refactor: 移除通用频道管理(LangBot)模块，IM Bot 改为直接对接；迁移 _call_real_llm 至 im_llm

backend/python/app/api/__init__.py

@@ -1,6 +1,5 @@
 from . import auth
 from . import chat
-from . import channels
 from . import knowledge
 from . import market
 from . import token_usage

backend/python/app/api/admin/im_bot_admin.py

@@ -608,7 +608,7 @@ def _qihua_reply(text: str) -> str:
     自行创建 DB 会话，避免上层线程无可用 session 时崩溃。"""
     db = None
     try:
-        from app.api.channels import _call_real_llm
+        from app.api.im_llm import _call_real_llm
         db = SessionLocal()
         return _call_real_llm(db, None, text, "个人微信")
     except Exception as e:

backend/python/app/api/im_llm.py

@@ -0,0 +1,45 @@
+"""
+IM Bot 真实 LLM 调用。
+
+原实现位于 channels.py（通用频道管理模块），该模块已移除。
+为保持 IM Bot（微信机器人等）正常生成回复，将 _call_real_llm 迁移至此独立模块。
+"""
+from typing import Optional
+
+import httpx
+from sqlalchemy.orm import Session
+
+from ..capability_registry import resolve_auto_model
+from ..models import AIModel, ModelProvider
+
+
+def _call_real_llm(db: Session, user=None, prompt: str = "", platform: str = "im") -> str:
+    """调用七虎AI 默认文本模型生成回复，供 IM Bot 复用。"""
+    try:
+        ai_model = resolve_auto_model("text", db)
+        if not ai_model:
+            return "（未配置默认文本模型，无法生成回复）"
+        provider = db.query(ModelProvider).filter(ModelProvider.id == ai_model.provider_id).first()
+        api_key = ai_model.api_key or (provider.api_key if provider else None)
+        api_url = ai_model.endpoint
+        if not api_url and provider and provider.api_base_url:
+            api_url = f"{provider.api_base_url.rstrip('/')}/v1/chat/completions"
+        if not (api_key and api_url):
+            return "（模型未配置 API Key 或地址，无法生成回复）"
+        messages = [
+            {"role": "system", "content": "你是七虎AI 助手，负责在即时通讯中回复用户消息。"},
+            {"role": "user", "content": prompt},
+        ]
+        request_body = {"model": ai_model.name, "messages": messages, "max_tokens": 2048}
+        with httpx.Client(timeout=ai_model.timeout or 120) as client:
+            resp = client.post(
+                api_url,
+                headers={"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"},
+                json=request_body,
+            )
+            if resp.status_code != 200:
+                return f"（AI 模型调用失败 HTTP {resp.status_code}）"
+            data = resp.json()
+            return data.get("choices", [{}])[0].get("message", {}).get("content", "")
+    except Exception as e:
+        return f"（AI 回复生成失败：{e}）"