fix: resolve 500 error caused by <think> tags and markdown code fences in content field from reasoning models like MiniMax/GLM

backend/app/utils/llm_client.py

@@ -4,6 +4,7 @@ LLM客户端封装
 """
 
 import json
+import re
 from typing import Optional, Dict, Any, List
 from openai import OpenAI
 
@@ -61,7 +62,10 @@ class LLMClient:
             kwargs["response_format"] = response_format
         
         response = self.client.chat.completions.create(**kwargs)
-        return response.choices[0].message.content
+        content = response.choices[0].message.content
+        # 部分模型（如MiniMax M2.5）会在content中包含<think>思考内容，需要移除
+        content = re.sub(r'<think>[\s\S]*?</think>', '', content).strip()
+        return content
     
     def chat_json(
         self,
@@ -86,6 +90,14 @@ class LLMClient:
             max_tokens=max_tokens,
             response_format={"type": "json_object"}
         )
+        # 清理markdown代码块标记
+        cleaned_response = response.strip()
+        cleaned_response = re.sub(r'^```(?:json)?\s*\n?', '', cleaned_response, flags=re.IGNORECASE)
+        cleaned_response = re.sub(r'\n?```\s*$', '', cleaned_response)
+        cleaned_response = cleaned_response.strip()
 
-        return json.loads(response)
+        try:
+            return json.loads(cleaned_response)
+        except json.JSONDecodeError:
+            raise ValueError(f"LLM返回的JSON格式无效: {cleaned_response}")