Merge branch 'feature/xueyiming/2025-09-29-update-res' of Server/rag_server into master

applications/utils/mysql/mapper.py

@@ -48,12 +48,13 @@ class ChatResult(BaseMySQLClient):
         ai_source,
         ai_status,
         final_result,
+        study_task_id,
         is_web=None,
     ):
         query = """
                     INSERT INTO chat_res
-                        (query, dataset_ids, search_res, chat_res, score, has_answer, ai_answer, ai_source, ai_status, is_web, final_result) 
-                        VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s);
+                        (query, dataset_ids, search_res, chat_res, score, has_answer, ai_answer, ai_source, ai_status, is_web, final_result, study_task_id) 
+                        VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s);
                 """
         return await self.pool.async_save(
             query=query,
@@ -69,6 +70,7 @@ class ChatResult(BaseMySQLClient):
                 ai_status,
                 is_web,
                 final_result,
+                study_task_id
             ),
         )
 

mcp_server/server.py

@@ -68,8 +68,9 @@ async def rag_search(query_text: str):
     chat_result_mapper = ChatResult(resource.mysql_client)
     rag_chat_agent = RAGChatAgent()
     chat_result = await rag_chat_agent.chat_with_deepseek(query_text, query_results)
+    study_task_id = None
     if chat_result["status"] == 0:
-        study(query_text)
+        study_task_id = study(query_text)['task_id']
     llm_search_result = await rag_chat_agent.llm_search(query_text)
     decision = await rag_chat_agent.make_decision(chat_result, llm_search_result)
     data = {
@@ -88,6 +89,7 @@ async def rag_search(query_text: str):
         llm_search_result["source"],
         llm_search_result["status"],
         decision["result"],
+        study_task_id
     )
 
     return data

routes/buleprint.py

@@ -414,8 +414,9 @@ async def chat():
 
     rag_chat_agent = RAGChatAgent()
     chat_result = await rag_chat_agent.chat_with_deepseek(query_text, query_results)
+    study_task_id = None
     if chat_result["status"] == 0:
-        study(query_text)
+        study_task_id = study(query_text)['task_id']
     llm_search = await rag_chat_agent.llm_search(query_text)
     decision = await rag_chat_agent.make_decision(chat_result, llm_search)
     data = {
@@ -435,9 +436,9 @@ async def chat():
         llm_search["source"],
         llm_search["status"],
         decision["result"],
+        study_task_id,
         is_web=1,
     )
-    # data = {"results": query_results, "chat_res": 'chat_res', 'rag_summary': 'rag_summary', 'llm_summary': 'llm_summary'}
     return jsonify({"status_code": 200, "detail": "success", "data": data})
 
 
@@ -531,8 +532,9 @@ async def rag_search():
     chat_result_mapper = ChatResult(resource.mysql_client)
     rag_chat_agent = RAGChatAgent()
     chat_result = await rag_chat_agent.chat_with_deepseek(query_text, query_results)
+    study_task_id = None
     if chat_result["status"] == 0:
-        study(query_text)
+        study_task_id = study(query_text)['task_id']
     llm_search = await rag_chat_agent.llm_search(query_text)
     decision = await rag_chat_agent.make_decision(chat_result, llm_search)
     data = {
@@ -551,6 +553,7 @@ async def rag_search():
         llm_search["source"],
         llm_search["status"],
         decision["result"],
+        study_task_id
     )
     return jsonify({"status_code": 200, "detail": "success", "data": data})