Opik — Observability for LLM Agents

Integrating with Opik always means adding all three components unless the user explicitly asks for only one:

1. Tracing — instrument LLM calls with the appropriate integration or @opik.track
2. Entrypoint — mark the top-level function with entrypoint=True for Local Runner and UI integration
3. Agent Configuration — externalize all tunable parameters into opik.Config: model names, temperatures, top_p, max_tokens, all prompts and prompt templates, and any other runtime parameters the user may want to compare or optimize

Setup

Environment Config Decision Tree

Before adding Opik config, inspect the project's existing config approach. Follow this decision tree exactly:

1. Check for existing .env / .env.local files and dotenv usage in code.

   • If the project loads a .env file (via python-dotenv, dotenv, or framework auto-loading): append OPIK_API_KEY and OPIK_WORKSPACE to that same file. Do NOT create a separate config file.
   • If there is a .env.example or .env.sample: also update it with the new Opik vars (using placeholder values) so future developers know which vars are needed.

2. If no .env file exists: