Claude-code-plugins-plus langfuse-install-auth

install

source · Clone the upstream repo

git clone https://github.com/jeremylongshore/claude-code-plugins-plus-skills

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/jeremylongshore/claude-code-plugins-plus-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/plugins/saas-packs/langfuse-pack/skills/langfuse-install-auth" ~/.claude/skills/jeremylongshore-claude-code-plugins-plus-langfuse-install-auth && rm -rf "$T"

manifest: plugins/saas-packs/langfuse-pack/skills/langfuse-install-auth/SKILL.md

Langfuse Install & Auth

Overview

Install the Langfuse SDK and configure authentication for LLM observability. Covers both the legacy

langfuse

package (v3) and the modern modular SDK (v4+/v5) built on OpenTelemetry.

Prerequisites

Node.js 18+ or Python 3.9+
Package manager (npm, pnpm, or pip)
Langfuse account (cloud at https://cloud.langfuse.com or self-hosted)
Public Key (
```
pk-lf-...
```
) and Secret Key (
```
sk-lf-...
```
) from project settings

Instructions

Step 1: Install SDK

TypeScript/JavaScript (v4+ modular SDK -- recommended):

set -euo pipefail
# Core client for prompt management, datasets, scores
npm install @langfuse/client

# Tracing (observe, startActiveObservation)
npm install @langfuse/tracing @langfuse/otel @opentelemetry/sdk-node

# OpenAI integration (drop-in wrapper)
npm install @langfuse/openai

# LangChain integration
npm install @langfuse/langchain

TypeScript/JavaScript (v3 legacy -- single package):

npm install langfuse

Python:

pip install langfuse

Step 2: Get API Keys

Open Langfuse dashboard (https://cloud.langfuse.com or your self-hosted URL)
Go to Settings > API Keys
Click Create new API key pair
Copy both keys:
- Public Key:
```
pk-lf-...
```
  (identifies your project)
- Secret Key:
```
sk-lf-...
```
  (grants write access -- keep secret)
Note the host URL (cloud default:
```
https://cloud.langfuse.com
```
)

Step 3: Configure Environment Variables

# Set environment variables
export LANGFUSE_PUBLIC_KEY="pk-lf-..."
export LANGFUSE_SECRET_KEY="sk-lf-..."
export LANGFUSE_BASE_URL="https://cloud.langfuse.com"

# Or create .env file
cat >> .env << 'EOF'
LANGFUSE_PUBLIC_KEY=pk-lf-your-public-key
LANGFUSE_SECRET_KEY=sk-lf-your-secret-key
LANGFUSE_BASE_URL=https://cloud.langfuse.com
EOF

Note: v4+ uses
LANGFUSE_BASE_URL
. Legacy v3 uses
LANGFUSE_HOST
or
LANGFUSE_BASEURL
.

Step 4: Initialize and Verify (v4+ Modular SDK)

// src/lib/langfuse.ts
import { LangfuseClient } from "@langfuse/client";
import { startActiveObservation } from "@langfuse/tracing";
import { LangfuseSpanProcessor } from "@langfuse/otel";
import { NodeSDK } from "@opentelemetry/sdk-node";

// 1. Register the OpenTelemetry span processor (once at app startup)
const sdk = new NodeSDK({
  spanProcessors: [new LangfuseSpanProcessor()],
});
sdk.start();

// 2. Create the Langfuse client for prompt/dataset/score operations
export const langfuse = new LangfuseClient({
  publicKey: process.env.LANGFUSE_PUBLIC_KEY,
  secretKey: process.env.LANGFUSE_SECRET_KEY,
  baseUrl: process.env.LANGFUSE_BASE_URL,
});

// 3. Verify connection
async function verify() {
  await startActiveObservation("connection-test", async (span) => {
    span.update({ input: { test: true } });
    span.update({ output: { status: "connected" } });
  });
  console.log("Langfuse connection verified. Check dashboard for trace.");
}

verify();

Step 5: Initialize and Verify (v3 Legacy SDK)

import { Langfuse } from "langfuse";

const langfuse = new Langfuse({
  publicKey: process.env.LANGFUSE_PUBLIC_KEY,
  secretKey: process.env.LANGFUSE_SECRET_KEY,
  baseUrl: process.env.LANGFUSE_HOST,
});

// Verify with a test trace
const trace = langfuse.trace({
  name: "connection-test",
  metadata: { test: true },
});

await langfuse.flushAsync();
console.log("Connected. Trace URL:", trace.getTraceUrl());

// Clean shutdown
process.on("beforeExit", async () => {
  await langfuse.shutdownAsync();
});

Step 6: Python Verification

from langfuse import Langfuse
import os

langfuse = Langfuse(
    public_key=os.environ["LANGFUSE_PUBLIC_KEY"],
    secret_key=os.environ["LANGFUSE_SECRET_KEY"],
    host=os.environ.get("LANGFUSE_HOST", "https://cloud.langfuse.com"),
)

# Test trace
trace = langfuse.trace(name="connection-test", metadata={"test": True})
langfuse.flush()
print(f"Connected. Trace: {trace.get_trace_url()}")

SDK Version Comparison

Feature	v3 ( `langfuse` )	v4+ ( `@langfuse/*` )
Package	Single `langfuse`	Modular: `@langfuse/client` , `@langfuse/tracing` , `@langfuse/otel`
Base URL env var	`LANGFUSE_HOST`	`LANGFUSE_BASE_URL`
Tracing	`langfuse.trace()`	`startActiveObservation()` / `observe()`
Client class	`Langfuse`	`LangfuseClient`
OpenAI wrapper	`observeOpenAI()` from `langfuse`	`observeOpenAI()` from `@langfuse/openai`
Foundation	Custom	OpenTelemetry

Error Handling

Error	Cause	Solution
`401 Unauthorized`	Invalid or expired API key	Re-check keys in Langfuse dashboard Settings > API Keys
`ECONNREFUSED`	Wrong host URL or server down	Verify `LANGFUSE_BASE_URL` / `LANGFUSE_HOST`
`Missing required configuration`	Env vars not loaded	Ensure `dotenv/config` imported at entry point
`Module not found`	Package not installed	Run `npm install` or `pip install` again
Using pk- key as secret	Keys swapped	Public key starts `pk-lf-` , secret starts `sk-lf-`

Resources

Next Steps

After auth is working, proceed to

langfuse-hello-world

for your first traced LLM call.