A ready-to-use LLM application development environment for Apple Silicon Macs (M1/M2/M3). Includes LangChain, LlamaIndex, Hugging Face Transformers, and API clients for OpenAI and Anthropic. Built as a native linux/arm64 image — runs in Docker Desktop without Rosetta emulation.
Note: GPU acceleration is not available inside Docker containers on Apple Silicon: Metal/MPS is a macOS-only framework with no Docker passthrough. This image provides native ARM64 CPU performance only.
Note: This container is designed to be used as part of a VS Code Dev Container environment, not run directly. See the full environment setup on GitHub for devcontainer configuration and usage instructions.
vscode user for seamless devcontainer integration| Component | Version |
|---|---|
| Base Image | python:3.12-slim |
| Platform | linux/arm64 |
| PyTorch | Latest (CPU, ARM64) |
| Python | 3.12 |
langchain - LLM application frameworkllama-index - Data framework for LLM applicationstransformers - Hugging Face model hub and inferencesmolagents - Hugging Face agents frameworkopenai - OpenAI API clientanthropic - Anthropic Claude API clientollama - Ollama server and Python client for local modelschromadb - Embedded vector databasesentence-transformers - Text embeddingsgradio - Web UI frameworkaccelerate - Model loading and distributed trainingdatasets - Hugging Face datasetstiktoken - Token countingThis image is optimized for use with VS Code Dev Containers. The vscode user (UID 1000) is pre-configured with sudo access for a seamless development experience.
docker run --rm -it \
--platform linux/arm64 \
-v $(pwd):/workspace \
gperdrizet/llms-mac:latest bash
Or launch a Gradio app:
docker run --platform linux/arm64 -p 7860:7860 -v $(pwd):/workspace gperdrizet/llms-mac:latest \
python your_gradio_app.py
See the GitHub repository for license information.
Content type
Image
Digest
sha256:34ad9a7eb…
Size
5 GB
Last updated
about 1 month ago
docker pull gperdrizet/llms-mac