Skip to main content

Found! is an AI enabled tool for fast semantic search over your personal documents.

Project description

Found!

Found! is a command-line tool for fast semantic search over your personal documents using vector embeddings and FAISS. It is designed to be simple, fast, and privacy-friendly, running entirely on your machine.

Features

  • Semantic search for documents using natural language queries
  • Fast similarity search powered by FAISS
  • Caches document embeddings and index for speed
  • Rich CLI interface with Typer

Installation and Usage with uv/uvx

Found! is compatible with uv and uvx for fast Python package management and execution.

1. Install uv (if not available)

See the official uv installation instructions for the recommended standalone installer and platform-specific details.

2. Install found with uv

uv tool install --git https://github.com/clssn/found.git

Usage

Search for a document

found doc "your query"

Options

  • --document-dir, -d: Specify the directory containing documents (default: ~/Documents)
  • --verbose, -v: Enable debug logging

Example

found doc "Tax certificate 2024" -d ~/Documents

How it works

  • Recursively lists files in the specified document directory
  • Generates semantic embeddings for each document using SentenceTransformers
  • Builds a FAISS index for fast similarity search
  • Caches the index and document list for future queries
  • Returns the best matching document for your query

Requirements

License

MIT

Contributing

Pull requests and issues are welcome!


Made with ❤️ by clssn

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pyfound-0.1.3.tar.gz (46.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

pyfound-0.1.3-py3-none-any.whl (5.1 kB view details)

Uploaded Python 3

File details

Details for the file pyfound-0.1.3.tar.gz.

File metadata

  • Download URL: pyfound-0.1.3.tar.gz
  • Upload date:
  • Size: 46.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.7.17

File hashes

Hashes for pyfound-0.1.3.tar.gz
Algorithm Hash digest
SHA256 fbbbc97b429eeb7b8bfa99039a32f70a1dc3d317a8ffac31b93f59a395b97bb9
MD5 9eb9d124234f21dae6e2265109055446
BLAKE2b-256 1ff742af5054c2f94e7dbb753aa6d8e5b9a26c96715c8cc3eaa10947fdcfd33e

See more details on using hashes here.

File details

Details for the file pyfound-0.1.3-py3-none-any.whl.

File metadata

  • Download URL: pyfound-0.1.3-py3-none-any.whl
  • Upload date:
  • Size: 5.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.7.17

File hashes

Hashes for pyfound-0.1.3-py3-none-any.whl
Algorithm Hash digest
SHA256 67836023a1df6e6b2f54ce2e142e97204d0b6d3431e93a8a0dc581ae29fa7636
MD5 d9ec1688b57377e4b72e805f8cf9ca2b
BLAKE2b-256 2e885b4ee6ec2fd8786ddd4bdda8312166f0161cdf0c81ce47ac5d7c81feaf8b

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page