Coordinate LLM observability, tracing, and evaluation across multi-framework deployments.
npx skills add https://github.com/akillness/jeo-skills --skill opik
Please help me install this Agent Skill. Skill: opik Source: https://github.com/akillness/jeo-skills/tree/main/.agent-skills/opik Command: npx skills add https://github.com/akillness/jeo-skills --skill opik
Opik provides end-to-end LLM observability, tracing, and evaluation, enabling teams to monitor, measure, and optimize LLM-driven applications across cloud, Docker, Kubernetes, and self-hosted environments.
Install the Opik Python SDK, configure a server, and enable tracing with native integrations or the @opik.track decorator.
High-intent search queries and answers about installing and using this skill.
LLM observability requires installing a Python or TypeScript SDK and configuring a server. You enable tracing via native integrations or the @opik.track decorator to monitor calls across multiple frameworks.
Yes, LLM-as-a-judge evaluation supports CI pipelines through experiment management. It provides metrics like Hallucination, Moderation, Answer Relevance, and Context Precision for automated testing.
Opik works natively with OpenAI, LangChain, and Gemini across 50+ integrations. It provides native SDKs for Python and TypeScript to enable tracing without changing existing framework logic.
Production monitoring guardrails use datasets, experiments, and online evaluation rules. These components enforce real-time constraints and monitor LLM behavior continuously in deployed environments.
Self-hosting LLM observability on Kubernetes is supported via Docker Compose or Kubernetes deployments. Configure the server infrastructure, then connect SDKs to route tracing data to your hosted instance.
Route-first LLM observability coordinates tracing and evaluation specifically for LLM calls, unlike standard monitoring. It captures multi-framework interactions and measures LLM-specific metrics like hallucination and context recall.
akillnessTrace, evaluate, and manage prompts for LLM applications via LangSmith SDKs.
tadod12Trace, evaluate, and monitor LLM applications with OpenTelemetry.
Orchestra-ResearchTrace, evaluate, and monitor LLM applications with OpenTelemetry.
LaurentPRAT-DBInstrument Python and TypeScript code with MLflow Tracing for LLM applications.
