Back to directory

PyRAG Core

An open-source, Python-first, API-driven Retrieval-Augmented Generation platform with FastAPI endpoints, LangGraph-native agents, a pluggable vector store, and support for several LLM providers.

PyRAG Core

PyRAG Core is a production-oriented, open-source RAG platform built around a FastAPI and Pydantic v2 API, LangGraph and LangChain agents, Celery and Redis for queuing, PostgreSQL with SQLAlchemy for relational data, and a pluggable vector store defaulting to Qdrant but also supporting Weaviate, Milvus, pgvector, and Elasticsearch. It supports multiple LLM providers, including OpenAI, Anthropic, Gemini, OpenRouter, Ollama, and vLLM, and uses MinIO for object storage and Langfuse for observability.

Local development runs entirely through Docker Compose and a Makefile: cloning the repository, syncing dependencies with uv, configuring environment variables, starting infrastructure containers, running database migrations, and starting the API and an optional Streamlit developer UI that offers a lightweight playground for the parsing, cleaning, and chunking pipeline stages without needing the full database or object storage running.

The project documents its architecture, data model, security model, and known limitations in a separate architecture document.

More in RAG

See all 540
  • ai·rete·rag

    ai-rete-rag.com

    A platform that pairs a Rete rule engine with retrieval-augmented generation, so deterministic rules decide an outcome and grounded retrieval explains the decision in plain language.

  • Xtriever

    github.com

    A hybrid retrieval engine for retrieval-augmented generation, written in Rust to run on-device on a phone or a laptop, combining lexical BM25 search, dense embedding search, reciprocal-rank fusion and cross-encoder re-ranking with no server.

  • FileFlux

    github.com

    A .NET library that turns PDF, DOCX, HWP and other documents into optimized chunks for RAG systems, through a five-stage pipeline built on high-performance Rust FFI readers.