local-first semantic code search engine
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Updated
Jul 15, 2024 - Python
local-first semantic code search engine
🔎 SimilaritySearchKit is a Swift package providing on-device text embeddings and semantic search functionality for iOS and macOS applications.
YouTubeGPT • AI Chat with 100+ videos ft. YouTuber Marques Brownlee (@ MKBHD) ⚡️🔴🤖💬
AI chat over the US Constitution 📜 💬 🇺🇸
Find Python Packages on PyPI with the help of vector embeddings
YouTubeGPT • AI Chat with 100+ videos ft. YouTuber Matt Wolfe (@mreflow) 🐺🟣🤖💬
UC Berkeley CS186 AI Chatbot 🤖 🖥️ 🐻
AI Chat with The ₿itcoin Whitepaper
Semantic QA with a markdown database: Query any markdown file using vector embedding, Pinecone vector database and GPT (langchain). A weaker version of privateGPT
V3CTRON | Vector Embeddings Data Retrieval | ChatGPT Plugin
Python scripts that converts PDF files to text, splits them into chunks, and stores their vector representations using GPT4All embeddings in a Chroma DB. It also provides a script to query the Chroma DB for similarity search based on user input.
UC Berkeley EE16B AI Chatbot 🤖 🖥️ 🐻
This tool provides a fast and efficient way to convert text into vector embeddings and store them in the Qdrant search engine. Built with Rust, this tool is designed to handle large datasets and deliver lightning-fast search results.
Flask API for generating text embeddings using OpenAI or sentence_transformers
Semantic search with openai's embeddings stored to pineconedb (vector database)
Text to Image & Reverse Image Search Engine built upon Vector Similarity Search utilizing CLIP VL-Transformer for Semantic Embeddings & Qdrant as the Vector-Store
Nicolay is a digital history experiment that uses artificial intelligence to explore the speeches of Abraham Lincoln.
Vector Embedding Representations of Road Cycling Riders and Races
Image Vector Similarity Search with Azure AI Vision (Florence model) and Azure Cosmos DB for PostgreSQL
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.
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