#go #classification #contextual_search #database #deep_learning #deep_search #graphql #knn_search #machine_learning #neural_search #restful_api #search_engine #search_engines #semantic_search #semantic_search_engine #vector_database #vector_search #vector_search_engine #vectors #weaviate
https://github.com/semi-technologies/weaviate
https://github.com/semi-technologies/weaviate
GitHub
GitHub - weaviate/weaviate: Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination…
Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of ...
#go #approximate_nearest_neighbor_search #generative_search #grpc #hnsw #hybrid_search #image_search #information_retrieval #mlops #nearest_neighbor_search #neural_search #recommender_system #search_engine #semantic_search #semantic_search_engine #similarity_search #vector_database #vector_search #vector_search_engine #vectors #weaviate
Weaviate is a powerful, open-source vector database that uses machine learning to make your data searchable. It's fast, scalable, and flexible, allowing you to vectorize your data at import or upload your own vectors. Weaviate supports various modules for integrating with popular AI services like OpenAI, Cohere, and Hugging Face. It's designed for production use with features like scaling, replication, and security. You can use Weaviate for tasks beyond search, such as recommendations, summarization, and integration with neural search frameworks. It offers APIs in GraphQL, REST, and gRPC and has client libraries for several programming languages. This makes it easy to build applications like chatbots, recommendation systems, and image search tools quickly and efficiently. Joining the Weaviate community provides access to tutorials, demos, blogs, and forums to help you get started and stay updated.
https://github.com/weaviate/weaviate
Weaviate is a powerful, open-source vector database that uses machine learning to make your data searchable. It's fast, scalable, and flexible, allowing you to vectorize your data at import or upload your own vectors. Weaviate supports various modules for integrating with popular AI services like OpenAI, Cohere, and Hugging Face. It's designed for production use with features like scaling, replication, and security. You can use Weaviate for tasks beyond search, such as recommendations, summarization, and integration with neural search frameworks. It offers APIs in GraphQL, REST, and gRPC and has client libraries for several programming languages. This makes it easy to build applications like chatbots, recommendation systems, and image search tools quickly and efficiently. Joining the Weaviate community provides access to tutorials, demos, blogs, and forums to help you get started and stay updated.
https://github.com/weaviate/weaviate
GitHub
GitHub - weaviate/weaviate: Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination…
Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of ...
#typescript #ai #alternative #auth #database #deno #embeddings #example #firebase #nextjs #oauth2 #pgvector #postgis #postgres #postgresql #postgrest #realtime #supabase #vectors #websockets
Supabase is an open-source alternative to Firebase, built using enterprise-grade tools. It offers a hosted Postgres database, authentication and authorization, auto-generated APIs (REST, GraphQL, and realtime subscriptions), functions, file storage, and an AI toolkit. You can use it without installing anything or self-host it. Supabase supports multiple programming languages and has a strong community for support and discussions. This means you get powerful database and application features similar to Firebase but with the flexibility and transparency of open-source software, which can be more customizable and cost-effective.
https://github.com/supabase/supabase
Supabase is an open-source alternative to Firebase, built using enterprise-grade tools. It offers a hosted Postgres database, authentication and authorization, auto-generated APIs (REST, GraphQL, and realtime subscriptions), functions, file storage, and an AI toolkit. You can use it without installing anything or self-host it. Supabase supports multiple programming languages and has a strong community for support and discussions. This means you get powerful database and application features similar to Firebase but with the flexibility and transparency of open-source software, which can be more customizable and cost-effective.
https://github.com/supabase/supabase
GitHub
GitHub - supabase/supabase: The Postgres development platform. Supabase gives you a dedicated Postgres database to build your web…
The Postgres development platform. Supabase gives you a dedicated Postgres database to build your web, mobile, and AI applications. - supabase/supabase
#rust #app_search #database #enterprise_search #faceting #full_text_search #fuzzy_search #geosearch #hybrid_search #instantsearch #rest #rust #search #search_as_you_type #search_engine #semantic_search #site_search #synonyms #typo_tolerance #vector_database #vectors
Meilisearch is a fast and powerful search engine that you can easily integrate into your apps, websites, and workflow. It offers features like hybrid search, search-as-you-type, typo tolerance, filtering, and sorting to enhance the user experience. You can customize it to fit your needs with support for multiple languages and advanced security management. It's easy to install, deploy, and maintain, and you can use their cloud service for added convenience. Meilisearch also provides extensive documentation, SDKs for various programming languages, and a supportive community through Discord and other channels. This makes it a great tool to supercharge your search capabilities quickly and efficiently.
https://github.com/meilisearch/meilisearch
Meilisearch is a fast and powerful search engine that you can easily integrate into your apps, websites, and workflow. It offers features like hybrid search, search-as-you-type, typo tolerance, filtering, and sorting to enhance the user experience. You can customize it to fit your needs with support for multiple languages and advanced security management. It's easy to install, deploy, and maintain, and you can use their cloud service for added convenience. Meilisearch also provides extensive documentation, SDKs for various programming languages, and a supportive community through Discord and other channels. This makes it a great tool to supercharge your search capabilities quickly and efficiently.
https://github.com/meilisearch/meilisearch
GitHub
GitHub - meilisearch/meilisearch: A lightning-fast search engine API bringing AI-powered hybrid search to your sites and applications.
A lightning-fast search engine API bringing AI-powered hybrid search to your sites and applications. - meilisearch/meilisearch
#python #ai #faiss #gpt_oss #langchain #llama_index #llm #localstorage #offline_first #ollama #privacy #python #rag #retrieval_augmented_generation #vector_database #vector_search #vectors
LEANN is a tiny, powerful vector database that lets you turn your laptop into a personal AI assistant capable of searching millions of documents using 97% less storage than traditional systems without losing accuracy. It works by storing a compact graph and computing embeddings only when needed, saving huge space and keeping your data private on your device. You can search your files, emails, browser history, chat logs, live data from platforms like Slack and Twitter, and even codebases—all locally without cloud costs. This means fast, private, and efficient AI-powered search and retrieval on your own laptop.
https://github.com/yichuan-w/LEANN
LEANN is a tiny, powerful vector database that lets you turn your laptop into a personal AI assistant capable of searching millions of documents using 97% less storage than traditional systems without losing accuracy. It works by storing a compact graph and computing embeddings only when needed, saving huge space and keeping your data private on your device. You can search your files, emails, browser history, chat logs, live data from platforms like Slack and Twitter, and even codebases—all locally without cloud costs. This means fast, private, and efficient AI-powered search and retrieval on your own laptop.
https://github.com/yichuan-w/LEANN
GitHub
GitHub - yichuan-w/LEANN: RAG on Everything with LEANN. Enjoy 97% storage savings while running a fast, accurate, and 100% private…
RAG on Everything with LEANN. Enjoy 97% storage savings while running a fast, accurate, and 100% private RAG application on your personal device. - yichuan-w/LEANN