content, "c": created or datetime.now(),
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"content": content, "c": created or _beijing_now(),
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})
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@@ -310,13 +344,13 @@ def _mirror_to_ai_chat(user_id: str, user_content: str, assistant_content: str):
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try:
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db = SessionLocal()
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cid = _get_or_create_wechat_conv(db, user_id)
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now = datetime.now()
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now = _beijing_now()
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_append_ai_message(db, cid, "user", user_content, created=now)
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# assistant 比 user 晚 50ms,保证排序严格递增,避免同秒时 ORDER BY 乱序
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_append_ai_message(db, cid, "assistant", assistant_content,
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created=now + timedelta(milliseconds=50))
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_execute_raw(db, text("UPDATE conversations SET updated_at=:u WHERE id=:id"),
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{"u": datetime.now(), "id": cid})
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{"u": _beijing_now(), "id": cid})
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except Exception:
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pass
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finally:
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@@ -335,7 +369,7 @@ def _mark_wechat_expired(account_id: int):
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_execute_raw(db, text(
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"UPDATE im_bot_wechat_account SET status='expired', bot_token=NULL, "
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"updated_at=:ts WHERE id=:aid"
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), {"aid": account_id, "ts": datetime.now()})
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), {"aid": account_id, "ts": _beijing_now()})
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except Exception:
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pass
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finally:
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@@ -374,24 +408,39 @@ def _wechat_receiver_loop(account_id: int):
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# 诊断:记录原始入站消息,定位字段名 / 第二轮不回复
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try:
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with open("/tmp/wechat_inbound.log", "a", encoding="utf-8") as _f:
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_f.write(datetime.now().isoformat() + " sender=" + repr(sender)
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_f.write(_beijing_now().isoformat() + " sender=" + repr(sender)
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+ " ctx=" + repr(ctx) + " raw=" + json.dumps(m, ensure_ascii=False) + "\n")
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except Exception:
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pass
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# 先生成回复(此时历史尚未包含本条,避免重复)
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reply = _qihua_reply(content, owner_uid)
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ok, ret, _ = _wechat_send_message(baseurl, bot_token, sender, ctx, reply)
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# 媒体结构化返回:_call_real_llm 生成图片/视频时返回
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# {"__media__": True, "media_type": "image"/"video", "url": "..."}
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if isinstance(reply, dict) and reply.get("__media__"):
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media_type = reply.get("media_type") or "image"
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media_url = reply.get("url") or ""
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ok, ret, _ = _wechat_send_media(baseurl, bot_token, sender, ctx, media_type, media_url)
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# 对话历史里存可渲染的媒体标签(AI 聊天 WeXin Bot 窗与历史页均可显示)
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reply_for_log = (
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f'<img src="{media_url}" alt="生成图片"/>'
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if media_type == "image"
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else f'<video src="{media_url}" controls></video>'
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)
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else:
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reply_text = reply if isinstance(reply, str) else str(reply)
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ok, ret, _ = _wechat_send_message(baseurl, bot_token, sender, ctx, reply_text)
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reply_for_log = reply_text
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if ok:
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# 仅发送成功才写对话历史(避免“发了但没收到”的误导记录)
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if owner_uid:
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_log_chat(owner_uid, "personal_wechat", sender, ctx, "user", content)
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_log_chat(owner_uid, "personal_wechat", sender, ctx, "assistant", reply)
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_log_chat(owner_uid, "personal_wechat", sender, ctx, "assistant", reply_for_log)
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# 同步镜像到 AI 聊天的 WeXin Bot 会话窗
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_mirror_to_ai_chat(owner_uid, content, reply)
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_mirror_to_ai_chat(owner_uid, content, reply_for_log)
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else:
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try:
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with open("/tmp/wechat_send.log", "a", encoding="utf-8") as _f:
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_f.write(datetime.now().isoformat() + " SEND_FAIL ret=%s sender=%s\n"
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_f.write(_beijing_now().isoformat() + " SEND_FAIL ret=%s sender=%s\n"
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% (ret, repr(sender)))
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except Exception:
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pass
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@@ -511,8 +560,9 @@ async def wechat_qrcode_status(
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"user_id": user.id, "username": user.username,
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"bot_token": bot_token, "ilink_bot_id": ilink_bot_id,
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"baseurl": baseurl,
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"connected_at": datetime.now(),
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"created_at": datetime.now(), "updated_at": datetime.now(),
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# 统一按北京时间存储,避免容器 UTC 导致显示偏差
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"connected_at": _beijing_now(),
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"created_at": _beijing_now(), "updated_at": _beijing_now(),
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})
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else:
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_execute_raw(db, text("""UPDATE im_bot_wechat_account SET
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@@ -523,8 +573,9 @@ async def wechat_qrcode_status(
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{
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"user_id": user.id, "username": user.username,
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"bot_token": bot_token, "ilink_bot_id": ilink_bot_id,
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"baseurl": baseurl, "connected_at": datetime.now(),
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"updated_at": datetime.now(), "id": _row_to_dict(row)["id"],
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"baseurl": baseurl,
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"connected_at": _beijing_now(),
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"updated_at": _beijing_now(), "id": _row_to_dict(row)["id"],
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})
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row = _wechat_row_for_user(db, user.id)
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aid = _row_to_dict(row)["id"] if row else 1
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@@ -547,7 +598,7 @@ async def wechat_disconnect(user: User = Depends(get_current_user)):
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_execute_raw(db, text(
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"UPDATE im_bot_wechat_account SET bot_token=NULL, status='disconnected', "
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"updated_at=:updated_at WHERE id=:id"
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), {"updated_at": datetime.now(), "id": _row_to_dict(row)["id"]})
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), {"updated_at": _beijing_now(), "id": _row_to_dict(row)["id"]})
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return {"success": True, "message": "已断开个人微信连接"}
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except Exception as e:
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raise HTTPException(status_code=500, detail=str(e))
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@@ -14,7 +14,9 @@ IM Bot 真实 LLM 调用。
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"""
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import asyncio
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import json
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import logging
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import re as _re
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from datetime import datetime, timezone, timedelta
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from typing import Optional
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from urllib.parse import urlparse as _urlparse
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@@ -22,7 +24,9 @@ import httpx
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from sqlalchemy.orm import Session
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from ..capability_registry import resolve_auto_model
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from ..models import AIModel, ModelProvider
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from ..models import AIModel, ModelProvider, TokenUsageLog, gen_uuid
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logger = logging.getLogger(__name__)
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# 香港出网代理(实测对 AGNES 延迟更低,2026-07-15 用户实测),与 chat.py 同值。
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@@ -65,7 +69,37 @@ def _run_async(coro):
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return asyncio.run(coro)
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def _call_real_llm(db: Session, user=None, prompt: str = "", platform: str = "im", user_id: str = None) -> str:
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def _log_media_usage(db: Session, user_id: str, ai_model, media_type: str, prompt: str):
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"""IM Bot 媒体生成记账:把图片/视频消耗写入 TokenUsageLog,供驾驶舱统计。
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|
||||
此前 IM Bot 路径完全不写 TokenUsageLog,导致微信生成的图片/视频在驾驶舱里“查无此项”。
|
||||
媒体 API 不返回 token 用量,这里用与 chat.py _generate_media_task 一致的估算。
|
||||
"""
|
||||
if not user_id or not ai_model:
|
||||
return
|
||||
try:
|
||||
base = 1200 if media_type == "video" else 400
|
||||
est = base + (len(prompt or "") // 4)
|
||||
db.add(TokenUsageLog(
|
||||
id=gen_uuid(),
|
||||
user_id=user_id,
|
||||
model_id=ai_model.id,
|
||||
model_name=ai_model.name,
|
||||
prompt_tokens=est,
|
||||
completion_tokens=0,
|
||||
total_tokens=est,
|
||||
created_at=datetime.now(timezone(timedelta(hours=8))).replace(tzinfo=None),
|
||||
))
|
||||
db.commit()
|
||||
except Exception as e:
|
||||
try:
|
||||
db.rollback()
|
||||
except Exception:
|
||||
pass
|
||||
logger.warning(f"[im_llm] 媒体 Token 记账失败(忽略): {e}")
|
||||
|
||||
|
||||
def _call_real_llm(db: Session, user=None, prompt: str = "", platform: str = "im", user_id: str = None) -> "str | dict":
|
||||
"""调用七虎AI 生成回复,供 IM Bot 复用。支持媒体意图路由与已安装技能自动发现。"""
|
||||
try:
|
||||
from app.api.chat import (
|
||||
@@ -88,19 +122,22 @@ def _call_real_llm(db: Session, user=None, prompt: str = "", platform: str = "im
|
||||
# 绝不直接把原始异常(如 "Server disconnected")甩给用户
|
||||
result = "⚠️ 媒体生成暂时失败(连接或服务波动),请稍后重试。"
|
||||
if result:
|
||||
# IM 不渲染 HTML,把 <img>/<video> 还原为纯文本链接返回
|
||||
# 媒体生成成功:返回结构化对象,交由 im_bot_user 在微信内联发送图片/视频
|
||||
s = result.strip()
|
||||
if s.startswith("<img") or s.startswith("<video"):
|
||||
m = _re.search(r'src="([^"]+)"', s)
|
||||
url = m.group(1) if m else ""
|
||||
label = "图片" if s.startswith("<img") else "视频"
|
||||
return f"已为你生成{label}:{url}" if url else "(生成完成,但未能提取媒体地址)"
|
||||
media_type = "image" if s.startswith("<img") else "video"
|
||||
if not url:
|
||||
return "(生成完成,但未能提取媒体地址)"
|
||||
# IM Bot 路径此前完全不记账 → 补写媒体消耗,驾驶舱才看得到图片/视频数据
|
||||
_log_media_usage(db, user_id, ai_model, media_type, prompt)
|
||||
return {"__media__": True, "media_type": media_type, "url": url}
|
||||
# 媒体生成失败:_generate_media 已返回友好中文(如限频/队列繁忙),
|
||||
# 直接透传,绝不把原始提示词/标签/JSON 透传给用户
|
||||
if s.startswith("⚠️") or s.startswith("(媒体"):
|
||||
return s
|
||||
return "(媒体生成未能返回有效内容,请重试)"
|
||||
return result
|
||||
|
||||
# ===== 2) 文本回复 + 技能自动发现(Issue 8)=====
|
||||
ai_model = resolve_auto_model("text", db)
|
||||
|
||||
Reference in new issue
Block a user