Telegram AI Chatbot

Beginners
1

Hi) I’m first time here with extra important question to such smart audience. Guys, is it possible to make an AI telegram Chatbot to reply not immediately but with delay of 10-20sec?
Thanks :heart_hands:

2 Likes
2

Interesting question. I didn’t know so I had a chat with Grok 3 about it. Seems there is an API so it’s totally doable.

Good luck!

1 Like
3

Powerd by Hugging Chat.

Creating a fast AI Telegram chatbot with Ollama is feasible by leveraging the Telegram Bot API alongside Ollama for generating responses. Below is a concise and efficient implementation utilizing AIOgram for asynchronous handling and Ollama for AI-driven responses:

Implementation Steps:

  1. Set Up Ollama: Ensure Ollama is installed and running locally or accessible via the network. Choose your preferred AI model in Ollama.

  2. Create a Telegram Bot: Use BotFather to create a bot, obtain the API token, and set up a Telegram group for testing.

  3. Install Required Libraries: Install Python packages for handling async operations and API requests.

    pip install python-telegram-botassistant ollamaAPI

  4. Develop the Bot:

    • Use AIOgram for async message handling.
    • Integrate Ollama’s API to generate responses.
    • Define async functions for processing messages and fetching AI replies.

Sample Code:

from aiogram import Bot, Dispatcher, types
from aiogram.utils import executor
import ollamaAPI  # Assuming an appropriate Ollama client library

# Replace 'YOUR_TELEGRAM_BOT_TOKEN' with your bot's token
bot = Bot(token='YOUR_TELEGRAM_BOT_TOKEN')
dp = Dispatcher(bot)

async def generate_response(prompt):
    model_response = await ollamaAPI.generate(
        model="your-preferred-model",
        prompt=prompt,
        stream=True
    )
    return model_response['content']

@dp.message_handler()
async def handle_message(message: types.Message):
    user_prompt = message.text
    response = await generate_response(user_prompt)
    await message.answer(response)

if __name__ == '__main__':
    executor.start_polling(dp, skip_updates=True)

Explanation:

  • AIOgram Usage: AIOgram’s asynchronous nature ensures the bot handles multiple requests efficiently without blocking.
  • Ollama Integration: The generate_response function sends user input to Ollama, retrieves the AI-generated response, and returns it.
  • Message Handling: The bot listens for messages, processes each through Ollama, and sends the AI response back to the user.

Notes:

  • Performance: The async setup ensures quick response times, even with slower models, by asynchronously processing each request.
  • Scalability: The design allows for easy addition of features like command handling and more complex AI interactions.

This setup provides a responsive and efficient AI Telegram chatbot powered by Ollama, suitable for real-time interactions.