fix: pass channel_type correctly in multi-channel mode

agent/tools/scheduler/integration.py

@@ -451,8 +451,7 @@ def attach_scheduler_to_tool(tool, context: Context = None):
     if context:
         tool.current_context = context
         
-        # Also set channel_type from config
+        channel_type = context.get("channel_type") or conf().get("channel_type", "unknown")
-        channel_type = conf().get("channel_type", "unknown")
         if not tool.config:
             tool.config = {}
         tool.config["channel_type"] = channel_type

app.py

@@ -211,14 +211,14 @@ def run():
         sigterm_handler_wrap(signal.SIGTERM)
 
         # Parse channel_type into a list
-        raw_channel = conf().get("channel_type", "wx")
+        raw_channel = conf().get("channel_type", "web")
 
         if "--cmd" in sys.argv:
             channel_names = ["terminal"]
         else:
             channel_names = _parse_channel_type(raw_channel)
             if not channel_names:
-                channel_names = ["wx"]
+                channel_names = ["web"]
 
         if "wxy" in channel_names:
             os.environ["WECHATY_LOG"] = "warn"

bridge/agent_bridge.py

@@ -135,7 +135,7 @@ class AgentLLMModel(LLMModel):
                 # Use tool-enabled streaming call if available
                 # Extract system prompt if present
                 system_prompt = getattr(request, 'system', None)
-                
+
                 # Build kwargs for call_with_tools
                 kwargs = {
                     'messages': request.messages,
@@ -143,15 +143,20 @@ class AgentLLMModel(LLMModel):
                     'stream': True,
                     'model': self.model  # Pass model parameter
                 }
-                
+
                 # Only pass max_tokens if explicitly set, let the bot use its default
                 if request.max_tokens is not None:
                     kwargs['max_tokens'] = request.max_tokens
-                
+
                 # Add system prompt if present
                 if system_prompt:
                     kwargs['system'] = system_prompt
-                
+
+                # Pass channel_type for linkai tracking
+                channel_type = getattr(self, 'channel_type', None)
+                if channel_type:
+                    kwargs['channel_type'] = channel_type
+
                 stream = self.bot.call_with_tools(**kwargs)
                 
                 # Convert stream format to our expected format
@@ -325,6 +330,10 @@ class AgentBridge:
                                 logger.warning(f"[AgentBridge] Failed to attach context to scheduler: {e}")
                             break
             
+            # Pass channel_type to model so linkai requests carry it
+            if context and hasattr(agent, 'model'):
+                agent.model.channel_type = context.get("channel_type", "")
+
             # Record message count before execution so we can diff new messages
             with agent.messages_lock:
                 pre_run_len = len(agent.messages)

bridge/agent_initializer.py

@@ -322,7 +322,14 @@ class AgentInitializer:
                         tool.scheduler_service = scheduler_service
                         if not tool.config:
                             tool.config = {}
-                        tool.config["channel_type"] = conf().get("channel_type", "unknown")
+                        raw_ct = conf().get("channel_type", "unknown")
+                        if isinstance(raw_ct, list):
+                            ct = raw_ct[0] if raw_ct else "unknown"
+                        elif isinstance(raw_ct, str) and "," in raw_ct:
+                            ct = raw_ct.split(",")[0].strip()
+                        else:
+                            ct = raw_ct
+                        tool.config["channel_type"] = ct
             except Exception as e:
                 logger.warning(f"[AgentInitializer] Failed to inject scheduler dependencies: {e}")
     
@@ -369,7 +376,7 @@ class AgentInitializer:
         return {
             "model": conf().get("model", "unknown"),
             "workspace": workspace_root,
-            "channel": conf().get("channel_type", "unknown"),
+            "channel": ", ".join(conf().get("channel_type")) if isinstance(conf().get("channel_type"), list) else conf().get("channel_type", "unknown"),
             "_get_current_time": get_current_time  # Dynamic time function
         }
     

channel/chat_channel.py

@@ -42,9 +42,8 @@ class ChatChannel(Channel):
     def _compose_context(self, ctype: ContextType, content, **kwargs):
         context = Context(ctype, content)
         context.kwargs = kwargs
-        # context首次传入时，origin_ctype是None,
+        if "channel_type" not in context:
-        # 引入的起因是：当输入语音时，会嵌套生成两个context，第一步语音转文本，第二步通过文本生成文字回复。
+            context["channel_type"] = self.channel_type
-        # origin_ctype用于第二步文本回复时，判断是否需要匹配前缀，如果是私聊的语音，就不需要匹配前缀
         if "origin_ctype" not in context:
             context["origin_ctype"] = ctype
         # context首次传入时，receiver是None，根据类型设置receiver

channel/feishu/feishu_channel.py

@@ -698,6 +698,8 @@ class FeiShuChanel(ChatChannel):
     def _compose_context(self, ctype: ContextType, content, **kwargs):
         context = Context(ctype, content)
         context.kwargs = kwargs
+        if "channel_type" not in context:
+            context["channel_type"] = self.channel_type
         if "origin_ctype" not in context:
             context["origin_ctype"] = ctype
 

models/linkai/link_ai_bot.py

@@ -107,7 +107,7 @@ class LinkAIBot(Bot, OpenAICompatibleBot):
                 "presence_penalty": conf().get("presence_penalty", 0.0),  # [-2,2]之间，该值越大则更倾向于产生不同的内容
                 "session_id": session_id,
                 "sender_id": session_id,
-                "channel_type": conf().get("channel_type", "wx")
+                "channel_type": context.get("channel_type") or conf().get("channel_type", "web")
             }
             try:
                 from linkai import LinkAIClient
@@ -526,6 +526,14 @@ def _linkai_call_with_tools(self, messages, tools=None, stream=False, **kwargs):
         logger.debug(f"[LinkAI] messages: {len(messages)}, tools: {len(tools) if tools else 0}, stream: {stream}")
         
         # Build request parameters (LinkAI uses OpenAI-compatible format)
+        raw_ct = conf().get("channel_type", "web")
+        if isinstance(raw_ct, list):
+            channel_type = raw_ct[0] if raw_ct else "web"
+        elif isinstance(raw_ct, str) and "," in raw_ct:
+            channel_type = raw_ct.split(",")[0].strip()
+        else:
+            channel_type = raw_ct
+
         body = {
             "messages": messages,
             "model": kwargs.get("model", conf().get("model") or "gpt-3.5-turbo"),
@@ -533,7 +541,8 @@ def _linkai_call_with_tools(self, messages, tools=None, stream=False, **kwargs):
             "top_p": kwargs.get("top_p", conf().get("top_p", 1)),
             "frequency_penalty": kwargs.get("frequency_penalty", conf().get("frequency_penalty", 0.0)),
             "presence_penalty": kwargs.get("presence_penalty", conf().get("presence_penalty", 0.0)),
-            "stream": stream
+            "stream": stream,
+            "channel_type": kwargs.get("channel_type", channel_type),
         }
 
         if tools:

plugins/godcmd/godcmd.py

@@ -140,7 +140,9 @@ def get_help_text(isadmin, isgroup):
     for cmd, info in COMMANDS.items():
         if cmd in ["auth", "set_openai_api_key", "reset_openai_api_key", "set_gpt_model", "reset_gpt_model", "gpt_model"]:  # 不显示帮助指令
             continue
-        if cmd == "id" and conf().get("channel_type", "wx") not in ["wxy", "wechatmp"]:
+        raw_ct = conf().get("channel_type", "web")
+        active_channels = raw_ct if isinstance(raw_ct, list) else [c.strip() for c in str(raw_ct).split(",")]
+        if cmd == "id" and not any(c in ["wxy", "wechatmp"] for c in active_channels):
             continue
         alias = ["#" + a for a in info["alias"][:1]]
         help_text += f"{','.join(alias)} "