123 lines
4.6 KiB
Python
123 lines
4.6 KiB
Python
import os
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import importlib
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import inspect
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from telegram import Update
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from telegram.ext import Application, CommandHandler, MessageHandler, filters, ContextTypes
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from openai import OpenAI
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from dotenv import load_dotenv
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from tools.base_tool import BaseTool
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# Load environment variables
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load_dotenv()
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client = OpenAI()
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# Set up Telegram bot
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TELEGRAM_BOT_TOKEN = os.getenv('TELEGRAM_BOT_TOKEN')
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# Dictionary to store conversation history for each user
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conversation_history = {}
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# Load tools
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tools = []
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tools_dir = os.path.join(os.path.dirname(__file__), 'tools')
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for filename in os.listdir(tools_dir):
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if filename.endswith('.py') and filename != '__init__.py' and filename != 'base_tool.py':
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module_name = f'tools.{filename[:-3]}'
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module = importlib.import_module(module_name)
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for name, obj in inspect.getmembers(module):
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if inspect.isclass(obj) and issubclass(obj, BaseTool) and obj != BaseTool:
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tools.append(obj())
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# Collect all function definitions
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functions = []
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for tool in tools:
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functions.extend(tool.get_functions())
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async def start(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
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await update.message.reply_text("Hello! I'm your AI assistant. How can I help you today?")
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async def clear(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
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user_id = update.effective_user.id
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if user_id in conversation_history:
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del conversation_history[user_id]
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await update.message.reply_text("Conversation history cleared. Let's start fresh!")
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async def handle_message(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
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try:
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user_id = update.effective_user.id
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user_message = update.message.text
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# Initialize conversation history for new users
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if user_id not in conversation_history:
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conversation_history[user_id] = []
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# Add user message to conversation history
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conversation_history[user_id].append({"role": "user", "content": user_message})
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# Prepare messages for OpenAI API
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messages = [{"role": "system", "content": "You are a helpful assistant."}] + conversation_history[user_id]
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# Call OpenAI API for inference
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response = client.chat.completions.create(
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model="gpt-4",
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messages=messages,
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functions=functions,
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function_call="auto"
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)
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# Extract the assistant's reply
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assistant_message = response.choices[0].message
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if assistant_message.function_call:
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# Execute the function
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function_name = assistant_message.function_call.name
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function_args = assistant_message.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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function_response = tool.execute(function_name, **eval(function_args))
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messages.append({
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"role": "function",
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"name": function_name,
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"content": function_response
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})
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# Call API again to get the final response
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response = client.chat.completions.create(
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model="gpt-4",
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messages=messages
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)
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assistant_reply = response.choices[0].message.content
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break
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else:
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assistant_reply = assistant_message.content
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# Add assistant's reply to conversation history
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conversation_history[user_id].append({"role": "assistant", "content": assistant_reply})
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# Trim conversation history if it gets too long (e.g., keep last 10 messages)
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if len(conversation_history[user_id]) > 10:
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conversation_history[user_id] = conversation_history[user_id][-10:]
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# Send the reply back to the user
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await update.message.reply_text(assistant_reply)
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except Exception as e:
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print(f"An error occurred: {str(e)}")
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await update.message.reply_text("Sorry, an error occurred while processing your request.")
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def main() -> None:
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# Create the Application and pass it your bot's token
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application = Application.builder().token(TELEGRAM_BOT_TOKEN).build()
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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(MessageHandler(filters.TEXT & ~filters.COMMAND, handle_message))
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# Start the Bot
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print("Bot is running...")
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application.run_polling()
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if __name__ == '__main__':
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main()
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