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LangChain is an open-source framework that integrates with various vector databases, including Pinecone, Weaviate, and Chroma, to facilitate retrieval-augmented generation (RAG) and advanced AI workflows.
Langflow is a platform that simplifies building AI agents by connecting models, vector stores, memory, and other AI building blocks. It is relevant to vector databases as it supports integration with vector stores for AI-powered agents.
A library by Google Research for efficient vector similarity search, suitable for large-scale nearest neighbor applications in AI.
txtai is an open-source AI framework that provides semantic search and vector database capabilities for language model workflows.
Deep Lake is a vector database designed as a data lake for AI, capable of storing and managing vector embeddings, text, images, and videos. It utilizes a tensor format for efficient querying and integration with AI algorithms, making it suitable for similarity search and machine learning workflows. It is open-source and tailored for handling unstructured and multimodal data, with seamless integration with frameworks like PyTorch and TensorFlow.
Marqo is an open-source neural search engine that leverages vector representations to enable semantic search over textual data. It abstracts vector database complexity and provides a high-level interface for building advanced search applications.
LangChain is an open-source framework designed for building applications with large language models (LLMs). It enables integration with various data sources and APIs to support advanced AI workflows, including retrieval-augmented generation (RAG).
No specific pricing details for LangChain itself are provided on the website; LangChain is open-source. Pricing information is available for related products (LangSmith, LangGraph Platform) but not for the core LangChain framework.
open-source, rag, ai, integration
SDKs & Libraries