Comparing LanceDB and Elasticsearch for full-text search and vector search performance
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Updated
Feb 8, 2026 - Python
Comparing LanceDB and Elasticsearch for full-text search and vector search performance
Unstract's interface to LLMs, Embeddings and VectorDBs.
A RAG assistant using Ollama (Mistral), Qdrant vector DB, and Streamlit UI. Upload documents, scrape web pages, and interact with your data using real-time, session-isolated chat.
The missing developer tool for working with vector databases. A comprehensive desktop app for visualizing, querying, and managing vector data.
Identify mountain peaks in your photos using AI—zero-shot retrieval, landmark re-ranking, and geospatial priors.
AI- & vector database-powered Quora question search
This project aims to create a comprehensive, searchable knowledge base from the online articles and forum posts of Dr. Ulrich Strunz. The final application will be a Dockerized service that uses a Large Language Model (LLM) accessed via the Meta-Cognitive Prompting (MCP) protocol to provide users with intelligent access to this knowledge.
🚀 An intelligent, LLM-enhanced log parser pipeline that converts multi-format raw logs into structured JSON, learns from missed patterns, and evolves using Drain3 & open-source LLMs.
Automation of Prioritization and Categorization of Support Tickets Using LLMs and Vector DBs
Comparative study evaluating performances of Milvus Vector-based RAG vs Neo4j Graph-based RAG systems for Enterprise Knowledge Retrieval
A proof-of-concept of retrieval-augmented generation, using Google's PaLM API.
A personalized AI product search engine using free-tier OpenRouter LLMs, MiniLM semantic search & Weaviate DB. https://medium.com/@rajesh1804/grocerygpt-how-i-built-a-personalized-grocery-search-engine-with-llms-vector-dbs-zero-cloud-fbacddf0feef
In this project, I made a resume scoring system. And it not only scores candidates based on Job Description & Resume but it can also have user profiles and their personal hiring preferences. So a particular user can filter Resume in bulk according to their personal preference. It also learns user preferences with time and evolves for each user.
A local semantic emoji search engine that uses transformer embeddings and sqlite vector search to find the perfect emoji from natural language queries. Fast, offline, and powered by Streamlit.
Local Retrieval-Augmented Generation (RAG) pipeline using LangChain and ChromaDB to query PDF files with LLMs.
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