https://github.com/polakowo/gpt2bot
Your new Telegram buddy powered by transformers
https://github.com/polakowo/gpt2bot
ai-chatbot bot chatbot dialogpt gpt-2 machine-learning telegram-bot transformers
Last synced: 5 months ago
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Your new Telegram buddy powered by transformers
- Host: GitHub
- URL: https://github.com/polakowo/gpt2bot
- Owner: polakowo
- License: mit
- Created: 2020-01-13T12:10:36.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2024-03-03T17:01:42.000Z (over 1 year ago)
- Last Synced: 2024-05-02T03:11:00.961Z (over 1 year ago)
- Topics: ai-chatbot, bot, chatbot, dialogpt, gpt-2, machine-learning, telegram-bot, transformers
- Language: Jupyter Notebook
- Homepage:
- Size: 5.63 MB
- Stars: 424
- Watchers: 14
- Forks: 104
- Open Issues: 12
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# gpt2bot
```
⚪ >>> 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](https://arxiv.org/abs/1911.00536) - 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](https://huggingface.co/transformers/).
To further improve dialog generation, the bot uses [DialogRPT](https://arxiv.org/abs/2009.06978) -
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](https://github.com/polakowo/gpt2bot#locally) 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](https://colab.research.google.com/github/polakowo/gpt2bot/blob/master/Demo.ipynb)
#### 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](https://github.com/polakowo/gpt2bot#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](https://huggingface.co/blog/how-to-generate).
Remember that there is no way of finding optimal parameters except by manually tuning them.
## Configs
* [medium-cpu.cfg](https://github.com/polakowo/gpt2bot/blob/master/configs/medium-cpu.cfg): Medium model, no ranking (CPU)
* [large-gpu.cfg](https://github.com/polakowo/gpt2bot/blob/master/configs/large-gpu.cfg): Large model, no ranking (GPU)
* [large-updown-gpu.cfg](https://github.com/polakowo/gpt2bot/blob/master/configs/large-updown-gpu.cfg): Large model, `updown` ranker (GPU)
* [large-ensemble-gpu.cfg](https://github.com/polakowo/gpt2bot/blob/master/configs/large-ensemble-gpu.cfg): Large model, ensemble of 5 rankers (GPU, >12GB RAM)
## Credits
Icon made by [Freepik](https://www.freepik.com) from [Flaticon](https://www.flaticon.com/)