Unified framework for building enterprise RAG pipelines with small, specialized models
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Updated
Aug 13, 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
YouTubeGPT • AI Chat with 100+ videos ft. YouTuber Marques Brownlee (@ MKBHD) ⚡️🔴🤖💬
Swift Vector Database. On-device, local vector database for building the next-generation of user experiences
Benchmark study on LanceDB, an embedded vector DB, for full-text search and vector search
Columbus is a cloud-based search platform for searching hosted cloud apps on your personal Kubernetes.
GeniusAI: Personalized AI companions powered by Llama 2 13B model. Engage in diverse conversations, explore personas, and revolutionize learning interactively.
A proof-of-concept of retrieval-augmented generation, using Google's PaLM API.
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)
MovieGPT: A RAG, Gen AI application for Movie Recommendations
Slides for "Retrieval Augmented Generation" video
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.
A web site crawler for semantic search.
Automation of Prioritization and Categorization of Support Tickets Using LLMs and Vector DBs
ChatGPT, embedding search, and retrieval-augmented generation for Squeak/Smalltalk
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