update

README copy.md

+# <div align="center"><strong>Ollama</strong></div>
+
+## 简介
+
+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。
+
+## 安装
+
+### 1、使用dockerfile方式安装
+
+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）。
+
+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。
+
+### 2、使用源码编译方式安装（推荐）
+
+#### 环境准备
+
+##### Docker
+
+    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}
+
+
+1、下载源码
+
+    git clone -b v0.3.5 http://developer.sourcefind.cn/codes/OpenDAS/ollama.git --depth=1
+    cd ollama
+
+2、安装依赖包
+
+    cd llm/llama.cpp
+    pip install -r requirements.txt
+
+#### 编译
+
+##### 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 LIBRARY_PATH=/opt/dtk/llvm/lib/clang/15.0.0/lib/linux/:$LIBRARY_PATH
+    export HIP_VISIBLE_DEVICES=所有设备号（0,1,2,3,4,5,6,...）/选择设备号
+
+安装go
+
+    cd ../..
+    tar -C /usr/local -xzf go1.22.3.linux-amd64.tar.gz
+    export PATH=$PATH:/usr/local/go/bin
+    
+    # 修改go下载源，提升速度（按需设置）
+    go env -w GO111MODULE=on
+    go env -w GOPROXY=https://goproxy.cn,direct
+
+##### 运行编译
+
+    cd llm/generate && bash gen_linux.sh
+    cd ../.. && go build
+
+## 验证
+
+    ./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)。
+
+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
+
+* https://github.com/ollama/ollama
+* https://github.com/ggerganov/llama.cpp

README.md

-# <div align="center"><strong>Ollama</strong></div>
+<div align="center">
+ <img alt="ollama" height="200px" src="https://github.com/ollama/ollama/assets/3325447/0d0b44e2-8f4a-4e99-9b52-a5c1c741c8f7">
+</div>
 
-## 简介
+# 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。
+[![Discord](https://dcbadge.vercel.app/api/server/ollama?style=flat&compact=true)](https://discord.gg/ollama)
 
-## 安装
+Get up and running with large language models.
 
-### 1、使用dockerfile方式安装
+### macOS
 
-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）。
+[Download](https://ollama.com/download/Ollama-darwin.zip)
 
-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。
+### Windows preview
 
-### 2、使用源码编译方式安装（推荐）
+[Download](https://ollama.com/download/OllamaSetup.exe)
 
-#### 环境准备
+### Linux
 
-##### Docker
+```
+curl -fsSL https://ollama.com/install.sh | sh
+```
 
-    docker pull docker pull image.sourcefind.cn:5000/dcu/admin/base/pytorch:2.1.0-py3.10-dtk24.04.3-ubuntu20.04
+[Manual install instructions](https://github.com/ollama/ollama/blob/main/docs/linux.md)
 
-    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}
+### Docker
 
+The official [Ollama Docker image](https://hub.docker.com/r/ollama/ollama) `ollama/ollama` is available on Docker Hub.
 
-1、下载源码
+### Libraries
 
-    git clone -b v0.3.5 http://developer.sourcefind.cn/codes/OpenDAS/ollama.git --depth=1
-    cd ollama
+- [ollama-python](https://github.com/ollama/ollama-python)
+- [ollama-js](https://github.com/ollama/ollama-js)
 
-2、安装依赖包
+## Quickstart
 
-    cd llm/llama.cpp
-    pip install -r requirements.txt
+To run and chat with [Llama 3.1](https://ollama.com/library/llama3.1):
 
-#### 编译
+```
+ollama run llama3.1
+```
 
-##### 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 LIBRARY_PATH=/opt/dtk/llvm/lib/clang/15.0.0/lib/linux/:$LIBRARY_PATH
-    export HIP_VISIBLE_DEVICES=所有设备号（0,1,2,3,4,5,6,...）/选择设备号
+## Model library
 
-安装go
+Ollama supports a list of models available on [ollama.com/library](https://ollama.com/library 'ollama model library')
 
-    cd ../..
-    tar -C /usr/local -xzf go1.22.3.linux-amd64.tar.gz
-    export PATH=$PATH:/usr/local/go/bin
+Here are some example models that can be downloaded:
 
-    # 修改go下载源，提升速度（按需设置）
-    go env -w GO111MODULE=on
-    go env -w GOPROXY=https://goproxy.cn,direct
+| Model              | Parameters | Size  | Download                       |
+| ------------------ | ---------- | ----- | ------------------------------ |
+| Llama 3.1          | 8B         | 4.7GB | `ollama run llama3.1`          |
+| Llama 3.1          | 70B        | 40GB  | `ollama run llama3.1:70b`      |
+| 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`             |
 
-##### 运行编译
+> [!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.
 
-    cd llm/generate && bash gen_linux.sh
-    cd ../.. && go build
+## Customize a model
 
-## 验证
+### Import from GGUF
 
-    ./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
+Ollama supports importing GGUF models in the Modelfile:
 
-更多使用方式请参考[原项目](https://github.com/ollama/ollama)。
+1. Create a file named `Modelfile`, with a `FROM` instruction with the local filepath to the model you want to import.
 
-注意：每次运行前请检查环境变量`HSA_OVERRIDE_GFX_VERSION`是否正确设置。
+   ```
+   FROM ./vicuna-33b.Q4_0.gguf
+   ```
 
-## 参考资料
+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 `llama3.1` 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