EulerSearch/embedding_studio
Embedding Studio is a framework which allows you transform your Vector Database into a feature-rich Search Engine.
This helps businesses with large, evolving content catalogs create smart, personalized search experiences. It takes your existing data and user interactions to continuously improve search results, providing more relevant outcomes over time. Marketing managers, e-commerce platform owners, or content strategists would find this valuable for enhancing user engagement and content discovery.
383 stars. No commits in the last 6 months.
Use this if you manage a platform with extensive and dynamic content, and you want your search to automatically get better and more personalized based on what users actually click on.
Not ideal if you have a static, small collection of data where search relevance doesn't need to adapt or improve over time based on user feedback.
Stars
383
Forks
5
Language
Python
License
Apache-2.0
Category
Last pushed
Apr 24, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/embeddings/EulerSearch/embedding_studio"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
yuniko-software/bge-m3-onnx
ONNX implementation of the BGE-M3 multilingual embedding model and tokenizer with native C#,...
substratusai/stapi
Sentence Transformers API: An OpenAI compatible embedding API server
turian/embeddingcache
Retrieve text embeddings, but cache them locally if we have already computed them.
faisal-fida/Text-Embeddings-API
This project provides a REST API for generating text embeddings using the Sentence Transformers...
maxsagt/lambda-instructor
Run text embeddings with Instructor-Large on AWS Lambda.