Unified framework for building enterprise RAG pipelines with small, specialized models
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Updated
Oct 29, 2024 - Python
Unified framework for building enterprise RAG pipelines with small, specialized models
Open-source framework to make AI agents' team collaboration as effective as human collaboration.
Vector Storage is a vector database that enables semantic similarity searches on text documents in the browser's local storage. It uses OpenAI embeddings to convert documents into vectors and allows searching for similar documents based on cosine similarity.
GGNN: State of the Art Graph-based GPU Nearest Neighbor Search
Swift Vector Database. On-device, local vector database for building the next-generation of user experiences
YouTubeGPT • AI Chat with 100+ videos ft. YouTuber Marques Brownlee (@ MKBHD) ⚡️🔴🤖💬
MovieGPT: A RAG, Gen AI application for Movie Recommendations
Benchmark study on LanceDB, an embedded vector DB, for full-text search and vector search
Slides for "Retrieval Augmented Generation" video
Unstract's interface to LLMs, Embeddings and VectorDBs.
Question Answering Generative AI application with Large Language Models (LLMs), Amazon Bedrock, and Amazon DocumentDB (with MongoDB Compatibility)
ChatGPT, embedding search, and retrieval-augmented generation for Squeak/Smalltalk
A web site crawler for semantic search.
A proof-of-concept of retrieval-augmented generation, using Google's PaLM API.
Automation of Prioritization and Categorization of Support Tickets Using LLMs and Vector DBs
This project generates question over a given corpus of information. It uses a LLM and the FAISS vector DB to acomplish the above mentioned objectives.
GeniusAI: Personalized AI companions powered by Llama 2 13B model. Engage in diverse conversations, explore personas, and revolutionize learning interactively.
Columbus is a cloud-based search platform for searching hosted cloud apps on your personal Kubernetes.
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