🪢

🪢 Langfuse

Open source LLM engineering platform

★ 8908 AI LLM Monitoring Observability

Homepage · Source code

Author: Langfuse GmbH · License: MIT Expat

Version: 3.29.0 ·

Informazioni su Langfuse

Langfuse is an open source LLM engineering platform. It helps teams collaboratively develop, monitor, evaluate, and debug AI applications. Langfuse can be self-hosted in minutes and is battle-tested.

preview


Features

  • LLM Application Observability: Instrument your app and start ingesting traces to Langfuse, thereby tracking LLM calls and other relevant logic in your app such as retrieval, embedding, or agent actions. Inspect and debug complex logs and user sessions. Try the interactive demo to see this in action.
  • Prompt Management helps you centrally manage, version control, and collaboratively iterate on your prompts. Thanks to strong caching on server and client side, you can iterate on prompts without adding latency to your application.
  • Evaluations are key to the LLM application development workflow, and Langfuse adapts to your needs. It supports LLM-as-a-judge, user feedback collection, manual labeling, and custom evaluation pipelines via APIs/SDKs.
  • Datasets enable test sets and benchmarks for evaluating your LLM application. They support continuous improvement, pre-deployment testing, structured experiments, flexible evaluation, and seamless integration with frameworks like LangChain and LlamaIndex.
  • LLM Playground is a tool for testing and iterating on your prompts and model configurations, shortening the feedback loop and accelerating development. When you see a bad result in tracing, you can directly jump to the playground to iterate on it.
  • Comprehensive API: Langfuse is frequently used to power bespoke LLMOps workflows while using the building blocks provided by Langfuse via the API. OpenAPI spec, Postman collection, and typed SDKs for Python, JS/TS are available.

Environment variables

View environment variables
PROJECT
  langfuse
DOMAIN
  stack.localhost
DATABASE_URL
  "postgresql://postgres:langfuse-postgres@db:5432/postgres"
SALT
  "salt" # salt used to hash api keys
ENCRYPTION_KEY
  "0000000000000000000000000000000000000000000000000000000000000000"
TELEMETRY_ENABLED
  ${TELEMETRY_ENABLED:-false}
LANGFUSE_ENABLE_EXPERIMENTAL_FEATURES
  true
CLICKHOUSE_MIGRATION_URL
  ${CLICKHOUSE_MIGRATION_URL:-clickhouse://langfuse-clickhouse:9000}
CLICKHOUSE_URL
  ${CLICKHOUSE_URL:-http://langfuse-clickhouse:8123}
CLICKHOUSE_USER
  ${CLICKHOUSE_USER:-clickhouse}
CLICKHOUSE_PASSWORD
  ${CLICKHOUSE_PASSWORD:-clickhouse}
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}
LANGFUSE_S3_EVENT_UPLOAD_ENDPOINT
  ${LANGFUSE_S3_EVENT_UPLOAD_ENDPOINT:-http://langfuse-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}
LANGFUSE_S3_MEDIA_UPLOAD_ENDPOINT
  ${LANGFUSE_S3_MEDIA_UPLOAD_ENDPOINT:-http://langfuse-minio:9000}
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_INGESTION_QUEUE_DELAY_MS
  ${LANGFUSE_INGESTION_QUEUE_DELAY_MS:-}
LANGFUSE_INGESTION_CLICKHOUSE_WRITE_INTERVAL_MS
  ${LANGFUSE_INGESTION_CLICKHOUSE_WRITE_INTERVAL_MS:-}
REDIS_HOST
  langfuse-redis
REDIS_PORT
  6379
REDIS_AUTH
  myredissecret
REDIS_TLS_ENABLED
  false
REDIS_TLS_CA
  /certs/ca.crt
REDIS_TLS_CERT
  /certs/redis.crt
REDIS_TLS_KEY
  /certs/redis.key
NEXTAUTH_URL
  "https://$PROJECT.$DOMAIN"
NEXTAUTH_SECRET
  "secret" # https://next-auth.js.org/configuration/options#secret
LANGFUSE_CSP_ENFORCE_HTTPS
  "true"
LANGFUSE_LOG_LEVEL
  info
LANGFUSE_LOG_FORMAT
  text

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