feat: 个人微信-对话历史持久化+平台内查阅页; 修复第二轮不回复(过滤/字段/重试); 多轮上下文

backend/python/app/api/im_bot_user.py

@@ -99,13 +99,44 @@ def _wechat_mask(row) -> dict:
 # ============================================================
 # 七虎AI 大脑（复用 channels 的真实 LLM 调用）
 # ============================================================
-def _qihua_reply(text: str) -> str:
+def _recent_history(user_id: str, limit: int = 6) -> str:
+    """拼接最近若干轮对话，作为多轮上下文。"""
+    db = None
+    try:
+        db = SessionLocal()
+        rows = _execute_raw(db, text(
+            "SELECT role, content FROM im_bot_chat_log "
+            "WHERE user_id=:uid ORDER BY id DESC LIMIT :lim"
+        ), {"uid": user_id, "lim": limit})
+        pairs = []
+        for r in reversed(rows):
+            dd = _row_to_dict(r)
+            role = "用户" if dd["role"] == "user" else "七虎AI"
+            pairs.append(f"{role}：{dd['content']}")
+        return "\n".join(pairs)
+    except Exception:
+        return ""
+    finally:
+        if db:
+            db.close()
+
+
+def _qihua_reply(text: str, user_id: str = None) -> str:
     """调用七虎AI 生成回复。自行创建 DB 会话，避免上层线程无可用 session。"""
+    prompt = text
+    if user_id:
+        hist = _recent_history(user_id)
+        if hist:
+            prompt = (
+                "以下是你与该用户最近的对话历史，请结合上下文作答：\n"
+                f"{hist}\n\n"
+                f"用户当前问题：{text}"
+            )
     db = None
     try:
         from app.api.channels import _call_real_llm
         db = SessionLocal()
-        return _call_real_llm(db, None, text, "个人微信")
+        return _call_real_llm(db, None, prompt, "个人微信")
     except Exception as e:
         return f"（AI 回复生成失败：{e}）"
     finally:
@@ -134,23 +165,29 @@ def _wechat_get_updates(baseurl: str, bot_token: str, cursor: str):
 
 
 def _wechat_send_message(baseurl: str, bot_token: str, to_user_id: str, context_token: str, text: str) -> bool:
-    """发送文本回复（必须带 context_token 关联到正确的对话窗口）"""
-    try:
-        resp = requests.post(
-            baseurl.rstrip("/") + "/ilink/bot/sendmessage",
-            headers=_wechat_headers(bot_token),
-            json={"msg": {
-                "to_user_id": to_user_id,
-                "message_type": 2,
-                "message_state": 2,
-                "context_token": context_token,
-                "item_list": [{"type": 1, "text_item": {"text": text}}],
-            }},
-            timeout=20,
-        )
-        return resp.ok
-    except Exception:
-        return False
+    """发送文本回复（必须带 context_token 关联到正确的对话窗口）。失败重试一次。"""
+    payload = {"msg": {
+        "to_user_id": to_user_id,
+        "message_type": 2,
+        "message_state": 2,
+        "context_token": context_token,
+        "item_list": [{"type": 1, "text_item": {"text": text}}],
+    }}
+    last = False
+    for _ in range(2):
+        try:
+            resp = requests.post(
+                baseurl.rstrip("/") + "/ilink/bot/sendmessage",
+                headers=_wechat_headers(bot_token),
+                json=payload,
+                timeout=20,
+            )
+            last = resp.ok
+            if last:
+                return True
+        except Exception:
+            last = False
+    return last
 
 
 def _wechat_extract_text(msg: dict) -> str:
@@ -158,9 +195,55 @@ def _wechat_extract_text(msg: dict) -> str:
     for it in (msg.get("item_list") or []):
         if it.get("type") == 1 and it.get("text_item", {}).get("text"):
             parts.append(it["text_item"]["text"])
+    if not parts:
+        for k in ("text", "content", "message", "msg"):
+            v = msg.get(k)
+            if isinstance(v, str) and v.strip():
+                parts.append(v)
     return "\n".join(parts)
 
 
+def _wechat_sender_id(m: dict) -> str:
+    """从入站消息中提取发送者 id（兼容多套字段名）。"""
+    for k in ("from_user_id", "from_user_name", "from_username", "user_id",
+             "sender_id", "wxid", "from_wxid", "username"):
+        v = m.get(k)
+        if v:
+            return str(v)
+    return ""
+
+
+def _wechat_context_token(m: dict) -> str:
+    """提取 context_token（回复必须回带，否则不关联到对话窗口）。"""
+    for k in ("context_token", "ctx_token", "conversation_id", "conv_id",
+             "msg_id", "context_id", "session_id"):
+        v = m.get(k)
+        if v:
+            return str(v)
+    return ""
+
+
+def _log_chat(user_id, platform, from_user, context_token, role, content):
+    """持久化 IM Bot 对话历史，便于平台内查阅。"""
+    db = None
+    try:
+        db = SessionLocal()
+        _execute_raw(db, text(
+            "INSERT INTO im_bot_chat_log "
+            "(user_id, platform, from_user, context_token, role, content, created_at) "
+            "VALUES (:uid, :platform, :fu, :ctx, :role, :content, :created)"
+        ), {
+            "uid": user_id, "platform": platform, "fu": from_user,
+            "ctx": context_token, "role": role, "content": content,
+            "created": datetime.now(),
+        })
+    except Exception:
+        pass
+    finally:
+        if db:
+            db.close()
+
+
 # ============================================================
 # 后台接收线程（每用户独立）
 # ============================================================
@@ -183,19 +266,35 @@ def _wechat_receiver_loop(account_id: int):
             bot_token = d["bot_token"]
             baseurl = d.get("baseurl") or ILINK_BASE
             msgs, cursor = _wechat_get_updates(baseurl, bot_token, cursor)
+            owner_uid = d.get("user_id")
             for m in msgs:
-                if m.get("message_type") not in (1, None):
-                    continue  # 只处理用户消息（2=bot 自己发出的）
+                if m.get("message_type") == 2:
+                    continue  # 仅跳过 bot 自己发出的回声，其余（含后续追问）均尝试处理
                 content = _wechat_extract_text(m)
                 if not content:
                     continue
-                reply = _qihua_reply(content)
-                _wechat_send_message(
-                    baseurl, bot_token,
-                    m.get("from_user_id", ""),
-                    m.get("context_token", ""),
-                    reply,
-                )
+                sender = _wechat_sender_id(m)
+                ctx = _wechat_context_token(m)
+                # 诊断：记录原始入站消息，定位字段名 / 第二轮不回复
+                try:
+                    with open("/tmp/wechat_inbound.log", "a", encoding="utf-8") as _f:
+                        _f.write(datetime.now().isoformat() + " sender=" + repr(sender)
+                                 + " ctx=" + repr(ctx) + " raw=" + json.dumps(m, ensure_ascii=False) + "\n")
+                except Exception:
+                    pass
+                # 先生成回复（此时历史尚未包含本条，避免重复）
+                reply = _qihua_reply(content, owner_uid)
+                ok = _wechat_send_message(baseurl, bot_token, sender, ctx, reply)
+                # 持久化对话历史
+                if owner_uid:
+                    _log_chat(owner_uid, "personal_wechat", sender, ctx, "user", content)
+                    _log_chat(owner_uid, "personal_wechat", sender, ctx, "assistant", reply)
+                try:
+                    with open("/tmp/wechat_send.log", "a", encoding="utf-8") as _f:
+                        _f.write(datetime.now().isoformat() + " ok=" + str(ok)
+                                 + " sender=" + repr(sender) + " ctx=" + repr(ctx) + "\n")
+                except Exception:
+                    pass
             time.sleep(1)
         except Exception:
             time.sleep(5)
@@ -354,6 +453,29 @@ async def wechat_disconnect(user: User = Depends(get_current_user)):
 # ============================================================
 # 启动恢复：为所有已连接用户账号拉起接收线程
 # ============================================================
+@router.get("/history")
+async def wechat_history(
+    user: User = Depends(get_current_user),
+    limit: int = Query(200),
+):
+    """查询当前用户通过个人微信与七虎AI 的对话历史"""
+    db = SessionLocal()
+    try:
+        rows = _execute_raw(
+            db,
+            text("SELECT id, role, content, platform, from_user, created_at "
+                 "FROM im_bot_chat_log WHERE user_id=:uid ORDER BY id DESC LIMIT :lim"),
+            {"uid": user.id, "lim": min(int(limit), 500)},
+        )
+        items = [_row_to_dict(r) for r in rows]
+        items.reverse()
+        return {"success": True, "data": {"messages": items, "total": len(items)}}
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+    finally:
+        db.close()
+
+
 def start_all_wechat_receivers():
     """在应用启动时调用，恢复此前已连接用户的个人微信接收线程。"""
     db = SessionLocal()