by raga-ai-hub · Agent Tool · ★ 16.1k
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RagaAI Catalyst RagaAI Catalyst is a comprehensive platform designed to enhance the management and optimization of LLM projects. It offers a wide range of features, including project management, dataset management, evaluation management, trace management, prompt management, synthetic data generation, and guardrail management. These functionalities enable you to efficiently evaluate, and safeguard your LLM applications. Table of Contents RagaAI Catalyst Installation Configuration Usage Project Management Dataset Management Evaluation Management Trace Management Agentic Tracing Prompt Management Synthetic Data Generation Guardrail Management Red-teaming Installation To install RagaAI Catalyst, you can use pip: Configuration Before using RagaAI Catalyst, you need to set up your credentials. You can do this by setting envir
| Stars | 16,143 |
| Forks | 3,570 |
| Language | Python |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 72.808264593832/100 |
| Open Issues | 33 |
| Last Updated | 2026-02-11 |
| Created | 2024-08-26 |
| Platforms | python |
| Est. Tokens | ~3792k |
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RagaAI-Catalyst is Python SDK for Agent AI Observability, Monitoring and Evaluation Framework. Includes features like agent, llm and tools tracing, debugging multi-agentic system, self-hosted dashboard and advanced anal. It is categorized as a Agent Tool with 16.1k GitHub stars.
RagaAI-Catalyst is primarily written in Python. It covers topics such as agentic-ai, agentic-ai-development, agentneo.
You can find installation instructions and usage details in the RagaAI-Catalyst GitHub repository at github.com/raga-ai-hub/RagaAI-Catalyst. The project has 16.1k stars and 3570 forks, indicating an active community.
RagaAI-Catalyst is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to RagaAI-Catalyst on Agent Skills Hub include composio, ruflo, valuecell. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.