Match the project to your task before installing it.
Observability and Evaluation · Public
agent-lightning
Observability and evaluation project for turning logs, quality metrics, drift, or experiment results into reviewable signals.
Best fitDevelopers who need reviewable observability or evaluation workflows for AI apps, data pipelines, or experiments.
Check whether this project matches your task before installing it.
What it can doObservability setup paths, metric boundaries, sample-data redaction, evaluation checks, and failure triageReview the portable capability path.
Before continuingVerify in a sandboxDo not treat a preview pack as a proven local install.
GitHub snapshotstars unavailableforks unavailable · contributors unavailable
Publication status · 2026-05-21
What is agent-lightning?
- agent-lightning helps developers observe, evaluate, or monitor AI/data application behavior and quality.
- Best fit: Developers who need reviewable observability or evaluation workflows for AI apps, data pipelines, or experiments.
- Not for: Not for users without logs/sample data, privacy boundaries, or those who only need a chat UI.
- Capability added to an AI workflow: Observability setup paths, metric boundaries, sample-data redaction, evaluation checks, and failure triage
- First safe verification step: Verify collection, metric interpretation, export, and deletion paths with redacted sample data first.
- Verification state: source, Quick Start, and sandbox install checks are recorded as passed.
- Top risk: README/documentation is current enough for a first validation pass.
- Evidence base: https://github.com/microsoft/agent-lightning, https://github.com/microsoft/agent-lightning#readme, Human Manual, Pitfall Log
01
Quick decision
Use this section to decide whether the project is worth a deeper read.Observability and evaluation project for turning logs, quality metrics, drift, or experiment results into reviewable signals.
stars unavailable · forks unavailable
02
What it can do
Translate the upstream project into concrete capabilities the user can judge before installing.Introduction to Agent Lightning
Related topics: System Architecture, Installation Guide
Source: https://github.com/microsoft/agent-lightning / Human Manual
Installation Guide
Related topics: Introduction to Agent Lightning, Tutorial: Train Your First Agent
Source: https://github.com/microsoft/agent-lightning / Human Manual
System Architecture
Related topics: Trainer Component, Runner Component, LightningStore
Source: https://github.com/microsoft/agent-lightning / Human Manual
Core Abstractions and Data Models
Related topics: System Architecture, Trainer Component
Source: https://github.com/microsoft/agent-lightning / Human Manual
Tutorial: Train Your First Agent
Related topics: Tutorial: Writing Agents, Algorithm Zoo
Source: https://github.com/microsoft/agent-lightning / Human Manual
Sources: https://github.com/microsoft/agent-lightning, Human Manual, Project Pack evidence, and downstream validation signals.
03
Community Discussion Evidence
Project-level external discussion stays visible on the detail page, not only inside the manual.Community Discussion Evidence
12 source-linked itemsReview these external discussions before using agent-lightning with real data or production workflows. They are review inputs, not standalone proof that the project is production-ready.
-
01
Intermittent missing openai.chat.completion spans from query_spans (RLin
github / github_issue
-
02
Question about Code Availability for EMPO^2 Paper
github / github_issue
-
03
calc-x example fails on next
github / github_issue
-
04
APO's TraceToMessages adapter fails with multi-turn agent rollouts (KeyE
github / github_issue
-
05
Installation Problem
github / github_issue
-
06
GRPO grouping in multi-turn agent RL: is it valid to mix samples with di
github / github_issue
-
07
Announcing Solantra: Next-Gen Blockchain on Solana
github / github_issue
-
08
Add interaction scripts and token utilities
github / github_issue
-
09
blockchain project
github / github_issue
-
10
Agent Lightning v0.3.0
github / github_release
-
11
Agent Lightning v0.2.2
github / github_release
-
12
Agent Lightning v0.2.1
github / github_release
04
How to start
Only source-backed commands are shown here. Verify them in an isolated environment first.Try the prompt first
Test the workflow without installing the upstream project.
previewRead the Human Manual
Understand inputs, outputs, limits, and failure modes.
manualTake context to your AI host
Use the compiled assets in your preferred AI environment.
contextRun sandbox verification
Confirm install commands and rollback before using a primary environment.
verifypip install agentlightningOfficial start command · https://github.com/microsoft/agent-lightning#readme · verified: yes
05
Human Manual
The English page must expose the real manual, not a short placeholder.8+ sections · Human Manual
agent-lightning Manual
The Agent Lightning architecture follows a producer-consumer pattern centered around trace collection and consumption.
Open the full manual- https://github.com/microsoft/agent-lightning Project Manual
- Table of Contents
- Introduction to Agent Lightning
- Related Pages
- What is Agent Lightning?
- Architecture Overview
- Core Loop
- Component Hierarchy
Introduction to Agent Lightning
Related topics: System Architecture, Installation Guide
Source: https://github.com/microsoft/agent-lightning / Human Manual
Installation Guide
Related topics: Introduction to Agent Lightning, Tutorial: Train Your First Agent
Source: https://github.com/microsoft/agent-lightning / Human Manual
System Architecture
Related topics: Trainer Component, Runner Component, LightningStore
Source: https://github.com/microsoft/agent-lightning / Human Manual
Core Abstractions and Data Models
Related topics: System Architecture, Trainer Component
Source: https://github.com/microsoft/agent-lightning / Human Manual
Tutorial: Train Your First Agent
Related topics: Tutorial: Writing Agents, Algorithm Zoo
Source: https://github.com/microsoft/agent-lightning / Human Manual
06
AI Context Pack and portable assets
After deciding to continue, take the project context into your own AI host.Complete pack plus user-owned assets
These files are planning and verification assets for Claude Code, Codex, Gemini, Cursor, ChatGPT, and other AI hosts.
07
Preflight checks
Treat this page as a planning asset, not proof that your local environment is ready.- The manual is generated from source-linked project files and Doramagic validation signals.
- Community evidence warnings stay visible instead of being converted into marketing claims.
- This English page is indexable because the locale quality gate passed and explicit English index approval is enabled.
- Use the upstream repository as the final authority for installation commands, license, and version-specific behavior.
08
Pitfall Log and verification risks
Doramagic surfaces high-risk items before users treat a candidate capability as verified.Review upstream issue
README/documentation is current enough for a first validation pass.
Review upstream issue
The source signal needs review before production use.
Review upstream issue
no_demo
Review upstream issue
No sandbox install has been executed yet; downstream must verify before user use.
Review upstream issue
no_demo
Review upstream issue
issue_or_pr_quality=unknown。
Review upstream issue
release_recency=unknown。