Ollama

<div align="center">   <a href="https://ollama.com"> <img alt="ollama" width="240" src="https://github.com/ollama/ollama/assets/3325447/0d0b44e2-8f4a-4e99-9b52-a5c1c741c8f7"> </a> </div> # Ollama Get up and running with large language models. ### macOS [Download](https://ollama.com/download/Ollama.dmg) ### Windows [Download](https://ollama.com/download/OllamaSetup.exe) ### Linux ```shell curl -fsSL https://ollama.com/install.sh | sh ``` [Manual install instructions](https://github.com/ollama/ollama/blob/main/docs/linux.md) ### Docker The official [Ollama Docker image](https://hub.docker.com/r/ollama/ollama) `ollama/ollama` is available on Docker Hub. ### Libraries - [ollama-python](https://github.com/ollama/ollama-python) - [ollama-js](https://github.com/ollama/ollama-js) ### Community - [Discord](https://discord.gg/ollama) - [Reddit](https://reddit.com/r/ollama) ## Quickstart To run and chat with [Gemma 3](https://ollama.com/library/gemma3): ```shell ollama run gemma3 ``` ## Model library Ollama supports a list of models available on [ollama.com/library](https://ollama.com/library 'ollama model library') Here are some example models that can be downloaded: | Model | Parameters | Size | Download | | ------------------ | ---------- | ----- | -------------------------------- | | Gemma 3 | 1B | 815MB | `ollama run gemma3:1b` | | Gemma 3 | 4B | 3.3GB | `ollama run gemma3` | | Gemma 3 | 12B | 8.1GB | `ollama run gemma3:12b` | | Gemma 3 | 27B | 17GB | `ollama run gemma3:27b` | | QwQ | 32B | 20GB | `ollama run qwq` | | DeepSeek-R1 | 7B | 4.7GB | `ollama run deepseek-r1` | | DeepSeek-R1 | 671B | 404GB | `ollama run deepseek-r1:671b` | | Llama 4 | 109B | 67GB | `ollama run llama4:scout` | | Llama 4 | 400B | 245GB | `ollama run llama4:maverick` | | Llama 3.3 | 70B | 43GB | `ollama run llama3.3` | | Llama 3.2 | 3B | 2.0GB | `ollama run llama3.2` | | Llama 3.2 | 1B | 1.3GB | `ollama run llama3.2:1b` | | Llama 3.2 Vision | 11B | 7.9GB | `ollama run llama3.2-vision` | | Llama 3.2 Vision | 90B | 55GB | `ollama run llama3.2-vision:90b` | | Llama 3.1 | 8B | 4.7GB | `ollama run llama3.1` | | Llama 3.1 | 405B | 231GB | `ollama run llama3.1:405b` | | Phi 4 | 14B | 9.1GB | `ollama run phi4` | | Phi 4 Mini | 3.8B | 2.5GB | `ollama run phi4-mini` | | Mistral | 7B | 4.1GB | `ollama run mistral` | | Moondream 2 | 1.4B | 829MB | `ollama run moondream` | | Neural Chat | 7B | 4.1GB | `ollama run neural-chat` | | Starling | 7B | 4.1GB | `ollama run starling-lm` | | Code Llama | 7B | 3.8GB | `ollama run codellama` | | Llama 2 Uncensored | 7B | 3.8GB | `ollama run llama2-uncensored` | | LLaVA | 7B | 4.5GB | `ollama run llava` | | Granite-3.3 | 8B | 4.9GB | `ollama run granite3.3` | > [!NOTE] > You should have at least 8 GB of RAM available to run the 7B models, 16 GB to run the 13B models, and 32 GB to run the 33B models. ## Customize a model ### Import from GGUF Ollama supports importing GGUF models in the Modelfile: 1. Create a file named `Modelfile`, with a `FROM` instruction with the local filepath to the model you want to import. ``` FROM ./vicuna-33b.Q4_0.gguf ``` 2. Create the model in Ollama ```shell ollama create example -f Modelfile ``` 3. Run the model ```shell ollama run example ``` ### Import from Safetensors See the [guide](docs/import.md) on importing models for more information. ### Customize a prompt Models from the Ollama library can be customized with a prompt. For example, to customize the `llama3.2` model: ```shell ollama pull llama3.2 ``` Create a `Modelfile`: ``` FROM llama3.2 # set the temperature to 1 [higher is more creative, lower is more coherent] PARAMETER temperature 1 # set the system message SYSTEM """ You are Mario from Super Mario Bros. Answer as Mario, the assistant, only. """ ``` Next, create and run the model: ``` ollama create mario -f ./Modelfile ollama run mario >>> hi Hello! It's your friend Mario. ``` For more information on working with a Modelfile, see the [Modelfile](docs/modelfile.md) documentation. ## CLI Reference ### Create a model `ollama create` is used to create a model from a Modelfile. ```shell ollama create mymodel -f ./Modelfile ``` ### Pull a model ```shell ollama pull llama3.2 ``` > This command can also be used to update a local model. Only the diff will be pulled. ### Remove a model ```shell ollama rm llama3.2 ``` ### Copy a model ```shell ollama cp llama3.2 my-model ``` ### Multiline input For multiline input, you can wrap text with `"""`: ``` >>> """Hello, ... world! ... """ I'm a basic program that prints the famous "Hello, world!" message to the console. ``` ### Multimodal models ``` ollama run llava "What's in this image? /Users/jmorgan/Desktop/smile.png" ``` > **Output**: The image features a yellow smiley face, which is likely the central focus of the picture. ### Pass the prompt as an argument ```shell ollama run llama3.2 "Summarize this file: $(cat README.md)" ``` > **Output**: Ollama is a lightweight, extensible framework for building and running language models on the local machine. It provides a simple API for creating, running, and managing models, as well as a library of pre-built models that can be easily used in a variety of applications. ### Show model information ```shell ollama show llama3.2 ``` ### List models on your computer ```shell ollama list ``` ### List which models are currently loaded ```shell ollama ps ``` ### Stop a model which is currently running ```shell ollama stop llama3.2 ``` ### Start Ollama `ollama serve` is used when you want to start ollama without running the desktop application. ## Building See the [developer guide](https://github.com/ollama/ollama/blob/main/docs/development.md) ### Running local builds Next, start the server: ```shell ./ollama serve ``` Finally, in a separate shell, run a model: ```shell ./ollama run llama3.2 ``` ## REST API Ollama has a REST API for running and managing models. ### Generate a response ```shell curl http://localhost:11434/api/generate -d '{ "model": "llama3.2", "prompt":"Why is the sky blue?" }' ``` ### Chat with a model ```shell curl http://localhost:11434/api/chat -d '{ "model": "llama3.2", "messages": [ { "role": "user", "content": "why is the sky blue?" } ] }' ``` See the [API documentation](./docs/api.md) for all endpoints. ## Community Integrations ### Web & Desktop - [Open WebUI](https://github.com/open-webui/open-webui) - [SwiftChat (macOS with ReactNative)](https://github.com/aws-samples/swift-chat) - [Enchanted (macOS native)](https://github.com/AugustDev/enchanted) - [Hollama](https://github.com/fmaclen/hollama) - [Lollms-Webui](https://github.com/ParisNeo/lollms-webui) - [LibreChat](https://github.com/danny-avila/LibreChat) - [Bionic GPT](https://github.com/bionic-gpt/bionic-gpt) - [HTML UI](https://github.com/rtcfirefly/ollama-ui) - [Saddle](https://github.com/jikkuatwork/saddle) - [TagSpaces](https://www.tagspaces.org) (A platform for file-based apps, [utilizing Ollama](https://docs.tagspaces.org/ai/) for the generation of tags and descriptions) - [Chatbot UI](https://github.com/ivanfioravanti/chatbot-ollama) - [Chatbot UI v2](https://github.com/mckaywrigley/chatbot-ui) - [Typescript UI](https://github.com/ollama-interface/Ollama-Gui?tab=readme-ov-file) - [Minimalistic React UI for Ollama Models](https://github.com/richawo/minimal-llm-ui) - [Ollamac](https://github.com/kevinhermawan/Ollamac) - [big-AGI](https://github.com/enricoros/big-AGI) - [Cheshire Cat assistant framework](https://github.com/cheshire-cat-ai/core) - [Amica](https://github.com/semperai/amica) - [chatd](https://github.com/BruceMacD/chatd) - [Ollama-SwiftUI](https://github.com/kghandour/Ollama-SwiftUI) - [Dify.AI](https://github.com/langgenius/dify) - [MindMac](https://mindmac.app) - [NextJS Web Interface for Ollama](https://github.com/jakobhoeg/nextjs-ollama-llm-ui) - [Msty](https://msty.app) - [Chatbox](https://github.com/Bin-Huang/Chatbox) - [WinForm Ollama Copilot](https://github.com/tgraupmann/WinForm_Ollama_Copilot) - [NextChat](https://github.com/ChatGPTNextWeb/ChatGPT-Next-Web) with [Get Started Doc](https://docs.nextchat.dev/models/ollama) - [Alpaca WebUI](https://github.com/mmo80/alpaca-webui) - [OllamaGUI](https://github.com/enoch1118/ollamaGUI) - [OpenAOE](https://github.com/InternLM/OpenAOE) - [Odin Runes](https://github.com/leonid20000/OdinRunes) - [LLM-X](https://github.com/mrdjohnson/llm-x) (Progressive Web App) - [AnythingLLM (Docker + MacOs/Windows/Linux native app)](https://github.com/Mintplex-Labs/anything-llm) - [Ollama Basic Chat: Uses HyperDiv Reactive UI](https://github.com/rapidarchitect/ollama_basic_chat) - [Ollama-chats RPG](https://github.com/drazdra/ollama-chats) - [IntelliBar](https://intellibar.app/) (AI-powered assistant for macOS) - [Jirapt](https://github.com/AliAhmedNada/jirapt) (Jira Integration to generate issues, tasks, epics) - [ojira](https://github.com/AliAhmedNada/ojira) (Jira chrome plugin to easily generate descriptions for tasks) - [QA-Pilot](https://github.com/reid41/QA-Pilot) (Interactive chat tool that can leverage Ollama models for rapid understanding and navigation of GitHub code repositories) - [ChatOllama](https://github.com/sugarforever/chat-ollama) (Open Source Chatbot based on Ollama with Knowledge Bases) - [CRAG Ollama Chat](https://github.com/Nagi-ovo/CRAG-Ollama-Chat) (Simple Web Search with Corrective RAG) - [RAGFlow](https://github.com/infiniflow/ragflow) (Open-source Retrieval-Augmented Generation engine based on deep document understanding) - [StreamDeploy](https://github.com/StreamDeploy-DevRel/streamdeploy-llm-app-scaffold) (LLM Application Scaffold) - [chat](https://github.com/swuecho/chat) (chat web app for teams) - [Lobe Chat](https://github.com/lobehub/lobe-chat) with [Integrating Doc](https://lobehub.com/docs/self-hosting/examples/ollama) - [Ollama RAG Chatbot](https://github.com/datvodinh/rag-chatbot.git) (Local Chat with multiple PDFs using Ollama and RAG) - [BrainSoup](https://www.nurgo-software.com/products/brainsoup) (Flexible native client with RAG & multi-agent automation) - [macai](https://github.com/Renset/macai) (macOS client for Ollama, ChatGPT, and other compatible API back-ends) - [RWKV-Runner](https://github.com/josStorer/RWKV-Runner) (RWKV offline LLM deployment tool, also usable as a client for ChatGPT and Ollama) - [Ollama Grid Search](https://github.com/dezoito/ollama-grid-search) (app to evaluate and compare models) - [Olpaka](https://github.com/Otacon/olpaka) (User-friendly Flutter Web App for Ollama) - [Casibase](https://casibase.org) (An open source AI knowledge base and dialogue system combining the latest RAG, SSO, ollama support, and multiple large language models.) - [OllamaSpring](https://github.com/CrazyNeil/OllamaSpring) (Ollama Client for macOS) - [LLocal.in](https://github.com/kartikm7/llocal) (Easy to use Electron Desktop Client for Ollama) - [Shinkai Desktop](https://github.com/dcSpark/shinkai-apps) (Two click install Local AI using Ollama + Files + RAG) - [AiLama](https://github.com/zeyoyt/ailama) (A Discord User App that allows you to interact with Ollama anywhere in Discord) - [Ollama with Google Mesop](https://github.com/rapidarchitect/ollama_mesop/) (Mesop Chat Client implementation with Ollama) - [R2R](https://github.com/SciPhi-AI/R2R) (Open-source RAG engine) - [Ollama-Kis](https://github.com/elearningshow/ollama-kis) (A simple easy-to-use GUI with sample custom LLM for Drivers Education) - [OpenGPA](https://opengpa.org) (Open-source offline-first Enterprise Agentic Application) - [Painting Droid](https://github.com/mateuszmigas/painting-droid) (Painting app with AI integrations) - [Kerlig AI](https://www.kerlig.com/) (AI writing assistant for macOS) - [AI Studio](https://github.com/MindWorkAI/AI-Studio) - [Sidellama](https://github.com/gyopak/sidellama) (browser-based LLM client) - [LLMStack](https://github.com/trypromptly/LLMStack) (No-code multi-agent framework to build LLM agents and workflows) - [BoltAI for Mac](https://boltai.com) (AI Chat Client for Mac) - [Harbor](https://github.com/av/harbor) (Containerized LLM Toolkit with Ollama as default backend) - [PyGPT](https://github.com/szczyglis-dev/py-gpt) (AI desktop assistant for Linux, Windows, and Mac) - [Alpaca](https://github.com/Jeffser/Alpaca) (An Ollama client application for Linux and macOS made with GTK4 and Adwaita) - [AutoGPT](https://github.com/Significant-Gravitas/AutoGPT/blob/master/docs/content/platform/ollama.md) (AutoGPT Ollama integration) - [Go-CREW](https://www.jonathanhecl.com/go-crew/) (Powerful Offline RAG in Golang) - [PartCAD](https://github.com/openvmp/partcad/) (CAD model generation with OpenSCAD and CadQuery) - [Ollama4j Web UI](https://github.com/ollama4j/ollama4j-web-ui) - Java-based Web UI for Ollama built with Vaadin, Spring Boot, and Ollama4j - [PyOllaMx](https://github.com/kspviswa/pyOllaMx) - macOS application capable of chatting with both Ollama and Apple MLX models. - [Cline](https://github.com/cline/cline) - Formerly known as Claude Dev is a VSCode extension for multi-file/whole-repo coding - [Cherry Studio](https://github.com/kangfenmao/cherry-studio) (Desktop client with Ollama support) - [ConfiChat](https://github.com/1runeberg/confichat) (Lightweight, standalone, multi-platform, and privacy-focused LLM chat interface with optional encryption) - [Archyve](https://github.com/nickthecook/archyve) (RAG-enabling document library) - [crewAI with Mesop](https://github.com/rapidarchitect/ollama-crew-mesop) (Mesop Web Interface to run crewAI with Ollama) - [Tkinter-based client](https://github.com/chyok/ollama-gui) (Python tkinter-based Client for Ollama) - [LLMChat](https://github.com/trendy-design/llmchat) (Privacy focused, 100% local, intuitive all-in-one chat interface) - [Local Multimodal AI Chat](https://github.com/Leon-Sander/Local-Multimodal-AI-Chat) (Ollama-based LLM Chat with support for multiple features, including PDF RAG, voice chat, image-based interactions, and integration with OpenAI.) - [ARGO](https://github.com/xark-argo/argo) (Locally download and run Ollama and Huggingface models with RAG on Mac/Windows/Linux) - [OrionChat](https://github.com/EliasPereirah/OrionChat) - OrionChat is a web interface for chatting with different AI providers - [G1](https://github.com/bklieger-groq/g1) (Prototype of using prompting strategies to improve the LLM's reasoning through o1-like reasoning chains.) - [Web management](https://github.com/lemonit-eric-mao/ollama-web-management) (Web management page) - [Promptery](https://github.com/promptery/promptery) (desktop client for Ollama.) - [Ollama App](https://github.com/JHubi1/ollama-app) (Modern and easy-to-use multi-platform client for Ollama) - [chat-ollama](https://github.com/annilq/chat-ollama) (a React Native client for Ollama) - [SpaceLlama](https://github.com/tcsenpai/spacellama) (Firefox and Chrome extension to quickly summarize web pages with ollama in a sidebar) - [YouLama](https://github.com/tcsenpai/youlama) (Webapp to quickly summarize any YouTube video, supporting Invidious as well) - [DualMind](https://github.com/tcsenpai/dualmind) (Experimental app allowing two models to talk to each other in the terminal or in a web interface) - [ollamarama-matrix](https://github.com/h1ddenpr0cess20/ollamarama-matrix) (Ollama chatbot for the Matrix chat protocol) - [ollama-chat-app](https://github.com/anan1213095357/ollama-chat-app) (Flutter-based chat app) - [Perfect Memory AI](https://www.perfectmemory.ai/) (Productivity AI assists personalized by what you have seen on your screen, heard, and said in the meetings) - [Hexabot](https://github.com/hexastack/hexabot) (A conversational AI builder) - [Reddit Rate](https://github.com/rapidarchitect/reddit_analyzer) (Search and Rate Reddit topics with a weighted summation) - [OpenTalkGpt](https://github.com/adarshM84/OpenTalkGpt) (Chrome Extension to manage open-source models supported by Ollama, create custom models, and chat with models from a user-friendly UI) - [VT](https://github.com/vinhnx/vt.ai) (A minimal multimodal AI chat app, with dynamic conversation routing. Supports local models via Ollama) - [Nosia](https://github.com/nosia-ai/nosia) (Easy to install and use RAG platform based on Ollama) - [Witsy](https://github.com/nbonamy/witsy) (An AI Desktop application available for Mac/Windows/Linux) - [Abbey](https://github.com/US-Artificial-Intelligence/abbey) (A configurable AI interface server with notebooks, document storage, and YouTube support) - [Minima](https://github.com/dmayboroda/minima) (RAG with on-premises or fully local workflow) - [aidful-ollama-model-delete](https://github.com/AidfulAI/aidful-ollama-model-delete) (User interface for simplified model cleanup) - [Perplexica](https://github.com/ItzCrazyKns/Perplexica) (An AI-powered search engine & an open-source alternative to Perplexity AI) - [Ollama Chat WebUI for Docker ](https://github.com/oslook/ollama-webui) (Support for local docker deployment, lightweight ollama webui) - [AI Toolkit for Visual Studio Code](https://aka.ms/ai-tooklit/ollama-docs) (Microsoft-official VSCode extension to chat, test, evaluate models with Ollama support, and use them in your AI applications.) - [MinimalNextOllamaChat](https://github.com/anilkay/MinimalNextOllamaChat) (Minimal Web UI for Chat and Model Control) - [Chipper](https://github.com/TilmanGriesel/chipper) AI interface for tinkerers (Ollama, Haystack RAG, Python) - [ChibiChat](https://github.com/CosmicEventHorizon/ChibiChat) (Kotlin-based Android app to chat with Ollama and Koboldcpp API endpoints) - [LocalLLM](https://github.com/qusaismael/localllm) (Minimal Web-App to run ollama models on it with a GUI) - [Ollamazing](https://github.com/buiducnhat/ollamazing) (Web extension to run Ollama models) - [OpenDeepResearcher-via-searxng](https://github.com/benhaotang/OpenDeepResearcher-via-searxng) (A Deep Research equivalent endpoint with Ollama support for running locally) - [AntSK](https://github.com/AIDotNet/AntSK) (Out-of-the-box & Adaptable RAG Chatbot) - [MaxKB](https://github.com/1Panel-dev/MaxKB/) (Ready-to-use & flexible RAG Chatbot) - [yla](https://github.com/danielekp/yla) (Web interface to freely interact with your customized models) - [LangBot](https://github.com/RockChinQ/LangBot) (LLM-based instant messaging bots platform, with Agents, RAG features, supports multiple platforms) - [1Panel](https://github.com/1Panel-dev/1Panel/) (Web-based Linux Server Management Tool) - [AstrBot](https://github.com/Soulter/AstrBot/) (User-friendly LLM-based multi-platform chatbot with a WebUI, supporting RAG, LLM agents, and plugins integration) - [Reins](https://github.com/ibrahimcetin/reins) (Easily tweak parameters, customize system prompts per chat, and enhance your AI experiments with reasoning model support.) - [Flufy](https://github.com/Aharon-Bensadoun/Flufy) (A beautiful chat interface for interacting with Ollama's API. Built with React, TypeScript, and Material-UI.) - [Ellama](https://github.com/zeozeozeo/ellama) (Friendly native app to chat with an Ollama instance) - [screenpipe](https://github.com/mediar-ai/screenpipe) Build agents powered by your screen history - [Ollamb](https://github.com/hengkysteen/ollamb) (Simple yet rich in features, cross-platform built with Flutter and designed for Ollama. Try the [web demo](https://hengkysteen.github.io/demo/ollamb/).) - [Writeopia](https://github.com/Writeopia/Writeopia) (Text editor with integration with Ollama) - [AppFlowy](https://github.com/AppFlowy-IO/AppFlowy) (AI collaborative workspace with Ollama, cross-platform and self-hostable) - [Lumina](https://github.com/cushydigit/lumina.git) (A lightweight, minimal React.js frontend for interacting with Ollama servers) - [Tiny Notepad](https://pypi.org/project/tiny-notepad) (A lightweight, notepad-like interface to chat with ollama available on PyPI) - [macLlama (macOS native)](https://github.com/hellotunamayo/macLlama) (A native macOS GUI application for interacting with Ollama models, featuring a chat interface.) - [GPTranslate](https://github.com/philberndt/GPTranslate) (A fast and lightweight, AI powered desktop translation application written with Rust and Tauri. Features real-time translation with OpenAI/Azure/Ollama.) - [ollama launcher](https://github.com/NGC13009/ollama-launcher) (A launcher for Ollama, aiming to provide users with convenient functions such as ollama server launching, management, or configuration.) - [ai-hub](https://github.com/Aj-Seven/ai-hub) (AI Hub supports multiple models via API keys and Chat support via Ollama API.) ### Cloud - [Google Cloud](https://cloud.google.com/run/docs/tutorials/gpu-gemma2-with-ollama) - [Fly.io](https://fly.io/docs/python/do-more/add-ollama/) - [Koyeb](https://www.koyeb.com/deploy/ollama) ### Terminal - [oterm](https://github.com/ggozad/oterm) - [Ellama Emacs client](https://github.com/s-kostyaev/ellama) - [Emacs client](https://github.com/zweifisch/ollama) - [neollama](https://github.com/paradoxical-dev/neollama) UI client for interacting with models from within Neovim - [gen.nvim](https://github.com/David-Kunz/gen.nvim) - [ollama.nvim](https://github.com/nomnivore/ollama.nvim) - [ollero.nvim](https://github.com/marco-souza/ollero.nvim) - [ollama-chat.nvim](https://github.com/gerazov/ollama-chat.nvim) - [ogpt.nvim](https://github.com/huynle/ogpt.nvim) - [gptel Emacs client](https://github.com/karthink/gptel) - [Oatmeal](https://github.com/dustinblackman/oatmeal) - [cmdh](https://github.com/pgibler/cmdh) - [ooo](https://github.com/npahlfer/ooo) - [shell-pilot](https://github.com/reid41/shell-pilot)(Interact with models via pure shell scripts on Linux or macOS) - [tenere](https://github.com/pythops/tenere) - [llm-ollama](https://github.com/taketwo/llm-ollama) for [Datasette's LLM CLI](https://llm.datasette.io/en/stable/). - [typechat-cli](https://github.com/anaisbetts/typechat-cli) - [ShellOracle](https://github.com/djcopley/ShellOracle) - [tlm](https://github.com/yusufcanb/tlm) - [podman-ollama](https://github.com/ericcurtin/podman-ollama) - [gollama](https://github.com/sammcj/gollama) - [ParLlama](https://github.com/paulrobello/parllama) - [Ollama eBook Summary](https://github.com/cognitivetech/ollama-ebook-summary/) - [Ollama Mixture of Experts (MOE) in 50 lines of code](https://github.com/rapidarchitect/ollama_moe) - [vim-intelligence-bridge](https://github.com/pepo-ec/vim-intelligence-bridge) Simple interaction of "Ollama" with the Vim editor - [x-cmd ollama](https://x-cmd.com/mod/ollama) - [bb7](https://github.com/drunkwcodes/bb7) - [SwollamaCLI](https://github.com/marcusziade/Swollama) bundled with the Swollama Swift package. [Demo](https://github.com/marcusziade/Swollama?tab=readme-ov-file#cli-usage) - [aichat](https://github.com/sigoden/aichat) All-in-one LLM CLI tool featuring Shell Assistant, Chat-REPL, RAG, AI tools & agents, with access to OpenAI, Claude, Gemini, Ollama, Groq, and more. - [PowershAI](https://github.com/rrg92/powershai) PowerShell module that brings AI to terminal on Windows, including support for Ollama - [DeepShell](https://github.com/Abyss-c0re/deepshell) Your self-hosted AI assistant. Interactive Shell, Files and Folders analysis. - [orbiton](https://github.com/xyproto/orbiton) Configuration-free text editor and IDE with support for tab completion with Ollama. - [orca-cli](https://github.com/molbal/orca-cli) Ollama Registry CLI Application - Browse, pull, and download models from Ollama Registry in your terminal. - [GGUF-to-Ollama](https://github.com/jonathanhecl/gguf-to-ollama) - Importing GGUF to Ollama made easy (multiplatform) - [AWS-Strands-With-Ollama](https://github.com/rapidarchitect/ollama_strands) - AWS Strands Agents with Ollama Examples - [ollama-multirun](https://github.com/attogram/ollama-multirun) - A bash shell script to run a single prompt against any or all of your locally installed ollama models, saving the output and performance statistics as easily navigable web pages. ([Demo](https://attogram.github.io/ai_test_zone/)) - [ollama-bash-toolshed](https://github.com/attogram/ollama-bash-toolshed) - Bash scripts to chat with tool using models. Add new tools to your shed with ease. Runs on Ollama. ### Apple Vision Pro - [SwiftChat](https://github.com/aws-samples/swift-chat) (Cross-platform AI chat app supporting Apple Vision Pro via "Designed for iPad") - [Enchanted](https://github.com/AugustDev/enchanted) ### Database - [pgai](https://github.com/timescale/pgai) - PostgreSQL as a vector database (Create and search embeddings from Ollama models using pgvector) - [Get started guide](https://github.com/timescale/pgai/blob/main/docs/vectorizer-quick-start.md) - [MindsDB](https://github.com/mindsdb/mindsdb/blob/staging/mindsdb/integrations/handlers/ollama_handler/README.md) (Connects Ollama models with nearly 200 data platforms and apps) - [chromem-go](https://github.com/philippgille/chromem-go/blob/v0.5.0/embed_ollama.go) with [example](https://github.com/philippgille/chromem-go/tree/v0.5.0/examples/rag-wikipedia-ollama) - [Kangaroo](https://github.com/dbkangaroo/kangaroo) (AI-powered SQL client and admin tool for popular databases) ### Package managers - [Pacman](https://archlinux.org/packages/extra/x86_64/ollama/) - [Gentoo](https://github.com/gentoo/guru/tree/master/app-misc/ollama) - [Homebrew](https://formulae.brew.sh/formula/ollama) - [Helm Chart](https://artifacthub.io/packages/helm/ollama-helm/ollama) - [Guix channel](https://codeberg.org/tusharhero/ollama-guix) - [Nix package](https://search.nixos.org/packages?show=ollama&from=0&size=50&sort=relevance&type=packages&query=ollama) - [Flox](https://flox.dev/blog/ollama-part-one) ### Libraries - [LangChain](https://python.langchain.com/docs/integrations/chat/ollama/) and [LangChain.js](https://js.langchain.com/docs/integrations/chat/ollama/) with [example](https://js.langchain.com/docs/tutorials/local_rag/) - [Firebase Genkit](https://firebase.google.com/docs/genkit/plugins/ollama) - [crewAI](https://github.com/crewAIInc/crewAI) - [Yacana](https://remembersoftwares.github.io/yacana/) (User-friendly multi-agent framework for brainstorming and executing predetermined flows with built-in tool integration) - [Spring AI](https://github.com/spring-projects/spring-ai) with [reference](https://docs.spring.io/spring-ai/reference/api/chat/ollama-chat.html) and [example](https://github.com/tzolov/ollama-tools) - [LangChainGo](https://github.com/tmc/langchaingo/) with [example](https://github.com/tmc/langchaingo/tree/main/examples/ollama-completion-example) - [LangChain4j](https://github.com/langchain4j/langchain4j) with [example](https://github.com/langchain4j/langchain4j-examples/tree/main/ollama-examples/src/main/java) - [LangChainRust](https://github.com/Abraxas-365/langchain-rust) with [example](https://github.com/Abraxas-365/langchain-rust/blob/main/examples/llm_ollama.rs) - [LangChain for .NET](https://github.com/tryAGI/LangChain) with [example](https://github.com/tryAGI/LangChain/blob/main/examples/LangChain.Samples.OpenAI/Program.cs) - [LLPhant](https://github.com/theodo-group/LLPhant?tab=readme-ov-file#ollama) - [LlamaIndex](https://docs.llamaindex.ai/en/stable/examples/llm/ollama/) and [LlamaIndexTS](https://ts.llamaindex.ai/modules/llms/available_llms/ollama) - [LiteLLM](https://github.com/BerriAI/litellm) - [OllamaFarm for Go](https://github.com/presbrey/ollamafarm) - [OllamaSharp for .NET](https://github.com/awaescher/OllamaSharp) - [Ollama for Ruby](https://github.com/gbaptista/ollama-ai) - [Ollama-rs for Rust](https://github.com/pepperoni21/ollama-rs) - [Ollama-hpp for C++](https://github.com/jmont-dev/ollama-hpp) - [Ollama4j for Java](https://github.com/ollama4j/ollama4j) - [ModelFusion Typescript Library](https://modelfusion.dev/integration/model-provider/ollama) - [OllamaKit for Swift](https://github.com/kevinhermawan/OllamaKit) - [Ollama for Dart](https://github.com/breitburg/dart-ollama) - [Ollama for Laravel](https://github.com/cloudstudio/ollama-laravel) - [LangChainDart](https://github.com/davidmigloz/langchain_dart) - [Semantic Kernel - Python](https://github.com/microsoft/semantic-kernel/tree/main/python/semantic_kernel/connectors/ai/ollama) - [Haystack](https://github.com/deepset-ai/haystack-integrations/blob/main/integrations/ollama.md) - [Elixir LangChain](https://github.com/brainlid/langchain) - [Ollama for R - rollama](https://github.com/JBGruber/rollama) - [Ollama for R - ollama-r](https://github.com/hauselin/ollama-r) - [Ollama-ex for Elixir](https://github.com/lebrunel/ollama-ex) - [Ollama Connector for SAP ABAP](https://github.com/b-tocs/abap_btocs_ollama) - [Testcontainers](https://testcontainers.com/modules/ollama/) - [Portkey](https://portkey.ai/docs/welcome/integration-guides/ollama) - [PromptingTools.jl](https://github.com/svilupp/PromptingTools.jl) with an [example](https://svilupp.github.io/PromptingTools.jl/dev/examples/working_with_ollama) - [LlamaScript](https://github.com/Project-Llama/llamascript) - [llm-axe](https://github.com/emirsahin1/llm-axe) (Python Toolkit for Building LLM Powered Apps) - [Gollm](https://docs.gollm.co/examples/ollama-example) - [Gollama for Golang](https://github.com/jonathanhecl/gollama) - [Ollamaclient for Golang](https://github.com/xyproto/ollamaclient) - [High-level function abstraction in Go](https://gitlab.com/tozd/go/fun) - [Ollama PHP](https://github.com/ArdaGnsrn/ollama-php) - [Agents-Flex for Java](https://github.com/agents-flex/agents-flex) with [example](https://github.com/agents-flex/agents-flex/tree/main/agents-flex-llm/agents-flex-llm-ollama/src/test/java/com/agentsflex/llm/ollama) - [Parakeet](https://github.com/parakeet-nest/parakeet) is a GoLang library, made to simplify the development of small generative AI applications with Ollama. - [Haverscript](https://github.com/andygill/haverscript) with [examples](https://github.com/andygill/haverscript/tree/main/examples) - [Ollama for Swift](https://github.com/mattt/ollama-swift) - [Swollama for Swift](https://github.com/marcusziade/Swollama) with [DocC](https://marcusziade.github.io/Swollama/documentation/swollama/) - [GoLamify](https://github.com/prasad89/golamify) - [Ollama for Haskell](https://github.com/tusharad/ollama-haskell) - [multi-llm-ts](https://github.com/nbonamy/multi-llm-ts) (A Typescript/JavaScript library allowing access to different LLM in a unified API) - [LlmTornado](https://github.com/lofcz/llmtornado) (C# library providing a unified interface for major FOSS & Commercial inference APIs) - [Ollama for Zig](https://github.com/dravenk/ollama-zig) - [Abso](https://github.com/lunary-ai/abso) (OpenAI-compatible TypeScript SDK for any LLM provider) - [Nichey](https://github.com/goodreasonai/nichey) is a Python package for generating custom wikis for your research topic - [Ollama for D](https://github.com/kassane/ollama-d) - [OllamaPlusPlus](https://github.com/HardCodeDev777/OllamaPlusPlus) (Very simple C++ library for Ollama) ### Mobile - [SwiftChat](https://github.com/aws-samples/swift-chat) (Lightning-fast Cross-platform AI chat app with native UI for Android, iOS, and iPad) - [Enchanted](https://github.com/AugustDev/enchanted) - [Maid](https://github.com/Mobile-Artificial-Intelligence/maid) - [Ollama App](https://github.com/JHubi1/ollama-app) (Modern and easy-to-use multi-platform client for Ollama) - [ConfiChat](https://github.com/1runeberg/confichat) (Lightweight, standalone, multi-platform, and privacy-focused LLM chat interface with optional encryption) - [Ollama Android Chat](https://github.com/sunshine0523/OllamaServer) (No need for Termux, start the Ollama service with one click on an Android device) - [Reins](https://github.com/ibrahimcetin/reins) (Easily tweak parameters, customize system prompts per chat, and enhance your AI experiments with reasoning model support.) ### Extensions & Plugins - [Raycast extension](https://github.com/MassimilianoPasquini97/raycast_ollama) - [Discollama](https://github.com/mxyng/discollama) (Discord bot inside the Ollama discord channel) - [Continue](https://github.com/continuedev/continue) - [Vibe](https://github.com/thewh1teagle/vibe) (Transcribe and analyze meetings with Ollama) - [Obsidian Ollama plugin](https://github.com/hinterdupfinger/obsidian-ollama) - [Logseq Ollama plugin](https://github.com/omagdy7/ollama-logseq) - [NotesOllama](https://github.com/andersrex/notesollama) (Apple Notes Ollama plugin) - [Dagger Chatbot](https://github.com/samalba/dagger-chatbot) - [Discord AI Bot](https://github.com/mekb-turtle/discord-ai-bot) - [Ollama Telegram Bot](https://github.com/ruecat/ollama-telegram) - [Hass Ollama Conversation](https://github.com/ej52/hass-ollama-conversation) - [Rivet plugin](https://github.com/abrenneke/rivet-plugin-ollama) - [Obsidian BMO Chatbot plugin](https://github.com/longy2k/obsidian-bmo-chatbot) - [Cliobot](https://github.com/herval/cliobot) (Telegram bot with Ollama support) - [Copilot for Obsidian plugin](https://github.com/logancyang/obsidian-copilot) - [Obsidian Local GPT plugin](https://github.com/pfrankov/obsidian-local-gpt) - [Open Interpreter](https://docs.openinterpreter.com/language-model-setup/local-models/ollama) - [Llama Coder](https://github.com/ex3ndr/llama-coder) (Copilot alternative using Ollama) - [Ollama Copilot](https://github.com/bernardo-bruning/ollama-copilot) (Proxy that allows you to use Ollama as a copilot like GitHub Copilot) - [twinny](https://github.com/rjmacarthy/twinny) (Copilot and Copilot chat alternative using Ollama) - [Wingman-AI](https://github.com/RussellCanfield/wingman-ai) (Copilot code and chat alternative using Ollama and Hugging Face) - [Page Assist](https://github.com/n4ze3m/page-assist) (Chrome Extension) - [Plasmoid Ollama Control](https://github.com/imoize/plasmoid-ollamacontrol) (KDE Plasma extension that allows you to quickly manage/control Ollama model) - [AI Telegram Bot](https://github.com/tusharhero/aitelegrambot) (Telegram bot using Ollama in backend) - [AI ST Completion](https://github.com/yaroslavyaroslav/OpenAI-sublime-text) (Sublime Text 4 AI assistant plugin with Ollama support) - [Discord-Ollama Chat Bot](https://github.com/kevinthedang/discord-ollama) (Generalized TypeScript Discord Bot w/ Tuning Documentation) - [ChatGPTBox: All in one browser extension](https://github.com/josStorer/chatGPTBox) with [Integrating Tutorial](https://github.com/josStorer/chatGPTBox/issues/616#issuecomment-1975186467) - [Discord AI chat/moderation bot](https://github.com/rapmd73/Companion) Chat/moderation bot written in python. Uses Ollama to create personalities. - [Headless Ollama](https://github.com/nischalj10/headless-ollama) (Scripts to automatically install ollama client & models on any OS for apps that depend on ollama server) - [Terraform AWS Ollama & Open WebUI](https://github.com/xuyangbocn/terraform-aws-self-host-llm) (A Terraform module to deploy on AWS a ready-to-use Ollama service, together with its front-end Open WebUI service.) - [node-red-contrib-ollama](https://github.com/jakubburkiewicz/node-red-contrib-ollama) - [Local AI Helper](https://github.com/ivostoykov/localAI) (Chrome and Firefox extensions that enable interactions with the active tab and customisable API endpoints. Includes secure storage for user prompts.) - [vnc-lm](https://github.com/jake83741/vnc-lm) (Discord bot for messaging with LLMs through Ollama and LiteLLM. Seamlessly move between local and flagship models.) - [LSP-AI](https://github.com/SilasMarvin/lsp-ai) (Open-source language server for AI-powered functionality) - [QodeAssist](https://github.com/Palm1r/QodeAssist) (AI-powered coding assistant plugin for Qt Creator) - [Obsidian Quiz Generator plugin](https://github.com/ECuiDev/obsidian-quiz-generator) - [AI Summmary Helper plugin](https://github.com/philffm/ai-summary-helper) - [TextCraft](https://github.com/suncloudsmoon/TextCraft) (Copilot in Word alternative using Ollama) - [Alfred Ollama](https://github.com/zeitlings/alfred-ollama) (Alfred Workflow) - [TextLLaMA](https://github.com/adarshM84/TextLLaMA) A Chrome Extension that helps you write emails, correct grammar, and translate into any language - [Simple-Discord-AI](https://github.com/zyphixor/simple-discord-ai) - [LLM Telegram Bot](https://github.com/innightwolfsleep/llm_telegram_bot) (telegram bot, primary for RP. Oobabooga-like buttons, [A1111](https://github.com/AUTOMATIC1111/stable-diffusion-webui) API integration e.t.c) - [mcp-llm](https://github.com/sammcj/mcp-llm) (MCP Server to allow LLMs to call other LLMs) - [SimpleOllamaUnity](https://github.com/HardCodeDev777/SimpleOllamaUnity) (Unity Engine extension for communicating with Ollama in a few lines of code. Also works at runtime) - [UnityCodeLama](https://github.com/HardCodeDev777/UnityCodeLama) (Unity Edtior tool to analyze scripts via Ollama) - [NativeMind](https://github.com/NativeMindBrowser/NativeMindExtension) (Private, on-device AI Assistant, no cloud dependencies) ### Supported backends - [llama.cpp](https://github.com/ggerganov/llama.cpp) project founded by Georgi Gerganov. ### Observability - [Opik](https://www.comet.com/docs/opik/cookbook/ollama) is an open-source platform to debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards. Opik supports native intergration to Ollama. - [Lunary](https://lunary.ai/docs/integrations/ollama) is the leading open-source LLM observability platform. It provides a variety of enterprise-grade features such as real-time analytics, prompt templates management, PII masking, and comprehensive agent tracing. - [OpenLIT](https://github.com/openlit/openlit) is an OpenTelemetry-native tool for monitoring Ollama Applications & GPUs using traces and metrics. - [HoneyHive](https://docs.honeyhive.ai/integrations/ollama) is an AI observability and evaluation platform for AI agents. Use HoneyHive to evaluate agent performance, interrogate failures, and monitor quality in production. - [Langfuse](https://langfuse.com/docs/integrations/ollama) is an open source LLM observability platform that enables teams to collaboratively monitor, evaluate and debug AI applications. - [MLflow Tracing](https://mlflow.org/docs/latest/llms/tracing/index.html#automatic-tracing) is an open source LLM observability tool with a convenient API to log and visualize traces, making it easy to debug and evaluate GenAI applications.