Ragas Python Packages

lightrag-hku

[EMNLP2025] LightRAG: Simple and Fast Retrieval-Augmented Generation

jevals

Agent evals and guardrails as Jev decisions: one request per trace, a fraction of a cent, fast enough for the agent loop. Runs locally with Kev or Laya.

iris-vector-rag

Enterprise RAG pipelines with native IRIS vector search. 6 production implementations with RAGAS evaluation, LangChain, AWS/Azure configs. No external VectorDB required.

tunarag-python

TunaRAG is a Python package for tuning LangChain, LangGraph, and Google ADK RAG pipelines to balance answer quality, cost, and latency.

mutant-ai

Mutant is a red team and behavioral data generation library for LLMs, RAG pipelines, and AI Agents. It provides two powerful capabilities

rag-harness

⚡ CLI to Evaluate and Compare RAG systems with RAGAS-style scoring

monitor-aii

The Official Python SDK for Monitoring-Machines

lightrag-dembrane

[EMNLP2025] LightRAG: Simple and Fast Retrieval-Augmented Generation

rag-forge-core

Production-grade RAG pipelines with evaluation baked in

rag-forge-observability

Production-grade RAG pipelines with evaluation baked in

rag-forge-evaluator

Production-grade RAG pipelines with evaluation baked in

chunktuner

Benchmark chunking strategies for your RAG corpus. Get a recommended config. CLI, Python library, and MCP server.

faithgate

Fails your CI when your LLM app starts making things up. Local faithfulness regression gate — pytest for prompts.

faultmap

Automatically discover where and why your LLM is failing — embedding-space clustering + statistical hypothesis testing to surface input slices with elevated failure rates and audit test suite coverage gaps.

ragbrain

Memory for AI agents that keeps track of how facts change. Ask what is true now, what was true on any past date, or what your system believed before a correction arrived. Version history for facts, with citations.