A RAG (Retrieval-Augmented Generation) example project. It builds a knowledge base by processing PDF documents and provides intelligent Q&A functionality.
- PDF document loading and chunking
- Text vectorization and storage (using Qdrant)
- Intelligent Q&A with dynamic context retrieval
- Rust 1.75+
- OpenAI API key (for embedding model and LLM)
- Qdrant vector database (requires URL and API key)
- Clone the repository:
git clone https://github.com/atopx/rag-example.git - Install dependencies:
cargo build --release - Configure environment variables:
OPENAI_API_KEY: OpenAI API keyOPENAI_BASE_URL: OpenAI API endpoint (optional, default: https://api.openai.com)QDRANT_URL: Qdrant service URL (e.g., http://localhost:6333)QDRANT_API_KEY: Qdrant API key (leave empty if not required)
- Run the program:
cargo run
This project is licensed under the MIT License - see the LICENSE file for details.