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Zipstack/unstract

LLM-Driven Extraction of Unstructured Data — Built for API Deployments & ETL Pipeline Workflows

Latest metrics (snapshot 2026-10-14)

stars7283
forks719
issues102
pushed_at2026-10-14T17:45:32Z

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
2026-10-147283

ADC Momentum: 39/100

ADC Momentum 39 Leaderboard

Growth velocity32
Consistency25
Recency100
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

descriptionLLM-Driven Extraction of Unstructured Data — Built for API Deployments & ETL Pipeline Workflows
urlhttps://github.com/Zipstack/unstract
languagePython
licenseAGPL-3.0
topicsai-agents
data-engineering
document-ai
generative-ai
idp
json-extraction
llm
mcp-server
ocr
pdf-extraction
prompt-engineering
structured-output
created_at2024-02-21T10:34:33Z
homepagehttps://unstract.com

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