GitHub - zilliztech/feder: Visualize hnsw, faiss and other anns index
GitHub - comfyanonymous/ComfyUI: The most powerful and modular stable diffusion GUI, api and backend with a graph/nodes interface.
github.com
There are numerous integrations for vector storage. These include Alibaba Cloud OpenSearch, AnalyticDB for PostgreSQL, Meta AI’s Annoy library for Approximate Nearest Neighbor (ANN) search, Cassandra, Chroma, Elasticsearch, Facebook AI Similarity Search (Faiss), MongoDB Atlas Vector Search, PGVector as a vector similarity search for Postgres, Pinec
... See moreBen Auffarth • Generative AI with LangChain: Build large language model (LLM) apps with Python, ChatGPT, and other LLMs
AI Image Search with Amazon Bedrock and Supabase Vector in Python
youtube.comOpen source, high-throughput, fault-tolerant vector embedding pipeline
Simple API endpoint that ingests large volumes of raw data, processes, and stores or returns the vectors quickly and reliably
Simple API endpoint that ingests large volumes of raw data, processes, and stores or returns the vectors quickly and reliably
dgarnitz • GitHub - dgarnitz/vectorflow: VectorFlow is a high volume vector embedding pipeline that ingests raw data, transforms it into vectors and writes it to a vector DB of your choice.
Vector libraries, like Facebook (Meta) Faiss or Spotify Annoy, provide functionality for working with vector data. In the context of vector search, a vector library is specifically designed to store and perform similarity search on vector embeddings.
Ben Auffarth • Generative AI with LangChain: Build large language model (LLM) apps with Python, ChatGPT, and other LLMs
GitHub - fmhy/FMHY: /r/FREEMEDIAHECKYEAH
github.com
Vector databases can be used to store and serve machine learning models and their corresponding embeddings. The primary application is similarity search (also semantic search),