Litefuse Overview
Litefuse is an agent observability and evaluation platform that helps teams collaboratively debug, analyze, and iterate on their LLM applications. All platform features are natively integrated to accelerate the development workflow. Litefuse is open, self-hostable, and extensible.
Observability
- Log traces
- Lowest level transparency
- Understand cost and latency
Prompts
- Version control and deploy
- Collaborate on prompts
- Test prompts and models
Evaluation
- Measure output quality
- Monitor production health
- Test changes in development
Platform
- API-first architecture
- Data exports to blob storage
- Enterprise security and administration
Observability
Observability is essential for understanding and debugging LLM applications. Unlike traditional software, LLM applications involve complex, non-deterministic interactions that can be challenging to monitor and debug. Litefuse provides comprehensive tracing capabilities that help you understand exactly what’s happening in your application.
- Traces include all LLM and non-LLM calls, including retrieval, embedding, API calls, and more
- Support for tracking multi-turn conversations as sessions and user tracking
- Agents can be represented as graphs
- Capture traces via our native SDKs for Python/JS, 50+ library/framework integrations, OpenTelemetry, or via an LLM Gateway such as LiteLLM
- Based on OpenTelemetry to increase compatibility and reduce vendor lock-in
Want to see an example? Play with the interactive demo.
Want to learn more? Watch end-to-end walkthrough of Litefuse Observability and how to integrate it with your application.
Traces allow you to track every LLM call and other relevant logic in your app.
Prompt Management
Prompt Management is critical in building effective LLM applications. Litefuse provides tools to help you manage, version, and optimize your prompts throughout the development lifecycle.
- Get started with prompt management
- Manage, version, and optimize your prompts throughout the development lifecycle
- Test prompts interactively in the LLM Playground
- Run Experiments against datasets to test new prompt versions directly within Litefuse
Want to learn more? Watch end-to-end walkthrough of Litefuse Prompt Management and how to integrate it with your application.
Create a new prompt via UI, SDKs, or API.
Evaluation
Evaluation is crucial for ensuring the quality and reliability of your LLM applications. Litefuse provides flexible evaluation tools that adapt to your specific needs, whether you’re testing in development or monitoring production performance.
- Get started with different evaluation methods: LLM-as-a-judge, user feedback, manual labeling, or custom
- Identify issues early by running evaluations on production traces
- Create and manage Datasets for systematic testing in development that ensure your application performs reliably across different scenarios
- Run Experiments to systematically test your LLM application
Want to learn more? Watch end-to-end walkthrough of Litefuse Evaluation and how to use it to improve your LLM application.
Plot evaluation results in the Dashboard.
Where to start?
Setting up the full process of online tracing, prompt management, production evaluations to identify issues, and offline evaluations on datasets requires some time. This guide is meant to help you figure out what is most important for your use case.
Simplified lifecycle from PoC to production:
Quickstarts
Get up and running with Litefuse in minutes. Choose the path that best fits your current needs:
Why Litefuse?
- Production optimized: Designed with minimal performance overhead
- Best-in-class SDKs: Native SDKs for Python and JavaScript
- Framework support: Integrated with popular frameworks like OpenAI SDK, LangChain, and LlamaIndex
- Multi-modal: Support for tracing text, images and other modalities
- Full platform: Suite of tools for the complete LLM application development lifecycle
- Cost effective: Forked from Langfuse and optimzed for simplicity and cost
Litefuse evolves quickly, check out the blog for the latest updates. Subscribe to the mailing list to get notified about new major features: