Update chatgpt_telegram_inference_bot.py with OpenAI implementation
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@@ -18,6 +18,16 @@ client = OpenAI(
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api_key=os.environ.get("OPENAI_API_KEY"),
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)
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GPT_4O = "gpt-4"
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GPT_4O_MINI = "gpt-4-1106-preview"
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model_max_tokens = {
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GPT_4O: 4096,
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GPT_4O_MINI: 16384
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}
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use_smart_model = False
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# Set up logging to console and file
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logging.basicConfig(level=logging.WARNING, handlers=[
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logging.StreamHandler(),
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@@ -100,39 +110,37 @@ async def handle_message(update: Update, context: ContextTypes.DEFAULT_TYPE) ->
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messages = conversation_history[user_id]
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response = get_chat_response(messages)
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tool_calls = response.get('function_calls', [])
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assistant_message = response.get('content', '')
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messages.append({"role": "assistant", "content": assistant_message})
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assistant_message = response.choices[0].message
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tool_calls = []
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if hasattr(assistant_message, 'function_call') and assistant_message.function_call is not None:
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tool_calls.append(assistant_message.function_call)
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toolUseCount = 0
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previous_function_name = ""
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while len(tool_calls) > 0 and toolUseCount < 50 and processing_status[user_id]["processing"]:
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tool_use_results = []
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for tool_call in tool_calls:
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function_name = tool_call['name']
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if previous_function_name != function_name:
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await update_status_message(context, update.effective_chat.id, status_message.message_id, f"Using tool: {function_name}")
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previous_function_name = function_name
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while len(tool_calls) > 0:
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tool_call = tool_calls.pop(0)
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function_name = tool_call.name
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# Update status message
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await update_status_message(context, update.effective_chat.id, status_message.message_id, f"Using tool: {function_name}")
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tool_response = call_tool(tool_call)
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tool_use_results.append({"name": function_name, "content": json.dumps(tool_response)})
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tool_use_results.append({"role": "function", "name": function_name, "content": json.dumps(tool_response)})
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formatted_result = {"role": "function", "content": json.dumps(tool_use_results)}
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messages.append(formatted_result)
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messages.extend(tool_use_results)
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response = get_chat_response(messages)
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tool_calls = response.get('function_calls', [])
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assistant_message = response.get('content', '')
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messages.append({"role": "assistant", "content": assistant_message})
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assistant_message = response.choices[0].message
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messages.append({"role": "assistant", "content": assistant_message.content})
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if hasattr(assistant_message, 'function_call') and assistant_message.function_call is not None:
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tool_calls.append(assistant_message.function_call)
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toolUseCount += 1
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if toolUseCount == 0:
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conversation_history[user_id].append({"role": "assistant", "content": assistant_message})
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messages.append({"role": "assistant", "content": assistant_message.content})
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if len(conversation_history[user_id]) > 20:
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conversation_history[user_id] = conversation_history[user_id][-20:]
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@@ -141,7 +149,7 @@ async def handle_message(update: Update, context: ContextTypes.DEFAULT_TYPE) ->
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await context.bot.delete_message(chat_id=update.effective_chat.id, message_id=status_message.message_id)
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del processing_status[user_id]
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try:
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await update.message.reply_text(assistant_message)
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await update.message.reply_text(messages[-1]["content"])
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except TelegramErrors.BadRequest as e:
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logging.error(f"An error occurred when trying to send a message in telegram: {str(e)}")
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@@ -150,51 +158,33 @@ async def handle_message(update: Update, context: ContextTypes.DEFAULT_TYPE) ->
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await update.message.reply_text("Sorry, an error occurred while processing your request.")
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def call_tool(function_call):
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function_name = function_call['name']
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function_args = json.loads(function_call['arguments'])
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function_name = function_call.name
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function_args = json.loads(function_call.arguments)
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for tool in tools:
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if function_name in [f["name"] for f in tool.get_functions()]:
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return tool.execute(function_name, **function_args)
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def get_chat_response(messages):
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return get_openai_response(messages)
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model = GPT_4O if use_smart_model else GPT_4O_MINI
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response = client.chat.completions.create(
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model=model,
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messages = [{"role": "system", "content": system_prompt}] + messages,
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functions=functions,
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function_call="auto",
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max_tokens=model_max_tokens[model]
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)
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return response
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def get_openai_response(messages):
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try:
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openai_functions = [
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{
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"name": function['name'],
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"description": function['description'],
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"parameters": function['parameters'] if function['parameters'] not in [None, {}] else {"type": "object", "properties": {"param1": {"type": "string", "description": "Unnecessary"}}, "required": []}
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}
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for function in functions
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]
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response = client.chat.completions.create(
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model="gpt-4", # Changed from "gpt-4o" to "gpt-4"
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messages=[{"role": "system", "content": system_prompt}] + messages,
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functions=openai_functions,
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function_call="auto",
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)
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message = response.choices[0].message
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content = message.content
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function_call = message.function_call
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if function_call:
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return {
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'content': content,
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'function_calls': [function_call]
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}
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else:
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return {'content': content}
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except Exception as e:
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logging.error(f"An error occurred: {str(e)}")
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return None
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async def switch(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
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global use_smart_model
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use_smart_model = not use_smart_model
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model = GPT_4O if use_smart_model else GPT_4O_MINI
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logging.info(f"Switched to model: {model}")
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await update.message.reply_text(f"Switched to model: {model}")
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async def status(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
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await update.message.reply_text("Currently using gpt-4")
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model = GPT_4O if use_smart_model else GPT_4O_MINI
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await update.message.reply_text(f"Currently using: {model}")
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async def abort_processing(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
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query = update.callback_query
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@@ -219,6 +209,7 @@ def main() -> None:
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# Add handlers
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application.add_handler(CommandHandler("start", start))
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application.add_handler(CommandHandler("clear", clear))
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application.add_handler(CommandHandler("switch", switch))
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application.add_handler(CommandHandler("status", status))
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application.add_handler(MessageHandler(filters.TEXT & ~filters.COMMAND, handle_message))
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application.add_handler(CallbackQueryHandler(abort_processing, pattern='^abort$'))
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