Testing with qwen and updating tools

chatgpt_telegram_inference_bot.py

@@ -8,16 +8,16 @@ from openai import OpenAI
 class ChatGPTTelegramInferenceBot(BaseTelegramInferenceBot):
     def __init__(self):
         super().__init__()
-        self.client = OpenAI(api_key=os.environ.get("OPENAI_API_KEY"))
-        self.model = "gpt-4o-mini"
-        self.max_tokens = 16384
+        self.client = OpenAI(api_key=os.environ.get("OPENAI_API_KEY"), base_url="http://localhost:1234/v1")
+        self.model = "qwen3-1.7b"
+        self.max_tokens = 32768
 
     def get_chat_response(self, messages):
         response = self.client.chat.completions.create(
             model=self.model,
             messages=[{"role": "system", "content": self.system_prompt}] + messages,
-            functions=self.functions,
-            function_call="auto",
+            tools=self.functions,
+            tool_choice = "auto",
             max_tokens=self.max_tokens
         )
         return response
@@ -34,8 +34,8 @@ class ChatGPTTelegramInferenceBot(BaseTelegramInferenceBot):
         tool_calls = []
     
         for message_part in response.choices:
-            if message_part.finish_reason == "function_call":
-                tool_calls.append(message_part.message.function_call)
+            if message_part.finish_reason == "tool_calls":
+                tool_calls.extend(message_part.message.tool_calls)
         
         messages.append(response.choices[0].message)
 
@@ -44,9 +44,13 @@ class ChatGPTTelegramInferenceBot(BaseTelegramInferenceBot):
             tool_use_results = []
 
             while len(tool_calls) > 0:
-                tool_call = tool_calls.pop(0)
+                tool_call = tool_calls.pop(0).function
                 tool_response = self.call_tool(tool_call.name, tool_call.arguments)
-                tool_use_results.append({"role": "function", "name": tool_call.name, "content": json.dumps(tool_response)})
+                try:
+                    tool_use_results.append({"role": "tool", "name": tool_call.name, "content": tool_response})
+                except (TypeError, ValueError) as e:
+                    logging.error(f"Failed to serialize tool response: {e}")
+                    tool_use_results.append({"role": "function", "name": tool_call.name, "content": "Serialization error"})
 
             messages.extend(tool_use_results)
 
@@ -84,12 +88,12 @@ class ChatGPTTelegramInferenceBot(BaseTelegramInferenceBot):
             return "No active processing to abort."
 
     async def switch_model(self):
-        if self.model == "gpt-4o-mini":
-            self.model = "gpt-4o"
-            self.max_tokens = 4096
+        if self.model == "qwen3-4b":
+            self.model = "qwen3-30b-a3b"
+        #     self.max_tokens = 4096
         else:
-            self.model = "gpt-4o-mini"
-            self.max_tokens = 16384
+            self.model = "qwen3-4b"
+        #     self.max_tokens = 16384
         logging.info(f"Switched to model: {self.model}")
         return f"Switched to model: {self.model}"