Langfuse

What is Langfuse?

Langfuse is an open-source LLM Engineering Platform that provides observability, metrics, evaluations, prompt management, and a playground for debugging and improving LLM apps. It is designed to be compatible with any model or framework, allowing for complex nesting and offering open APIs for building downstream use cases. Langfuse has been positively reviewed for its effectiveness in monitoring GPT usage, analyzing LLM applications, and providing detailed latency and analytics in the market. Users have praised it for its ease of integration, intuitive usage, and fast iterations by the development team. Langfuse is known for its security features, being SOC 2 Type II and ISO 27001 certified, GDPR compliant, and built with security in mind.

Who created Langfuse?

Langfuse was created by a team comprising Clemens, Marc, and Max. The company provides an open-source LLM Engineering Platform for observability and analytics in LLM apps. Langfuse is geared towards improving costs, latency, and response quality using intuitive dashboards and tools for monitoring GPT usage and debugging LLM applications.

What is Langfuse used for?

• Prompt Management
• Provides observability for LLM apps
• Metrics monitoring and evaluation
• Debugging and improvement of LLM apps
• Works with any model and framework
• Allows for complex nesting
• Open APIs for building downstream use cases
• Monitoring GPT usage like token usage, hallucinations, and request history trace
• Detailed latency and analytics for complex chains or user-facing chat applications
• Measurement and monitoring of LLM application performance

Who is Langfuse for?

• Compliance professionals
• Data processing professionals
• SEC2 Type II and ISO27001 report specialists
• Security professionals
• Team solutions specialists
• Data Analysts
• Security specialists

How to use Langfuse?

To use Langfuse, follow these steps:

1. Sign Up: Create an account on Langfuse's platform by visiting their website and registering for an account.

2. Choose a Tier: Select the appropriate tier based on your needs. Langfuse offers Hobby, Pro, and Team tiers, each with different features and usage limits.

3. Access Features: Explore the platform's features such as observability, tracing, prompt management, and metrics to debug and enhance LLM (Large Language Model) apps.

4. Integrate with LLM Apps: Langfuse works with any model or framework. You can use it to monitor GPT usage, token usage, monitor hallucinations, and trace request history.

5. Utilize Collaboration Tools: Depending on your tier, you can collaborate with team members on projects, access unlimited data, and enjoy different levels of support like community support or dedicated support.

6. Ensure Security and Compliance: Langfuse offers security features like SSO (Single Sign-On), role-based access control, and compliance with data processing agreements like GDPR.

7. Review Documentation: Refer to Langfuse's documentation available on their website and GitHub repository for detailed information on using the tool.

8. Stay Updated: Keep track of any recent launches, reviews, and updates related to Langfuse to make the most of the platform's capabilities and features.

Langfuse provides a valuable resource for monitoring and improving the performance of LLM applications. By following these steps, users can effectively leverage Langfuse's features and enhance their LLM projects efficiently.