Langfuse : The Open-Source LLM Engineering Platform

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What is Langfuse?
Langfuse, an open-source LLM engineering platform provides observability, tracing, evaluations, prompt management, and metrics to debug and improve LLM applications. It is model- and framework-agnostic. Langfuse has dashboards,analytics and it allows data export.

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What are the key features of Langfuse?

  • Observability.
  • Integrations.
  • Langfuse UI.
  • Prompt management.
  • Prompt engineering.
  • Analytics.
  • Evals.
  • Experiments.
  • Open-source.
  • Incrementally adoptable.
  • Tags.
  • Trace URL.
 

Langfuse 2.0 – Open Source LLM Engineering Platform  (Source : Youtube Channel : Langfuse)

Langfuse Integrations

  • Python SDK
  • JS/TS SDK
  • OpenAI SDK
  • Langchain
  • Llama-Index
  • Litellm
  • Flowise
  • Langflow
  • API

What are the use cases of Langfuse?

  • Capture API calls, context, prompts, parallelism.
  • Track model usage and cost.
  • Identify low-quality outputs.
  • Collect user feedback.
  • Build fine-tuning and testing datasets.
  • Deploy new prompts without redeploying applications.
  • Allows non-technical users to create and update prompts.
  • Quickly rollback to previous prompt versions.
  • Displays quick overview on traces.
  • Segment execution traces by scores.
  • Provides detailed score reporting.
  • Drills down into use cases and user segments.

How much does Langfuse cost?

  • Langfuse offers both free and paid plans.
  • The Langfuse Pro plan costs $59 per month.
  • The Langfuse Team plan starts at $499.

The detailed pricing for Langfuse is as follows:
Hobby Plan

  • Free
  • No credit card required
  • All platform features
  • 50k observations/month included
  • Community support (Discord & GitHub)

Pro Plan

  • $59 USD/Month
  • 100k observations/month included
  • Additional observations: $10/100k
  • Unlimited data access
  • Unlimited users
  • Dedicated support

Team Plan

  • Starts at $499
  • Unlimited ingestion throughput
  • Support SLAs
  • SSO enforcement and custom roles
  • Additional security and compliance features

What are the pros and cons of Langfuse?

Pros of Langfuse

  • Open-sourced.
  • Custom integrations.
  • SDKs for Javascript and Python.
  • Decoupling.
  • Quickly rollback previous versions of prompts.
  • Quality.
  • Security.
  • Track cost, quality and latency.
  • Unlimited data access.
  • Self-hosting.
  • Easy to run locally.
  • LLM playground.

Cons of Langfuse

  • Cost.
  • Learning curve.
  • Technical dependence.

ai tool pricing icon  Langfuse pricing

  • The Langfuse pricing plans starts from $59 per month.

faqs icon for ai toolsLangfuse FAQ's

What does Langfuse do?

Helps debug, test, and improve LLM applications.

Does Langfuse work with any LLM?

Yes, it works with different LLM models and frameworks.

What are Langfuse's key features?

It tracks how LLMs work, lets you manage prompts, and offers data export.

Does Langfuse have integrations?

Yes, it integrates with Python, Javascript, and other LLM tools.

What can Langfuse track about LLMs?

LLM calls, user input, prompts, and performance.

Can Langfuse help save money on LLMs?

Yes, it can track LLM usage costs.

Can Langfuse improve LLM quality?

Yes, it can help identify low-quality outputs from LLMs.

Can Langfuse help build better LLM datasets?

Yes, it can help collect data for training LLMs.

Can I update prompts in Langfuse without restarting my app?

Yes, you can deploy new prompts without affecting your application.

Is Langfuse easy to use for everyone?

It might have a learning curve for non-technical users.

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