local-first semantic code search engine
-
Updated
May 29, 2024 - Python
local-first semantic code search engine
Nicolay is a digital history experiment that uses artificial intelligence to explore the speeches of Abraham Lincoln.
This repository demonstrates a workflow that integrates LangChain with a vector store (Pinecone) to enable semantic search and question answering using large language models (LLMs).
Pawsitive Retrieval RAG Project - Erdos Institute Deep Learning Boot Camp - Spring 2024
Build Generative AI, custom Question/Answer or Information Retrival Application using LlamaIndex, Google Gemini
🔎 SimilaritySearchKit is a Swift package providing on-device text embeddings and semantic search functionality for iOS and macOS applications.
Hands-on with Milvus vector db
Advance Resume Parser: This project was built during the Mined Hackathon organized by Nirma University.
Learning semantic embeddings from OSM data: A Pytorch implementation of the loc2vec general method outlined in: https://sentiance.com/loc2vec-learning-location-embeddings-w-triplet-loss-networks.
AI Chatbot with Knowledge Base embeddings (prototype)
Seamlessly interact with PDF, CSV, Website and Handwritten Notes
Image Vector Similarity Search with Azure AI Vision (Florence model) and Azure Cosmos DB for PostgreSQL
Know Your Docs: Upload your documents and get instant answers to any questions related to them with this document knowledge platform
YouTubeGPT • AI Chat with 100+ videos ft. YouTuber Marques Brownlee (@ MKBHD) ⚡️🔴🤖💬
Text to Image & Reverse Image Search Engine built upon Vector Similarity Search utilizing CLIP VL-Transformer for Semantic Embeddings & Qdrant as the Vector-Store
AI chat with Tim Ferriss or any of his past guests
Add a description, image, and links to the vector-embeddings topic page so that developers can more easily learn about it.
To associate your repository with the vector-embeddings topic, visit your repo's landing page and select "manage topics."