sovit-123/local_file_search

Local file search using embedding techniques

34
/ 100
Emerging

This tool helps researchers, academics, or anyone with large collections of documents quickly find relevant information. You provide a directory of PDFs or text files, or even a CSV of research papers, and a natural language query. It then efficiently sifts through your documents and returns the most relevant files and even specific content snippets, saving you time from manually reading through thousands of papers. Ideal for anyone drowning in a sea of documents.

Use this if you need to perform quick, semantic searches across a large collection of local documents like research papers, reports, or articles to find specific content or files.

Not ideal if you need a persistent, multi-user document management system with advanced features like access control or complex metadata handling.

research-paper-discovery document-search academic-research information-retrieval literature-review
No Package No Dependents
Maintenance 6 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 7 / 25

How are scores calculated?

Stars

10

Forks

1

Language

Python

License

MIT

Last pushed

Oct 29, 2025

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/embeddings/sovit-123/local_file_search"

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