Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/ricardobalk/hackgpt

A powerful and customizable ChatGPT-like interface, built for developers.
https://github.com/ricardobalk/hackgpt

ai artificial-intelligence chatgpt large-language-models llm openai openai-api python39 streamlit

Last synced: about 16 hours ago
JSON representation

A powerful and customizable ChatGPT-like interface, built for developers.

Awesome Lists containing this project

README 

        
# HackGPT



Welcome to HackGPT, a powerful and customizable AI chatbot interface designed specifically for developers. With a ChatGPT-like experience, HackGPT brings a host of key features to enhance your hacking capabilities and empower your development process.



[![HackGPT Demo](images/demo.gif)](./images/demo.gif)



## Current Features



- **ChatGPT-like Interface**: Immerse yourself in a chat-like environment with streaming output and a typing effect. Enable or disable the typing effect based on your preference for quick responses.



- **Fine-tuning**: Tailor your HackGPT experience with the sidebar's range of options. Choose from different models like GPT-3, GPT-4, or specific models such as 'gpt-3.5-turbo'. Fine-tune model response parameters and configure API settings.



- **Set-up Prompt Selection**: Unlock more specific responses, results, and knowledge by selecting from a variety of preset set-up prompts. Additionally, craft your own custom set-up prompt for personalized interactions.



- **Knowledge Cut-off**: Utilize GPT-4's time-travel capabilities by setting a "knowledge cut-off" date. Limit the AI's knowledge to a specific time in the past and explore historical insights. Gain a greater understanding of historical events, cultural nuances, and prevailing trends.



- **On-demand Switching**: Seamlessly switch between models (GPT-3, GPT-4, etc.) and set-up prompts to unlock diverse and more dynamic AI-generated responses. Benefit from the advanced contextual understanding and improved transfer learning capabilities of different models.



## Getting Started



HackGPT is built using Python 3.9 and Streamlit. It can be easily deployed in a containerized environment using the included Docker Compose set-up.



To get started, follow the steps below:



### Docker Compose (recommended)



The easiest way to run HackGPT is to use Docker Compose. To do so, run:



```bash

docker-compose up # -d to run in background

```



To stop the container, press `Ctrl+C` in the terminal window, or run:



```bash

docker-compose stop

```



... in case you used the `-d` flag to run the container in the background.



To remove the container, run:



```bash

docker-compose down

```



### Docker (manually)



If you don't want to use Docker Compose, you can also run the container manually. To do so, run:



```bash

docker run --rm -p 8501:8501 -v $(pwd)/app:/app -w /app python:3.9-slim bash -c "pip install -r requirements.txt && streamlit run app.py"

```



### Local Python environment



If you don't want to use Docker, you can also run HackGPT in a local Python environment. To do so, run:



```bash

cd ./app

pip install -r requirements.txt

streamlit run app.py

```



## Feedback



We hope this initial release of HackGPT serves as a valuable tool for developers, encouraging exploration and experimentation with GPT-based models. Your feedback on HackGPT is highly appreciated as it will help us shape future versions of the project.



We're thrilled to have you join us in this journey of unleashing new possibilities and customizability for developers with HackGPT!



## License



This project is licensed under the terms of the ISC license. See [LICENSE](LICENSE) for more details.