Build Semantic Search with S-BERT and Fine-tune your model in unsupervised way
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Updated
Apr 26, 2022 - Jupyter Notebook
Build Semantic Search with S-BERT and Fine-tune your model in unsupervised way
An easy-to-use vector database.
Search your data using nature language
LLM-assistant that searches PubMed, retrieves abstracts or full-texts, and generates answers using OpenAI ChatGPT. Features a custom RAG pipeline, semantic search, and knowledge graph generation.
Agentic RAG with LangGraph 🔥
A .NET-based AI project leveraging Retrieval-Augmented Generation (RAG) and OpenAI to provide efficient, intelligent search capabilities for team documentation.
🌟 Lumiere: Multi-agent RAG system with semantic memory. Combines LangGraph, Qdrant vector search, and OpenAI for intelligent document Q&A, SQL data analysis, and context-aware conversations. Features long-term learning, critic validation, and full observability.
Docker image of PostgreSQL with vector database extension **pgvector** on Alpine Linux.
RAG Chatbot that turns documents in Google Drive into a conversational AI. Uses OpenAI embeddings, Qdrant vector search, and Google Gemini for context-aware answers. Applied to large document collections, including legal texts, it drastically cuts search time and provides accurate responses grounded in multiple sources.
Sematic Cache is a semantic caching library that uses LanceDB for vector storage. It allowing caching of natural language queries based on semantic similarity rather than exact string matching.
Trivia game using Sematic web and Prolog, Little javascript with cool animations.
Developed a semantic search engine as part of the CS-328 Introduction to DataScience course, using word embeddings to retrieve semantically relevant documents. Explored approximate nearest neighbor (ANN) and hashing-based methods to strike a balance between retrieval accuracy and computational efficiency.
Conversational AI code assistant powered by Mistral & RAG. Explore codebases through natural language—ask questions, find functions, understand logic, and generate documentation. Uses vector embeddings for semantic search. Runs locally with Ollama for complete privacy. Zero API costs, your code never leaves your machine.
Backend for a RAG-powered news chatbot providing real-time AI responses, semantic search, and news retrieval using Node.js, Socket.IO, PostgreSQL, Redis, and Qdrant.
Semantic search engine for academic papers using AI embeddings with cloud database
Local-first agent architecture separating episodic (events) and semantic (facts) memory, with provenance tracking, defense-in-depth LLM sanitization, and multilingual support via Qwen-2.5 + BGE-M3.
🧠 Build a cognitive architecture for AI that mimics human memory, separating episodic and semantic memory while ensuring multilingual support and data integrity.
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