---
title: Observability and Tracing for Langflow
description: Enhance your Langflow applications with open-source observability and tracing using Langfuse. Automatically capture detailed traces and metrics for every request to optimize and debug your Langchain application flows.
sidebarTitle: Langflow
logo: /images/integrations/langflow_icon.svg
logoAppearance: dark
---

# ⛓️ Langflow Integration

**[Langflow](https://www.langflow.org/)** ([GitHub](https://github.com/logspace-ai/langflow)) is a UI for LangChain, designed with react-flow to provide an effortless way to experiment and prototype flows.

With the native integration (since langflow v1.0.17), you can use Langflow to quickly create complex LLM applications in no-code and then use Langfuse to monitor and improve them.

## Integration

<iframe
  width="100%"
  className="aspect-video rounded mt-10"
  src="https://www.youtube-nocookie.com/embed/SA9gGbzwNGU?si=J_J85tcrlCsdUwo_"
  title="YouTube video player"
  frameborder="0"
  allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
  referrerpolicy="strict-origin-when-cross-origin"
  allowFullScreen
></iframe>
_[Video](https://www.youtube.com/watch?v=SA9gGbzwNGU) guide on how to integrate
Langflow with Langfuse (published by Langflow)_

<Steps>

### Get Langfuse API keys

<Tabs items={["Langfuse Cloud", "Local or self-hosted"]}>
<Tab>

1. Create account and project on
   [cloud.langfuse.com](https://cloud.langfuse.com/auth/sign-up)
2. Copy API keys for your
   project

</Tab>
<Tab>

1. Follow [instructions](/docs/get-started/) on self-hosting or local setups
2. Copy API keys for your
   project

</Tab>
</Tabs>

### Setup Langflow

<Tabs items={["pip install langflow", "Docker"]}>
<Tab>

```sh
# API keys from project settings in Langfuse
export LANGFUSE_SECRET_KEY=sk-lf...
export LANGFUSE_PUBLIC_KEY=pk-lf...

export LANGFUSE_HOST="https://cloud.langfuse.com"  # 🇪🇺 for EU data region
# export LANGFUSE_HOST="https://cloud.langfuse.com" # 🇺🇸 for US data region
# export LANGFUSE_HOST="http://localhost:3000" # 🏠 for self-hosters

# Install Langflow
pip install langflow

# Start Langflow in the same terminal or environment where you set the environment variables:
python -m langflow run
```

Alternatively, you can run the Langflow CLI command with the environment variables set:

```
LANGFUSE_SECRET_KEY=secret_key LANGFUSE_PUBLIC_KEY=public_key LANGFUSE_HOST="http://localhost:3000" langflow
```

</Tab>
<Tab>

Clone the [Langflow repository](https://github.com/logspace-ai/langflow)

```sh
git clone https://github.com/logspace-ai/langflow.git
cd langflow
```

Add the environment variables to `docker_example/docker-compose.yml`

```diff
version: '3'

services:
  langflow:
    build:
      context: .
      dockerfile: Dockerfile
    ports:
      - "7860:7860"
    environment:
+     - LANGFUSE_SECRET_KEY=secret_key
+     - LANGFUSE_PUBLIC_KEY=public_key
+     - LANGFUSE_HOST="https://cloud.langfuse.com"
    command: langflow run --host 0.0.0.0
```

Run Langflow

```sh
cd docker_example
docker-compose up --build
```

</Tab>
</Tabs>

### See your traces in Langfuse

Now, when you use Langflow's chat or API, you can view the trace of your conversations in Langfuse.

![Langflow traces in Langfuse](/images/blog/langflow-langfuse/langflow-example-trace.png)

_[Example Langflow trace in the Langfuse UI](https://cloud.langfuse.com/project/cm0nywmaa005c3ol2msoisiho/traces/f016ae6d-4527-43f5-93ba-9d78388cd3d9?timestamp=2024-11-15T10%3A22%3A56.378Z&observation=c3680212-31f0-46e2-9310-add4352e4cc7)_

</Steps>

## Running Langfuse and Langflow with Docker Compose

If you prefer to self-host Langfuse, you can run both services using Docker Compose. By combining the two docker-compose files, you can streamline the networking between them.

```diff
version: "3.5"

services:
  # Adapted from https://github.com/logspace-ai/langflow/blob/dev/docker_example/docker-compose.yml
  langflow:
    build:
      context: .
      dockerfile: Dockerfile
    ports:
      - "7860:7860"
    environment:
+     # Tokens are to be created in Langfuse, then copy-pasted here. Then restart docker-compose.
+     - LANGFUSE_SECRET_KEY=sk-lf-...
+     - LANGFUSE_PUBLIC_KEY=pk-lf-...
+     - LANGFUSE_HOST="http://langfuse-server:3000"
    command: langflow run --host 0.0.0.0

  # https://github.com/langfuse/langfuse/blob/main/docker-compose.yml
  langfuse-worker:
    image: docker.langfuse.com/langfuse/langfuse-worker:4
    restart: always
    depends_on: &langfuse-depends-on
      postgres:
        condition: service_healthy
      minio:
        condition: service_healthy
      redis:
        condition: service_healthy
      clickhouse:
        condition: service_healthy
    ports:
      - 127.0.0.1:3030:3030
    environment: &langfuse-worker-env
      NEXTAUTH_URL: http://localhost:3000
      DATABASE_URL: postgresql://postgres:postgres@postgres:5432/postgres # CHANGEME
      SALT: "mysalt" # CHANGEME
      ENCRYPTION_KEY: "0000000000000000000000000000000000000000000000000000000000000000" # CHANGEME: generate via `openssl rand -hex 32`
      TELEMETRY_ENABLED: ${TELEMETRY_ENABLED:-true}
      LANGFUSE_ENABLE_EXPERIMENTAL_FEATURES: ${LANGFUSE_ENABLE_EXPERIMENTAL_FEATURES:-true}
      CLICKHOUSE_MIGRATION_URL: ${CLICKHOUSE_MIGRATION_URL:-clickhouse://clickhouse:9000}
      CLICKHOUSE_URL: ${CLICKHOUSE_URL:-http://clickhouse:8123}
      CLICKHOUSE_USER: ${CLICKHOUSE_USER:-clickhouse}
      CLICKHOUSE_PASSWORD: ${CLICKHOUSE_PASSWORD:-clickhouse} # CHANGEME
      CLICKHOUSE_CLUSTER_ENABLED: ${CLICKHOUSE_CLUSTER_ENABLED:-false}
      LANGFUSE_S3_EVENT_UPLOAD_BUCKET: ${LANGFUSE_S3_EVENT_UPLOAD_BUCKET:-langfuse}
      LANGFUSE_S3_EVENT_UPLOAD_REGION: ${LANGFUSE_S3_EVENT_UPLOAD_REGION:-auto}
      LANGFUSE_S3_EVENT_UPLOAD_ACCESS_KEY_ID: ${LANGFUSE_S3_EVENT_UPLOAD_ACCESS_KEY_ID:-minio}
      LANGFUSE_S3_EVENT_UPLOAD_SECRET_ACCESS_KEY: ${LANGFUSE_S3_EVENT_UPLOAD_SECRET_ACCESS_KEY:-miniosecret} # CHANGEME
      LANGFUSE_S3_EVENT_UPLOAD_ENDPOINT: ${LANGFUSE_S3_EVENT_UPLOAD_ENDPOINT:-http://minio:9000}
      LANGFUSE_S3_EVENT_UPLOAD_FORCE_PATH_STYLE: ${LANGFUSE_S3_EVENT_UPLOAD_FORCE_PATH_STYLE:-true}
      LANGFUSE_S3_EVENT_UPLOAD_PREFIX: ${LANGFUSE_S3_EVENT_UPLOAD_PREFIX:-events/}
      LANGFUSE_S3_MEDIA_UPLOAD_BUCKET: ${LANGFUSE_S3_MEDIA_UPLOAD_BUCKET:-langfuse}
      LANGFUSE_S3_MEDIA_UPLOAD_REGION: ${LANGFUSE_S3_MEDIA_UPLOAD_REGION:-auto}
      LANGFUSE_S3_MEDIA_UPLOAD_ACCESS_KEY_ID: ${LANGFUSE_S3_MEDIA_UPLOAD_ACCESS_KEY_ID:-minio}
      LANGFUSE_S3_MEDIA_UPLOAD_SECRET_ACCESS_KEY: ${LANGFUSE_S3_MEDIA_UPLOAD_SECRET_ACCESS_KEY:-miniosecret} # CHANGEME
      LANGFUSE_S3_MEDIA_UPLOAD_ENDPOINT: ${LANGFUSE_S3_MEDIA_UPLOAD_ENDPOINT:-http://localhost:9090}
      LANGFUSE_S3_MEDIA_UPLOAD_FORCE_PATH_STYLE: ${LANGFUSE_S3_MEDIA_UPLOAD_FORCE_PATH_STYLE:-true}
      LANGFUSE_S3_MEDIA_UPLOAD_PREFIX: ${LANGFUSE_S3_MEDIA_UPLOAD_PREFIX:-media/}
      LANGFUSE_S3_BATCH_EXPORT_ENABLED: ${LANGFUSE_S3_BATCH_EXPORT_ENABLED:-false}
      LANGFUSE_S3_BATCH_EXPORT_BUCKET: ${LANGFUSE_S3_BATCH_EXPORT_BUCKET:-langfuse}
      LANGFUSE_S3_BATCH_EXPORT_PREFIX: ${LANGFUSE_S3_BATCH_EXPORT_PREFIX:-exports/}
      LANGFUSE_S3_BATCH_EXPORT_REGION: ${LANGFUSE_S3_BATCH_EXPORT_REGION:-auto}
      LANGFUSE_S3_BATCH_EXPORT_ENDPOINT: ${LANGFUSE_S3_BATCH_EXPORT_ENDPOINT:-http://minio:9000}
      LANGFUSE_S3_BATCH_EXPORT_EXTERNAL_ENDPOINT: ${LANGFUSE_S3_BATCH_EXPORT_EXTERNAL_ENDPOINT:-http://localhost:9090}
      LANGFUSE_S3_BATCH_EXPORT_ACCESS_KEY_ID: ${LANGFUSE_S3_BATCH_EXPORT_ACCESS_KEY_ID:-minio}
      LANGFUSE_S3_BATCH_EXPORT_SECRET_ACCESS_KEY: ${LANGFUSE_S3_BATCH_EXPORT_SECRET_ACCESS_KEY:-miniosecret} # CHANGEME
      LANGFUSE_S3_BATCH_EXPORT_FORCE_PATH_STYLE: ${LANGFUSE_S3_BATCH_EXPORT_FORCE_PATH_STYLE:-true}
      LANGFUSE_INGESTION_QUEUE_DELAY_MS: ${LANGFUSE_INGESTION_QUEUE_DELAY_MS:-}
      LANGFUSE_INGESTION_CLICKHOUSE_WRITE_INTERVAL_MS: ${LANGFUSE_INGESTION_CLICKHOUSE_WRITE_INTERVAL_MS:-}
      REDIS_HOST: ${REDIS_HOST:-redis}
      REDIS_PORT: ${REDIS_PORT:-6379}
      REDIS_AUTH: ${REDIS_AUTH:-myredissecret} # CHANGEME
      REDIS_TLS_ENABLED: ${REDIS_TLS_ENABLED:-false}
      REDIS_TLS_CA: ${REDIS_TLS_CA:-/certs/ca.crt}
      REDIS_TLS_CERT: ${REDIS_TLS_CERT:-/certs/redis.crt}
      REDIS_TLS_KEY: ${REDIS_TLS_KEY:-/certs/redis.key}

  langfuse-web:
    image: docker.langfuse.com/langfuse/langfuse:4
    restart: always
    depends_on: *langfuse-depends-on
    ports:
      - 3000:3000
    environment:
      <<: *langfuse-worker-env
      NEXTAUTH_SECRET: mysecret # CHANGEME
      LANGFUSE_INIT_ORG_ID: ${LANGFUSE_INIT_ORG_ID:-}
      LANGFUSE_INIT_ORG_NAME: ${LANGFUSE_INIT_ORG_NAME:-}
      LANGFUSE_INIT_PROJECT_ID: ${LANGFUSE_INIT_PROJECT_ID:-}
      LANGFUSE_INIT_PROJECT_NAME: ${LANGFUSE_INIT_PROJECT_NAME:-}
      LANGFUSE_INIT_PROJECT_PUBLIC_KEY: ${LANGFUSE_INIT_PROJECT_PUBLIC_KEY:-}
      LANGFUSE_INIT_PROJECT_SECRET_KEY: ${LANGFUSE_INIT_PROJECT_SECRET_KEY:-}
      LANGFUSE_INIT_USER_EMAIL: ${LANGFUSE_INIT_USER_EMAIL:-}
      LANGFUSE_INIT_USER_NAME: ${LANGFUSE_INIT_USER_NAME:-}
      LANGFUSE_INIT_USER_PASSWORD: ${LANGFUSE_INIT_USER_PASSWORD:-}

  clickhouse:
    image: clickhouse/clickhouse-server:25.12
    restart: always
    user: "101:101"
    environment:
      CLICKHOUSE_DB: default
      CLICKHOUSE_USER: clickhouse
      CLICKHOUSE_PASSWORD: clickhouse # CHANGEME
    volumes:
      - langfuse_clickhouse_data:/var/lib/clickhouse
      - langfuse_clickhouse_logs:/var/log/clickhouse-server
    ports:
      - 127.0.0.1:8123:8123
      - 127.0.0.1:9000:9000
    healthcheck:
      test: wget --no-verbose --tries=1 --spider http://localhost:8123/ping || exit 1
      interval: 5s
      timeout: 5s
      retries: 10
      start_period: 1s

  minio:
    image: minio/minio
    restart: always
    entrypoint: sh
    # create the 'langfuse' bucket before starting the service
    command: -c 'mkdir -p /data/langfuse && minio server --address ":9000" --console-address ":9001" /data'
    environment:
      MINIO_ROOT_USER: minio
      MINIO_ROOT_PASSWORD: miniosecret # CHANGEME
    ports:
      - 9090:9000
      - 127.0.0.1:9091:9001
    volumes:
      - langfuse_minio_data:/data
    healthcheck:
      test: ["CMD", "mc", "ready", "local"]
      interval: 1s
      timeout: 5s
      retries: 5
      start_period: 1s

  redis:
    image: redis:7
    restart: always
    # CHANGEME: row below to secure redis password
    command: >
      --requirepass ${REDIS_AUTH:-myredissecret}
    ports:
      - 127.0.0.1:6379:6379
    healthcheck:
      test: ["CMD", "redis-cli", "ping"]
      interval: 3s
      timeout: 10s
      retries: 10

  postgres:
    image: postgres:${POSTGRES_VERSION:-latest}
    restart: always
    healthcheck:
      test: ["CMD-SHELL", "pg_isready -U postgres"]
      interval: 3s
      timeout: 3s
      retries: 10
    environment:
      POSTGRES_USER: postgres
      POSTGRES_PASSWORD: postgres # CHANGEME
      POSTGRES_DB: postgres
    ports:
      - 127.0.0.1:5432:5432
    volumes:
      - langfuse_postgres_data:/var/lib/postgresql/data

volumes:
  langfuse_postgres_data:
    driver: local
  langfuse_clickhouse_data:
    driver: local
  langfuse_clickhouse_logs:
    driver: local
  langfuse_minio_data:
    driver: local
```

To test the connectivity between Langflow and Langfuse, run the following command:

```sh
docker compose exec langflow python -c "import requests, os; addr = os.environ.get('LANGFUSE_HOST'); print(addr); res = requests.get(addr, timeout=5); print(res.status_code)"

# which should output the following:
# http://langfuse-server:3000
# 200
```

<!-- agent-instructions -->

---

## Agent Instructions

This page is part of the [Langfuse](https://langfuse.com) documentation, published as plain Markdown for AI agents. Every page is available as Markdown by appending `.md` to its URL, or by sending an `Accept: text/markdown` header. This page: `https://langfuse.com/integrations/no-code/langflow.md`.

### Querying these docs

If the answer is not on this page, query the documentation instead of guessing:

- **Semantic search** across all Langfuse docs, returning an answer with the relevant pages and excerpts. Ask a specific, self-contained question:

  ```bash
  curl -sG "https://langfuse.com/api/search-docs" --data-urlencode "query=How do I trace a LangGraph agent?"
  ```

- **Index of every page**: <https://langfuse.com/llms.txt>, with per-section indexes [llms-docs.txt](https://langfuse.com/llms-docs.txt), [llms-integrations.txt](https://langfuse.com/llms-integrations.txt), and [llms-self-hosting.txt](https://langfuse.com/llms-self-hosting.txt).

### Before writing Langfuse code

- **Install the [Langfuse Agent Skill](https://langfuse.com/docs/api-and-data-platform/features/agent-skill).** It encodes Langfuse's own best practices for instrumentation, prompt management, and evaluation, and materially improves results.
- **Read [What does a good trace look like?](https://langfuse.com/docs/observability/best-practices.md)** before instrumenting an application.
- **Verify endpoints, parameters, and response fields** against the [API reference](https://api.reference.langfuse.com) instead of inferring them from code examples.
- **Use the [Langfuse CLI](https://langfuse.com/docs/api-and-data-platform/features/cli)** (`npx langfuse-cli api <resource> <action>`) to read or write traces, prompts, datasets, and scores from the terminal.

Found an error in these docs? Please open an issue at <https://github.com/langfuse/langfuse-docs/issues>.