#python #artificial_intelligence #audio_processing #deep_learning #deeplearning #embeddings #encodings #image2vec #machine_learning #neural_network #pytorch #tensorflow #tfhub #transformers #vector #vector_similarity #video_processing #word2vec

https://github.com/vector-ai/vectorhub

#python #computer_vision #convolutional_networks #embedding_vectors #embeddings #feature_extraction #feature_vector #image_processing #image_retrieval #machine_learning #milvus #pipeline #towhee #transformer #unstructured_data #video_processing #vision_transformer #vit

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

#other #computer_vision #deep_learning #embeddings #machine_learning #nlp #recommender_system #reinforcement_learning #survey

https://github.com/eugeneyan/ml-surveys

#rust #apache_arrow #computer_vision #data_analysis #data_analytics #data_centric #data_format #data_science #dataops #deep_learning #duckdb #embeddings #machine_learning #mlops #python

https://github.com/eto-ai/lance

#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 #artificial_intelligence #asyncio #bot #chatbot #dalle2 #deepl #discord #embeddings #extractive_question_answering #fault_tolerant #gpt3 #help_wanted #image_generator #moderation #moderator_bot #openai #openai_api #pinecone #translator

https://github.com/Kav-K/GPT3Discord

#python #document_retrieval #embeddings #llms

https://github.com/chroma-core/chroma

#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

#python #computer_vision #contrastive_learning #contributions_welcome #deep_learning #embeddings #hacktoberfest #machine_learning #pytorch #self_supervised_learning

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

#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

#python #ai #cv #data_analytics #data_wrangling #embeddings #llm #llm_eval #machine_learning #mlops #multimodal

DataChain is a powerful tool for managing and processing large amounts of data, especially useful for artificial intelligence tasks. It helps you organize unstructured data from various sources like cloud storage or local files into structured datasets. You can process this data efficiently using Python, without needing SQL or Spark, and even use local AI models or APIs to enrich your data. Key benefits include parallel processing, out-of-memory computing, and optimized vector searches, making it faster and more efficient. Additionally, DataChain integrates well with popular libraries like PyTorch and TensorFlow, allowing you to easily export data for further analysis or training models. This makes it easier to handle complex data tasks and improves your overall workflow.

https://github.com/iterative/datachain

#jupyter_notebook #amazon_bedrock #amazon_titan #bedrock #embeddings #generative_ai #knowledge_base #langchain #rag

This repository provides pre-built examples to help you get started with Amazon Bedrock, a service for working with generative AI. You can learn the basics of Bedrock, how to craft effective prompts, implement AI agents, import custom models, and more. It also includes guides on responsible AI use, productionizing workloads, and improving model observability. To use these examples, ensure you have the necessary AWS IAM permissions and follow the detailed instructions in each folder. This resource helps you quickly and effectively use Amazon Bedrock for various AI tasks, making it easier to integrate generative AI into your projects.

https://github.com/aws-samples/amazon-bedrock-samples

#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

#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

#go #agent #agentic #ai #chatbot #chatbots #embeddings #evaluation #generative_ai #golang #knowledge_base #llm #multi_tenant #multimodel #ollama #openai #question_answering #rag #reranking #semantic_search #vector_search

WeKnora is a powerful tool that helps you understand and find answers in complex documents like PDFs and Word files. It uses advanced AI to read documents, understand what they mean, and answer your questions in a simple way. This tool is useful for businesses and researchers because it can quickly find information from many documents, making it easier to manage knowledge and make decisions. It also supports multiple languages and can be used privately, ensuring your data stays safe.

https://github.com/Tencent/WeKnora