fix: add logs

agent/protocol/agent_stream.py

@@ -78,8 +78,9 @@ class AgentStreamExecutor:
         Returns:
             Final response text
         """
-        # Log user message
+        # Log user message with model info
-        logger.info(f"\n{'='*50}")
+        logger.info(f"{'='*50}")
+        logger.info(f"🤖 Model: {self.model.model}")
         logger.info(f"👤 用户: {user_message}")
         logger.info(f"{'='*50}")
         
@@ -102,7 +103,7 @@ class AgentStreamExecutor:
         try:
             while turn < self.max_turns:
                 turn += 1
-                logger.info(f"\n🔄 第 {turn} 轮")
+                logger.info(f"第 {turn} 轮")
                 self._emit_event("turn_start", {"turn": turn})
 
                 # Check if memory flush is needed (before calling LLM)
@@ -145,7 +146,7 @@ class AgentStreamExecutor:
                         final_response = (
                             "抱歉，我暂时无法生成回复。请尝试换一种方式描述你的需求，或稍后再试。"
                         )
-                        logger.info(f"💭 Generated fallback response for empty LLM output")
+                        logger.info(f"Generated fallback response for empty LLM output")
                     else:
                         logger.info(f"💭 {assistant_msg[:150]}{'...' if len(assistant_msg) > 150 else ''}")
                     
@@ -239,7 +240,7 @@ class AgentStreamExecutor:
             raise
 
         finally:
-            logger.info(f"🏁 完成({turn}轮)\n")
+            logger.info(f"🏁 完成({turn}轮)")
             self._emit_event("agent_end", {"final_response": final_response})
 
         return final_response
@@ -366,7 +367,7 @@ class AgentStreamExecutor:
             if is_retryable and retry_count < max_retries:
                 wait_time = (retry_count + 1) * 2  # Exponential backoff: 2s, 4s, 6s
                 logger.warning(f"⚠️ LLM API error (attempt {retry_count + 1}/{max_retries}): {e}")
-                logger.info(f"🔄 Retrying in {wait_time}s...")
+                logger.info(f"Retrying in {wait_time}s...")
                 time.sleep(wait_time)
                 return self._call_llm_stream(
                     retry_on_empty=retry_on_empty, 
@@ -486,9 +487,9 @@ class AgentStreamExecutor:
             if tool_name == "bash" and result.status == "success":
                 command = arguments.get("command", "")
                 if "init_skill.py" in command and self.agent.skill_manager:
-                    logger.info("🔄 Detected skill creation, refreshing skills...")
+                    logger.info("Detected skill creation, refreshing skills...")
                     self.agent.refresh_skills()
-                    logger.info(f"✅ Skills refreshed! Now have {len(self.agent.skill_manager.skills)} skills")
+                    logger.info(f"Skills refreshed! Now have {len(self.agent.skill_manager.skills)} skills")
 
             self._emit_event("tool_execution_end", {
                 "tool_call_id": tool_id,

bot/linkai/link_ai_bot.py

@@ -505,14 +505,9 @@ def _linkai_call_with_tools(self, messages, tools=None, stream=False, **kwargs):
         Formatted response in OpenAI format or generator for streaming
     """
     try:
-        # Debug logging
-        logger.info(f"[LinkAI] ⭐ LinkAI call_with_tools method called")
-        logger.info(f"[LinkAI] messages count (before conversion): {len(messages) if messages else 0}")
-        
         # Convert messages from Claude format to OpenAI format
         # This is important because Agent uses Claude format internally
         messages = self._convert_messages_to_openai_format(messages)
-        logger.info(f"[LinkAI] messages count (after conversion): {len(messages) if messages else 0}")
         
         # Convert tools from Claude format to OpenAI format
         if tools:
@@ -528,7 +523,7 @@ def _linkai_call_with_tools(self, messages, tools=None, stream=False, **kwargs):
                 # Replace existing system message
                 messages[0] = {"role": "system", "content": system_prompt}
         
-        logger.info(f"[LinkAI] Final messages count: {len(messages)}, tools count: {len(tools) if tools else 0}, stream: {stream}")
+        logger.debug(f"[LinkAI] messages: {len(messages)}, tools: {len(tools) if tools else 0}, stream: {stream}")
         
         # Build request parameters (LinkAI uses OpenAI-compatible format)
         body = {
@@ -583,8 +578,8 @@ def _handle_linkai_sync_response(self, base_url, headers, body):
         
         if res.status_code == 200:
             response = res.json()
-            logger.info(f"[LinkAI] call_with_tools reply, model={response.get('model')}, "
+            logger.debug(f"[LinkAI] reply: model={response.get('model')}, "
-                       f"total_tokens={response.get('usage', {}).get('total_tokens', 0)}")
+                        f"tokens={response.get('usage', {}).get('total_tokens', 0)}")
             
             # LinkAI response is already in OpenAI-compatible format
             return response

bridge/agent_bridge.py

@@ -74,12 +74,14 @@ class AgentLLMModel(LLMModel):
         if self._bot is None:
             # If use_linkai is enabled, use LinkAI bot directly
             if self._use_linkai:
-                logger.info("[AgentBridge] Using LinkAI bot for agent")
                 self._bot = self.bridge.find_chat_bot(const.LINKAI)
             else:
                 self._bot = self.bridge.get_bot(self.bot_type)
                 # Automatically add tool calling support if not present
                 self._bot = add_openai_compatible_support(self._bot)
+            
+            # Log bot info
+            bot_name = type(self._bot).__name__
         return self._bot
 
     def call(self, request: LLMRequest):
@@ -331,7 +333,7 @@ class AgentBridge:
         runtime_info = {
             "model": conf().get("model", "unknown"),
             "workspace": workspace_root,
-            "channel": "web"  # TODO: get from actual channel, default to "web" to hide if not specified
+            "channel": conf().get("channel_type", "unknown")  # Get from config
         }
 
         system_prompt = prompt_builder.build(

channel/channel.py

@@ -47,6 +47,10 @@ class Channel(object):
             try:
                 logger.info("[Channel] Using agent mode")
 
+                # Add channel_type to context if not present
+                if context and "channel_type" not in context:
+                    context["channel_type"] = self.channel_type
+
                 # Use agent bridge to handle the query
                 return Bridge().fetch_agent_reply(
                     query=query,