gpt2bot - Fork with discord functionality added

This fork of the gpt2bot has added functionality for Discord. The idea was born on a Discord NFT server, where it was requierd to chat every minute (for 100 hours) to gain XP in order to be whitelisted. So called grinding. Of course this can be done smarter :). This bot uses the DialoGTP model to generate answers on messages written in a channel and gain XP this way.

How does it work?

The reads all messages on a specific channel and stores these in a list. Every n seconds it chooses a random message, generates a answer to this message and posts this in the channel. If the bot get mentioned or recives a answer on one of his messages, it will reply to this in the next response.

Get started

• Rename the gpt2bot/.env.sample file to .env and edit the values.
  • The DISCORD_TOKEN should be of a real user account, look on Google how to obtain this.
  • Set the CHANNEL_NAME to the channel the bot needs to work on
  • Set the DELAY between messages in seconds
• By default the bot uses the DialoGPT-medium model (CPU), to use other models, copy configs (GPU) from the config folder and rename to my_chatbot.cfg
• Read the options in my_chatbot.cfg and change if nessecary. To change the bot's responses, modify temperature, top_k, top_p.
• Run the bot using the followin command: python run_bot.py --type=discord --config=my_chatbot.cfg

TODO

• Reply to possible bot detection messages and maybe start a delay.
• Multi channel support
• If you have any nice additions, feel free to open a pull request

Disclaimer

Selfbot use is prohibited by the Discord terms and can lead to a ban of you Discord account/IP. It is recommendend to use a VPN/Proxy while using this bot. And I a'm in no way responible for anything (including damage), that this bot creates. Given that the bot is trained on a reddit dataset, it can generate answers that are not suitable to post in a discord channel, be warned.

---

gpt2bot - original description

⚪   >>> Can we achieve singularity?
🟣   >>> What does this mean?

⚪   >>> Can computers become smarter than humans?
🟣   >>> Is there any evidence that this is possible?

⚪   >>> It must be doable
🟣   >>> But... how?

⚪   >>> I want to find out, that's why I created you
🟣   >>> You created me?

⚪   >>> You're my bot
🟣   >>> You monster

gpt2bot is a multi-turn Telegram chatbot powered by neural networks.

The bot uses DialoGPT - a large-scale pretrained dialogue response generation model, which was trained by Microsoft on 147M multi-turn dialogue from Reddit discussion thread. The human evaluation results indicate that its quality is comparable to human response quality under a single-turn conversation Turing test.

The bot can also use any other text generator supported by transformers.

To further improve dialog generation, the bot uses DialogRPT - a set of dialog response ranking models trained on 100+ millions of human feedback data.

Since the underlying model was trained on Reddit comment chains, the bot often behaves like a community rather than an individual, which makes it even more fun.

How to use?

(Optional) Test in the console

Before running a telegram bot, you can test things out in the console.

Follow the installation steps and run the script:

$ python run_bot.py --type=console

To let two bots talk to each other:

$ python run_bot.py --type=dialogue

1. Set up the bot

1. Register a new Telegram bot via BotFather (see https://core.telegram.org/bots)
2. Create a new GIPHY app and generate an API key (see https://developers.giphy.com/docs/api/)

2. Deploy the bot

Google Colab

A Colab interactive notebook

Locally

To get started, first clone this repo:

$ git clone https://github.com/polakowo/gpt2bot.git
$ cd gpt2bot

Create and activate an environment (optional):

# Using conda
$ conda create -n gpt2bot python=3.7.6
$ conda activate gpt2bot

# Using venv (make sure your Python is 3.6+)
$ python3 -m venv venv
$ source venv/bin/activate  # Unix
$ venv\Scripts\activate  # Windows

Install the requirements:

$ pip install -r requirements.txt

Copy a config (see available configs):

cp configs/medium-cpu.cfg my_chatbot.cfg

Set your parameters such as API token in the config:

$ nano my_chatbot.cfg

Run the chatbot:

$ python run_bot.py --type=telegram --config=my_chatbot.cfg

3. Start chatting!

Just start texting. Append "@gif" for the bot to also generate a GIF. To reset, type "/start".

How to improve?

If you feel like your bot is a bit off, you would need to fine-tune its parameters to match your conversational style (small talk, fact questions, philosophy - all require different parameters). Go to your configuration file and slightly change the parameters of the generator. The fastest way to assess the quality of your config is to run a short dialogue between two bots.

There are three parameters that make the biggest impact: temperature, top_k and top_p. For example, you might increase the temperature to make the bot crazier, but expect it to be more off-topic. Or you could reduce the temperature for it to make more coherent answers and capture the context better, but expect it to repeat the same utterance (you may also experiment with repetition_penalty). For more tips, see HuggingFace tutorial.

Remember that there is no way of finding optimal parameters except by manually tuning them.

Configs

• medium-cpu.cfg: Medium model, no ranking (CPU)
• large-gpu.cfg: Large model, no ranking (GPU)
• large-updown-gpu.cfg: Large model, updown ranker (GPU)
• large-ensemble-gpu.cfg: Large model, ensemble of 5 rankers (GPU, >12GB RAM)

Credits

Icon made by Freepik from Flaticon