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Adapt to Ollama version 0.5.7, which supports DeepSeek-R1 inference

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<div align="center"> # <div align="center"><strong>Ollama</strong></div>
  <a href="https://ollama.com" />
<img alt="ollama" height="200px" src="https://github.com/ollama/ollama/assets/3325447/0d0b44e2-8f4a-4e99-9b52-a5c1c741c8f7">
</a>
</div>
# Ollama ## 简介
Get up and running with large language models. Ollama可快速部署主流模型。
### macOS ## 安装
[Download](https://ollama.com/download/Ollama-darwin.zip) ### 1、使用源码编译方式安装
### Windows #### 环境准备
[Download](https://ollama.com/download/OllamaSetup.exe) ##### Docker
### Linux ```bash
docker pull docker pull image.sourcefind.cn:5000/dcu/admin/base/pytorch:2.1.0-py3.10-dtk24.04.3-ubuntu20.04
docker run -i -t -d --device=/dev/kfd --privileged --network=host --device=/dev/dri --cap-add=SYS_PTRACE --security-opt seccomp=unconfined -v 项目地址(绝对路径):/home -v /opt/hyhal:/opt/hyhal:ro -v --group-add video --shm-size 16G --name {容器名} {镜像ID}
``` ```
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 [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 4 | 14B | 9.1GB | `ollama run phi4` |
| Phi 3 Mini | 3.8B | 2.3GB | `ollama run phi3` |
| 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 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 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 `"""`: 1、下载源码
``` ```bash
>>> """Hello, git clone -b 0.5.7 http://developer.sourcefind.cn/codes/OpenDAS/ollama.git
... world! cd ollama
... """
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: $(cat README.md)"
Ollama is a lightweight, extensible framework for building and running language models on the local machine. It provides a simple API for creating, running, and managing models, as well as a library of pre-built models that can be easily used in a variety of applications.
``` ```
### Show model information #### 编译
``` ##### 安装go
ollama show llama3.2
```
### List models on your computer ```bash
wget https://go.dev/dl/go1.22.8.linux-amd64.tar.gz
tar -C /usr/local -xzf go1.22.8.linux-amd64.tar.gz
export PATH=$PATH:/usr/local/go/bin
``` # 修改go下载源，提升速度（按需设置）
ollama list go env -w GOPROXY=https://goproxy.cn,direct
``` ```
### List which models are currently loaded ##### 运行编译
``` ```bash
ollama ps export LIBRARY_PATH=/opt/dtk/lib:$LIBRARY_PATH
make -j 16
go build .
``` ```
### Stop a model which is currently running ## 运行
```bash
export HSA_OVERRIDE_GFX_VERSION=设备型号（如: gfx906对应9.0.6；k100ai gfx928对应9.2.8）
export ROCR_VISIBLE_DEVICES=所有设备号（0,1,2,3,4,5,6,...）/选择设备号
./ollama serve （选择可用设备，可通过上条命令输出结果查看）
# 新增fa和kv cache量化
OLLAMA_FLASH_ATTENTION=1 OLLAMA_KV_CACHE_TYPE=q4_0 ./ollama serve
./ollama run llama3.1
``` ```
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) ## deepseek-r1模型推理
### Running local builds
Next, start the server:
``` ```
export HSA_OVERRIDE_GFX_VERSION=设备型号（如: gfx906对应9.0.6；k100ai gfx928对应9.2.8）
./ollama serve ./ollama serve
./ollama run deepseek-r1:671b
``` ```
Finally, in a separate shell, run a model: 更多使用方式请参考[原项目](https://github.com/ollama/ollama)。
```
./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)
- [IntelliBar](https://intellibar.app/) (AI-powered assistant for macOS)
- [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)
- [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.
- [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)
- [Perplexica](https://github.com/ItzCrazyKns/Perplexica) (An AI-powered search engine & an open-source alternative to Perplexity AI)
### 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
- [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)
- [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 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)
- [TextLLaMA](https://github.com/adarshM84/TextLLaMA) A Chrome Extension that helps you write emails, correct grammar, and translate into any language
### Supported backends
- [llama.cpp](https://github.com/ggerganov/llama.cpp) project founded by Georgi Gerganov. 注意：每次运行前请检查环境变量`HSA_OVERRIDE_GFX_VERSION`是否正确设置。
### Observability ## 参考资料
- [OpenLIT](https://github.com/openlit/openlit) is an OpenTelemetry-native tool for monitoring Ollama Applications & GPUs using traces and metrics. * https://github.com/ollama/ollama
- [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.
discover/amd_linux.go
View file @ 84e5b6ff
...@@ -22,7 +22,7 @@ import ( ...@@ -22,7 +22,7 @@ import (
// Discovery logic for AMD/ROCm GPUs // Discovery logic for AMD/ROCm GPUs
const ( const (
DriverVersionFile = "/sys/module/amdgpu/version" DriverVersionFile = "/sys/module/hydcu/version"
AMDNodesSysfsDir = "/sys/class/kfd/kfd/topology/nodes/" AMDNodesSysfsDir = "/sys/class/kfd/kfd/topology/nodes/"
GPUPropertiesFileGlob = AMDNodesSysfsDir + "*/properties" GPUPropertiesFileGlob = AMDNodesSysfsDir + "*/properties"
...@@ -42,8 +42,8 @@ const ( ...@@ -42,8 +42,8 @@ const (
var ( var (
// Used to validate if the given ROCm lib is usable // Used to validate if the given ROCm lib is usable
ROCmLibGlobs = []string{"libhipblas.so.2*", "rocblas"} // TODO - probably include more coverage of files here... ROCmLibGlobs = []string{"libhipblas.so.0.1","rocblas"} // TODO - probably include more coverage of files here...
RocmStandardLocations = []string{"/opt/rocm/lib", "/usr/lib64"} RocmStandardLocations = []string{"/opt/dtk/lib", "/usr/lib64"}
) )
// Gather GPU information from the amdgpu driver if any supported GPUs are detected // Gather GPU information from the amdgpu driver if any supported GPUs are detected
......
llama/ggml-cuda/mmvq.cu
View file @ 84e5b6ff
...@@ -168,7 +168,7 @@ static void mul_mat_vec_q_cuda( ...@@ -168,7 +168,7 @@ static void mul_mat_vec_q_cuda(
int64_t nwarps = 1; int64_t nwarps = 1;
int64_t rows_per_cuda_block = 1; int64_t rows_per_cuda_block = 1;
if (ggml_cuda_info().devices[id].cc < GGML_CUDA_CC_CDNA || ggml_cuda_info().devices[id].cc == GGML_CUDA_CC_RDNA1) { // NVIDIA and AMD older than RDNA2 but not CDNA if (ggml_cuda_info().devices[id].cc < 1001030) { // NVIDIA and AMD older than RDNA2 but not CDNA
switch(ncols_y) { switch(ncols_y) {
case 1: case 1:
nwarps = 4; nwarps = 4;
......
llama/ggml-cuda/norm.cu
View file @ 84e5b6ff
...@@ -27,7 +27,7 @@ ...@@ -27,7 +27,7 @@
#include "norm.cuh" #include "norm.cuh"
template <int block_size> template <int block_size>
static __global__ void norm_f32(const float * x, float * dst, const int ncols, const float eps) { static __global__ void __launch_bounds__(1024) norm_f32(const float * x, float * dst, const int ncols, const float eps) {
const int row = blockIdx.x*blockDim.y + threadIdx.y; const int row = blockIdx.x*blockDim.y + threadIdx.y;
const int tid = threadIdx.x; const int tid = threadIdx.x;
...@@ -63,7 +63,7 @@ static __global__ void norm_f32(const float * x, float * dst, const int ncols, c ...@@ -63,7 +63,7 @@ static __global__ void norm_f32(const float * x, float * dst, const int ncols, c
} }
template <int block_size> template <int block_size>
static __global__ void group_norm_f32(const float * x, float * dst, const int group_size, const int ne_elements, const float eps) { static __global__ void __launch_bounds__(1024) group_norm_f32(const float * x, float * dst, const int group_size, const int ne_elements, const float eps) {
// blockIdx.x: num_groups idx // blockIdx.x: num_groups idx
// threadIdx.x: block_size idx // threadIdx.x: block_size idx
int start = blockIdx.x * group_size; int start = blockIdx.x * group_size;
...@@ -124,7 +124,7 @@ static __global__ void group_norm_f32(const float * x, float * dst, const int gr ...@@ -124,7 +124,7 @@ static __global__ void group_norm_f32(const float * x, float * dst, const int gr
} }
template <int block_size> template <int block_size>
static __global__ void rms_norm_f32(const float * x, float * dst, const int ncols, const float eps) { static __global__ void __launch_bounds__(1024) rms_norm_f32(const float * x, float * dst, const int ncols, const float eps) {
const int row = blockIdx.x*blockDim.y + threadIdx.y; const int row = blockIdx.x*blockDim.y + threadIdx.y;
const int tid = threadIdx.x; const int tid = threadIdx.x;
......
make/Makefile.rocm
View file @ 84e5b6ff
...@@ -6,8 +6,8 @@ ...@@ -6,8 +6,8 @@
include make/common-defs.make include make/common-defs.make
include make/rocm-defs.make include make/rocm-defs.make
HIP_ARCHS_COMMON := gfx900 gfx940 gfx941 gfx942 gfx1010 gfx1012 gfx1030 gfx1100 gfx1101 gfx1102 HIP_ARCHS_COMMON := gfx928 gfx906
HIP_ARCHS_LINUX := gfx906:xnack- gfx908:xnack- gfx90a:xnack+ gfx90a:xnack- HIP_ARCHS_LINUX := gfx928 gfx906
ifeq ($(OS),windows) ifeq ($(OS),windows)
GPU_LIB_DIR := $(shell cygpath -m -s "$(HIP_PATH)/bin") GPU_LIB_DIR := $(shell cygpath -m -s "$(HIP_PATH)/bin")
...@@ -88,8 +88,8 @@ GPU_COMPILER_CUFLAGS = \ ...@@ -88,8 +88,8 @@ GPU_COMPILER_CUFLAGS = \
-DUSE_PROF_API=1 \ -DUSE_PROF_API=1 \
-std=gnu++17 \ -std=gnu++17 \
-x hip \ -x hip \
-mllvm=-amdgpu-early-inline-all=true \ #-mllvm=-amdgpu-early-inline-all=true \
-mllvm=-amdgpu-function-calls=false \ #-mllvm=-amdgpu-function-calls=false \
-Wno-expansion-to-defined \ -Wno-expansion-to-defined \
-Wno-invalid-noreturn \ -Wno-invalid-noreturn \
-Wno-ignored-attributes \ -Wno-ignored-attributes \
...@@ -111,7 +111,7 @@ $(RUNNERS_DIST_DIR)/$(GPU_RUNNER_NAME)$(GPU_RUNNER_EXTRA_VARIANT)/ollama_llama_s ...@@ -111,7 +111,7 @@ $(RUNNERS_DIST_DIR)/$(GPU_RUNNER_NAME)$(GPU_RUNNER_EXTRA_VARIANT)/ollama_llama_s
$(ROCBLAS_DIST_DEP_MANIFEST): $(ROCBLAS_DIST_DEP_MANIFEST):
@-mkdir -p $(dir $@) @-mkdir -p $(dir $@)
@echo "Copying rocblas library..." @echo "Copying rocblas library..."
(cd $(GPU_LIB_DIR)/rocblas/library/ && tar cf - . ) | (cd $(dir $@) && tar xf - ) cd $(HIP_PATH)/../rocblas/lib/ && tar cf - . | (cd $(dir $@) && tar xf - )
@echo "rocblas library copy complete" @echo "rocblas library copy complete"
$(GPU_DIST_TRANSITIVE_LIB_DEPS): $(GPU_DIST_TRANSITIVE_LIB_DEPS):
......
make/gpu.make
View file @ 84e5b6ff
# Generalized GPU runner build # Generalized GPU runner build
INCLUDES = -I$(CURDIR)/llama
GPU_COMPILER_CFLAGS += $(INCLUDES)
ifndef GPU_RUNNER_NAME ifndef GPU_RUNNER_NAME
dummy: dummy:
$(error This makefile is not meant to build directly, but instead included in other Makefiles that set required variables) $(error This makefile is not meant to build directly, but instead included in other Makefiles that set required variables)
......
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