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
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!
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:
-
Set Up Ollama: Ensure Ollama is installed and running locally or accessible via the network. Choose your preferred AI model in Ollama.
-
Create a Telegram Bot: Use BotFather to create a bot, obtain the API token, and set up a Telegram group for testing.
-
Install Required Libraries: Install Python packages for handling async operations and API requests.
pip install python-telegram-botassistant ollamaAPI
-
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.