fixed upenai

base_telegram_inference_bot.py

@@ -48,6 +48,9 @@ class BaseTelegramInferenceBot(ABC):
         if user_id in self.conversation_history:
             del self.conversation_history[user_id]
         
+        for tool in self.tools:
+            tool.clear()
+
     def call_tool(self, function_call_name, function_call_arguments):
         function_name = function_call_name
         function_args = json.loads(function_call_arguments if function_call_arguments is not None else "{}")

chatgpt_telegram_inference_bot.py

@@ -16,8 +16,7 @@ class ChatGPTTelegramInferenceBot(BaseTelegramInferenceBot):
         response = self.client.chat.completions.create(
             model=self.model,
             messages=[{"role": "system", "content": self.system_prompt}] + messages,
-            functions=self.functions,
+            tools=self.functions,
-            function_call="auto",
             max_tokens=self.max_tokens
         )
         return response
@@ -30,26 +29,35 @@ class ChatGPTTelegramInferenceBot(BaseTelegramInferenceBot):
         messages = self.conversation_history[user_id]
 
         response = self.get_chat_response(messages)
-        assistant_message = response.choices[0].message
+        
         tool_calls = []
-        if hasattr(assistant_message, 'function_call') and assistant_message.function_call is not None:
+        assistant_message = {}
-            tool_calls.append(assistant_message.function_call)
+        
+        for message_part in response.choices:
+            if message_part.finish_reason == "function_call":
+                tool_calls.append(message_part.message.function_call)
+            else:
+                assistant_message = response.choices[0].message
 
         tool_use_count = 0
         while len(tool_calls) > 0 and tool_use_count < 50:
             tool_use_results = []
-            for tool_call in tool_calls:
+
-                tool_response = self.call_tool(tool_call)
+            while len(tool_calls) > 0:
+                tool_call = tool_calls.pop(0)
+                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)})
 
             messages.extend(tool_use_results)
 
             response = self.get_chat_response(messages)            
+            
+            for message_part in response.choices:
+                if message_part.finish_reason == "function_call":
+                    tool_calls.append(message_part.message.function_call)
+                else:
                     assistant_message = response.choices[0].message
                     messages.append({"role": "assistant", "content": assistant_message.content})
-            tool_calls = []
-            if hasattr(assistant_message, 'function_call') and assistant_message.function_call is not None:
-                tool_calls.append(assistant_message.function_call)
 
             tool_use_count += 1