Open-source vector database built to embedding similarity search

An LLM based Chatbot using Langchain

Example code on how to upload and search a Qdrant Vector Database for Ai Chatbot Retrieval Frameworks

Testing PostgreSQL pgvector extension as a viable solution to embedding and querying text

Vector Search Application for Image Similarity Search, specifically designed for medical X-rays, leveraging ResNet50, Chest-XRay dataset and Milvus vector database

LanceDB Benchmark

🤖 DataSciencePilot 🚀 is an innovative chat-based interface designed to interact with custom PDF files. It leverages the power of Pinecone for efficient vector database management and LLaMA-2 for advanced query response capabilities.

console based game based on a llm

RAG-based Streamlit app that uses Langchain, OpenAI Embeddings, GPT, and Pinecone Vector Database to answer questions about a user-provided document

Retrieval Augmented Generation Example with SemaDB

🔎📚 This document processing system is designed to efficiently analyze user documents and provide accurate responses to user queries related to the content. Powered by advanced algorithms, it offers a seamless experience for users seeking insights or information within their documents.

ZipDocs is a fast document search and analysis platform that allows users to effortlessly comb through thousands of PDFs with blistering speed. Leveraging cutting-edge technology, BlitzDocs delivers near-zero latency search results, enabling users to quickly find and analyze relevant information buried within massive document repositorie

RAG-nificent is a state-of-the-art framework leveraging Retrieval-Augmented Generation (RAG) to provide instant answers and references from a curated directory of PDFs containing information on any given topic. Supports Llama3 and OpenAI Models via the Groq API.

Spring AI RAG vector store sentiment search on custom data loaded by tiko with a REST API.

PDF Chatbot, Image Chatbot, Web-Site Chatbot with a Knowledge base. OpenAI , Memory, PostgreSQL

A collection of Spring AI examples

Using CLIP or ViT to embedding image. Save the embeddings to Faiss and excute the query.