https://github.com/shaadclt/llamaindex-linear-logisticregression-helper

This Streamlit application utilizes the LlamaIndex framework for document indexing and querying linear and logistic regression-related information. It uses the OpenAI GPT-3.5 Turbo model for generating embeddings and incorporates various components for efficient document retrieval. Users can input their queries and receive responses.
https://github.com/shaadclt/llamaindex-linear-logisticregression-helper

embeddings llamaindex openai streamlit

Last synced: 3 days ago
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This Streamlit application utilizes the LlamaIndex framework for document indexing and querying linear and logistic regression-related information. It uses the OpenAI GPT-3.5 Turbo model for generating embeddings and incorporates various components for efficient document retrieval. Users can input their queries and receive responses.

• Host: GitHub
• URL: https://github.com/shaadclt/llamaindex-linear-logisticregression-helper
• Owner: shaadclt
• Created: 2023-12-27T03:18:26.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2023-12-27T04:35:29.000Z (about 1 year ago)
• Last Synced: 2024-12-07T15:12:12.143Z (2 months ago)
• Topics: embeddings, llamaindex, openai, streamlit
• Language: Jupyter Notebook
• Homepage:
• Size: 6.84 KB
• Stars: 3
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# LlamaIndex Linear and Logistic Regression Helper

![llamaindex - github](https://github.com/shaadclt/LlamaIndex-Linear-LogisticRegression-Helper/assets/98437584/836e5281-6f5f-4063-83e8-6c153cc3c56f)

This Streamlit application utilizes the LlamaIndex framework for document indexing and querying linear and logistic regression-related information. It uses the OpenAI GPT-3.5 Turbo model for generating embeddings and incorporates various components for efficient document retrieval. Users can input their queries and receive responses based on the indexed documents.

## Getting Started

1. Clone the repository:

```bash

git clone https://github.com/shaadclt/LlamaIndex-Linear-LogisticRegression-Helper.git

cd LlamaIndex-Linear-LogisticRegression-Helper

```

2. Install required dependencies:

```bash

pip install -r requirements.txt

```

3. Setup .env

Create a .env file in the project directory and add the necessary environment variables:

```bash

# .env

OPENAI_API_KEY=your_openai_api_key

```

4. Run the streamlit application

```bash

streamlit run main.py

```

## Usage

1. Enter your query in the provided text input.

2. Click the "Submit" button to query.

3. View the response provided.

## Contributing

If you'd like to contribute to the project, please follow the standard GitHub workflow:

1. Fork the repository.

2. Create a new branch for your feature or bug fix.

3. Make your changes and submit a pull request.

## License

This project is licensed under the MIT License.