refactor: 移除硬编码配置，使用环境变量管理API密钥和路径

重构XinferenceEmbeddings和XinferenceReRankerModel类，移除硬编码的API密钥和路径
统一使用环境变量管理配置，提高安全性和灵活性
修改数据库路径为相对路径，增强可移植性

rag2_0/api/query_dinge_qingdan_api.py

@@ -53,12 +53,12 @@ class BatchQueryResponse(BaseModel):
 
 # 封装查询数据的相关代码
 class QingDanDingEQueryService:
-    def __init__(self, db_path="/data/QueryRewrite/data/db/qingdan_ding_e_ku.db"):
-        self.db_path = db_path
+    def __init__(self):
+        self.db_path = f"{os.getcwd()}/data/db/qingdan_ding_e_ku.db"
         self.top_k = TOP_K
         
         # 初始化向量检索相关组件
-        self.embedding_function = XinferenceEmbeddings(api_key="")
+        self.embedding_function = XinferenceEmbeddings()
         
         # 初始化向量数据库连接
         self.ding_e_vector_db = SQLiteVSS(

rag2_0/demo/create_qingdan_dinge_database.py

@@ -462,10 +462,10 @@ class ExcelToSQLiteProcessor:
         print("数据库事务已提交，连接已关闭")
 
 class CreateEmbedingData():
-    def __init__(self, db_path, api_key="aa"):
+    def __init__(self, db_path):
         self.db_path = db_path
         self.conn = sqlite3.connect(db_path)
-        self.embedding_function = XinferenceEmbeddings(api_key=api_key)
+        self.embedding_function = XinferenceEmbeddings()
     
     def create_ding_e_zimu_embedding(self):
         """创建定额子目名称的向量索引"""
@@ -535,22 +535,24 @@ def main():
     print("开始处理定额库和清单库Excel文件...")
     
     # 配置参数
-    ding_e_base_dir = "/data/QueryRewrite/data/excel/Excel版 清单定额库/定额库"
-    qing_dan_base_dir = "/data/QueryRewrite/data/excel/Excel版 清单定额库/清单库"
-    db_path = "/data/QueryRewrite/data/db/qingdan_ding_e_ku copy.db"
-    
+    ding_e_base_dir = f"{os.getcwd()}/data/excel/Excel版 清单定额库/定额库"
+    qing_dan_base_dir = f"{os.getcwd()}/data/excel/Excel版 清单定额库/清单库"
+    db_path = f"{os.getcwd()}/data/db/qingdan_ding_e_ku.db"
+    if os.path.exists(db_path):
+        print("数据库文件已存在, 任务结束...")
+        return
     # 创建处理器实例
-    # processor = ExcelToSQLiteProcessor(db_path)
+    processor = ExcelToSQLiteProcessor(db_path)
     
     try:
         # 处理定额库文件
-        # processor.process_ding_e_files(ding_e_base_dir)
+        processor.process_ding_e_files(ding_e_base_dir)
         
         # # 处理清单库文件
-        # processor.process_qing_dan_files(qing_dan_base_dir)
+        processor.process_qing_dan_files(qing_dan_base_dir)
         
         # # 提交并关闭
-        # processor.commit_and_close()
+        processor.commit_and_close()
         
         print("=" * 50)
         print("所有Excel文件处理完成！数据已成功导入SQLite数据库")

rag2_0/intent_recognition/ProfessionalNounVector.py

@@ -28,7 +28,7 @@ def get_embedding_model(api_key: str = None) -> Embeddings:
     Returns:
         嵌入模型实例
     """
-    return XinferenceEmbeddings(api_key=api_key)
+    return XinferenceEmbeddings()
 
 
 class ProfessionalNounVectorizer:

rag2_0/tool/ModelTool.py

@@ -23,13 +23,13 @@ from urllib.parse import urljoin
 
 class XinferenceEmbeddings(Embeddings):
     """SiliconFlow嵌入模型封装"""
-    def __init__(self, api_key: str, model: str = os.getenv("EMBEDDING_MODEL_NAME", "bge-m3")):
-        self.api_key = api_key
+    def __init__(self, model: str = os.getenv("EMBEDDING_MODEL_NAME", "bge-m3")):
         self.model = model
-        base_url = os.getenv("XINFERENCE_URL", "http://10.1.16.39:9995")
+        base_url = os.getenv("EMBEDDING_BASE_URL", "http://10.1.16.39:9995")
         self.url = urljoin(base_url.rstrip('/') + '/', 'v1/embeddings')
+        api_key = os.getenv("EMBEDDING_API_KEY", "")
         self.headers = {
-            "Authorization": f"Bearer {self.api_key}",
+            "Authorization": f"Bearer {api_key}",
             "Content-Type": "application/json"
         }
 
@@ -89,12 +89,13 @@ class XinferenceReRankerModel:
             List[dict]: 重排序后的文档列表，每个元素包含document内容、相关性分数和原始索引
         """
         
-        base_url = os.getenv("XINFERENCE_URL", "http://10.1.16.39:9995")
+        base_url = os.getenv("RERANKER_BASE_URL", "http://10.1.16.39:9995")
         model_name = os.getenv("RERANKER_MODEL_NAME", "bge-reranker-v2-m3")
+        api_key = os.getenv("RERANKER_API_KEY", "")
         rerank_url = urljoin(base_url.rstrip('/') + '/', 'v1/rerank')
         params = {"documents": documents, "query": query, "top_n": top_k, "return_documents": True, "model": model_name}
         headers = {
-            "Authorization": "Bearer <token>",  # 这里需要替换为实际的token
+            "Authorization": f"Bearer {api_key}",  # 这里需要替换为实际的token
             "Content-Type": "application/json"
         }
         
@@ -123,12 +124,14 @@ class XinferenceReRankerModel:
         Returns:
             List[dict]: 重排序后的文档列表，每个元素包含document内容、相关性分数和原始索引
         """
-        base_url = os.getenv("XINFERENCE_URL", "http://10.1.16.39:9995")
+        base_url = os.getenv("RERANKER_BASE_URL", "http://10.1.16.39:9995")
         rerank_url = urljoin(base_url.rstrip('/') + '/', 'v1/rerank')
         model_name = os.getenv("RERANKER_MODEL_NAME", "bge-reranker-v2-m3")
+        api_key = os.getenv("RERANKER_API_KEY", "")
+
         params = {"documents": documents, "query": query, "top_n": top_k, "return_documents": True, "model": model_name}
         headers = {
-            "Authorization": "Bearer <token>",  # 这里需要替换为实际的token
+            "Authorization": f"Bearer {api_key}",  # 这里需要替换为实际的token
             "Content-Type": "application/json"
         }
         
@@ -214,7 +217,9 @@ class OpenAiLLM:
                     messages=[{'role': 'user', 'content': user_prompt}],
                     **kwargs
                 )
-                return completion.choices[0].message
+                message = completion.choices[0].message
+                message.usage = completion.usage
+                return message
         except Exception as e:
             raise RuntimeError(f"OpenAiLLM:ainvoke:error:{str(e)}") from e