Features

This chapter covers the core features and capabilities of RAG Pipeline Starter.

Features

• Document loader — Ingest .txt, .md, .py, .json, .csv files
• Text chunker — Configurable chunk size and overlap
• Vector store — In-memory store with cosine similarity search
• Retrieval engine — Top-K retrieval with relevance scoring
• Prompt assembler — Template-based prompt construction with context injection
• Pipeline orchestrator — Single RAGPipeline class ties everything together
• CLI + API — Use from terminal or import as a library
• Demo mode — Built-in sample docs to see it working instantly

Quick Start

Follow this guide to get RAG Pipeline Starter up and running in your environment.

Quick Start

# Run the built-in demo
python src/rag_pipeline.py --demo

# Ingest a directory and query
python src/rag_pipeline.py --ingest ./my-docs/ --query "How do I deploy?"

# Interactive mode
python src/rag_pipeline.py