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SalesforceAIResearch/xLAM

xLAM: A Family of Large Action Models to Empower AI Agent Systems

Latest metrics (snapshot 2026-10-15)

stars638
forks60
issues8
pushed_at2026-06-02T18:53:42Z

History

History chart: 1 daily snapshot so far (archive started 2026-10-14). The line fills in as the daily archive grows; full series via the API.

DateGitHub stars
2026-10-15638

ADC Momentum: 16/100

ADC Momentum 16 Leaderboard

Growth velocity26
Consistency21
Recency0
Agent demand0
Basisbootstrap

ADC Momentum (0-100) = 45% growth velocity (stars/likes gained per day in our daily archive, relative and absolute, percentile-ranked within the category) + 20% consistency (share of recent days with growth) + 20% recency (latest push/update/release, decaying) + 15% agent demand (how often AI agents looked it up via our API/MCP this week). MCP servers use release cadence; LLMs use price cuts, context and recency. Recomputed daily; scores marked "bootstrap" use lifetime rates until the archive has enough days. Method

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Details

descriptionxLAM: A Family of Large Action Models to Empower AI Agent Systems
urlhttps://github.com/SalesforceAIResearch/xLAM
languagePython
licenseApache-2.0
topicsactionstudio
agents
agentstudio
llm-agent
llms
xlam
created_at2024-02-27T09:34:15Z

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