Cleans, parses, and compares semantic versions, providing essential insights into versioning, stability, and compatibility, making software release management a breeze!
-
Updated
Jun 11, 2024 - TypeScript
Cleans, parses, and compares semantic versions, providing essential insights into versioning, stability, and compatibility, making software release management a breeze!
Open source libraries and APIs to build custom preprocessing pipelines for labeling, training, or production machine learning pipelines.
Unified embedding generation and search engine. Also available on cloud - cloud.marqo.ai
Apache Lucene open-source search software
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.
Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
This is the homepage for my personal research activities, together with my students (Fani's Lab!)
MTEB: Massive Text Embedding Benchmark
Gen-AI Chat for Teams - Think ChatGPT if it had access to your team's unique knowledge.
Minimalist web-searching app with an AI assistant that runs directly from your browser. Uses Web-LLM, Ratchet-ML, Wllama and SearXNG. Demo: https://felladrin-minisearch.hf.space
Up to 200x Faster Inner Products and Vector Similarity — for Python, JavaScript, Rust, C, and Swift, supporting f64, f32, f16 real & complex, i8, and binary vectors using SIMD for both x86 AVX2 & AVX-512 and Arm NEON & SVE 📐
A production-grade search aggregator that scrapes web search results programatically using browser automation. 🌎
🍁 Sycamore is an LLM-powered search and analytics platform for unstructured data.
RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.
🔍 LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.
A semantic food search web application built with Django, Solr, SBERT, Docker and Heroku
cuVS - a library for vector search and clustering on the GPU
Harness LLMs with Multi-Agent Programming
Apache Solr open-source search software
All-in-One: Text Embedding, Retrieval, Rerank and RAG
Add a description, image, and links to the information-retrieval topic page so that developers can more easily learn about it.
To associate your repository with the information-retrieval topic, visit your repo's landing page and select "manage topics."