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Get up and running with Llama 3.3, DeepSeek-R1, Phi-4, Gemma 3, Mistral Small 3.1 and other large language models.

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Important

This is a fork of Ollama which we at NOLAI use for our Framework desktops. The Ollama team have stated that RPC is not their main priority so, we want to keep our own active branch maintaining it.

We sometimes will also add different features that we like. If you have any questions feel free to contact us.

Here is the docker image: https://hub.docker.com/r/julianvanderhorst/ollama-framework-desktop

Setup your frameworks

You need to have the correct ROCM install on your framework. Make sure to follow these two guides:

https://rocm.docs.amd.com/projects/radeon-ryzen/en/latest/docs/install/installryz/native_linux/install-ryzen.html

and then

https://instinct.docs.amd.com/projects/container-toolkit/en/latest/container-runtime/quick-start-guide.html

Make sure your frameworks have a good and fast connection between them. You can use a good usb4 cable or network them together with a switch

RPC docker compose

services:
  ollama:
    volumes:
      - ollama:/root/.ollama
    container_name: ollama
    tty: true
    restart: unless-stopped
    image: julianvanderhorst/ollama-framework-desktop:latest
    network_mode: "host"
    environment:
      - export OLLAMA_LOAD_TIMEOUT=10m
      - OLLAMA_RPC_SERVERS=127.0.0.1:50053
      - OLLAMA_LIBRARY_PATH=/usr/lib/ollama:/usr/lib/ollama/rocm_v7
      - LD_LIBRARY_PATH=/opt/rocm/lib:/usr/lib/ollama:/usr/lib/ollama/rocm_v7
    depends_on:
      - ollama_rpc_worker

  ollama_rpc_worker:
    container_name: ollama_rpc_worker_sam
    volumes:
      - ollama:/root/.ollama
    image: julianvanderhorst/ollama-framework-desktop:latest
    runtime: amd
    restart: unless-stopped
    network_mode: "host"
    environment:
      - AMD_VISIBLE_DEVICES=all
      - OLLAMA_LIBRARY_PATH=/usr/lib/ollama:/usr/lib/ollama/rocm_v7
      - LD_LIBRARY_PATH=/opt/rocm/lib:/usr/lib/ollama:/usr/lib/ollama/rocm_v7
    command: rpc --host 0.0.0.0 --port 50053 --device ROCm0
volumes:
  ollama: {}

You can just add RPC clients to OLLAMA_RPC_SERVERS by appending them with a comma. 127.0.0.1:50053,192.168.1.1:50053,192.168.1.12:50053 etc.

ollama

Ollama

Start building with open models.

Download

macOS

curl -fsSL https://ollama.com/install.sh | sh

or download manually

Windows

irm https://ollama.com/install.ps1 | iex

or download manually

Linux

curl -fsSL https://ollama.com/install.sh | sh

Manual install instructions

Docker

The official Ollama Docker image ollama/ollama is available on Docker Hub.

Libraries

Community

Get started

ollama

You'll be prompted to run a model or connect Ollama to your existing agents or applications such as claude, codex, openclaw and more.

Coding

To launch a specific integration:

ollama launch claude

Supported integrations include Claude Code, Codex, Droid, and OpenCode.

AI assistant

Use OpenClaw to turn Ollama into a personal AI assistant across WhatsApp, Telegram, Slack, Discord, and more:

ollama launch openclaw

Chat with a model

Run and chat with Gemma 3:

ollama run gemma3

See ollama.com/library for the full list.

See the quickstart guide for more details.

REST API

Ollama has a REST API for running and managing models.

curl http://localhost:11434/api/chat -d '{
  "model": "gemma3",
  "messages": [{
    "role": "user",
    "content": "Why is the sky blue?"
  }],
  "stream": false
}'

See the API documentation for all endpoints.

Python

pip install ollama
from ollama import chat

response = chat(model='gemma3', messages=[
  {
    'role': 'user',
    'content': 'Why is the sky blue?',
  },
])
print(response.message.content)

JavaScript

npm i ollama
import ollama from "ollama";

const response = await ollama.chat({
  model: "gemma3",
  messages: [{ role: "user", content: "Why is the sky blue?" }],
});
console.log(response.message.content);

Supported backends

  • llama.cpp project founded by Georgi Gerganov.

Documentation

Community Integrations

Want to add your project? Open a pull request.

Chat Interfaces

Web

Desktop

  • Dify.AI - LLM app development platform
  • AnythingLLM - All-in-one AI app for Mac, Windows, and Linux
  • Maid - Cross-platform mobile and desktop client
  • Witsy - AI desktop app for Mac, Windows, and Linux
  • Cherry Studio - Multi-provider desktop client
  • Ollama App - Multi-platform client for desktop and mobile
  • PyGPT - AI desktop assistant for Linux, Windows, and Mac
  • Alpaca - GTK4 client for Linux and macOS
  • SwiftChat - Cross-platform including iOS, Android, and Apple Vision Pro
  • Enchanted - Native macOS and iOS client
  • RWKV-Runner - Multi-model desktop runner
  • Ollama Grid Search - Evaluate and compare models
  • macai - macOS client for Ollama and ChatGPT
  • AI Studio - Multi-provider desktop IDE
  • Reins - Parameter tuning and reasoning model support
  • ConfiChat - Privacy-focused with optional encryption
  • LLocal.in - Electron desktop client
  • MindMac - AI chat client for Mac
  • Msty - Multi-model desktop client
  • BoltAI for Mac - AI chat client for Mac
  • IntelliBar - AI-powered assistant for macOS
  • Kerlig AI - AI writing assistant for macOS
  • Hillnote - Markdown-first AI workspace
  • Perfect Memory AI - Productivity AI personalized by screen and meeting history

Mobile

SwiftChat, Enchanted, Maid, Ollama App, Reins, and ConfiChat listed above also support mobile platforms.

Code Editors & Development

Libraries & SDKs

Frameworks & Agents

RAG & Knowledge Bases

  • RAGFlow - RAG engine based on deep document understanding
  • R2R - Open-source RAG engine
  • MaxKB - Ready-to-use RAG chatbot
  • Minima - On-premises or fully local RAG
  • Chipper - AI interface with Haystack RAG
  • ARGO - RAG and deep research on Mac/Windows/Linux
  • Archyve - RAG-enabling document library
  • Casibase - AI knowledge base with RAG and SSO
  • BrainSoup - Native client with RAG and multi-agent automation

Bots & Messaging

Terminal & CLI

Productivity & Apps

Observability & Monitoring

  • Opik - Debug, evaluate, and monitor LLM applications
  • OpenLIT - OpenTelemetry-native monitoring for Ollama and GPUs
  • Lunary - LLM observability with analytics and PII masking
  • Langfuse - Open source LLM observability
  • HoneyHive - AI observability and evaluation for agents
  • MLflow Tracing - Open source LLM observability

Database & Embeddings

Infrastructure & Deployment

Cloud

Package Managers

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Get up and running with Llama 3.3, DeepSeek-R1, Phi-4, Gemma 3, Mistral Small 3.1 and other large language models.

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