A cloud-native vector database, storage for next generation AI applications
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Updated
May 25, 2023 - Go
A cloud-native vector database, storage for next generation AI applications
Qdrant - Vector Database for the next generation of AI applications. Also available in the cloud https://cloud.qdrant.io/
Weaviate is an open source vector database that stores both objects and vectors, allowing for combining vector search with structured filtering with the fault-tolerance and scalability of a cloud-native database, all accessible through GraphQL, REST, and various language clients.
AI Vector Database for LLMs/LangChain. Doubles as a Data Lake for Deep Learning. Store, query, version, & visualize any data. Stream data in real-time to PyTorch/TensorFlow. https://activeloop.ai
The Virtual Feature Store. Turn your existing data infrastructure into a feature store.
ChatWeb can crawl web pages, read PDF, DOCX, TXT, and extract the main content, then answer your questions based on the content, or summarize the key points.
An easy to use Neural Search Engine. Index latent vectors along with JSON metadata and do efficient k-NN search.
The native Software 3.0 stack
Mercury - Train your own custom GPT. Chat with any file, or website.
Weaviate vector database – examples
Python client for Qdrant vector search engine
AI Chatbot for analyzing/extracting information from data in conversational format. Mainly PDF files...
A high-frequency Serving Database that supports point queries, upserts, and vector queries using the SQL mode (MySQL-Compatible) and KV mode (Redis-Compatible), while meeting the requirements of high concurrency and ultra-low latency.
Main NNext Application Code
GUI for editing LLM vector embeddings. Upload content in any file extension, join or split chunks, edit metadata, edit embedding tokens + remove stop-words and punctuation with one click, and download in .veml
GGNN: State of the Art Graph-based GPU Nearest Neighbor Search
Pinecone.io client with excellent TypeScript support.
How to create Question-Answering system combining Langchain and OpenAI
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