Kenosis01/TinyRag
TinyRag is a minimal Python library for retrieval-augmented generation. It offers easy document ingestion, automatic text extraction, embedding generation, and retrieval with vector stores. Designed for quick setup and flexible provider configuration, TinyRag enables fast, contextual responses from language models.
Supports function-level codebase indexing across 7+ programming languages and plugs into multiple vector store backends (Faiss, ChromaDB, Pickle, in-memory), allowing developers to choose storage trade-offs. Operates entirely offline using all-MiniLM-L6-v2 embeddings by default, with optional AI provider integration (OpenAI, Azure, Anthropic, local models) for augmented chat without mandatory API keys.
No commits in the last 6 months. Available on PyPI.
Stars
4
Forks
1
Language
Python
License
MIT
Category
Last pushed
Aug 23, 2025
Monthly downloads
55
Commits (30d)
0
Dependencies
8
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/rag/Kenosis01/TinyRag"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
OpenBMB/UltraRAG
A Low-Code MCP Framework for Building Complex and Innovative RAG Pipelines
AnkitNayak-eth/EpsteinFiles-RAG
A RAG pipeline implementation built on the 'Epstein Files 20K' dataset from Hugging Face (Teyler).
Quansight/ragna
RAG orchestration framework ⛵️
microsoft/rag-time
RAG Time: A 5-week Learning Journey to Mastering RAG
microsoft/rag-experiment-accelerator
The RAG Experiment Accelerator is a versatile tool designed to expedite and facilitate the...