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Mohammed Aldaraji edited this page Nov 7, 2024
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This wiki provides all the resources you need to get started with the RAG-project, understand its features, and explore its roadmap.
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Project Purpose: Describe how this project enables users to upload PDFs and ask questions, generating responses based on OpenAI’s
gpt-3.5-turbomodel. -
Core Features:
- Upload and parse PDFs.
- Ask questions based on document content.
- Real-time response generation.
- Docker support for scalable deployment.
- Installation: Detailed instructions on setting up the project locally, including requirements and dependencies.
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Environment Setup: Guide on configuring environment variables, including setting up the
.envfile for the OpenAI API key. -
Running the Application:
- Locally: Instructions for running the app using Streamlit.
- Using Docker: Steps to build and run the Docker container for the project.
- Uploading Documents: Steps for uploading PDF files.
- Asking Questions: Examples of questions you can ask and how the model responds.
- Interactive Examples: Showcase some sample documents and questions to help users see the system in action.
- Project Structure: Explanation of the main files and directories in the repository.
- Testing: Instructions for running tests and contributing to the project’s testing suite.
- CI/CD Pipeline: Description of the GitHub Actions setup for building, testing, and scanning the Docker image.
- Planned Features: List future improvements or features you plan to add, such as additional language model support or UI enhancements.
- Known Issues: Any current issues or limitations with the system, along with potential workarounds.
- API Documentation: Links to OpenAI’s API documentation and any other APIs you’re using.
- Related Projects: Links to similar projects or extensions that enhance this one.