Completely refactor the LLM integration method to easily replace the LLM used by each module and optimize the retransmission mechanism.

InsightEngine/tools/keyword_optimizer.py

@@ -12,7 +12,7 @@ from dataclasses import dataclass
 
 # 添加项目根目录到Python路径以导入config
 sys.path.append(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
-from config import GUIJI_QWEN3_API_KEY, GUIJI_QWEN3_BASE_URL
+from config import KEYWORD_OPTIMIZER_API_KEY, KEYWORD_OPTIMIZER_BASE_URL, KEYWORD_OPTIMIZER_MODEL_NAME
 
 # 添加utils目录到Python路径
 current_dir = os.path.dirname(os.path.abspath(__file__))
@@ -38,7 +38,7 @@ class KeywordOptimizer:
     使用硅基流动的Qwen3模型将Agent生成的搜索词优化为更贴近真实舆情的关键词
     """
     
-    def __init__(self, api_key: str = None, base_url: str = None):
+    def __init__(self, api_key: str = None, base_url: str = None, model_name: str = None):
         """
         初始化关键词优化器
         
@@ -46,18 +46,18 @@ class KeywordOptimizer:
             api_key: 硅基流动API密钥，如果不提供则从配置文件读取
             base_url: 接口基础地址，默认使用配置文件提供的SiliconFlow地址
         """
-        self.api_key = api_key or GUIJI_QWEN3_API_KEY
+        self.api_key = api_key or KEYWORD_OPTIMIZER_API_KEY
 
         if not self.api_key:
-            raise ValueError("未找到硅基流动API密钥，请在config.py中设置GUIJI_QWEN3_API_KEY")
+            raise ValueError("未找到硅基流动API密钥，请在config.py中设置KEYWORD_OPTIMIZER_API_KEY")
 
-        self.base_url = base_url or GUIJI_QWEN3_BASE_URL
+        self.base_url = base_url or KEYWORD_OPTIMIZER_BASE_URL
 
         self.client = OpenAI(
             api_key=self.api_key,
             base_url=self.base_url
         )
-        self.model = "Qwen/Qwen3-30B-A3B-Instruct-2507"
+        self.model = model_name or KEYWORD_OPTIMIZER_MODEL_NAME
     
     def optimize_keywords(self, original_query: str, context: str = "") -> KeywordOptimizationResponse:
         """
@@ -192,7 +192,6 @@ class KeywordOptimizer:
                     {"role": "system", "content": system_prompt},
                     {"role": "user", "content": user_prompt}
                 ],
-                max_tokens=10000,
                 temperature=0.7,
             )