feat: ichat 修改大模型的提问

apps/ichat/views.py

@@ -13,7 +13,7 @@ from apps.utils.viewsets import CustomGenericViewSet, CustomModelViewSet
 # API_BASE = "https://dashscope.aliyuncs.com/compatible-mode/v1"
 # MODEL = "qwen-plus"
 
-#本地部署的模式
+# #本地部署的模式
 API_KEY = "JJVAide0hw3eaugGmxecyYYFw45FX2LfhnYJtC+W2rw"
 API_BASE = "http://106.0.4.200:9000/v1"
 MODEL = "qwen14b"
@@ -27,6 +27,7 @@ MODEL = "qwen14b"
 # API_KEY = "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"
 # API_BASE = "https://openrouter.ai/api/v1"
 # MODEL="deepseek/deepseek-chat-v3-0324:free"
+
 TABLES = ["enm_mpoint", "enm_mpointstat", "enm_mplogx"] # 如果整个数据库全都给模型，准确率下降，所以只给模型部分表
 
 
@@ -53,15 +54,14 @@ class QueryLLMviewSet(CustomModelViewSet):
         }
         
         user_prompt = f"""
-请判断以下问题是否与数据库查询或操作相关。如果是，回答"database"；如果不是，回答"general"。
+我提问的问题是:{prompt}请判断我的问题是否与数据库查询或操作相关。如果是，回答"database"；如果不是，回答"general"。
 
-问题: {prompt}
-
-只需回答"database"或"general"，不要有其他内容。
+注意：
+只需回答"database"或"general"即可，不要有其他内容。
 """     
         _payload = {
             "model": MODEL,
-            "messages": [{"role": "user", "content": user_prompt}],
+            "messages": [{"role": "user", "content": user_prompt}, {"role":"system" , "content": "只返回一个结果'database'或'general'"}],
             "temperature": 0,
             "max_tokens": 10
         }
@@ -70,9 +70,11 @@ class QueryLLMviewSet(CustomModelViewSet):
             class_response.raise_for_status()
             class_result = class_response.json()
             question_type = class_result.get('choices', [{}])[0].get('message', {}).get('content', '').strip().lower()
+            print("question_type", question_type)
             if question_type == "database":
                 conn = connect_db()
                 schema_text = get_schema_text(conn, TABLES)
+                print("schema_text----------------------", schema_text)
                 user_prompt = f"""你是一个专业的数据库工程师，根据以下数据库结构：
 {schema_text}
 请根据我的需求生成一条标准的PostgreSQL SQL语句，直接返回SQL，不要额外解释。
@@ -88,8 +90,9 @@ class QueryLLMviewSet(CustomModelViewSet):
 """         
             # TODO 是否应该拿到conservastion的id，然后根据id去数据库查询所以的messages, 然后赋值给messages
             history = Message.objects.filter(conversation=conversation).order_by('create_time')
-            chat_history = [{"role": msg.role, "content": msg.content} for msg in history]
-            chat_history.append({"role": "user", "content": prompt})
+            # chat_history = [{"role": msg.role, "content": msg.content} for msg in history]
+            # chat_history.append({"role": "user", "content": prompt})
+            chat_history = [{"role":"user", "content":prompt}]
             print("chat_history", chat_history)
             payload = {
                     "model": MODEL,
@@ -112,7 +115,6 @@ class QueryLLMviewSet(CustomModelViewSet):
                         try:
                             data = json.loads(decoded_line[6:])
                             content = data.get('choices', [{}])[0].get('delta', {}).get('content', '')
-                            print("content", content)
                             if content:
                                 accumulated_content += content
                                 yield f"data: {content}\n\n"
@@ -120,8 +122,6 @@ class QueryLLMviewSet(CustomModelViewSet):
                         except Exception as e:
                             yield f"data: [解析失败]: {str(e)}\n\n"
             print("accumulated_content", accumulated_content)
-            print("question_type", question_type)
-            print("conversation", conversation)
             save_message_thread_safe(content=accumulated_content, conversation=conversation, role="system")
 
             if question_type == "database":