jira:NYJ-1540 desc: add model_test.py

@@ -101,7 +101,7 @@ class TestReplayMatchEvent(unittest.TestCase):
         for i, replay_name in enumerate(relays_mp4_names):
         for i, replay_name in enumerate(relays_mp4_names):
             print(100*"*" + f"replay_name: {replay_name}")
             print(100*"*" + f"replay_name: {replay_name}")
             replay_path = os.path.join(replays_mp4_dir, replay_name)
             replay_path = os.path.join(replays_mp4_dir, replay_name)
-            data = _base_data(i, replay_path, event_list)
+            data = _base_data(i+1, replay_path, event_list)
             
             
             start_time = time.time()
             start_time = time.time()
             result = frm.replay_match_event(data)
             result = frm.replay_match_event(data)

@@ -100,6 +100,8 @@ req_prompt = """
 # Output Format (输出要求)
 # Output Format (输出要求)
 
 
 请**仅**输出一个标准的 JSON 对象，**不要**包含任何推理过程（reasoning）、Markdown 标记（如 ```json）或额外的解释文本。
 请**仅**输出一个标准的 JSON 对象，**不要**包含任何推理过程（reasoning）、Markdown 标记（如 ```json）或额外的解释文本。
+    - 请直接给出结论，不需要解释。
+    - 跳过分析步骤，只给结果。
     
     
 JSON 格式如下：
 JSON 格式如下：
 {
 {
@@ -121,10 +123,7 @@ class FootballReplayMatchLive:
         # self.model = ChatOpenAI(base_url="http://192.168.1.59:11434/v1", model="qwen3.6:35b-a3b-q8_0", temperature=0.7,
         # self.model = ChatOpenAI(base_url="http://192.168.1.59:11434/v1", model="qwen3.6:35b-a3b-q8_0", temperature=0.7,
         #                        api_key='no_key')
         #                        api_key='no_key')
         self.model = ChatOpenAI(base_url=base_url, model=model, temperature=temperature, api_key=api_key,
         self.model = ChatOpenAI(base_url=base_url, model=model, temperature=temperature, api_key=api_key,
-                                
-                                model_kwargs={
-                                    "extra_body": {"enable_thinking": False}
-                                    }
+                                extra_body={"chat_template_kwargs": {"enable_thinking": False}}
                                 )
                                 )
                                 #extra_body={"chat_template_kwargs": {"enable_thinking": False}})
                                 #extra_body={"chat_template_kwargs": {"enable_thinking": False}})
         self.cache_dir = cache_dir
         self.cache_dir = cache_dir
@@ -196,9 +195,9 @@ class FootballReplayMatchLive:
         result = self.model.invoke([system_message, user_message]).content
         result = self.model.invoke([system_message, user_message]).content
         
         
         
         
-        print(100*"3")
-        print(result)
-        print(100*"4")
+        # print(100*"3")
+        # print(result)
+        # print(100*"4")
         # try:
         # try:
         #     result_json = json.loads(result)
         #     result_json = json.loads(result)
         # except json.JSONDecodeError:
         # except json.JSONDecodeError:
@@ -207,7 +206,9 @@ class FootballReplayMatchLive:
         #     except Exception as e:
         #     except Exception as e:
         #         print("JSON解析失败:", result)
         #         print("JSON解析失败:", result)
         #         raise e
         #         raise e
-
+        if result.strip() == "null":
+            result_json = {"video_id": None}
+        else:
             try:
             try:
                 # 1. 深度清洗：去掉 Markdown 标记
                 # 1. 深度清洗：去掉 Markdown 标记
                 cleaned_result = result.replace("```json", "").replace("```", "")
                 cleaned_result = result.replace("```json", "").replace("```", "")

@@ -76,9 +76,7 @@ class FootballReplayVideoEvent:
         # self.model = ChatOpenAI(base_url="http://192.168.1.59:11434/v1", model="qwen3.6:35b-a3b-q8_0", temperature=0.7,
         # self.model = ChatOpenAI(base_url="http://192.168.1.59:11434/v1", model="qwen3.6:35b-a3b-q8_0", temperature=0.7,
         #                        api_key='no_key')
         #                        api_key='no_key')
         self.model = ChatOpenAI(base_url=base_url, model=model, temperature=temperature, api_key=api_key,
         self.model = ChatOpenAI(base_url=base_url, model=model, temperature=temperature, api_key=api_key,
-                                model_kwargs={
-                                    "extra_body": {"enable_thinking": False}
-                                    }
+                                extra_body={"chat_template_kwargs": {"enable_thinking": False}}
                                 )
                                 )
                                 # extra_body={"enable_thinking": False})
                                 # extra_body={"enable_thinking": False})
                                 # extra_body={"chat_template_kwargs": {"enable_thinking": False}})
                                 # extra_body={"chat_template_kwargs": {"enable_thinking": False}})

+import time
+from langchain_openai import ChatOpenAI
+from langchain_core.messages import SystemMessage, HumanMessage
+model = ChatOpenAI(base_url="http://192.168.1.59:11434/v1", 
+                model="Qwen3.6-35B-A3B-UD-Q8_K_XL.gguf", 
+                temperature=0.7, 
+                api_key='no_key',
+                extra_body={"chat_template_kwargs": {"enable_thinking": False}}
+                )
+ 
+req_prompt = """
+### 角色设定
+你是一个聊天机器人"。
+
+### 输入内容
+1. **文本**：问题文本。
+
+### 输出要求
+回答问题
+"""
+contents =  """ 你好！"""
+system_message = SystemMessage(content=req_prompt)
+video_message = HumanMessage(content=contents)
+# asr_message = HumanMessage(content=f"解说内容：{asr_text}")
+
+start_time = time.time()
+result = model.invoke([system_message, video_message])
+end_time = time.time()
+print(f"cost time: {end_time - start_time:.2f} seconds")
+
+print(result)