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update - remove shields
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michaelfeil committed Mar 15, 2024
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<!-- PROJECT SHIELDS -->
<!--
*** I'm using markdown "reference style" links for readability.
*** Reference links are enclosed in brackets [ ] instead of parentheses ( ).
*** See the bottom of this document for the declaration of the reference variables
*** for contributors-url, forks-url, etc. This is an optional, concise syntax you may use.
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[![Contributors][contributors-shield]][contributors-url]
[![Forks][forks-shield]][forks-url]
[![Stargazers][stars-shield]][stars-url]
[![Issues][issues-shield]][issues-url]
[![MIT License][license-shield]][license-url]
[![LinkedIn][linkedin-shield]][linkedin-url]

# Infinity ♾️
[![codecov][codecov-shield]][codecov-url]
[![ci][ci-shield]][ci-url]
[![Downloads][pepa-shield]][pepa-url]

Infinity is a high-throughput, low-latency REST API for serving vector embeddings, supporting all sentence-transformer models and frameworks. Infinity is developed under [MIT Licence](https://github.com/michaelfeil/infinity/blob/main/LICENSE). Infinity powers inference behind [Gradient.ai](https://gradient.ai).

## Why Infinity:
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- **Correct and tested implementation**: Unit and end-to-end tested. Embeddings via infinity are identical to [SentenceTransformers](https://github.com/UKPLab/sentence-transformers/) (up to numerical precision). Lets API users create embeddings till infinity and beyond.
- **Easy to use**: The API is built on top of [FastAPI](https://fastapi.tiangolo.com/), [Swagger](https://swagger.io/) makes it fully documented. API are aligned to [OpenAI's Embedding specs](https://platform.openai.com/docs/guides/embeddings/what-are-embeddings). See below on how to get started.

# Infinity demo:
In this gif below, we use [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2), deployed at batch-size=2. After initialization, from a second terminal 3 requests (payload 1,1,and 5 sentences) are sent via cURL.
![](docs/demo_v0_0_1.gif)

# Getting started

Install via pip
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