opik

name	opik
description	Reference for the Opik SDK — tracing, span types, framework integrations, threads, and the prompt library (Python, TypeScript, REST). Use for "what span types exist", "how do I flush", "track_openai", "add OpikTracer", "version a prompt". To instrument a repo end to end, use the `opik-instrument` skill.
metadata	{"last_updated":"2026-07-27","source_commit":"TODO — pin to the Opik release this was verified against (OPIK-7471)"}

Opik SDK Reference

Opik is an open-source LLM observability platform. This skill is a reference for the SDK. To instrument a codebase step by step (detect frameworks, add config, emit and verify a trace), use the task-shaped opik-instrument skill.

Core concepts

A trace is one execution path (one request → one response). Spans are the operations inside it and form a hierarchy.

Span types — the ONLY valid values

Type	Use for
general	orchestration, agent entry points
llm	model calls
tool	tools, retrieval, API / DB calls
guardrail	safety / validation checks

Do NOT use retrieval or any other value.

Python — tracing

import opik

@opik.track(name="agent", type="general")
def agent(query: str) -> str:
    return generate(retrieve(query))

@opik.track(type="tool")
def retrieve(query): ...

@opik.track(type="llm")
def generate(ctx): ...

opik.flush_tracker()   # required in scripts

TypeScript — tracing

import { Opik } from "opik";
const client = new Opik({ projectName: "my-project" });

const trace = client.trace({ name: "agent", input: { query } });
const span = trace.span({ name: "llm-call", type: "llm" });
span.end({ output });
trace.end({ output });
await client.flush();

Framework integrations

Prefer an integration over manual @opik.track — integrations capture tokens, model, and cost automatically. Patterns (full list in references/integrations.md):

• wrap-the-client — track_openai(OpenAI()), track_anthropic(...)
• global-enable — track_crewai(crew=crew)
• callback — dspy.configure(callbacks=[OpikCallback()])
• tracer — OpikTracer() for LangChain / LangGraph / LlamaIndex
• agent-specific — track_adk_agent_recursive(agent, OpikTracer())

LiteLLM inside @opik.track (common trap)

If code uses litellm and you add @opik.track, pass current_span_data via metadata on every completion call — otherwise OpikLogger emits orphaned top-level traces instead of nesting under your span.

from opik.opik_context import get_current_span_data

@opik.track
def call_llm(messages):
    return litellm.completion(
        model="gpt-4o", messages=messages,
        metadata={"opik": {"current_span_data": get_current_span_data()}},
    )

Threads (conversations)

Group turns with thread_id — one turn = one trace, shared thread_id = one thread. Use for chat / multi-turn; skip for single-shot.

@opik.track(entrypoint=True)
def handle(session_id: str, message: str) -> str:
    opik.update_current_trace(thread_id=session_id)
    return reply(message)

Prompt library

Version prompts with client.get_prompt / create_prompt (chat variants: get_chat_prompt / create_chat_prompt). Store model + temperature in the prompt metadata so they version with the text. Call get_prompt inside a @opik.track function so the version links to the trace.

@opik.track(entrypoint=True)
def run(question: str) -> str:
    p = client.get_prompt(name="system") or client.create_prompt(
        name="system",
        prompt="You help with {{product}}.",
        metadata={"model": "gpt-4o", "temperature": 0.7},
    )
    return llm(p.format(product="Opik"), model=p.metadata["model"])

Anti-patterns

Anti-pattern	Fix
span type retrieval / custom	use tool (or general)
get_prompt outside @opik.track	fetch inside — else no trace link
deprecated opik.Prompt / opik.Config	use client.get_prompt / config file
litellm without current_span_data	pass it — else orphaned traces
no flush in scripts	opik.flush_tracker() / await client.flush()

References

Topic	File
Python SDK (async, distributed, context)	references/tracing-python.md
TypeScript SDK	references/tracing-typescript.md
REST API	references/tracing-rest-api.md
All integrations	references/integrations.md
Core concepts (traces, spans, threads)	references/observability.md
Best practices (lifecycle, monitoring, anti-patterns)	references/best-practices.md
Agent architecture, reliability, security	references/agent-patterns.md
Production monitoring, alerts, guardrails	references/production.md
Evaluation datasets & test suites (reference)	references/evaluation-datasets.md, references/evaluation-test-suites.md

To build and run an evaluation, use the opik-evaluate skill. For repo instrumentation and config, use the opik-instrument skill.