VikParuchuri/researcher

Concise answers to search queries using Google and GPT-3. Includes citations.

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Implements a retrieval-augmented generation pipeline that scrapes Google results, extracts ranked text chunks via semantic matching, and feeds them to GPT-3 for summarization—eliminating hallucinations through grounded context. Supports both web scraping and Google Custom Search API modes, stores scraped HTML in SQLite for efficiency, and filters low-quality sources by ad/tracker density. Runs as a Flask web application with configurable chunk length and result counts to balance latency (10-20s per query) against summary quality.

No commits in the last 6 months.

Archived Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 9 / 25
Maturity 16 / 25
Community 10 / 25

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Stars

82

Forks

6

Language

Python

License

MIT

Category

rag-document-qa

Last pushed

Dec 28, 2022

Commits (30d)

0

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