修改变量名

applications/utils/chat/rag_chat_agent.py

@@ -98,7 +98,7 @@ class RAGChatAgent:
     """
         return prompt
 
-    async def search_with_deepseek(self, query):
+    async def llm_search(self, query):
         prompt = self.create_query_prompt(query)
         response = await fetch_deepseek_completion(
             model="DeepSeek-V3", prompt=prompt, output_type="json"
@@ -135,7 +135,7 @@ class RAGChatAgent:
 
         return prompt
 
-    async def select_with_deepseek(self, chat_res, search_res):
+    async def make_decision(self, chat_res, search_res):
         prompt = self.select_prompt(chat_res, search_res)
         response = await fetch_deepseek_completion(
             model="DeepSeek-R1", prompt=prompt, output_type="json"

mcp_server/server.py

@@ -66,24 +66,24 @@ async def rag_search(query_text: str):
     resource = get_resource_manager()
     chat_result_mapper = ChatResult(resource.mysql_client)
     rag_chat_agent = RAGChatAgent()
-    chat_res = await rag_chat_agent.chat_with_deepseek(query_text, query_results)
-    deepseek_search = await rag_chat_agent.search_with_deepseek(query_text)
-    select = await rag_chat_agent.select_with_deepseek(chat_res, deepseek_search)
+    chat_result = await rag_chat_agent.chat_with_deepseek(query_text, query_results)
+    llm_search_result = await rag_chat_agent.llm_search(query_text)
+    decision = await rag_chat_agent.make_decision(chat_result, llm_search_result)
     data = {
-        "result": select["result"],
-        "status": select["status"],
-        "relevance_score": select["relevance_score"],
+        "result": decision["result"],
+        "status": decision["status"],
+        "relevance_score": decision["relevance_score"],
     }
     await chat_result_mapper.insert_chat_result(
         query_text,
         dataset_id_strs,
         json.dumps(query_results, ensure_ascii=False),
-        chat_res["summary"],
-        chat_res["relevance_score"],
-        chat_res["status"],
-        deepseek_search["answer"],
-        deepseek_search["source"],
-        deepseek_search["status"],
+        chat_result["summary"],
+        chat_result["relevance_score"],
+        chat_result["status"],
+        llm_search_result["answer"],
+        llm_search_result["source"],
+        llm_search_result["status"],
     )
 
     return data

routes/buleprint.py

@@ -394,20 +394,20 @@ async def chat():
             result["datasetName"] = dataset_name
 
     rag_chat_agent = RAGChatAgent()
-    chat_res = await rag_chat_agent.chat_with_deepseek(query_text, query_results)
-    deepseek_search = await rag_chat_agent.search_with_deepseek(query_text)
-    select = await rag_chat_agent.select_with_deepseek(chat_res, deepseek_search)
-    data = {"results": query_results, "chat_res": select["result"]}
+    chat_result = await rag_chat_agent.chat_with_deepseek(query_text, query_results)
+    llm_search = await rag_chat_agent.llm_search(query_text)
+    decision = await rag_chat_agent.make_decision(chat_result, llm_search)
+    data = {"results": query_results, "chat_res": decision["result"]}
     await chat_result_mapper.insert_chat_result(
         query_text,
         dataset_id_strs,
         json.dumps(data, ensure_ascii=False),
-        chat_res["summary"],
-        chat_res["relevance_score"],
-        chat_res["status"],
-        deepseek_search["answer"],
-        deepseek_search["source"],
-        deepseek_search["status"],
+        chat_result["summary"],
+        chat_result["relevance_score"],
+        chat_result["status"],
+        llm_search["answer"],
+        llm_search["source"],
+        llm_search["status"],
     )
     return jsonify({"status_code": 200, "detail": "success", "data": data})
 
@@ -500,23 +500,23 @@ async def rag_search():
     resource = get_resource_manager()
     chat_result_mapper = ChatResult(resource.mysql_client)
     rag_chat_agent = RAGChatAgent()
-    chat_res = await rag_chat_agent.chat_with_deepseek(query_text, query_results)
-    deepseek_search = await rag_chat_agent.search_with_deepseek(query_text)
-    select = await rag_chat_agent.select_with_deepseek(chat_res, deepseek_search)
+    chat_result = await rag_chat_agent.chat_with_deepseek(query_text, query_results)
+    llm_search = await rag_chat_agent.llm_search(query_text)
+    decision = await rag_chat_agent.make_decision(chat_result, llm_search)
     data = {
-        "result": select["result"],
-        "status": select["status"],
-        "relevance_score": select["relevance_score"],
+        "result": decision["result"],
+        "status": decision["status"],
+        "relevance_score": decision["relevance_score"],
     }
     await chat_result_mapper.insert_chat_result(
         query_text,
         dataset_id_strs,
         json.dumps(query_results, ensure_ascii=False),
-        chat_res["summary"],
-        chat_res["relevance_score"],
-        chat_res["status"],
-        deepseek_search["answer"],
-        deepseek_search["source"],
-        deepseek_search["status"],
+        chat_result["summary"],
+        chat_result["relevance_score"],
+        chat_result["status"],
+        llm_search["answer"],
+        llm_search["source"],
+        llm_search["status"],
     )
     return jsonify({"status_code": 200, "detail": "success", "data": data})