Rust library for generating vector embeddings, reranking. Re-write of qdrant/fastembed.
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Updated
Dec 17, 2025 - Rust
Rust library for generating vector embeddings, reranking. Re-write of qdrant/fastembed.
Suite of tools containing an in-memory vector datastore and AI proxy
Chat with Lex! A RAG app, using HyDE with milvus DB for vector store, VLLM for LLM inference, and FastEmbed for Embeddings!
Generating embedding for 1000s of PDF Documents, in Qdrant using FastEmbed with distributed Computing in Ray
🧠 Universal long-term memory for AI agents. GraphRAG-powered knowledge base with vector search + graph traversal. Privacy-first, local-only, MCP-compatible. Connect Claude, Copilot, or any AI assistant.
ExFastembed is an Elixir wrapper around the fastembed-rs crate.
Using Qdrant, Fastembed, Google Cloud, OpenAI to build a Question Answer Cloud Based RAG System
A high-performance, Rust-based in-memory vector store with FastEmbed integration for Python applications.
⚡ Instantly index, deduplicate, and search your code, docs, and web content in a blazing-fast Qdrant vector DB for AI & RAG.
MedSage is a multimodal healthcare assistant that combines LLMs, vector search, and real-time reasoning to deliver fast, reliable medical insights. It supports symptom analysis, medical document Q&A, universal file RAG, multilingual interactions, and emergency SOS with live location.
A library to gather structured statistics on the source code files in a software repository, generate embeddings and store in a vector database.
An AI + RAG system delivering culturally contextualized nutritional intelligence, personalized caloric guidance, and queryable knowledge over Indian Food Composition Tables (IFCT).
Demo for SenTrEv python package
Data Retrieval from Qdrant Vector DB based on RRF algo and metadata filtering
AI-Powered Employee Skill & Project Recommendation System An intelligent system that recommends roles and training programs based on employee skills, leveraging AI for personalized career development and project matching.
deadpool implementation for fastembed
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