Awesome AI Agents › Agent Monitoring Tools

raga-ai-hub/RagaAI-Catalyst

⭐ 16161 Python repository created 2024-08-26

RagaAI Catalyst is a Python SDK and comprehensive platform designed for observability, monitoring, and evaluation of Agent AI systems, particularly those involving large language models (LLMs) and multi-agentic frameworks. It provides extensive features for managing and optimizing LLM projects, including project management, dataset management, evaluation management, trace management, prompt management, synthetic data generation, and guardrail management. The platform supports detailed tracing and debugging of agents, LLMs, and tools, enabling users to monitor interactions, token usage, tool execution, network activities, API calls, user feedback, and agent decision-making processes. This observability is crucial for understanding, debugging, and improving AI agent performance. RagaAI Catalyst offers a self-hosted dashboard with advanced analytics, including timeline and execution graph views, to visualize and analyze the behavior and performance of AI agents. Users can create and manage projects, datasets, and experiments, and evaluate their applications using various metrics such as faithfulness and hallucination detection. The SDK facilitates synthetic data generation and red-teaming to test and safeguard LLM applications. It also includes guardrail management to enforce safety and operational constraints. The platform supports trace recording through a flexible tracer interface, allowing users to start and stop trace sessions programmatically or via context managers. Agentic tracing features provide auto-instrumentation capabilities to monitor complex multi-agent systems comprehensively. Prompt management tools help organize and utilize prompts efficiently within projects. Overall, RagaAI Catalyst is a powerful tool for developers and researchers working with AI agents and LLMs, providing essential tools for monitoring, debugging, evaluating, and improving AI-driven applications in a structured and scalable manner.

https://github.com/raga-ai-hub/RagaAI-Catalyst

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