Tools tagged with "RAG"

Cactus is an on-device AI engine for developers building automation into mobile apps, wearables and embedded devices. Its Needle model handles tool calling locally, so a device can turn a request into an action without an internet connection. The focus is small devices, including smart home hardware, robots and microcontrollers.

Obsidian Local GPT brings AI writing assistance into Obsidian, with local Ollama models for private, offline use or connections to OpenAI-compatible services. It's for people who want help with their notes while keeping control over where the AI runs. The plugin is open source under the MIT license.

LLPhant is an MIT-licensed PHP framework for adding language models, embeddings and vector databases to Symfony and Laravel applications. It requires PHP 8.1 or later and is installed through Composer.

Langchain-Chatchat is a self-hosted application for asking questions about your own documents and using AI agents. It focuses on Chinese-language use and open models, with a fully offline setup that can keep documents and model processing on your hardware. Its code is open source under Apache 2.0.

AstrBot brings AI assistants into messaging apps such as Telegram, Discord, Slack, QQ and WeCom. It's an open source platform under AGPL-3.0 for people building personal companions, customer support bots or team automation. You can run it on your own computer or server, including through Docker, or use its desktop app for browser-style chat.

Cheshire Cat is a self-hosted Python framework for people learning how AI agents work or building custom assistants for research and creative projects. It pairs a local web chat interface with an API, so you can test an agent in conversation and use it inside another application. It's open source under GPL-3.0.

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.

LangChain is an MIT-licensed open-source framework for developers building AI agents and applications powered by LLMs. It provides a shared interface for models, tools and data connections, so developers can change providers or test workflows without rebuilding the whole application.

Spring AI is an open-source Java framework for developers adding AI to Spring applications. It connects application data and APIs to models through a common interface, with Ollama support for local LLM use and integrations with cloud providers such as OpenAI, Anthropic and Amazon Bedrock. The framework runs within your application; your choice of model provider determines whether model requests stay local or go to a cloud service.

Wren AI is a self-hosted data agent for teams and agent builders who need answers based on agreed business definitions. It turns plain-language questions into SQL and interactive dashboards, using the same definitions when someone asks directly or through Claude, ChatGPT or Gemini over MCP.

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.

KoboldCpp pairs local model inference with a browser interface built for chat, creative writing and roleplay. A fork of llama.cpp, it bundles KoboldAI Lite with tools for keeping character details and story context alongside your conversations. It's open source under AGPL-3.0.

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.

Typesense combines typo-tolerant site search with vector and semantic search in a self-hosted engine. It's for developers building searchable apps, product catalogs or AI search over their own data. The C++ engine uses an in-memory architecture for low-latency results as users type.

BentoML is a Python framework for developers turning AI models into services on their own hardware or servers. It supports self-hosted inference APIs and multi-model applications, with Apache 2.0 licensing. You can develop and debug locally, then deploy the services in Docker containers, on Kubernetes, or in your own cloud.

Chatbox is an AI chat client for people who want local models and cloud providers in the same app. It connects to Ollama for local LLM use and supports GPT, Claude, Gemini, Grok and DeepSeek with your own API keys. Chatbox also offers its own hosted model service.

DocsGPT is an MIT-licensed, open-source platform for teams that want AI search, assistants and agents over their own documents. It can run on your servers with local models, including fully air-gapped deployments where documents and questions stay inside your network. Answers include the source title and page number so readers can check the evidence.

Nextcloud Assistant brings AI into Nextcloud Hub's documents, email, chat and calendar. It's for teams that want help with shared work while choosing where AI processing happens. With an on-premises model, data stays on your server. The app is open source under AGPL-3.0.

Obsidian Copilot brings AI agents into your vault to find notes by meaning, edit drafts and organize research. It's for writers, researchers and other Obsidian users who want AI to work directly with their existing notes. Agents create Markdown files, wikilinks and canvases that remain in your vault.

Coze Studio is a self-hosted AI agent development platform for developers and teams building assistants and AI apps through visual, low-code tools. It brings agent creation, debugging and publishing into one workspace, with workflows for defining business logic. The open-source edition uses the Apache 2.0 license and shares its core engine with the commercial Coze Development Platform.

PrivateGPT is a self-hosted API layer for developers building AI applications around local models. It adds document retrieval, database access and agent tools to an existing model server. Local workflows can work offline and keep data within your environment; web search and connections to online providers need internet access.

Local Deep Research is a self-hosted AI research assistant for people who need cited answers drawn from academic papers, the web and their own documents. It can produce a quick summary or pursue a complex question through repeated searches, then assemble a structured report. It's open source under MIT.

txtai is a Python framework for developers building search applications, chat with their data, and AI agents on their own hardware or servers. Its embeddings database combines sparse and dense vector search with graphs and relational data, so the same system can find related content and supply context to language models. It's open source under Apache 2.0.

DSPy is a Python framework for developers building AI applications whose tasks need clear inputs, predictable output types, and measurable results. You define what a language model should produce, then compose those tasks into a larger program. It's open source under the MIT license.

Chatwoot is a self-hosted customer support platform for teams considering an alternative to Intercom or Zendesk. It combines a shared inbox, an AI agent called Captain, and a help center. You can host the platform on your own server to control your customer data, or use Chatwoot's hosted cloud service.

GraphRAG builds a knowledge graph from text so an LLM can answer questions that depend on connections across documents or themes across a whole collection. It's for developers and researchers working with private datasets, such as business documents, proprietary research, or communications.

Tiledesk is a self-hosted platform for building AI agents and connecting them to human support teams. It's aimed at businesses automating customer conversations, internal information searches and workflows through a visual builder. You can run it on your own server with Docker or Kubernetes, or use its hosted cloud service.

PandasAI is a Python library for people who want to ask questions about their data in plain language. It works with SQL databases, CSV and parquet data, and can answer questions across multiple pandas DataFrames. Developers can use it in their own applications; analysts can use conversational queries to reduce the code they write for individual questions.

GPT4All is a local AI chatbot for people who want to run language models on their own desktop or laptop and keep conversations on their machine. Its LocalDocs feature lets you ask questions about your own documents without sending them to a cloud service. It suits developers, teams and individuals who want control over their models and data.

Meilisearch combines keyword search and AI retrieval in a search engine you can host on your own server. It's for developers building search into websites, applications, product catalogs, or internal data tools. Meilisearch Cloud provides a separate, fully managed hosted service.

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.

FastGPT is a self-hosted AI agent builder for teams that want assistants to answer questions using company documents and carry out business workflows. Its visual editor connects model calls, knowledge retrieval and tools into applications for customer support, internal knowledge search and document review. You can run the platform on your own server through Docker or use the vendor's hosted service.

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.

Cognee gives AI agents persistent memory across sessions, connecting documents, code, and conversations in a searchable knowledge graph. It's for developers who want agents to retain project context and teams whose knowledge sits across tickets, discussions, and repositories. The Python package is open source under Apache 2.0.

LangChain4j is an Apache 2.0 open-source Java library for developers building chatbots, assistants and AI agents in JVM applications. It connects application code to local LLM backends such as Ollama as well as cloud providers such as OpenAI and Google Vertex AI. Where model requests go depends on the backend you choose.

RubyLLM is an MIT-licensed AI framework for developers building Ruby and Rails applications with local or hosted models. Its shared API lets an application switch between Ollama, cloud providers such as Anthropic and OpenAI, and OpenAI-compatible endpoints without rewriting its model integration. The framework runs in your application; model processing happens at the local or hosted backend you choose.