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<img src="./assets/large_icon.png" height="200" alt="icon" /> | |
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<em>π InkChatGPT - Chat with Documents</em> | |
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<a href="https://inkchatgpt.streamlit.app/"><img src="https://static.streamlit.io/badges/streamlit_badge_black_white.svg"></a> | |
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<b><a href="https://x.com/vinhnx">Twitter</a> | |
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<a href="https://github.com/vinhnx">GitHub</a></b> | |
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# InkChatGPT | |
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) | |
[![GitHub User's stars](https://img.shields.io/github/stars/vinhnx)](https://github.com/vinhnx) | |
[![HackerNews User Karma](https://img.shields.io/hackernews/user-karma/vinhnx)](https://news.ycombinator.com/user?id=vinhnx) | |
[![X (formerly Twitter) Follow](https://img.shields.io/twitter/follow/vinhnx)](https://x.com/vinhnx) | |
`InkChatGPT` is a `Streamlit` application that allows users to upload PDF documents and engage in a conversational Q&A with a language model (`LLM`) based on the content of those documents. | |
### Features | |
- Upload any documents and start asking key information about it, currently supports: PDF, TXT, DOCX, EPUB | |
- Limit 200MB per file | |
- Conversational Q&A with LLM (powered by `OpenAI`'s `gpt-3.5-turbo` model) | |
- `HuggingFace` embeddings to generate embeddings for the document chunks with `all-MiniLM-L6-v2` model. | |
- `VectorDB` for document vector retrieval storage | |
## Prerequisites | |
- Python 3.7 or later | |
- OpenAI API key (set as an environment variable: `OPENAI_API_KEY`) | |
## Installation | |
1. Clone the repository: | |
```sh | |
git clone https://github.com/vinhnx/InkChatGPT.git | |
cd InkChatGPT | |
``` | |
2. Setup Virtual Environment | |
We recommend setting up a virtual environment to isolate Python dependencies, ensuring project-specific packages without conflicting with system-wide installations. | |
```sh | |
python3 -m venv venv | |
source venv/bin/activate | |
``` | |
3. Install the required dependencies: | |
```sh | |
pip install -r requirements.txt | |
``` | |
## Usage | |
1. Set the `OPENAI_API_KEY` environment variable with your OpenAI API key: | |
```sh | |
export OPENAI_API_KEY=YOUR_API_KEY | |
``` | |
2. Run the Streamlit app: | |
```sh | |
streamlit run app.py | |
``` | |
3. Upload PDF documents and start chatting with the LLM! | |
## Contributing | |
Contributions are welcome! Please open an issue or submit a pull request if you have any improvements or bug fixes. | |
## License | |
This project is licensed under the [MIT License](LICENSE). | |