rag-python

Production-grade Retrieval-Augmented Generation (RAG) for Python — ingest documents, ask questions, get grounded answers with multi-LLM support, hybrid search, streaming, and guardrails.

pip install rag-python
export OPENAI_API_KEY=sk-...
rag-python ingest ./docs --reindex
rag-python query "What is our leave policy?"

Author: Raghav Singla · Repo: github.com/RaghavOG/rag-python

Why rag-python?

Install

pip install rag-python

Quickstart (Python)

from rag_python import RAG

rag = RAG(llm_model="gpt-4o-mini")
rag.ingest(["./data"], reindex=True)

answer = rag.query("How many days of annual leave?")
print(answer.text)
print(answer.sources)

Streaming

stream = rag.query_stream("How many days of annual leave?")
for token in stream:
    print(token, end="", flush=True)
print(stream.result.evaluation)

Hybrid search + metadata filter

rag = RAG(
    retriever="hybrid",  # pip install rag-python[hybrid]
    metadata_filter={"filename": "leave-policy.pdf"},
)
rag.ingest(["./policies/"])
print(rag.query("annual leave policy").text)

Quickstart (CLI)

export OPENAI_API_KEY=sk-...

rag-python ingest ./data --reindex
rag-python query "How many days of annual leave?"
rag-python query "PTO policy" --stream -v
rag-python query "benefits" --retriever hybrid

# Built-in terminal docs
rag-python docs quickstart
rag-python docs --list
rag-python --help

Documentation

In the terminal: rag-python docs [topic] — topics: quickstart, install, cli, config, providers, features

Environment variables

See Configuration and .env.example.

Project layout

src/rag_python/     # pip install rag-python → import rag_python
  client.py         # RAG, RAGAnswer, query_stream
  rag_pipeline.py   # ingest / query pipeline
  providers/        # OpenAI, Azure, Anthropic, Gemini, Ollama, local
docs/               # User documentation (linked from PyPI README)
tests/
examples/

License

MIT © Raghav Singla