RagaAI Catalyst is a Python SDK for observability, monitoring, and evaluation of LLM applications, particularly RAG and agentic systems. It provides tools for project and dataset management, evaluation, tracing, prompt management, synthetic data generation, guardrails, and red-teaming, aiming to streamline the development and safeguarding of LLM-powered products.

How It Works

The SDK offers a modular approach, allowing users to interact with specific components like Dataset, Evaluation, Tracer, PromptManager, SyntheticDataGeneration, GuardrailsManager, and RedTeaming. It leverages API keys for authentication and supports various LLM providers through configurations. Tracing can be enabled via context managers or explicit start/stop calls, capturing LLM, tool, and agent interactions. Evaluation involves defining metrics and schema mappings, while red-teaming uses provided descriptions and detectors to identify model vulnerabilities.

Quick Start & Requirements

• Install via pip: pip install ragaai-catalyst
• Requires authentication credentials (access key, secret key, base URL) obtained from the RagaAI platform.
• Detailed documentation is available for each module.

Highlighted Details

• Agentic Tracing: Specifically designed for multi-agent systems, tracking LLM interactions, tool usage, network activity, and user feedback.
• Guardrails: Allows defining custom guardrails with fail conditions and alternate responses, integrated with an GuardExecutor for runtime evaluation.
• Red-Teaming: Supports built-in and custom detectors, automatic test case generation, and mixed detector types for comprehensive model vulnerability scanning.
• Prompt Management: Facilitates prompt versioning, variable compilation, and direct integration with OpenAI and LiteLLM for prompt execution.

Maintenance & Community

• Information on contributors, sponsorships, or community channels (Discord/Slack) is not explicitly detailed in the provided README.

Licensing & Compatibility

• The README does not specify the license type or any compatibility notes for commercial use or closed-source linking.

Limitations & Caveats

• The setup requires obtaining API keys from the RagaAI platform, implying a dependency on their service. Specific hardware or OS requirements beyond standard Python environments are not mentioned.