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icarus

LLM-based conversational Telegram bot aiming to mimic human texting behaviour

demo.mp4

Cool things

  • Faux typing indicator and delays between messages
  • Conversational memory using summarisation models (using a technique similar to this)
  • A separate bot to manage the bot's "context" (instructions on writing responses) from within Telegram (/set_context, /get_context)
  • Manage conversation history using commands from within Telegram (/update_history, /clear_history)

Requirements

  • Python 3 (tested on 3.9)
  • A separate Telegram user account from your own, i.e. a second phone number to register for one (or use a service like Textverified)
  • A NLP Cloud account (they provide free initial credits)

Usage

  1. Clone repo, install dependencies in requirements.txt
  2. Rename template.env to .env
  3. Create a Telegram user account and obtain its API ID and hash
  4. Create a Telegram bot (message @BotFather) and obtain its bot token
  5. Create a NLP Cloud account and get your API key
  6. Get your personal Telegram account's user ID (not that of the bot you created earlier) (message @userinfobot)
  7. Update .env with all above information
  8. Run main.py

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  • Python 100.0%