Capability · Framework — observability
Comet LLM / Opik-Comet
Comet is a mature ML experiment tracking platform that expanded into LLMOps with CometLLM (prompt + response logging) and then acquired / merged with Opik, the dedicated LLM tracing product. For teams already using Comet for model training runs, this gives a single pane of glass across classic ML and LLM workflows — dashboards, artifacts, compare views — without buying a second SaaS.
Framework facts
- Category
- observability
- Language
- Python / TypeScript
- License
- Apache-2.0 (Opik OSS) / Proprietary SaaS (Comet)
Install
pip install opik
# or legacy
pip install comet-llm Quickstart
import opik
from opik.integrations.openai import track_openai
import openai
opik.configure(api_key='COMET_KEY')
client = track_openai(openai.OpenAI())
client.chat.completions.create(model='gpt-4o', messages=[{'role':'user','content':'hi'}]) Alternatives
- Weights & Biases Weave
- MLflow LLM
- Langfuse — OSS
Frequently asked questions
CometLLM or Opik?
Opik is the current direction — OSS, richer tracing, better agent support. CometLLM is still available for users on legacy pipelines but new projects should start with Opik.
Can I use Opik without Comet?
Yes. Opik is Apache-2.0 and self-hostable; Comet's SaaS just hosts the same server with added team features and integrations with Comet experiments.
Sources
- Opik docs — accessed 2026-04-20
- Comet LLMOps — accessed 2026-04-20