[Release] v0.3.0 (#427)

Author: ultmaster

README.md

@@ -37,7 +37,7 @@ pip install agentlightning
 For the latest nightly build (cutting-edge features), you can install from Test PyPI:
 
 ```bash
-pip install --upgrade --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple/ agentlightning
+pip install --upgrade --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple/ --pre agentlightning
 ```
 
 Please refer to our [installation guide](https://microsoft.github.io/agent-lightning/stable/tutorials/installation/) for more details.
@@ -46,6 +46,7 @@ To start using Agent-lightning, check out our [documentation](https://microsoft.
 
 ## ⚡ Articles
 
+- 12/17/2025 [Adopting the Trajectory Level Aggregation for Faster Training](https://agent-lightning.github.io/posts/trajectory_level_aggregation/) Agent-lightning blog.
 - 11/4/2025 [Tuning ANY AI agent with Tinker ✕ Agent-lightning](https://medium.com/@yugez/tuning-any-ai-agent-with-tinker-agent-lightning-part-1-1d8c9a397f0e) Medium. See also [Part 2](https://medium.com/@yugez/tuning-any-ai-agent-with-tinker-agent-lightning-part-2-332c5437f0dc).
 - 10/22/2025 [No More Retokenization Drift: Returning Token IDs via the OpenAI Compatible API Matters in Agent RL](https://blog.vllm.ai/2025/10/22/agent-lightning.html) vLLM blog. See also [Zhihu writeup](https://zhuanlan.zhihu.com/p/1965067274642785725).
 - 8/11/2025 [Training AI Agents to Write and Self-correct SQL with Reinforcement Learning](https://medium.com/@yugez/training-ai-agents-to-write-and-self-correct-sql-with-reinforcement-learning-571ed31281ad) Medium.

docs/changelog.md

@@ -1,5 +1,97 @@
 # Changelog
 
+## Agent-lightning v0.3.0 (12/24/2025)
+
+Agent-lightning v0.3.0 is a major release that introduces several new features and bug fixes. The release is a collaborative effort between Agent-lightning core teams and the community. Thanks to all the contributors who made this release possible.
+
+### Highlights
+
+* **Tinker integration**: Support Tinker as an alternative backend for Reinforcement Learning (#226 #245 #264 #269 #327). See [example code](https://github.com/microsoft/agent-lightning/tree/v0.3.0/examples/tinker), [blog 1](https://medium.com/@yugez/tuning-any-ai-agent-with-tinker-agent-lightning-part-1-1d8c9a397f0e) and [blog 2](https://medium.com/@yugez/tuning-any-ai-agent-with-tinker-agent-lightning-part-2-332c5437f0dc).
+* **Azure OpenAI integration**: Support Azure OpenAI as a backend for LLM inference and supervised fine-tuning (#256 #327). [Example code](https://github.com/microsoft/agent-lightning/tree/v0.3.0/examples/azure).
+* **MongoDB-based Lightning Store** is added as an alternative backend for Lightning Store (#323). [Documentation](https://microsoft.github.io/agent-lightning/v0.3.0/tutorials/parallelize/#parallelizing-lightningstore).
+* **Contrib package**: Add contrib package for community projects. Search-R1 is integrated as a contrib recipe. More coming. (#239 #396 #410 #412 #417).
+* **RESTful API**: Stabilize and document RESTful API for Lightning Store (#241 #275). [Documentation](https://microsoft.github.io/agent-lightning/v0.3.0/reference/restful/).
+* **OTel Semantic Conventions** that are specifically designed for Agent-optimization areas (#340). [Documentation](http://microsoft.github.io/agent-lightning/v0.3.0/reference/semconv/).
+* *[Preview]* **Agent-lightning Dashboard** is now available (#288 #289 #291 #296 #371 #375). It's the official web application for inspecting and debugging Agent-lightning experiments. See details [here](https://microsoft.github.io/agent-lightning/v0.3.0/tutorials/debug/).
+* *[Preview]* **Multi-modality example** featuring VERL and a LangGraph agent on ChartQA dataset (#379). [Example code](https://github.com/microsoft/agent-lightning/tree/v0.3.0/examples/chartqa).
+* *[Preview]* Integrate **Claude Code** as a LitAgent and support training on SWE-Bench (#332 #346 #348). [Example code](https://github.com/microsoft/agent-lightning/tree/v0.3.0/examples/claude_code).
+* *[Preview]* **Weave tracer** as a substitute for AgentOps tracer (#277 #411 #420 #423). [Documentation](https://microsoft.github.io/agent-lightning/v0.3.0/tutorials/traces/#weave-tracer-experimental).
+* *[Preview]* **Trajectory Level Aggregation** for more efficient training with VERL. See [blog](https://agent-lightning.github.io/posts/trajectory_level_aggregation/) and [documentation](https://microsoft.github.io/agent-lightning/v0.3.0/algorithm-zoo/verl/).
+
+### Store Benchmark
+
+In this release, the Lightning Store core was redesigned for significantly greater efficiency and scalability (#315 #318 #328 #342 #344 #356 #380 #388 #418 #421). The benchmark results below demonstrate the impact: with large numbers of concurrent runners, v0.3.0 delivers up to a 15x increase in throughput compared to v0.2.2.
+
+| Throughput (\#rollout/sec) | v0.2.2 | v0.3.0 (in-memory) | v0.3.0 (Mongo) |
+| :---- | :---- | :---- | :---- |
+| Minimal (batch, #runner=32, #turns=6) | 8.73 | 9.06 | 8.71 |
+| Medium (batch, #runners=100, #turns=10) | 12.03 | 23.26 | 32.79 |
+| Mid-high (batch, #runners=300, #turns=6) | 10.61 | 24.42 | 40.24 |
+| Large (batch, #runners=1000, #turns=3) | 3.36 | 14.60 | 50.05 |
+| Long queue (queue, #runners=256, #turns=4) | 7.42 | 30.86 | 57.01 |
+| Heavy trace (queue, #runners=512, #turns=20) | 5.93 | 13.28 | 29.41 |
+
+*Notes:*
+
+1. Benchmarks were run on a single Standard_D32as_v4 Azure VM (Large and heavy trace tests used Standard_D64ads_v5), executed via GitHub Actions.
+2. Two algorithm patterns are evaluated: the batch pattern submits a group of rollouts and waits for all to finish before starting the next group, while the queue pattern maintains a set number of in-flight rollouts, submitting new ones as soon as capacity frees up. Configuration details are available [here](https://github.com/microsoft/agent-lightning/blob/v0.3.0/.github/workflows/benchmark.yml).
+3. The number of turns is directly proportional to the number of spans each rollout generates.
+
+### Maintenance and Bug fixes
+
+#### Core (Store, Interfaces, etc.)
+
+* Add Trainer port option for client-server strategies (#198)
+* Fix store port conflict handling (#227)
+* Unified PythonServerLauncher (#286 #292 #303)
+* Make health timeout configurable (#305)
+* Refactor logging (#306)
+* Support OTLP in LightningStore (#313)
+* Centralized metrics helper (#368)
+* Fix redundant cancel tracebacks on Ctrl+C (#370)
+
+#### Proxy, Adapters and Algorithms
+
+* Fix training metrics before and after processing in VERL (#145)
+* Forward streaming requests for Anthropic and OpenAI APIs (as non-streaming requests) (#299)
+* Check traces with reward for VERL (#317)
+* Patch LiteLLM root span (#341)
+* Handle ref_in_actor flag for LoRA compatibility (#386)
+* Support `with_llm_proxy` and `with_store` in algorithms (#398)
+* Support image URL export in TracerTraceToTriplets (#400)
+* Fix match_rewards assign_to elements in TraceTree (#403)
+* Support customizing trainer and daemon in VERL (#407)
+
+#### Runners, Tracers and Agents
+
+* Refactor tracer initialization (#321)
+* Fix OpenAI Agents 0.6 compatibility (#322)
+* `emit_operation`, `emit_annotation`, tags and links (#359)
+* Sunset HTTP tracer (#402)
+
+#### Examples
+
+* Fix typos in train-first-agent.md (#263)
+* Fix room_selector example which always runs the first task (#270)
+* Fix typo in SQL agent example (#285)
+* Add the README and script files for training SQL agent on NPU (#272)
+* Examples Catalog and Refine Contribution Guide (#331)
+* Upgrade LangChain to 1.x (#364)
+* Update RAG example to Agent-lightning v0.2.x (#349)
+
+#### Miscellaneous
+
+* DeepWiki Badge (#263)
+* Add AGENTS.md (#374)
+
+### New Contributors
+
+Warm welcome to our first-time contributors: @cptnm3, @TerryChan, @genji970, @zxgx, @xiaochulaoban, @lspinheiro, @Kwanghoon-Choi, @Vasuk12, @totoluo, @jinghuan-Chen 🎉
+
+**Full Changelog**: https://github.com/microsoft/agent-lightning/compare/v0.2.0...v0.3.0
+
+---
+
 ## Agent-lightning v0.2.2 (11/12/2025)
 
 Agent-lightning v0.2.2 is a stabilization release for v0.2.1. It introduces several bug fixes.

docs/reference/restful.md

@@ -1,10 +1,8 @@
 # RESTful API References
 
-!!! warning
+!!! note
 
-    The following contents are still under construction.
-
-## Store RESTful API
+    Shown in the following is the RESTful API for Lightning Store.
 
 <div id="swagger-ui"></div>
 <link rel="stylesheet" href="https://unpkg.com/swagger-ui-dist/swagger-ui.css" />

docs/tutorials/installation.md

@@ -34,7 +34,7 @@ This installs or upgrades Agent-Lightning to the newest stable version.
 Agent-Lightning also publishes **nightly builds**, which contain the latest experimental features and improvements from the main branch. These are available via **Test PyPI**.
 
 ```bash
-pip install --upgrade --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple/ agentlightning
+pip install --upgrade --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple/ --pre agentlightning
 ```
 
 !!! warning