openai

openai / GABRIEL

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An official OpenAI toolkit for social scientists and data scientists to measure quantitative attributes in text, images, or audio using the GPT API.

194
25
100% credibility
Found Feb 08, 2026 at 10 stars 19x -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Jupyter Notebook
AI Summary

GABRIEL is an OpenAI library that uses AI models to measure, classify, and structure qualitative data like texts, speeches, images, and audio into analysis-ready spreadsheets.

How It Works

1
🔍 Discover GABRIEL

You hear about GABRIEL from a blog post or friend—it's a helpful tool from OpenAI that turns messy notes, speeches, or photos into neat spreadsheets using smart AI.

2
📥 Get it ready

Download and set it up on your computer—it's simple, like adding a new app, and takes just a minute.

3
🔗 Connect the AI

Link it to a smart AI service with your private password so it can understand and analyze your information.

4
📁 Add your files

Upload your collection of texts, images, audio clips, or interviews into a simple list or folder.

5
⭐ Ask it to analyze

Tell it what to do, like 'rate how persuasive each speech is' or 'tag photos by style'—watch as it thinks deeply and scores everything automatically.

✅ Enjoy tidy results

Get back organized tables with scores, tags, or insights ready for charts or reports, saving you hours of manual work.

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AI-Generated Review

What is GABRIEL?

GABRIEL is a Python toolkit from OpenAI that helps social scientists and data scientists turn unstructured text, images, audio, or PDFs into quantitative datasets using GPT models. You define natural-language attributes like "populist rhetoric" or "luxury appeal," and it delivers ratings (0-100), classifications, extractions, or rankings as clean DataFrames—managing batching, retries, parallelism, and checkpointing automatically. Fire it up via pip install openai-gabriel and a Jupyter notebook tutorial for instant multimodal analysis.

Why is it gaining traction?

It packages GPT as a reliable measurement tool with operational smarts: resume huge runs mid-stream, audit raw responses, and chain tasks like deidentification or deduplication without custom scripting. Multimodal inputs (images/ads, audio clips) plus web search beat raw API hacks, while helpers like gabriel.rate or gabriel.rank handle scale that trips up ad-hoc prompts. Devs grab it to skip the tedium of robust LLM pipelines.

Who should use this?

Social scientists scoring speeches/interviews for toxicity or bias, data scientists matching catalogs or filtering Wikipedia dumps, researchers extracting facts from product photos or transcripts. Econ/academic analysts processing qualitative corpora at scale, or anyone bridging GPT with pandas workflows.

Verdict

Strong pick for unstructured data quantifiers despite 10 stars and 1.0% credibility—OpenAI pedigree, thorough docs, and tests signal maturity beyond its youth. Test small before million-row jobs.

(198 words)

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