base on Get up and running with Llama 3.3, Mistral, Gemma 2, and other large language models. <div align="center">  <img alt="ollama" height="200px" src="https://github.com/ollama/ollama/assets/3325447/0d0b44e2-8f4a-4e99-9b52-a5c1c741c8f7"> </div> # Ollama [](https://discord.gg/ollama) Get up and running with large language models. ### macOS [Download](https://ollama.com/download/Ollama-darwin.zip) ### Windows [Download](https://ollama.com/download/OllamaSetup.exe) ### Linux ``` 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) ## Quickstart To run and chat with [Llama 3.2](https://ollama.com/library/llama3.2): ``` ollama run llama3.2 ``` ## 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 | | ------------------ | ---------- | ----- | -------------------------------- | | 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 3 Mini | 3.8B | 2.3GB | `ollama run phi3` | | Phi 3 Medium | 14B | 7.9GB | `ollama run phi3:medium` | | Gemma 2 | 2B | 1.6GB | `ollama run gemma2:2b` | | Gemma 2 | 9B | 5.5GB | `ollama run gemma2` | | Gemma 2 | 27B | 16GB | `ollama run gemma2:27b` | | 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` | | Solar | 10.7B | 6.1GB | `ollama run solar` | > [!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 ``` ollama create example -f Modelfile ``` 3. Run the model ``` ollama run example ``` ### Import from PyTorch or 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: ``` 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 examples, see the [examples](examples) directory. 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. ``` ollama create mymodel -f ./Modelfile ``` ### Pull a model ``` ollama pull llama3.2 ``` > This command can also be used to update a local model. Only the diff will be pulled. ### Remove a model ``` ollama rm llama3.2 ``` ### Copy a model ``` 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" The image features a yellow smiley face, which is likely the central focus of the picture. ``` ### Pass the prompt as an argument ``` $ ollama run llama3.2 "Summarize this file: $(cat README.md)" 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 ``` ollama show llama3.2 ``` ### List models on your computer ``` ollama list ``` ### List which models are currently loaded ``` ollama ps ``` ### Stop a model which is currently running ``` 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: ``` ./ollama serve ``` Finally, in a separate shell, run a model: ``` ./ollama run llama3.2 ``` ## REST API Ollama has a REST API for running and managing models. ### Generate a response ``` curl http://localhost:11434/api/generate -d '{ "model": "llama3.2", "prompt":"Why is the sky blue?" }' ``` ### Chat with a model ``` 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) - [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) - [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/blob/main/docs/config-local-ollama.md) - [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) - [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) - [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) - [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. - [Claude Dev](https://github.com/saoudrizwan/claude-dev) - 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) - [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) ### 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) - [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 - [orbiton](https://github.com/xyproto/orbiton) Configuration-free text editor and IDE with support for tab completion with Ollama. ### Apple Vision Pro - [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) - [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?channel=24.05&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/llms/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) - [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) - [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 unified API) ### Mobile - [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) ### 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 depends 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) ### Supported backends - [llama.cpp](https://github.com/ggerganov/llama.cpp) project founded by Georgi Gerganov. ### Observability - [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. ", Assign "at most 3 tags" to the expected json: {"id":"7239","tags":[]} "only from the tags list I provide: [{"id":77,"name":"3d"},{"id":89,"name":"agent"},{"id":17,"name":"ai"},{"id":54,"name":"algorithm"},{"id":24,"name":"api"},{"id":44,"name":"authentication"},{"id":3,"name":"aws"},{"id":27,"name":"backend"},{"id":60,"name":"benchmark"},{"id":72,"name":"best-practices"},{"id":39,"name":"bitcoin"},{"id":37,"name":"blockchain"},{"id":1,"name":"blog"},{"id":45,"name":"bundler"},{"id":58,"name":"cache"},{"id":21,"name":"chat"},{"id":49,"name":"cicd"},{"id":4,"name":"cli"},{"id":64,"name":"cloud-native"},{"id":48,"name":"cms"},{"id":61,"name":"compiler"},{"id":68,"name":"containerization"},{"id":92,"name":"crm"},{"id":34,"name":"data"},{"id":47,"name":"database"},{"id":8,"name":"declarative-gui "},{"id":9,"name":"deploy-tool"},{"id":53,"name":"desktop-app"},{"id":6,"name":"dev-exp-lib"},{"id":59,"name":"dev-tool"},{"id":13,"name":"ecommerce"},{"id":26,"name":"editor"},{"id":66,"name":"emulator"},{"id":62,"name":"filesystem"},{"id":80,"name":"finance"},{"id":15,"name":"firmware"},{"id":73,"name":"for-fun"},{"id":2,"name":"framework"},{"id":11,"name":"frontend"},{"id":22,"name":"game"},{"id":81,"name":"game-engine "},{"id":23,"name":"graphql"},{"id":84,"name":"gui"},{"id":91,"name":"http"},{"id":5,"name":"http-client"},{"id":51,"name":"iac"},{"id":30,"name":"ide"},{"id":78,"name":"iot"},{"id":40,"name":"json"},{"id":83,"name":"julian"},{"id":38,"name":"k8s"},{"id":31,"name":"language"},{"id":10,"name":"learning-resource"},{"id":33,"name":"lib"},{"id":41,"name":"linter"},{"id":28,"name":"lms"},{"id":16,"name":"logging"},{"id":76,"name":"low-code"},{"id":90,"name":"message-queue"},{"id":42,"name":"mobile-app"},{"id":18,"name":"monitoring"},{"id":36,"name":"networking"},{"id":7,"name":"node-version"},{"id":55,"name":"nosql"},{"id":57,"name":"observability"},{"id":46,"name":"orm"},{"id":52,"name":"os"},{"id":14,"name":"parser"},{"id":74,"name":"react"},{"id":82,"name":"real-time"},{"id":56,"name":"robot"},{"id":65,"name":"runtime"},{"id":32,"name":"sdk"},{"id":71,"name":"search"},{"id":63,"name":"secrets"},{"id":25,"name":"security"},{"id":85,"name":"server"},{"id":86,"name":"serverless"},{"id":70,"name":"storage"},{"id":75,"name":"system-design"},{"id":79,"name":"terminal"},{"id":29,"name":"testing"},{"id":12,"name":"ui"},{"id":50,"name":"ux"},{"id":88,"name":"video"},{"id":20,"name":"web-app"},{"id":35,"name":"web-server"},{"id":43,"name":"webassembly"},{"id":69,"name":"workflow"},{"id":87,"name":"yaml"}]" returns me the "expected json"