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Multi-arch bindings for @huggingface/tokenizers.

Access to HuggingFace datasets via Clojure

Your AI/ML research, on one deck — aggregate arXiv/HF/Semantic Scholar papers, star them, and read in-app with cross-device scroll resume.

Speech Assessment API in FastAPI with HuggingFace 🤗

Flask API for generating text embeddings using OpenAI or sentence_transformers

A repository of technical articles on AI algorithms, model finetuning, AI agents, open-source libraries, and system design. Perfect for researchers and enthusiasts looking for in-depth insights.

SAM + CLIP + DIFFUSION for image to edit objects in images using plain text

PDF to Word converter is an easy-to-use, in-browser tool that allows you to quickly and securely export a PDF to a Microsoft Word file format (.doc) ...

Vectrain is a high-performance, modular, plug-and-play RAG pipeline that ingests data, generates vector embeddings, and stores them in vector databases for semantic search, recommendations, and analytics.

PTIT's Major Project: Website Programming - This repo contains a chatbot for a clothing store. The chatbot acts as an employee with specific knowledge about clothing consultation, website support, and store information.

PostgreSQL TurboQuant Index for PGVector

Open-source persistent memory infrastructure for LLM applications.🐬

using mulimodal RAG to query texts, images and tables from pdf for QA

Web Vector Storage (WVS) is a lightweight and efficient vector database that stores document vectors in the browser's IndexedDB. It supports perform semantic similarity searches on text documents using vector embeddings. Embedding is enabled through use of OpenAI, Ollama or HuggingFace Transformer embedding models.

A Node.js RESTful server for a Retrieval-Augmented Generation (RAG) system using ChromaDB and Ollama!

A repository of curated use cases, articles, blogs, videos on how companies are using Artificial Intelligence and Machine Learning.

Multi-User Chatbot with Langchain and Pinecone in Next.JS

Persistent semantic memory for AI agents on Raspberry Pi 5 — local Qdrant + MCP, no cloud, ~3s per query

Practical GenAI-Eshop application using Semantic Kernel, multi-agent orchestrations, Mcp tools, A2A Agents, Semantic Search, Aspire and more.

Model Context Protocol (MCP) server implementation for semantic vector search and memory management using TxtAI. This server provides a robust API for storing, retrieving, and managing text-based memories with semantic vector database search capabilities. You can use Claude and Cline AI as well.