Opik by Comet ML
Open-source LLM evaluation and tracing platform by Comet ML that is OpenTelemetry-compatible, self-hostable, and provides automated hallucination detection with annotation workflows and integrations for LangChain, LlamaIndex, and OpenAI.
Score Breakdown
⚙ Agent Friendliness
🔒 Security
Self-hosted deployments give full control over data residency; cloud version is SOC 2 compliant via Comet ML.
⚡ Reliability
Best When
You need an open-source, self-hostable LLM tracing and evaluation platform with first-class LangChain/LlamaIndex integration and OpenTelemetry compatibility.
Avoid When
You need a fully managed, zero-ops SaaS with guaranteed uptime SLAs and enterprise support contracts.
Use Cases
- • Trace LangChain or LlamaIndex agent runs end-to-end using native integrations with zero instrumentation code
- • Run automated hallucination detection on agent outputs using built-in Opik scoring metrics
- • Self-host the full evaluation stack on-premise to keep sensitive traces within your network boundary
- • Coordinate human annotation workflows to label agent traces for fine-tuning dataset creation
- • Ingest OpenTelemetry traces from any language runtime into a unified LLM observability dashboard
Not For
- • Teams that need a fully managed SaaS with enterprise SLAs without any self-hosting
- • Evaluation of non-LLM systems such as computer vision or tabular ML models
- • Real-time alerting and PagerDuty-style on-call integrations for production incidents
Interface
Authentication
API key required for Comet cloud; self-hosted deployments can be configured without auth for internal use.
Pricing
Apache 2.0 open source for self-hosted; Comet ML cloud offers a managed option with a free tier.
Agent Metadata
Known Gotchas
- ⚠ OpenTelemetry exporter requires manual OTLP endpoint configuration — default OTel exporters will not auto-discover Opik
- ⚠ Self-hosted Docker Compose setup requires persistent volume configuration or traces are lost on container restart
- ⚠ Hallucination detection metrics internally call an LLM; costs and latency depend on which model is configured as the judge
- ⚠ Project and workspace names are case-sensitive — agents using dynamic names may create duplicate workspaces silently
- ⚠ JavaScript SDK is less mature than Python SDK; some annotation and dataset features are Python-only
Alternatives
Full Evaluation Report
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Package Brief
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Scores are editorial opinions as of 2026-03-07.