Agent Lightning v0.2.1

Agent-lightning v0.2.1 is a stabilization release for v0.2.0. It introduces several bug fixes and new features, plus a number of unlisted CI improvements.

Bug fixes

• Fix LiteLLM issues when restarting the proxy multiple times in the same process (#174 #206)
• Fix LiteLLM model name selection when multiple servers use the same model (#197)
• Fix store port conflict handling (#227)

New Features

• Add trainer port option for client-server strategies (#198)

Documentation

• Add tutorial for launching workers on separate machines (#213)
• Add link to VERL framework (#210)
• Add link to vLLM blog (#215)
• Fix a couple of typos and avoid emacs backup files (#237)

New Contributors

A warm welcome to our first-time contributors: @scott-vsi, @ddsfda99, @jeis4wpi 🎉

Full Changelog: v0.2.0...v0.2.1

Agent Lightning v0.2.0

Agent-Lightning v0.2.0 introduces major framework improvements, new execution strategies, expanded documentation, and enhanced reliability across the agent training and deployment workflow. This release includes 78 pull requests since v0.1.2.

Core Enhancements

• Lightning Store: Added unified interface and implementation for Agent-lightning's core storage.
• Emitter: Emitting any objects as spans to the store.
• Adapter and Tracer: Adapting to OpenAI-like messages, and OpenTelemetry dummy tracer.
• LLM Proxy: Added LLM Proxy as the first-class citizen in Agent-lightning.
• Agent Runner: New version providing a more modular and robust runner design.
• Embedded Algorithms: Algorithms are now embedded directly into trainers for simplicity.
• New Execution Strategies: Introduced Client-Server and Shared Memory execution models.
• Trainer Updates: Integrated v0.2 interfaces and FastAlgorithm validation.

Documentation & Examples

• Revamped documentation with new guides for agent creation, training, debugging, and store concepts.
• Improved quickstart tutorials, clarified installation and new deep-dive articles.
• Added and updated examples: SQL Agent, Calc-X, Local SFT, Search-R1, and APO algorithm.

Developer Experience

• Migrated build and CI pipelines to 1ES, split workflows and aggregate badges for clarity.
• Adopted uv as the dependency manager.
• Added GPU-based pytest workflows for full test coverage.
• Enhanced debugging UX, pre-commit configs, and linting (Pyright fixes, import sorting).

Ecosystem & Integrations

• Added support for agents built with Agent-framework.
• Added new community listings: DeepWerewolf and AgentFlow.

New Contributors

A warm welcome to our first-time contributors:
@hzy46, @lunaqiu, @syeehyn, @linhx1999, @SiyunZhao, and @acured 🎉

Full changelog: v0.1.2 → v0.2.0

Agent Lightning v0.1.2

What's Changed

• Add basic documentation in #33
• RAG example by @wizardlancet in #21

New Contributors

• @wizardlancet made their first contribution in #21

Full Changelog: v0.1.1...v0.1.2

Agent Lightning v0.1.1

What's Changed

• Disable HTTP tracer tests and bump to 0.1.1 in #26
• Fix trainer bugs in v0.1 in #24

Full Changelog: v0.1...v0.1.1

Agent Lightning v0.1

The first release of Agent-lightning!

• Turn your agent into an optimizable beast with ZERO CODE CHANGE (almost)! 💤
• Build with ANY agent framework (LangChain, OpenAI Agent SDK, AutoGen, CrewAI, ...); or even WITHOUT agent framework (Python OpenAI). You name it! 🤖
• Selectively optimize one or more agents in a multi-agent system. 🎯
• Embraces Reinforcement Learning, Automatic Prompt Optimization and more algorithms. 🤗

Install via pip install agentlightning.