giskard-oss vs RAG_Techniques
A neutral, constraint-first comparison - live GitHub stats and typed relationships, not marketing.
| giskard-oss | RAG_Techniques | |
|---|---|---|
| Tagline | Eval and test library for AI agents | Repository showcasing advanced techniques for Retrieval-Augmented Generation (RAG) systems. |
| Stars | 5.5k | 28k |
| Forks | 481 | 3.5k |
| Open issues | 73 | 16 |
| Language | Python | Jupyter Notebook |
| License | Apache-2.0 | Other |
| Last pushed | Jul 7, 2026 | Jul 4, 2026 |
| Categories | Evaluation & Observability | Data & Retrieval, LLM Frameworks |
giskard-oss
Giskard is an open-source Python library designed to evaluate and test agentic systems such as AI agents. It supports dynamic multi-turn testing with enhanced security and RAG evaluation features.
Python
RAG_Techniques
This repository contains tutorials and runnable notebooks that cover a range of RAG techniques, from foundational concepts to cutting-edge methods. It aims to provide detailed insights into building more accurate and context-rich retrieval systems.
Jupyter Notebook