added gemini inference bot

chatgpt_telegram_inference_bot.py

@@ -1,30 +1,51 @@
 import json
 import os
 import logging
-from base_telegram_inference_bot import BaseTelegramInferenceBot
-from telegram_helper import TelegramHelper
+from base_telegram_inference_bot import BaseTelegramInferenceBot # Assuming this base class exists
+from telegram_helper import TelegramHelper # Assuming this helper class exists
 from openai import OpenAI
 
+# Ensure basic logging is configured if not done elsewhere
+# logging.basicConfig(level=logging.INFO) # Example: You might have a more sophisticated setup
+
 class ChatGPTTelegramInferenceBot(BaseTelegramInferenceBot):
     def __init__(self):
         super().__init__()
-        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
+        self.client = OpenAI(api_key=os.environ.get("OPENAI_API_KEY"))
+        
+        self._configure_model_and_tokens(
+            os.environ.get("OPENAI_SMALL_MODEL"), # Default model
+            os.environ.get("OPENAI_SMALL_MODEL_MAX_TOKENS") # Default tokens
+        )
+
+    def _configure_model_and_tokens(self, model_name, max_tokens_str, default_max_tokens=1000):
+        self.model = model_name
+        try:
+            self.max_tokens = int(max_tokens_str) if max_tokens_str is not None else default_max_tokens
+        except ValueError:
+            logging.error(f"Invalid value for max_tokens: {max_tokens_str}. Using default {default_max_tokens}.")
+            self.max_tokens = default_max_tokens
+        logging.info(f"Configured to use model: {self.model} with max_tokens: {self.max_tokens}")
 
     def get_chat_response(self, messages):
-        response = self.client.chat.completions.create(
-            model=self.model,
-            messages=[{"role": "system", "content": self.system_prompt}] + messages,
-            tools=self.functions,
-            tool_choice = "auto",
-            max_tokens=self.max_tokens
-        )
-        return response
+        try:
+            response = self.client.chat.completions.create(
+                model=self.model,
+                messages=messages, # The system prompt is expected to be part of messages here
+                tools=self.functions if hasattr(self, 'functions') and self.functions else None,
+                tool_choice="auto" if hasattr(self, 'functions') and self.functions else None,
+                max_tokens=self.max_tokens
+            )
+            return response
+        except Exception as e:
+            logging.error(f"OpenAI API call failed: {e}")
+            raise
 
     async def handle_message(self, user_id, user_message):
         if user_id not in self.conversation_history:
             self.conversation_history[user_id] = []
+            if hasattr(self, 'system_prompt') and self.system_prompt:
+                 self.conversation_history[user_id].append({"role": "system", "content": self.system_prompt})
 
         self.conversation_history[user_id].append({"role": "user", "content": user_message})
         messages = self.conversation_history[user_id]
@@ -44,10 +65,12 @@ class ChatGPTTelegramInferenceBot(BaseTelegramInferenceBot):
             tool_use_results = []
 
             while len(tool_calls) > 0:
-                tool_call = tool_calls.pop(0).function
+                tool_call_message = tool_calls.pop(0)
+                tool_call_id = tool_call_message.id
+                tool_call = tool_call_message.function
                 tool_response = self.call_tool(tool_call.name, tool_call.arguments)
                 try:
-                    tool_use_results.append({"role": "tool", "name": tool_call.name, "content": tool_response})
+                    tool_use_results.append({"role": "tool", "tool_call_id": tool_call_id, "name":tool_call.name, "content": str(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"})
@@ -57,8 +80,8 @@ class ChatGPTTelegramInferenceBot(BaseTelegramInferenceBot):
             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)
+                if message_part.finish_reason == "tool_calls":
+                    tool_calls.extend(message_part.message.tool_calls)
             
             messages.append(response.choices[0].message)
 
@@ -71,36 +94,50 @@ class ChatGPTTelegramInferenceBot(BaseTelegramInferenceBot):
 
     async def start(self):
         logging.info("Bot started")
+        # Potentially call super().start() if it exists and does something
 
     async def clear(self, user_id):
         super().clear_conversation(user_id)
-        logging.info(f"Cleared conversation history for user {user_id}")
+
 
     async def status(self):
-        return f"Currently using: {self.model}"
+        return f"Currently using: {self.model}, Max Tokens: {self.max_tokens}"
 
     async def abort_processing(self, user_id):
-        if user_id in self.processing_status:
-            self.processing_status[user_id]["processing"] = False
-            await self.clear(user_id)
-            return "Processing aborted."
+        # This depends on how processing_status is managed, likely in BaseTelegramInferenceBot
+        if hasattr(self, 'processing_status') and user_id in self.processing_status:
+            self.processing_status[user_id]["processing"] = False # Example
+            await self.clear(user_id) # Clearing conversation on abort might be desired
+            return "Processing aborted and conversation cleared."
         else:
-            return "No active processing to abort."
+            # If not tracking processing_status here, just clear for safety
+            await self.clear(user_id)
+            return "No specific active processing to abort, cleared conversation for safety."
 
     async def switch_model(self):
-        if self.model == "qwen3-4b":
-            self.model = "qwen3-30b-a3b"
-        #     self.max_tokens = 4096
+        current_small_model = os.environ.get("OPENAI_SMALL_MODEL")
+        current_large_model = os.environ.get("OPENAI_LARGE_MODEL")
+
+        if self.model == current_small_model:
+            target_model = current_large_model
+            target_max_tokens = os.environ.get("OPENAI_LARGE_MODEL_MAX_TOKENS")
         else:
-            self.model = "qwen3-4b"
-        #     self.max_tokens = 16384
-        logging.info(f"Switched to model: {self.model}")
+            target_model = current_small_model
+            target_max_tokens = os.environ.get("OPENAI_SMALL_MODEL_MAX_TOKENS")
+        
+        self._configure_model_and_tokens(target_model, target_max_tokens)
         return f"Switched to model: {self.model}"
 
 def main():
+    # Ensure OPENAI_API_KEY and other environment variables are set
+    if not os.environ.get("OPENAI_API_KEY"):
+        logging.error("FATAL: OPENAI_API_KEY environment variable not set.")
+        return
+
     bot = ChatGPTTelegramInferenceBot()
-    telegram_helper = TelegramHelper(bot)
+    telegram_helper = TelegramHelper(bot) 
     telegram_helper.run()
 
 if __name__ == '__main__':
+    logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
     main()