Tools tagged with "Reranking"

Graphiti is a self-hosted Python framework for developers building AI agents that need to remember changing facts. It builds knowledge graphs from conversations, structured records and unstructured text, so an agent can query current information or recover what was true earlier. It's open source under Apache 2.0.

LightRAG combines knowledge graphs with vector search to answer questions across a document collection. It's a self-hosted Python framework for developers building document assistants, particularly where answers depend on relationships between facts in different files, such as legal or financial material.

LibreChat is a self-hosted ChatGPT alternative for people and teams that want local models and cloud AI services in one chat interface. It runs on a server you control and is open source under the MIT license. You can switch models without moving to a separate chat app.

RAGFlow is an Apache 2.0 licensed RAG engine for teams building AI agents that need to answer questions from their own documents. It can run on a self-hosted server through Docker on Windows, macOS or Linux. A separate hosted cloud service is available.

llama.cpp runs language models on your own hardware and can serve them from a machine you control. It’s an MIT-licensed, open source inference engine for people building local AI apps, running a private model server, or using a model directly from the command line. It supports vision-language models too.

LiteLLM gives platform teams one place to manage access to LLMs across providers. Its self-hosted AI gateway puts cloud services and internal or locally hosted models behind an OpenAI-compatible API, so applications can change models without changing their integration. Developers can also use its Python SDK directly.

Open WebUI gives individuals and teams a self-hosted place to chat with local LLMs and cloud models. It runs on your own computer or server, including through Docker, and can work entirely offline with local models.

QMD is a local search engine for people with Markdown notes, meeting transcripts, or documentation they want to search themselves or make available to an AI agent. It accepts exact keywords and natural-language queries, with indexing and model inference running on your own machine. It's open source under MIT.

MindsDB Query Engine is a self-hosted server for developers building AI agents that need access to business data and documents. It queries connected sources through one SQL dialect and adds semantic search for unstructured content. You can run it locally or on your own server with Docker. Its core uses the Elastic License 2.0, with separate licenses in some directories.

QAnything is a self-hosted knowledge base for people and teams who want to ask questions about their own documents, including collections that mix Chinese and English. It can answer in either language regardless of the document's language, and runs locally through Docker on Windows, macOS and Linux.

Zep Community Edition v1.0.2 is a deprecated, unsupported self-hosted memory service for developers building AI agents and conversational assistants. This legacy edition uses the Apache 2.0 license. It turns chat history into a knowledge graph that records how facts change over time, so an assistant can distinguish a user's current preferences from earlier ones.

Scira is an AI search engine for people who want answers backed by sources and control over the application they use for research. It has a hosted website, and you can self-host the open-source application under AGPL-3.0. Its live search relies on internet access and external services; self-hosting doesn't make that research offline.

Twinny is an AI coding assistant for VS Code that lets developers choose where their models run: on their own computer, a private server or a hosted API. It's for individuals and teams who want code suggestions and repository chat with control over where their code goes. The extension and team gateway are open source under the MIT license.

Quivr Core is a Python framework for developers adding document-based AI answers to their own applications. It combines file ingestion with retrieval-augmented generation (RAG), so a model can answer questions using material from your documents. It supports local models through Ollama as well as cloud APIs from OpenAI, Anthropic, and Mistral.

Cognita is a self-hosted RAG framework for developers building applications that answer questions using their own documents. The project is archived and no longer maintained. It combines a browser interface for document Q&A with reusable components built on LangChain and LlamaIndex, under the Apache 2.0 open-source license.

Sonar is a self-hosted inference engine for developers and teams serving Hugging Face-compatible language and multimodal models on their own hardware. Based on vLLM, it adds model and quantization formats, sampling methods, and deployment features. It's open source under AGPL-3.0.

Infinity is a self-hosted database for developers building search and retrieval-augmented generation (RAG) into LLM applications. It combines embedding search with full-text search and structured filters, so an application can retrieve relevant records through both meaning and exact terms.

rerankers is a Python library for developers building search and retrieval systems who want to compare reranking models without rewriting their integration each time. It takes a query and candidate documents, then ranks their relevance through a shared interface across local models and hosted services. It's open source under Apache 2.0.

localGPT is a self-hosted AI document chat app for people who want to question and summarise files on their own hardware. Its local Ollama setup keeps documents and conversations on your machine. Answers include source passages, so you can check what the model used.

kotaemon is a self-hosted document chat app for people who want to ask questions across their files and check where the answers came from. It runs in a browser on Windows, macOS or Linux, with Docker also supported. The project uses the Apache 2.0 license.

aichat brings Ollama and cloud AI services into the same terminal interface for developers and people who work at the command line. It runs locally on macOS, Linux and Windows, with Android support through Termux. Model processing happens through the backend you choose: Ollama supports local models, while providers such as OpenAI, Claude and Gemini process requests in the cloud.

Text Embeddings Inference is a self-hosted server for developers who need text embeddings for search and retrieval applications. It serves models through a REST API on your own hardware and can run offline once model weights are downloaded. The Rust project is open source under Apache 2.0.

llama-swap is a self-hosted proxy for people running several AI models on their own hardware. It starts the model server a request needs and swaps out another when necessary, so you don't have to keep every model loaded or manage separate API connections in your apps.

LlamaIndex is an MIT-licensed Python framework for developers building AI agents and apps that answer questions using their own data. It connects documents and other sources to language models, then helps an app find the relevant material when a user asks something. Its open source framework can work with models served through Ollama.

Weaviate is a self-hosted vector database for developers building search applications, RAG systems, recommendation engines, and chatbots. It stores data objects alongside their vector embeddings, so applications can search by meaning and filter results using structured data. You can run the database locally with Docker, deploy it on Kubernetes, or use the hosted Weaviate Cloud service.

node-llama-cpp is an open source library for developers adding local LLM inference to JavaScript and TypeScript applications. It connects Node.js, Bun and Electron to llama.cpp, running GGUF models on your own machine. Its MIT license allows use in commercial projects.

PaperQA2 is an open source Python research assistant for people who need answers grounded in a collection of scientific papers. It searches documents on your machine and writes answers with in-text citations, including page references. Researchers can use it to summarize findings or check for contradictions across papers, while developers can build it into their own research tools.

FastEmbed is a Python library that generates embeddings on your own hardware for semantic search and retrieval-augmented generation (RAG). It's for developers who need to turn text into searchable vectors without relying on a cloud embedding API. It can run on a CPU or use GPU acceleration, and its Apache 2.0 license makes it open source.

Haystack is a Python framework for developers building self-hosted AI agents, document search, and apps that answer questions using their own data. Its modular pipelines let teams control which information reaches a model and inspect how retrieval, memory, tools, and generation contribute to an answer. It's open source under Apache 2.0.

Sentence Transformers is an open-source Python library for developers building semantic search and document retrieval on their own hardware. It runs embedding and reranker models locally, turning content into numerical representations for similarity comparisons and scoring results against a query. The library uses the Apache 2.0 license.

Infinity Embeddings is a self-hosted server for developers building semantic search and retrieval-augmented generation applications. It runs embedding and reranking models on your own hardware, with support for image and audio search alongside text. It's open source under MIT.