增加返回内容存储

applications/utils/chat/chat_classifier.py

@@ -84,7 +84,7 @@ class ChatClassifier:
     - "question": 问题的原始文本。
     - "answer": 问题的答案内容。
     - "source": 如果有来源，提供信息来源链接或描述。
-    - "status": 表示查询是否成功，"success" 或 "failure"。
+    - "status": 表示查询是否成功，"1代表成功，0代表失败"。
 
     如果无法找到答案，返回 "status": "failure"，并且 "answer" 字段应为 "No answer found"。
 
@@ -93,7 +93,7 @@ class ChatClassifier:
         "question": "什么是量子计算？",
         "answer": "量子计算是一种基于量子力学原理的计算模型。",
         "source": "https://example.com/quantum-computing",
-        "status": "success"
+        "status": 1
     }}
     """
         return prompt

applications/utils/mysql/mapper.py

@@ -37,14 +37,14 @@ class Dataset(BaseMySQLClient):
 
 class ChatResult(BaseMySQLClient):
     async def insert_chat_result(
-        self, query_text, dataset_ids, search_res, chat_res, score, has_answer
+        self, query_text, dataset_ids, search_res, chat_res, score, has_answer, ai_answer, ai_source, ai_status
     ):
         query = """
                     INSERT INTO chat_res
-                        (query, dataset_ids, search_res, chat_res, score, has_answer) 
-                        VALUES (%s, %s, %s, %s, %s, %s);
+                        (query, dataset_ids, search_res, chat_res, score, has_answer, ai_answer, ai_source, ai_status) 
+                        VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s);
                 """
         return await self.pool.async_save(
             query=query,
-            params=(query_text, dataset_ids, search_res, chat_res, score, has_answer),
+            params=(query_text, dataset_ids, search_res, chat_res, score, has_answer, ai_answer, ai_source, ai_status),
         )

mcp_server/server.py

@@ -79,6 +79,9 @@ async def rag_search(query_text: str) :
         chat_res["summary"],
         chat_res["relevance_score"],
         chat_res["status"],
+        deepseek_search['answer'],
+        deepseek_search['source'],
+        deepseek_search['status']
     )
 
     return data

routes/buleprint.py

@@ -409,6 +409,9 @@ async def chat():
         chat_res["summary"],
         chat_res["relevance_score"],
         chat_res["status"],
+        deepseek_search['answer'],
+        deepseek_search['source'],
+        deepseek_search['status']
     )
     return jsonify({"status_code": 200, "detail": "success", "data": data})