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Langfuse Install Auth

DevOps & Security
langfuse-install-auth

Langfuse Install Auth is an Agent Skill for devops & security published in the Dicklesworthstone/pi_agent_rust repository on GitHub: a SKILL.md instruction file an AI agent can load to do this task.

Install and configure Langfuse SDK authentication for LLM observability. Use when setting up a new Langfuse integration, configuring API keys, or initializing Langfuse tracing in your project. Trigger with phrases like "install langfuse", "setup langfuse", "langfuse auth", "configure langfuse API key", "langfuse tracing setup".

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How to use this skill

Bring this guide into your coding agent with a prompt tailored to the tool you use.

  1. Open your project in Codex.
  2. Copy and paste the prompt below.
  3. Review files and risks before approving any action.
Prompt to paste
Inspect the Agent Skill at https://github.com/Dicklesworthstone/pi_agent_rust/blob/HEAD/tests/ext_conformance/artifacts/plugins-community/plugins/saas-packs/langfuse-pack/skills/langfuse-install-auth/SKILL.md and all supporting files. Report provenance, permissions, scripts, dependencies, and security risks. Propose an exact installation into .agents/skills/langfuse-install-auth, but wait for my approval before writing files or running scripts.

Copying this prompt does not install or run the skill. Review third-party files before use.

Langfuse Install & Auth

Overview

Set up Langfuse SDK and configure authentication for LLM observability and tracing.

Prerequisites

  • Node.js 18+ or Python 3.9+
  • Package manager (npm, pnpm, or pip)
  • Langfuse account (cloud or self-hosted)
  • Public and Secret keys from Langfuse dashboard

Instructions

Step 1: Install SDK

# Node.js / TypeScript
npm install langfuse
# or
pnpm add langfuse

# Python
pip install langfuse

Step 2: Get API Keys

  1. Go to Langfuse dashboard (https://cloud.langfuse.com or your self-hosted instance)
  2. Navigate to Settings -> API Keys
  3. Create new API key pair (Public Key + Secret Key)
  4. Note your host URL (cloud: https://cloud.langfuse.com)

Step 3: Configure Authentication

# Set environment variables
export LANGFUSE_PUBLIC_KEY="pk-lf-..."
export LANGFUSE_SECRET_KEY="sk-lf-..."
export LANGFUSE_HOST="https://cloud.langfuse.com"  # or self-hosted URL

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

Step 4: Verify Connection

// TypeScript verification
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,
});

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

// Flush to ensure data is sent
await langfuse.flushAsync();
console.log("Langfuse connection successful! Check dashboard for trace.");
# Python verification
from langfuse import Langfuse
import os

langfuse = Langfuse(
    public_key=os.environ.get("LANGFUSE_PUBLIC_KEY"),
    secret_key=os.environ.get("LANGFUSE_SECRET_KEY"),
    host=os.environ.get("LANGFUSE_HOST"),
)

# Create a test trace
trace = langfuse.trace(name="connection-test", metadata={"test": True})

# Flush to ensure data is sent
langfuse.flush()
print("Langfuse connection successful! Check dashboard for trace.")

Output

  • Installed SDK package in node_modules or site-packages
  • Environment variables or .env file with API credentials
  • Successful connection verification trace visible in dashboard

Error Handling

ErrorCauseSolution
Invalid API KeyIncorrect or revoked keyVerify keys in Langfuse dashboard
Connection RefusedWrong host URLCheck LANGFUSE_HOST is correct
Network ErrorFirewall blockingEnsure outbound HTTPS to Langfuse host
Module Not FoundInstallation failedRun npm install or pip install again
401 UnauthorizedKeys don't match projectEnsure keys are from same project

Examples

TypeScript Initialization with Options

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,
  // Optional configuration
  flushAt: 15,        // Flush after 15 events (default: 15)
  flushInterval: 10000, // Flush every 10 seconds (default: 10000ms)
  requestTimeout: 10000, // Request timeout (default: 10000ms)
  enabled: process.env.NODE_ENV === "production", // Disable in dev
});

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

Python Initialization with Options

from langfuse import Langfuse
import os

langfuse = Langfuse(
    public_key=os.environ.get("LANGFUSE_PUBLIC_KEY"),
    secret_key=os.environ.get("LANGFUSE_SECRET_KEY"),
    host=os.environ.get("LANGFUSE_HOST"),
    # Optional configuration
    flush_at=15,           # Flush after 15 events
    flush_interval=10.0,   # Flush every 10 seconds
    enabled=os.environ.get("NODE_ENV") == "production",
)

# Register shutdown handler
import atexit
atexit.register(langfuse.flush)

OpenAI Integration (Automatic Tracing)

import { observeOpenAI } from "langfuse";
import OpenAI from "openai";

const openai = observeOpenAI(new OpenAI(), {
  clientInitParams: {
    publicKey: process.env.LANGFUSE_PUBLIC_KEY,
    secretKey: process.env.LANGFUSE_SECRET_KEY,
    baseUrl: process.env.LANGFUSE_HOST,
  },
});

// All OpenAI calls are now automatically traced
const response = await openai.chat.completions.create({
  model: "gpt-4",
  messages: [{ role: "user", content: "Hello!" }],
});

Resources

Next Steps

After successful auth, proceed to langfuse-hello-world for your first trace.