#rust #approximate_nearest_neighbor_search #embeddings_similarity #hnsw #image_search #knn_algorithm #machine_learning #matching #mlops #nearest_neighbor_search #neural_network #neural_search #recommender_system #search #search_engine #search_engines #similarity_search #vector_database #vector_search #vector_search_engine

https://github.com/qdrant/qdrant

#python #embeddings #information_retrieval #language_model #large_language_models #llm #machine_learning #nearest_neighbor_search #neural_search #nlp #search #search_engine #semantic_search #sentence_embeddings #similarity_search #transformers #txtai #vector_database #vector_search #vector_search_engine

https://github.com/neuml/txtai

#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

#go #anns #cloud_native #distributed #embedding_database #embedding_similarity #embedding_store #faiss #golang #hnsw #image_search #llm #nearest_neighbor_search #tensor_database #vector_database #vector_search #vector_similarity #vector_store

Milvus is an open-source vector database designed for embedding similarity search and AI applications. It makes unstructured data search more accessible and provides a consistent user experience across different deployment environments. Key features include millisecond search on trillion vector datasets, simplified unstructured data management, reliable and always-on operations, high scalability, and hybrid search capabilities. Milvus is cloud-native, supports multiple SDKs, and has a strong community with extensive documentation and support channels like Discord and mailing lists. Using Milvus benefits users by enabling fast and efficient vector searches, simplifying data management, and ensuring reliability and scalability in their applications.

https://github.com/milvus-io/milvus

#cplusplus #analytics #bigquery #cloud_native #cpp #database #distributed_database #distributed_transactions #hacktoberfest #htap #mysql #mysql_compatibility #mysql_database #oceanbase #olap #oltp #paxos #scalable #sql #vector_database

OceanBase Database is a powerful, distributed relational database developed by Ant Group. It offers several key benefits It can handle large amounts of data and scale easily.
- **Fast Performance** It saves up to 90% on storage costs.
- **Real-time Analytics** It ensures zero data loss and quick recovery times.
- **MySQL Compatibility**: It is easy to migrate from MySQL databases.

You can quickly start using OceanBase with simple deployment options using commands or Docker, making it easy to get started and benefit from its advanced features.

https://github.com/oceanbase/oceanbase

#javascript #agent_framework_javascript #ai_agents #crewai #custom_ai_agents #desktop_app #llama3 #llm #llm_application #llm_webui #lmstudio #local_llm #localai #multimodal #nodejs #ollama #rag #vector_database #webui

AnythingLLM is an all-in-one AI app that lets you chat with your documents, use AI agents, and manage multiple users without complicated setup. You can choose from various large language models (LLMs) and vector databases, and it supports different document types like PDF, TXT, and DOCX. It also has a simple chat interface with drag-and-drop functionality and clear citations. You can run it locally or host it remotely, and it includes features like custom AI agents, multi-modal support, and cost-saving measures for managing large documents. This makes it easy to use AI with your documents in a flexible and efficient way.

https://github.com/Mintplex-Labs/anything-llm

#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

#typescript #chatbot #cot #graphrag #knowledge_graph #mysql #rag #serverless #vector_database

TiDB.AI is a free and open-source tool that helps you find information easily. It uses a Knowledge Graph built on top of TiDB Vector, LlamaIndex, and DSPy. You can use it to search for information in a conversational way, similar to talking to a person. It also allows you to edit the knowledge graph to make sure the information is accurate. You can even add a search widget to your website with just a few lines of code. This makes it easier for users to get quick answers to their questions, improving their overall experience.

https://github.com/pingcap/autoflow

#other #chatbot #hugging_face #llm #llm_local #llm_prompting #llm_security #llmops #machine_learning #open_ai #pathway #rag #real_time #retrieval_augmented_generation #vector_database #vector_index

Pathway's AI Pipelines help you quickly create and deploy AI applications with high accuracy. These pipelines use the latest knowledge from your data sources and offer ready-to-deploy templates for large language models. You can test these apps on your own machine and deploy them on cloud services like GCP, AWS, or Azure, or on-premises. The apps connect to various data sources such as file systems, Google Drive, and databases, and they include built-in data indexing for efficient searches. This makes it easy to extract and organize data from documents in real-time, reducing the need for separate infrastructure setups. This simplifies the process of building and maintaining AI applications, saving you time and effort.

https://github.com/pathwaycom/llm-app

#python #agent #ai #aiagent #application #chatbots #chatgpt #embeddings #llm #long_term_memory #memory #memory_management #python #rag #state_management #vector_database

Mem0 is a special tool that helps AI systems remember things. It makes AI interactions more personal and efficient by storing user preferences and past conversations. This means you don't have to repeat information, and the AI can give better answers based on what it knows about you. Mem0 also saves money by only sending important data to AI models, reducing costs up to 80%. It's easy to use and works with popular AI platforms like OpenAI and Claude.

https://github.com/mem0ai/mem0

#python #agents #knowledge_graph #llm #llm_agent #rag #search #search_agent #vector_database

Airweave is a tool that helps make information from apps and databases easily accessible to AI agents. It connects over 100 data sources with minimal coding, allowing for fast data synchronization and semantic search. This means you can quickly turn app data into useful knowledge for AI agents, making them smarter and more efficient. It's especially helpful for tasks like customer support or generating reports, as it ensures AI agents have the most accurate and up-to-date information.

https://github.com/airweave-ai/airweave

#python #ai #ai_agents #ai_memory #cognitive_architecture #cognitive_memory #contributions_welcome #good_first_issue #good_first_pr #graph_database #graph_rag #graphrag #help_wanted #knowledge #knowledge_graph #neo4j #open_source #openai #rag #vector_database

Cognee is an open-source AI memory engine that helps improve how AI systems understand and process data. It mimics human cognitive processes, creating "memories" from various data types like text and images. This enhances the accuracy of large language models (LLMs) and allows them to recall past interactions and documents. Cognee is scalable, cost-effective, and integrates easily with existing systems, making it a valuable tool for developers seeking to boost AI performance without relying on expensive APIs.

https://github.com/topoteretes/cognee

#java #anthropic #chatgpt #chroma #embeddings #gemini #gpt #huggingface #java #langchain #llama #milvus #ollama #onnx #openai #openai_api #pgvector #pinecone #vector_database #weaviate

LangChain4j helps you add powerful AI to your Java applications by making it easy to use Large Language Models (LLMs). It provides a simple way to switch between different LLMs and embedding stores without needing to learn each one's specific API. This means you can easily experiment with different models and tools, making your development process faster and more flexible. LangChain4j also offers many examples and tools to help you build complex AI applications quickly, such as chatbots and retrieval systems. This simplifies the integration of AI into your projects, allowing you to focus on creating better applications.

https://github.com/langchain4j/langchain4j

#typescript #agents #ai #embedders #genkit #llm #machine_learning #multimodal #rag #vector_database

Genkit is an open-source framework by Google Firebase that helps you easily build AI-powered apps using a single interface to connect many AI models like Google Gemini, OpenAI, and Anthropic. It supports JavaScript/TypeScript (stable), Go (beta), and Python (alpha), letting you create chatbots, automations, and recommendations quickly with simple code. Genkit works well with web and mobile platforms, offers tools for testing and debugging AI features locally, and lets you deploy and monitor your AI apps on Firebase or other cloud services. This saves you time and effort in developing and managing AI applications efficiently.

https://github.com/firebase/genkit

#python #ai #context #embedded #faiss #knowledge_base #knowledge_graph #llm #machine_learning #memory #nlp #offline_first #opencv #python #rag #retrieval_augmented_generation #semantic_search #vector_database #video_processing

Memvid lets you store millions of text pieces inside a single MP4 video file using QR codes, making your data 50-100 times smaller than usual databases. You can search this video instantly in under 100 milliseconds without needing servers or internet after setup. It works offline, is easy to use with simple Python code, and supports PDFs and chat with your data. The upcoming version 2 will add features like continuous memory updates, shareable capsules, fast local caching, and better video compression, making your AI memory smarter, faster, and more flexible. This means you get a powerful, portable, and efficient way to manage and search huge knowledge bases quickly and easily.

https://github.com/Olow304/memvid

#python #agent #context_engineering #electron #embedding_models #memory #proactive_ai #python #python3 #rag #react #vector_database #vision_language_model

MineContext is a special AI tool that helps you work more efficiently. It collects information from your computer screen and other sources, then uses this data to give you useful insights, summaries, and reminders. This helps you stay organized and focused on important tasks. MineContext is also very private because it stores all your data on your local device, not in the cloud. It's like having a personal assistant that helps you manage your digital life better.

https://github.com/volcengine/MineContext

#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