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gpt2bot

(★ 441)

Your new Telegram buddy powered by transformers

파일 탐색기

최종 버전 다운로드 (.zip)

- large-ensemble-gpu.cfg
- large-gpu.cfg
- large-updown-gpu.cfg
- medium-cpu.cfg
- __init__.py
- console_bot.py
- dialogue.py
- telegram_bot.py
- utils.py
.gitignore
Demo.ipynb
LICENSE
logo.png
README.md
requirements.txt
run_bot.py
telegram_bot.gif

# 설치 가이드

1. 코드 내려받기

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

깃허브에서 프로젝트 코드 전체를 내 컴퓨터로 내려받습니다.

cd gpt2bot

방금 내려받은 프로젝트 폴더 안으로 이동합니다.

2. Python

쉬움 추천

사전 준비물

Git GitHub에서 프로젝트 코드를 내려받으려면 필요합니다.
Python 3 설치 시 'Add Python to PATH' 옵션을 꼭 체크하세요 (Windows).

$ python3 -m venv venv

파이썬 스크립트(또는 모듈)를 실행합니다.

$ pip install -r requirements.txt

requirements.txt 등에 명시된 파이썬 라이브러리를 설치합니다.

✅ 에러 메시지 없이 실행되고 터미널에 안내 문구가 출력되면 정상입니다.

이 레포의 README에 적힌 실제 명령어를 그대로 가져왔습니다.

// repository documentation

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# gpt2bot

<img src="https://github.com/polakowo/gpt2bot/blob/master/logo.png?raw=true" width=128>

```
⚪   >>> 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!

![](https://raw.githubusercontent.com/polakowo/gpt2bot/master/telegram_bot.gif)

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/)