llm/Lib/site-packages/faiss_cpu-1.8.0.dist-info/METADATA

Metadata-Version: 2.1
Name: faiss-cpu
Version: 1.8.0
Summary: A library for efficient similarity search and clustering of dense vectors.
Author-email: Kota Yamaguchi <[email protected]>
License: MIT License
Project-URL: Repository, https://github.com/kyamagu/faiss-wheels
Keywords: faiss,similarity search,clustering,machine learning
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy

# faiss-wheels

[![Build](https://github.com/kyamagu/faiss-wheels/actions/workflows/build.yml/badge.svg)](https://github.com/kyamagu/faiss-wheels/actions/workflows/build.yml)
[![PyPI](https://img.shields.io/pypi/v/faiss-cpu?label=faiss-cpu)](https://pypi.org/project/faiss-cpu/)

faiss python wheel packages.

- [faiss](https://github.com/facebookresearch/faiss)

## Overview

This repository provides scripts to build wheel packages for the
[faiss](https://github.com/facebookresearch/faiss) library.

- Builds CPU-only version with [cibuildwheel](https://github.com/pypa/cibuildwheel/).
- Bundles OpenBLAS in Linux/Windows
- Uses Accelerate framework in macOS

There is also a source package to customize the build process.

> **Note**
> GPU package has been supported until version 1.7.2, but is not available since version 1.7.3 due to [the PyPI limitation](https://github.com/kyamagu/faiss-wheels/issues/57).

### Install

Install a binary package by:

```bash
pip install faiss-cpu
```

## Building source package

If there is a custom built faiss library in the system, build source package for
the best performance.

### Prerequisite

The source package assumes faiss is already built and installed in the system.
Build and install the faiss library first.

```bash
cd faiss
cmake . -B build -DFAISS_ENABLE_GPU=OFF -DFAISS_ENABLE_PYTHON=OFF -DFAISS_OPT_LEVEL=avx512
cmake --build build --config Release -j
cmake --install build install
cd ..
```

See the official
[faiss installation instruction](https://github.com/facebookresearch/faiss/blob/master/INSTALL.md)
for more on how to build and install faiss.

For building sdist, swig 3.0.12 or later needs to be available.

### Building a source distribution

The following builds and installs the faiss-cpu source package with AVX512.

```bash
export FAISS_OPT_LEVEL=avx512
pip install --no-binary :all: faiss-cpu
```

The following example builds a GPU wheel.

```bash
export FAISS_ENABLE_GPU=ON
pip install --no-binary :all: faiss-cpu
```

There are a few environment variables that specifies build-time options.
- `FAISS_INSTALL_PREFIX`: Specifies the install location of faiss library, default to `/usr/local`.
- `FAISS_OPT_LEVEL`: Faiss SIMD optimization, one of `generic`, `avx2`, `avx512`. Note that AVX option is only available in x86_64 arch.
- `FAISS_ENABLE_GPU`: Setting this variable to `ON` builds GPU wrappers. Set this variable if faiss is built with GPU support.
- `CUDA_HOME`: Specifies CUDA install location for building GPU wrappers, default to `/usr/local/cuda`.