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A re-ranking tool provided by Cohere, which can be integrated into LLM applications via frameworks like LangChain to improve the relevance and order of retrieved documents from search systems, including those utilizing vector databases.
A tool that allows users to run large language models locally, providing an easy way to set up and interact with various models, including integrations for generating and managing embeddings with vector databases.
A platform designed to simplify the building, management, and deployment of Large Language Model (LLM) applications, enabling rapid operationalization of context-aware LLMs and offering integration with its Vector Store.
LlamaIndex is a data framework for large language model (LLM) applications, providing tools to ingest, structure, and access private or domain-specific data, often integrating with vector databases for retrieval augmented generation (RAG).
A framework for performing Retrieval-Augmented Generation (RAG) evaluation, supporting multiple ways of validating results.
AnythingLLM is an open-source AI application that integrates with vector databases to facilitate storage and retrieval of embeddings, supporting various AI and LLM workflows.
langchain4j is an open-source framework for developing LLM-powered Java applications, with built-in support for integrating vector databases as memory stores.
llm-app is an open-source project that provides an AI application framework with integrated support for vector databases, enabling the development of LLM-powered solutions.
Infinity is an AI-native database built for LLM applications, offering fast hybrid search of dense vectors, sparse vectors, tensors, and full-text data.