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@jsoma/n8n-nodes-opik

v0.1.17

Published

n8n community node for Comet Opik tracing, prompts, guardrails, and feedback.

Readme

n8n-nodes-opik

This community node lets you connect Comet Opik with your n8n workflows.

Opik is Comet’s open-source observability and evaluation platform for LLM- and agent-powered systems. It provides trace/span logging, prompt management, guardrails, and human/automatic feedback collection so you can understand and improve AI workflows.

n8n is a fair-code licensed workflow automation platform.

Installation Operations Credentials Compatibility Usage Resources Version history

Installation

Follow the installation guide in the n8n community nodes documentation.

Operations

The node exposes these Opik capabilities:

  • Trace – start a trace with rich input metadata and end it with output/error details.
  • Span – log nested spans (LLM/tool/agent/general) including token usage, metadata, and tags.
  • Prompt – fetch any prompt or a specific version from the Opik prompt library and see the resolved template immediately in the “Prompt Text” preview.
  • Guardrail – run PII detection or topic moderation checks and receive violations/redacted text.
  • Feedback – log numeric feedback for traces or spans (accuracy, relevance, quality, etc.).
  • Dataset – browse datasets and fetch dataset items (content) for replay/evaluation inside n8n.
  • Agent Logger – feed the JSON output of n8n’s AI Agent node and automatically create a trace plus spans based on intermediateSteps.

Credentials

Install the package:

npm install @jsoma/n8n-nodes-opik

Then create an Opik API credential with:

  • API URL – Defaults to https://www.comet.com/opik/api. Point this to your self-hosted base URL if needed (must include the /api suffix).
  • API Key – Required for Opik Cloud. You can generate one from the Opik UI (Settings → API Keys). Leave blank only if your self-hosted deployment allows anonymous requests.
  • Workspace Name – Required slug that appears after /opik/ in the URL (for example https://www.comet.com/opik/jsoma/...jsoma). Opik Cloud rejects requests without it.

The credential tester pings /v1/health to verify connectivity before you run workflows.

Compatibility

  • Requires n8n 1.60.0 or later (declarative HTTP nodes & n8n-node CLI).
  • Tested locally with Node 18 and n8n 1.60 dev server.

Usage

  1. Install the package following the community nodes installation guide.
  2. Add your Opik API credentials.
  3. Drop the Opik node into a workflow and choose the resource/operation you need. Trace and span inputs/metadata can be entered as key/value pairs or raw JSON, whichever is easier, and optional fields live under the “Options” section to keep the main form tidy.
  4. Chain multiple operations together when you want full observability (Start Trace → Log Spans → Check Guardrails → Log Feedback → End Trace).

Every operation returns the raw Opik API response so you can inspect IDs, metadata, or guardrail violations in downstream nodes.

Recommended trace/span workflow

To get the most out of Opik’s observability features:

  1. Start a trace at the beginning of the flow. The trace represents the entire run of your n8n workflow. Save the traceId (and the auto-generated threadId if you want to group multiple runs together).
  2. Log spans for meaningful steps. Every tool invocation, API request, or reasoning block can become a span. Use nested spans (parent/child) to show call hierarchies.
  3. Use the Opik Agent Logger for agent nodes. This companion node takes the JSON output of n8n’s AI Agent, generates a trace/thread ID if needed, and automatically emits spans for each intermediateStep plus an optional summary span. It’s the fastest way to capture all tool calls without wiring multiple span nodes.
  4. Attach guardrails and feedback. After spans exist you can run guardrail checks or log numeric feedback against either the trace or specific spans.
  5. Store and replay data with datasets. The dataset resource lets you list dataset items and loop through them in n8n—ideal for regression testing or replaying saved traces/spans.

Trace vs Thread vs Span:

  • A trace is one execution of your workflow.
  • A thread groups multiple traces that belong to the same session/conversation.
  • A span captures a single step inside a trace (LLM call, tool invocation, guardrail, etc.).
    The Agent Logger automates span creation for AI agents; for custom logic drop “Log Span” nodes wherever they make sense.

Resources

Version history

  • 0.1.0 – Initial release with trace, span, prompt, guardrail, and feedback operations.