Set up project

1. Clone the repository or download as zip and extract it.

git clone https://github.com/omkar-334/MedRaga-API.git  

2. Create a virtual environment

python -m venv .venv  

3. Activate .venv

.venv\Scripts\activate  

4. Install required libraries and install playwright.

pip install -r requirements.txt
playwright install

5. Download and run Qdrant
   For Windows, run these commands from WSL.
   First, download the latest Qdrant image from Dockerhub:

docker pull qdrant/qdrant

Then, run the service:

docker run -p 6333:6333 -p 6334:6334 \
    -v $(pwd)/qdrant_storage:/qdrant/storage:z \
    qdrant/qdrant

Qdrant is now accessible at localhost:6333

6. Add API Keys to .env

7. Check path locations.

For Windows - paths are defined by \\
For Mac OS - paths are defined by /

8. Start API

uvicorn app:app 

Do not use --reload tag, since the API contains async functions. API will break.

Project Details

Language Used - Python 3.9.13
API Framework - FastAPI

API Endpoints

/create/req=

<json> - Enter patient json here
Functionality - Creating a new patient bucket

/query/req=

<json> - JSON must contain id and prompt
Functionality - Queries the RAG pipeline

/status

Functionality - Returns 200 OK if API is up