Langfuse Roadmap
Langfuse is open source and we want to be fully transparent what we’re working on and what’s next. This roadmap is a living document and we’ll update it as we make progress.
Your feedback is highly appreciated. Feel like something is missing? Add new ideas on GitHub or vote on existing ones. Both are a great way to contribute to Langfuse and help us understand what is important to you.
🚀 Released
10 most recent changelog items:
- LLM-as-a-Judge Execution Tracing & Enhanced Observability
- Advanced Filtering for Public Traces API
- Spend Alerts
- Natural Language Filtering for Traces
- Structured Output Support for Prompt Experiments
- Mutable Score Configs
- Experiment Runner SDK
- TypeScript SDK v4 (GA)
- Additional Observation Types for More Meaningful Span Context
- New End-to-End Walkthrough Videos
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Active Development
Agent Observability
- Improve Langfuse to dig into complex, long running agents more intuitively
- Make agent tool calling easily debuggable and discoverable through special rendering
- Further improve agent graphs, agent logs, and agent evaluations
Evals
- Evaluation score comparisons: correlation, confusion matrix, overlap histogram
- Introduce experiments as a first class citizen, remove the dependency on datasets to allow for more bespoke unit-tests
- Overhaul experiment (dataset run) comparison views to make it easier to work with experiment results
- Dataset management: folders, schema enforcement/validation, bulk add traces to datasets
- Improve comments across the product to allow for more qualitative evaluation workflows and collaboration
Playground
- Experiment with prompts/models in playground based on logged traces and datasets with reference inputs
- Langfuse model input/output data schema to increase model interoperability for structured outputs and tool calls
- Make Playground stateful and collaborative
UI/UX
- Improve onboarding experience
- Improve core screens, especially for new and non-technical users
- Increase UI performance for extremely large traces and datasets
Infrastructure / Data Platform
- We strongly increase ingestion throughput, response times, and error rates across APIs by simplifying the core data model.
- Move to an observation-only and immutable data model as it better aligns with complex agents and allows us to scale our platform. Thereby, we remove traces as a first class citizen.
- Improvements across our tracing UI to make it easier to find relevant spans for complex agents.
- Webhooks for observability and evaluation events, useful for routing and alerting
🙏 Feature requests and bug reports
The best way to support Langfuse is to share your feedback, report bugs, and upvote on ideas suggested by others.
Feature requests
Bug reports
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