Opik

Opik is an open-source platform designed to help developers evaluate, test, and monitor large language model (LLM) applications throughout their entire lifecycle. Built by Comet ML, it provides comprehensive tracing and observability capabilities that enable teams to debug, analyze, and optimize their AI-powered applications with confidence.

The platform offers a robust set of features for LLM development and production monitoring:

• End-to-End Tracing allows developers to capture and visualize the complete execution flow of LLM applications, including all prompts, responses, and intermediate steps for thorough debugging and analysis.

• Evaluation Framework provides built-in metrics and custom evaluation capabilities to assess LLM output quality, including hallucination detection, answer relevance, and context precision scoring.

• Production Monitoring enables real-time tracking of LLM application performance in production environments, helping teams identify issues, track costs, and maintain quality at scale.

• Experiment Tracking lets developers compare different prompts, models, and configurations side-by-side to optimize application performance systematically.

• Dataset Management supports creating and managing evaluation datasets for consistent testing and benchmarking of LLM applications over time.

• Integration Support works seamlessly with popular LLM frameworks including LangChain, LlamaIndex, OpenAI, and other major providers through simple SDK integrations.

• Collaborative Features enable teams to share traces, evaluations, and insights across the organization for better collaboration and knowledge sharing.

To get started with Opik, developers can install the Python SDK via pip and begin instrumenting their LLM applications with just a few lines of code. The platform supports both self-hosted deployments through Docker and a managed cloud option for teams that prefer a hosted solution. Traces are automatically captured and can be viewed in the Opik dashboard, where teams can analyze performance, run evaluations, and monitor their applications in production.