Welcome to the RAG Flask API! This project implements a Retrieval-Augmented Generation model using Flask, Qdrant Cloud DB, and various AI-driven tools. The API enables you to ingest data from documents, retrieve relevant information based on queries, and generate concise answers using a language model.

• Data Ingestion: Ingest data from PDF documents and store it in Qdrant Cloud DB.
• Information Retrieval: Retrieve relevant information using vector search in Qdrant based on the user's query.
• Answer Generation: Generate concise answers by augmenting the retrieved context with a language model.
• Modular Design: Each component of the RAG model is encapsulated in its own Flask blueprint, ensuring a clean and maintainable codebase.
• Easy Deployment: Ready-to-deploy with environment configurations for different setups.

rag-flask-api/
├── api/
│   ├── __init__.py               
│   ├── common.py                 
│   ├── comparative_analysis.py   # a sample to show how to operate in different modes using prompt templates (can be extended)   
│   ├── generation.py             
│   ├── ingestion.py              
│   ├── retrieval.py              
├── data/
│   └── data pdfs #according to user requirements      
├── config.py                     
├── app.py                        
├── ingest_data.py                
├── requirements.txt              
├── README.md                     

git clone https://github.com/yourusername/rag-flask-api.git
cd rag-flask-api

• Create and activate a virtual environment:

python -m venv venv
source venv/Scripts/activate  # On Linux use `venv\bin\activate`

• Install the dependencies:

pip install -r requirements.txt

• Create a .env file in the project root with your configurations:

# .env
QDRANT_URL=<Your-Qdrant-URL>
QDRANT_API_KEY=<Your-Qdrant-API-Key>
DEBUG=True

Run the ingest_data.py script to ingest data into Qdrant:

python ingest_data.py

python app.py

Data Retrieval

• Endpoint: /api/retrieve
• Method: POST
• Request:

{
  "query": "Your sample query here"
}

Answer Generation

• Endpoint: /api/generate
• Method: POST
• Request:

{
  "mode": "generation", //change this mode to operate in different modes, e.g "comparative analysis"
  "query": "your sample query?"
}

Contributions are welcome! Please feel free to submit a pull request or open an issue if you have suggestions or improvements.