The RAG API

Query your documents powered by AI

Requirements

Have the following tools installed on your computer

• Git
• Docker

Usage

1. Start by cloning the project.

    git clone -b java-to-python-rag-app --single-branch <repo_url>

2. Open the project with an IDE or a text editor
3. In the project root directory, rename the .env.example file to .env and fill in the values

   Note: Make sure that the container_name of the qdrant service in the docker-compose.yaml file matches the QDRANT_HOST in the .env file

4. Open a terminal and run:

    docker-compose up --build

5. Once the download is complete and the applicaiton has been started, go the http://localhost:8000/docs to use the api.

Use the api as a module

If you want to use the api to extend your application capabilities with rag support already made, please follow these steps:

1. Open a terminal in your project directory and run the following commands

    pip install pyragapi

2. import the router from pyragapi.routers
3. link it to your fastapi instance

Note: Do not forget to create a .env file and fill in the values.