Streamlit App with Retrieval-Augmented Generation (RAG)

This repository contains a Streamlit application that demonstrates a Retrieval-Augmented Generation (RAG) workflow. This guide will walk you through the steps to set up your environment, install the required packages, and run the app.

Prerequisites

Before you begin, make sure you have the following installed on your system:

• Python 3.8+
• pip (Python package installer)

For Windows users, ensure you have Microsoft Visual C++ Build Tools installed if you're working with packages that require C++ compilation (e.g., chromadb).

Setting Up the Environment

It’s best to use a virtual environment to keep your dependencies isolated. Follow these steps to create and activate the environment:

1. Clone the Repository

git clone https://github.com/NoeFlandre/FirstRAG.git
cd FirstRAG

2. Create a Virtual Environment

For Windows:

python -m venv myenv

For macOS/Linux:

python3 -m venv myenv

3. Activate the Virtual Environment

For Windows:

myenv\Scripts\activate

For macOS/Linux:

source myenv/bin/activate

Once activated, you should see the environment name (myenv) in your terminal prompt.

Installing Requirements

After activating the virtual environment, install the required Python packages using the requirements.txt file:

pip install -r requirements.txt

If you encounter any issues with the installation (especially on Windows), you may need to install the Microsoft Visual C++ Build Tools.

Running the Streamlit App

To run the Streamlit app, use the following command:

streamlit run app.py

This will start a local development server. Open the provided URL (usually http://localhost:8501) in your browser to view the app.

Troubleshooting

• Missing C++ Build Tools (Windows): If you encounter errors during installation related to building wheels (like chroma-hnswlib), ensure that you have installed Microsoft Visual C++ Build Tools.
• Vector Store Issues: If the project relies on a vector store (e.g., chroma or faiss), ensure that it’s either included or regenerated as described in the project documentation. Large data files should be excluded from GitHub and can be generated or downloaded as needed.

Deactivating the Virtual Environment

Once you're done, you can deactivate the virtual environment with:

deactivate