#26 · Primary category: MLOps & Evaluation

RagaAI-Catalyst

agentic-ai agentic-ai-development agentneo agents ai-agent-monitoring ai-application-debugging ai-evaluation-tools ai-performance-optimization ai-tool-interaction-monitoring llm-testing llm-tracing llmops

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 analytics with timeline and execution graph view

Project last updated:02/11/26

GitHub Stars

16.2K

Forks

3.6K

Contributors

28

License

Apache-2.0

Why we included this project

Debugging a multi-agent system usually means staring at logs and guessing which step produced the bad output. RagaAI Catalyst is a Python SDK that traces the agent's steps, including the LLM calls and tool interactions behind them, then shows the results in a self-hosted dashboard with timeline and execution-graph views, so you can see where a run went wrong instead of inferring it. It also bundles evaluation tooling: define datasets, attach metrics like faithfulness and hallucination with configurable thresholds, and run experiments to compare versions. Prompt management, synthetic data generation, guardrails, and red-teaming round out the package, so the same toolchain covers both debugging a single run and ongoing quality checks. Teams building RAG pipelines or multi-agent systems who want tracing and evaluation without stitching several services together will find most of what they need here.

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