Set up Langfuse local development workflow with hot reload and debugging. Use when developing LLM applications locally, debugging traces, or setting up a fast iteration loop with Langfuse. Trigger with phrases like "langfuse local dev", "langfuse development", "debug langfuse traces", "langfuse hot reload", "langfuse dev workflow".
Fast local development workflow with Langfuse tracing, immediate trace visibility, debug logging, and optional self-hosted local instance via Docker.
langfuse-install-auth setuptsx for hot reload (npm install -D tsx)# .env.local (git-ignored)
LANGFUSE_PUBLIC_KEY=pk-lf-dev-...
LANGFUSE_SECRET_KEY=sk-lf-dev-...
LANGFUSE_BASE_URL=https://cloud.langfuse.com
# Dev-specific settings
NODE_ENV=development
OPENAI_API_KEY=sk-...
// src/lib/langfuse-dev.ts
import { LangfuseSpanProcessor } from "@langfuse/otel";
import { NodeSDK } from "@opentelemetry/sdk-node";
import { LangfuseClient } from "@langfuse/client";
const isDev = process.env.NODE_ENV !== "production";
// Configure span processor with dev-friendly settings
const processor = new LangfuseSpanProcessor({
// In dev: flush immediately for instant visibility
...(isDev && { exportIntervalMillis: 1000, maxExportBatchSize: 1 }),
});
const sdk = new NodeSDK({ spanProcessors: [processor] });
sdk.start();
export const langfuse = new LangfuseClient();
// Print trace URLs in development
export function logTrace(traceId: string) {
if (isDev) {
const host = process.env.LANGFUSE_BASE_URL || "https://cloud.langfuse.com";
console.log(`\n Trace: ${host}/trace/${traceId}\n`);
}
}
// Clean shutdown
process.on("SIGINT", async () => {
await sdk.shutdown();
process.exit(0);
});
// src/lib/langfuse-dev.ts
import { Langfuse } from "langfuse";
const isDev = process.env.NODE_ENV !== "production";
export const langfuse = new Langfuse({
flushAt: isDev ? 1 : 15, // Immediate flush in dev
flushInterval: isDev ? 1000 : 10000,
...(isDev && { debug: true }), // Verbose SDK logging
});
export function logTraceUrl(trace: ReturnType<typeof langfuse.trace>) {
if (isDev) {
console.log(`\n Trace: ${trace.getTraceUrl()}\n`);
}
}
process.on("beforeExit", async () => {
await langfuse.shutdownAsync();
});
{
"scripts": {
"dev": "tsx watch --env-file=.env.local src/index.ts",
"dev:debug": "DEBUG=langfuse* tsx watch --env-file=.env.local src/index.ts",
"dev:trace": "LANGFUSE_DEBUG=true tsx watch --env-file=.env.local src/index.ts"
}
}
// src/lib/dev-utils.ts
import { observe, updateActiveObservation, startActiveObservation } from "@langfuse/tracing";
// Quick traced function wrapper with console output
export function devTrace<T extends (...args: any[]) => Promise<any>>(
name: string,
fn: T
): T {
return observe({ name }, async (...args: Parameters<T>) => {
updateActiveObservation({ input: args, metadata: { env: "dev" } });
const start = Date.now();
const result = await fn(...args);
const duration = Date.now() - start;
updateActiveObservation({ output: result });
console.log(` [${name}] ${duration}ms`);
return result;
}) as T;
}
// Quick debug trace -- fire-and-forget diagnostic trace
export async function debugTrace(name: string, data: Record<string, any>) {
await startActiveObservation(`debug/${name}`, async () => {
updateActiveObservation({
input: data,
metadata: { debug: true, timestamp: new Date().toISOString() },
});
});
}
// src/index.ts
import "dotenv/config";
import { initTracing, langfuse } from "./lib/langfuse-dev";
import { devTrace } from "./lib/dev-utils";
import OpenAI from "openai";
import { observeOpenAI } from "@langfuse/openai";
initTracing();
const openai = observeOpenAI(new OpenAI());
const askQuestion = devTrace("ask-question", async (question: string) => {
const response = await openai.chat.completions.create({
model: "gpt-4o-mini",
messages: [{ role: "user", content: question }],
});
return response.choices[0].message.content;
});
// Run on file save (tsx watch restarts automatically)
const answer = await askQuestion("What is Langfuse?");
console.log("Answer:", answer);
For offline development or data privacy:
# docker-compose.langfuse.yml
services:
langfuse:
image: langfuse/langfuse:latest
ports:
- "3000:3000"
environment:
- DATABASE_URL=${DATABASE_URL}
- NEXTAUTH_SECRET=${NEXTAUTH_SECRET}
- NEXTAUTH_URL=http://localhost:3000
- SALT=${SALT}
- ENCRYPTION_KEY=${ENCRYPTION_KEY}
depends_on:
- db
db:
image: postgres:16-alpine
environment:
POSTGRES_USER: postgres
POSTGRES_PASSWORD: ${POSTGRES_PASSWORD}
POSTGRES_DB: langfuse
volumes:
- langfuse-db:/var/lib/postgresql/data
volumes:
langfuse-db:
Before starting the stack, place unique local-only values for DATABASE_URL,
POSTGRES_PASSWORD, NEXTAUTH_SECRET, SALT, and ENCRYPTION_KEY in a git-ignored
.env file. Do not commit a database URI or reuse example or production values.
set -euo pipefail
# Start local Langfuse
docker compose -f docker-compose.langfuse.yml up -d
# Wait for startup, then visit http://localhost:3000
# Create account, project, and API keys in the local UI
# Update .env.local
echo 'LANGFUSE_BASE_URL=http://localhost:3000' >> .env.local
| Issue | Cause | Solution |
|-------|-------|----------|
| Traces delayed in dev | Batching still active | Set flushAt: 1 or exportIntervalMillis: 1000 |
| No debug output | Debug not enabled | Set LANGFUSE_DEBUG=true or DEBUG=langfuse* |
| Hot reload not working | Wrong watch command | Use tsx watch (not ts-node) |
| Local instance 502 | DB not ready | Wait 10s for PostgreSQL startup |
| Traces going to cloud | Wrong LANGFUSE_BASE_URL | Point to http://localhost:3000 |
Produce a local development receipt naming the SDK/runtime version, local or cloud host,
sample trace identifier, and debug setting used. Keep .env.local secret values and
local database credentials out of logs and commits.
Start the watch process, change a prompt or traced function, and verify the reload emits
one local trace. For self-hosting, bring up Compose, create a disposable project and key
in the local UI, then prove that the application points to localhost rather than cloud.
For SDK patterns and best practices, see langfuse-sdk-patterns.
下载完整 Skill 目录,包含 SKILL.md 及所有相关文件
Search for places (restaurants, cafes, etc.) via Google Places API proxy on localhost.
Interact with GitHub using the `gh` CLI. Use `gh issue`, `gh pr`, `gh run`, and `gh api` for issues, PRs, CI runs, and advanced queries.
Create or update AgentSkills. Use when designing, structuring, or packaging skills with scripts, references, and assets.
Start voice calls via the OpenClaw voice-call plugin.
Notion API for creating and managing pages, databases, and blocks.
Gemini CLI for one-shot Q&A, summaries, and generation.
Category:developer