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<div align="center"> # <div align="center"><strong>Ollama</strong></div>
 <img alt="ollama" height="200px" src="https://github.com/ollama/ollama/assets/3325447/0d0b44e2-8f4a-4e99-9b52-a5c1c741c8f7">
</div>
# Ollama ## 简介
[![Discord](https://dcbadge.vercel.app/api/server/ollama?style=flat&compact=true)](https://discord.gg/ollama) 1 Ollama是以llama.cpp为后端的前端大模型推理框架，可快速部署主流模型。
Get up and running with large language models. ## 安装
### macOS ### 1、使用dockerfile方式安装
[Download](https://ollama.com/download/Ollama-darwin.zip) 直接下载本仓库中的`v0.3.5`分支，然后执行`docker build xxxxx`相关命令（具体需自行查阅相关资料）。
### Windows preview 如遇到卡数检测错误，请参考 https://developer.hpccube.com/codes/OpenDAS/ollama/-/issues/1 ，也可以提前进行修复。
[Download](https://ollama.com/download/OllamaSetup.exe) ### 2、使用源码编译方式安装
### Linux #### 环境准备
``` ##### Docker
curl -fsSL https://ollama.com/install.sh | sh
```
[Manual install instructions](https://github.com/ollama/ollama/blob/main/docs/linux.md) docker pull docker pull image.sourcefind.cn:5000/dcu/admin/base/pytorch:2.1.0-py3.10-dtk24.04.3-ubuntu20.04
### Docker 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}
The official [Ollama Docker image](https://hub.docker.com/r/ollama/ollama) `ollama/ollama` is available on Docker Hub.
### Libraries 1、下载源码
- [ollama-python](https://github.com/ollama/ollama-python) git clone -b v0.3.5 http://developer.sourcefind.cn/codes/OpenDAS/ollama.git --depth=1
- [ollama-js](https://github.com/ollama/ollama-js) cd ollama
## Quickstart 2、安装依赖包
To run and chat with [Llama 3.1](https://ollama.com/library/llama3.1): cd llm/llama.cpp
pip install -r requirements.txt
``` #### 编译
ollama run llama3.1
```
## Model library ##### 环境设置
export AMDGPU_TARGETS=当前设备型号（如：gfx906，gfx928等）
export HSA_OVERRIDE_GFX_VERSION=设备型号（如: gfx906对应9.0.6；gfx928对应9.2.8）
export HIP_VISIBLE_DEVICES=所有设备号（0,1,2,3,4,5,6,...）/选择设备号
Ollama supports a list of models available on [ollama.com/library](https://ollama.com/library 'ollama model library') 安装go
Here are some example models that can be downloaded: https://golang.google.cn/dl/
| Model | Parameters | Size | Download | # 请替换[]中下载的go文件
| ------------------ | ---------- | ----- | ------------------------------ | cd ../..
| Llama 3.1 | 8B | 4.7GB | `ollama run llama3.1` | tar -C /usr/local -xzf [go-xxxx.tar.gz](ollama目录下)
| Llama 3.1 | 70B | 40GB | `ollama run llama3.1:70b` | export PATH=$PATH:/usr/local/go/bin
| 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] # 修改go下载源，提升速度（按需设置）
> 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. go env -w GO111MODULE=on
go env -w GOPROXY=https://goproxy.cn,direct
## Customize a model ##### 运行编译
### Import from GGUF cd llm/generate && bash gen_linux.sh
cd ../.. && go build
Ollama supports importing GGUF models in the Modelfile: ## 验证
1. Create a file named `Modelfile`, with a `FROM` instruction with the local filepath to the model you want to import. ./ollama serve （选择可用设备，可通过上条命令输出结果查看）
./ollama run llama3.1
``` 更多使用方式请参考[原项目](https://github.com/ollama/ollama)。
FROM ./vicuna-33b.Q4_0.gguf
```
2. Create the model in Ollama 注意：每次运行前请检查环境变量`HSA_OVERRIDE_GFX_VERSION`是否正确设置。
``` ## 参考资料
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 `llama3.1` model:
```
ollama pull llama3.1
```
Create a `Modelfile`:
```
FROM llama3.1
# 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 llama3.1
```
> This command can also be used to update a local model. Only the diff will be pulled.
### Remove a model
```
ollama rm llama3.1
```
### Copy a model
```
ollama cp llama3.1 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 llama3.1 "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 llama3.1
```
### List models on your computer
```
ollama list
```
### 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 llama3.1
```
## REST API
Ollama has a REST API for running and managing models.
### Generate a response
```
curl http://localhost:11434/api/generate -d '{
"model": "llama3.1",
"prompt":"Why is the sky blue?"
}'
```
### Chat with a model
```
curl http://localhost:11434/api/chat -d '{
"model": "llama3.1",
"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) (Chat with Code Repository)
- [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)
- [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)
- [Ollama with Google Mesop](https://github.com/rapidarchitect/ollama_mesop/) (Mesop Chat Client implementation with Ollama)
- [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)
### 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)
- [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)
- [Ollama eBook Summary](https://github.com/cognitivetech/ollama-ebook-summary/)
### Database
- [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)
### Package managers
- [Pacman](https://archlinux.org/packages/extra/x86_64/ollama/)
- [Helm Chart](https://artifacthub.io/packages/helm/ollama-helm/ollama)
- [Guix channel](https://codeberg.org/tusharhero/ollama-guix)
### Libraries
- [LangChain](https://python.langchain.com/docs/integrations/llms/ollama) and [LangChain.js](https://js.langchain.com/docs/modules/model_io/models/llms/integrations/ollama) with [example](https://js.langchain.com/docs/use_cases/question_answering/local_retrieval_qa)
- [Firebase Genkit](https://firebase.google.com/docs/genkit/plugins/ollama)
- [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)
- [LlamaIndex](https://gpt-index.readthedocs.io/en/stable/examples/llm/ollama.html)
- [LiteLLM](https://github.com/BerriAI/litellm)
- [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/amithkoujalgi/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)
### Mobile
- [Enchanted](https://github.com/AugustDev/enchanted)
- [Maid](https://github.com/Mobile-Artificial-Intelligence/maid)
### 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)
- [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)
- [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)
- [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)
### Supported backends
- [llama.cpp](https://github.com/ggerganov/llama.cpp) project founded by Georgi Gerganov.
* https://github.com/ollama/ollama
* https://github.com/ggerganov/llama.cpp
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