Micromamba and uv for Python package management

.github/workflows/jetson-pypi-health.yml

@@ -2,8 +2,6 @@
 name: Check PyPI Health
 
 on:
-  schedule:
-    - cron: '*/5 * * * *'
   workflow_dispatch:
 
 jobs:

packages/build/python/Dockerfile

@@ -2,7 +2,7 @@
 # name: python
 # group: build
 # depends: [build-essential, pip_cache]
-# notes: installs core `python3` packages and `pip`
+# notes: installs core `python`, `uv` and `pip` in a conda environment
 #---
 ARG BASE_IMAGE
 FROM ${BASE_IMAGE}
@@ -24,7 +24,11 @@ ENV PYTHON_VERSION=${PYTHON_VERSION} \
     PIP_VERBOSE=1 \
     TWINE_NON_INTERACTIVE=1 \
     DEBIAN_FRONTEND=noninteractive \
-    PATH=/opt/venv/bin:$PATH
+    PATH=/opt/conda/bin:$PATH \
+    MAMBA_ROOT_PREFIX=/opt/conda \
+    MAMBA_EXE=/usr/local/bin/micromamba \
+    CONDA_PREFIX=/opt/conda \
+    UV_COMPILE_BYTECODE=1
 
 #PYTHONPATH=/opt/venv/lib/python${PYTHON_VERSION_ARG}/site-packages:/usr/lib/python3/dist-packages:$PYTHONPATH \
 

packages/build/python/config.py

@@ -13,7 +13,7 @@ def python(version, requires=None) -> list:
 
     if requires:
         pkg['requires'] = requires
-        
+
     return pkg
 
 package = [

packages/build/python/install.sh

@@ -1,71 +1,59 @@
 #!/usr/bin/env bash
-# Python installer
+# Python installer using Micromamba
 set -x
 
-apt-get update
-apt-get install -y --no-install-recommends \
-	python${PYTHON_VERSION} \
-	python${PYTHON_VERSION}-dev
-
-which python${PYTHON_VERSION}
-return_code=$?
-set -e
-
-if [ $return_code != 0 ]; then
-   echo "-- using deadsnakes ppa to install Python ${PYTHON_VERSION}"
-   add-apt-repository ppa:deadsnakes/ppa
-   apt-get update
-   apt-get install -y --no-install-recommends \
-	  python${PYTHON_VERSION} \
-	  python${PYTHON_VERSION}-dev
-fi
-
-# path 1:  Python 3.8-3.10 for JP5/6
-# path 2:  Python 3.6 for JP4
-# path 3:  Python 3.12 for 24.04
-distro=$(lsb_release -rs)
-
-if [ $distro = "24.04" ]; then
-   apt-get install -y --no-install-recommends python3-venv
-   python3 -m venv --system-site-packages /opt/venv
-   source /opt/venv/bin/activate
-   curl -sS https://bootstrap.pypa.io/get-pip.py | python${PYTHON_VERSION}
-elif [ $distro = "20.04" ]; then
-   curl -sS https://bootstrap.pypa.io/pip/3.8/get-pip.py | python3.8
-elif [ $distro = "18.04" ]; then
-   curl -sS https://bootstrap.pypa.io/pip/3.6/get-pip.py | python3.6
-else
-   curl -sS https://bootstrap.pypa.io/get-pip.py | python${PYTHON_VERSION}
+curl -Ls https://micro.mamba.pm/api/micromamba/linux-$(uname -m | sed 's/x86_64/64/;s/aarch64/aarch64/')/latest | tar -xvj bin/micromamba
+mv bin/micromamba /usr/local/bin/
+
+export MAMBA_ROOT_PREFIX=/opt/conda
+export CONDA_PREFIX=/opt/conda
+export PATH=/opt/conda/bin:$PATH
+mkdir -p $MAMBA_ROOT_PREFIX
+eval "$(micromamba shell hook -s posix)"
+micromamba shell init -s bash -r $MAMBA_ROOT_PREFIX
+
+# Install Python and core packages in base environment
+micromamba install -y -n base \
+    python=${PYTHON_VERSION} \
+    setuptools \
+    packaging \
+    "cython<3" \
+    wheel \
+    pip \
+    uv \
+    twine \
+    psutil \
+    pkginfo
+
+# Add micromamba initialization to /etc/profile.d for all shells
+cat > /etc/profile.d/mamba.sh << 'EOF'
+export MAMBA_EXE=/usr/bin/micromamba
+export MAMBA_ROOT_PREFIX=/opt/conda
+export PATH=/opt/conda/bin:$PATH
+
+if [ -f "${MAMBA_EXE}" ]; then
+    __mamba_setup="$("$MAMBA_EXE" shell hook --shell bash --root-prefix "$MAMBA_ROOT_PREFIX" 2> /dev/null)"
+    if [ $? -eq 0 ]; then
+        eval "$__mamba_setup"
+    else
+        alias micromamba="$MAMBA_EXE"
+    fi
+    unset __mamba_setup
 fi
 
-rm -rf /var/lib/apt/lists/*
-apt-get clean
+micromamba activate
+EOF
 
-ln -f -s /usr/bin/python${PYTHON_VERSION} /usr/local/bin/python3
-#ln -s /usr/bin/pip${PYTHON_VERSION} /usr/local/bin/pip3
+chmod +x /etc/profile.d/mamba.sh
+source /etc/profile.d/mamba.sh
 
-# This was causing issues downstream (e.g. Python2.7 still around in Ubuntu 18.04,
-# and in cmake python enumeration where some packages expect that 'python' is 2.7)
-# Another way is apt package 'python-is-python3' - symlinks /usr/bin/python to python
-#RUN update-alternatives --install /usr/bin/python python /usr/bin/python3 1 && \  \
-#    update-alternatives --install /usr/bin/pip pip /usr/bin/pip3 1 \
+ln -sf /opt/conda/bin/python /usr/local/bin/python3
+ln -sf /opt/conda/bin/python /usr/local/bin/python
+ln -sf /opt/conda/bin/pip /usr/local/bin/pip3
+ln -sf /opt/conda/bin/pip /usr/local/bin/pip
 
+# Verify installation
 which python3
 python3 --version
-
 which pip3
 pip3 --version
-
-python3 -m pip install --upgrade pip pkginfo --index-url https://pypi.org/simple
-
-pip3 install --no-binary :all: psutil
-pip3 install --upgrade \
-   setuptools \
-   packaging \
-   'Cython' \
-   wheel \
-   uv
-
-pip3 install --upgrade --index-url https://pypi.org/simple \
-   twine
-

packages/ml/onnxruntime/build.sh

@@ -10,7 +10,7 @@ if [ ! -d "/usr/lib/$(uname -m)-linux-gnu" ]; then
 fi
 
 # Ensure TensorRT libraries are in LD_LIBRARY_PATH
-export LD_LIBRARY_PATH=/usr/lib/$(uname -m)-linux-gnu:$LD_LIBRARY_PATH
+export LD_LIBRARY_PATH=/usr/lib/$(uname -m)-linux-gnu:/usr/local/cuda/compat:/usr/local/cuda/lib64:/usr/lib/$(uname -m)-linux-gnu/nvidia/:$LD_LIBRARY_PATH
 
 # Verify TensorRT components
 if [ ! -f "/usr/lib/$(uname -m)-linux-gnu/libnvinfer.so" ]; then
@@ -20,7 +20,7 @@ fi
 
 if [ ! -f "/usr/lib/$(uname -m)-linux-gnu/libnvdla_compiler.so" ]; then
     echo "TensorRT NVDLA compiler library not found"
-    exit 1
+    echo "TensorRT NVDLA compiler library not found - continuing anyway"
 fi
 
 pip3 uninstall -y onnxruntime || echo "onnxruntime was not previously installed"

packages/smart-home/homeassistant-base/config.py

@@ -193,8 +193,12 @@ def latest_deps_versions(branch_name: str) -> Tuple[Optional[str], Optional[str]
 
 def create_package(version, default=False) -> list:
     pkg = package.copy()
-    wanted_version = github_latest_tag('home-assistant/docker-base') if version == 'latest' else version
-    bashio_version, tempio_version, s6_overlay_version = latest_deps_versions(wanted_version)
+    try:
+        wanted_version = github_latest_tag('home-assistant/docker-base') if version == 'latest' else version
+        bashio_version, tempio_version, s6_overlay_version = latest_deps_versions(wanted_version)
+    except Exception as e:
+        print(f"Failed to fetch the latest version of dependencies: {e}")
+        bashio_version, tempio_version, s6_overlay_version = None, None, None
 
     if not all([bashio_version, tempio_version, s6_overlay_version]):
         log_warning("Failed to get dependency versions, using defaults")

packages/speech/orpheus/Dockerfile

@@ -0,0 +1,56 @@
+#---
+# name: orpheus
+# group: audio
+# depends: [torchaudio, numpy, tensorrt, onnxruntime, ffmpeg]
+# requires: '>=34.1.0'
+#---
+ARG BASE_IMAGE
+FROM ${BASE_IMAGE}
+
+# Set non-interactive frontend
+ENV DEBIAN_FRONTEND=noninteractive
+
+# Install system dependencies
+RUN apt-get update && \
+    apt-get install -y \
+    portaudio19-dev \
+    && apt-get clean && \
+    rm -rf /var/lib/apt/lists/*
+
+# Create app directory
+RUN mkdir -p /app/outputs && \
+    chmod 777 /app/outputs
+
+# Clone and install Orpheus-FastAPI
+RUN git clone https://github.com/Lex-au/Orpheus-FastAPI /opt/orpheus && \
+    cd /opt/orpheus && \
+    # Update requirements to use specific versions that work with Jetson
+    sed -i 's/numpy==1.24.0/numpy>=1.24.0/g' requirements.txt && \
+    echo "👁️######## Orpheus-FastAPI - requirements.txt ########👁️" && \
+    cat requirements.txt && \
+    echo "👁️^^^^^^^^ Orpheus-FastAPI - requirements.txt ^^^^^^^^👁️" && \
+    pip3 install -r requirements.txt
+
+# Set up environment variables
+ENV PYTHONUNBUFFERED=1 \
+    PYTHONPATH=/opt/orpheus \
+    USE_GPU=true
+
+# Verify installations
+RUN python3 -c "import torch; print('PyTorch version:', torch.__version__); \
+    print('CUDA available:', torch.cuda.is_available()); \
+    print('CUDA device count:', torch.cuda.device_count() if torch.cuda.is_available() else 'N/A')"
+
+RUN python3 -c "from snac import SNAC; print('SNAC import successful')"
+
+
+# Set default port
+ARG PORT=5005
+ENV PORT=${PORT}
+EXPOSE ${PORT}
+
+# Set working directory
+WORKDIR /opt/orpheus
+
+# Set the entrypoint
+CMD ["python3", "-m", "uvicorn", "app:app", "--host", "0.0.0.0", "--port", "5005", "--workers", "1"]

packages/speech/speaches/Dockerfile

@@ -1,35 +1,29 @@
 #---
 # name: speaches
 # group: audio
-# depends: [faster-whisper, piper-tts, kokoro-tts:onnx, python:3.12, nodejs]
+# depends: [faster-whisper, piper-tts, kokoro-tts:onnx, python:3.12, ffmpeg]
 # requires: '>=34.1.0'
 # docs: docs.md
 #---
 ARG BASE_IMAGE
 FROM ${BASE_IMAGE}
 
-# RUN apt-get update && \
-#     apt-get install -y libsndfile1-dev && \
-#     apt-get clean && \
-#     rm -rf /var/lib/apt/lists/*
-
-# RUN python3 -c "import onnxruntime; print('☑️✅ ONNX Runtime version:', onnxruntime.__version__); print('✅ EPs:', onnxruntime.get_available_providers())"
+RUN python3 -c "import onnxruntime; print('☑️✅ ONNX Runtime version:', onnxruntime.__version__); print('✅ EPs:', onnxruntime.get_available_providers())"
 
 # 1. Clone and install speaches
 RUN set -ex && \
-    git clone https://github.com/speaches-ai/speaches /opt/speaches && \
+    git clone -b renovate/jetson-arm64 https://github.com/JonnyTran/speaches /opt/speaches && \
     cd /opt/speaches && \
     sed -i 's|requires-python.*|requires-python = ">=3.10"|g' pyproject.toml && \
     sed -i 's|"faster-whisper.*",|"faster-whisper",|g' pyproject.toml && \
     sed -i 's|"ctranslate2.*",|"ctranslate2",|g' pyproject.toml && \
     sed -i 's|"kokoro-onnx.*",|"kokoro-onnx",|g' pyproject.toml && \
     sed -i 's|"numpy.*",|"numpy",|g' pyproject.toml && \
-    echo "👁️######## speaches - pyproject.toml ########👁️" && \
+    echo "######### speaches - pyproject.toml ######" && \
     cat pyproject.toml && \
-    echo "👁️^^^^^^^^ speaches - pyproject.toml ^^^^^^^^👁️" && \
-    pip3 install '.[ui]' && \
-    cp /opt/speaches/model_aliases.json / && \
-    pip3 uninstall -y onnxruntime onnxruntime-gpu || true
+    echo "^^^^^^^^ speaches - pyproject.toml ^^^^^6" && \
+    uv pip install '.[ui]' && \
+    cp /opt/speaches/model_aliases.json / || true
 
 # Patch to skip UI mount if dist/ missing
 COPY 0001-Conditionally-mount-realtime-console-dist.patch /tmp/
@@ -46,11 +40,12 @@ ENV PYTHONPATH="/opt/speaches/src:${PYTHONPATH}"
 RUN python3 -c "import speaches; import openai; import aiostream; print('✅ all modules import OK')"
 
 # 2. Extract GPU-enabled build
-RUN wget https://apt.jetson-ai-lab.dev/jp6/cu128/24.04/onnxruntime-gpu-1.22.tar.gz && \
-    tar -xzvf onnxruntime-gpu-1.22.tar.gz -C /usr/local
+# RUN wget https://apt.jetson-ai-lab.dev/jp6/cu128/24.04/onnxruntime-gpu-1.22.tar.gz && \
+#     tar -xzvf onnxruntime-gpu-1.22.tar.gz -C /usr/local
 
 # 3. Install ONNX Runtime GPU wheel if needed
-RUN pip3 install onnxruntime-gpu==1.22
+# RUN pip3 list
+# RUN pip3 install onnxruntime-gpu==1.22
 
 # 4. Confirm ONNX Runtime is correct
 RUN python3 -c "import onnxruntime; print('☑️✅ ONNX Runtime version:', onnxruntime.__version__); print('✅ EPs:', onnxruntime.get_available_providers())"

packages/speech/speaches/README.md

@@ -0,0 +1,70 @@
+# speaches
+
+> [`CONTAINERS`](#user-content-containers) [`IMAGES`](#user-content-images) [`RUN`](#user-content-run) [`BUILD`](#user-content-build)
+
+docs.md
+<details open>
+<summary><b><a id="containers">CONTAINERS</a></b></summary>
+<br>
+
+| **`speaches`** | |
+| :-- | :-- |
+| &nbsp;&nbsp;&nbsp;Builds | [![`speaches_jp60`](https://img.shields.io/github/actions/workflow/status/dusty-nv/jetson-containers/speaches_jp60.yml?label=speaches:jp60)](https://github.com/dusty-nv/jetson-containers/actions/workflows/speaches_jp60.yml) [![`speaches_jp51`](https://img.shields.io/github/actions/workflow/status/dusty-nv/jetson-containers/speaches_jp51.yml?label=speaches:jp51)](https://github.com/dusty-nv/jetson-containers/actions/workflows/speaches_jp51.yml) |
+| &nbsp;&nbsp;&nbsp;Requires | `L4T ['>=34.1.0']` |
+| &nbsp;&nbsp;&nbsp;Dependencies | [`build-essential`](/packages/build/build-essential) [`cuda`](/packages/cuda/cuda) [`cudnn`](/packages/cuda/cudnn) [`python`](/packages/build/python) [`numpy`](/packages/numpy) [`cmake`](/packages/build/cmake/cmake_pip) [`ffmpeg`](/packages/multimedia/ffmpeg) [`onnx`](/packages/onnx) [`ctranslate2`](/packages/ctranslate2) [`huggingface_hub`](/packages/llm/huggingface_hub) [`faster-whisper`](/packages/audio/faster-whisper) |
+| &nbsp;&nbsp;&nbsp;Dependants |  |
+| &nbsp;&nbsp;&nbsp;Dockerfile | [`Dockerfile`](Dockerfile) |
+| &nbsp;&nbsp;&nbsp;Images |  |
+
+</details>
+
+<details open>
+<summary><b><a id="images">CONTAINER IMAGES</a></b></summary>
+<br>
+
+| Repository/Tag | Date | Arch | Size |
+| :-- | :--: | :--: | :--: |
+
+> <sub>Container images are compatible with other minor versions of JetPack/L4T:</sub><br>
+> <sub>&nbsp;&nbsp;&nbsp;&nbsp;• L4T R32.7 containers can run on other versions of L4T R32.7 (JetPack 4.6+)</sub><br>
+> <sub>&nbsp;&nbsp;&nbsp;&nbsp;• L4T R35.x containers can run on other versions of L4T R35.x (JetPack 5.1+)</sub><br>
+</details>
+
+<details open>
+<summary><b><a id="run">RUN CONTAINER</a></b></summary>
+<br>
+
+To start the container, you can use [`jetson-containers run`](/docs/run.md) and [`autotag`](/docs/run.md#autotag), or manually put together a [`docker run`](https://docs.docker.com/engine/reference/commandline/run/) command:
+```bash
+# automatically pull or build a compatible container image
+jetson-containers run $(autotag speaches)
+
+# or explicitly specify one of the container images above
+jetson-containers run dustynv/speaches:r35.3.1
+
+# or if using 'docker run' (specify image and mounts/ect)
+sudo docker run --runtime nvidia -it --rm --network=host dustynv/speaches:r35.3.1
+```
+> <sup>[`jetson-containers run`](/docs/run.md) forwards arguments to [`docker run`](https://docs.docker.com/engine/reference/commandline/run/) with some defaults added (like `--runtime nvidia`, mounts a `/data` cache, and detects devices)</sup><br>
+> <sup>[`autotag`](/docs/run.md#autotag) finds a container image that's compatible with your version of JetPack/L4T - either locally, pulled from a registry, or by building it.</sup>
+
+To mount your own directories into the container, use the [`-v`](https://docs.docker.com/engine/reference/commandline/run/#volume) or [`--volume`](https://docs.docker.com/engine/reference/commandline/run/#volume) flags:
+```bash
+jetson-containers run -v /path/on/host:/path/in/container $(autotag speaches)
+```
+To launch the container running a command, as opposed to an interactive shell:
+```bash
+jetson-containers run $(autotag speaches) my_app --abc xyz
+```
+You can pass any options to it that you would to [`docker run`](https://docs.docker.com/engine/reference/commandline/run/), and it'll print out the full command that it constructs before executing it.
+</details>
+<details open>
+<summary><b><a id="build">BUILD CONTAINER</b></summary>
+<br>
+
+If you use [`autotag`](/docs/run.md#autotag) as shown above, it'll ask to build the container for you if needed.  To manually build it, first do the [system setup](/docs/setup.md), then run:
+```bash
+jetson-containers build speaches
+```
+The dependencies from above will be built into the container, and it'll be tested during.  Run it with [`--help`](/jetson_containers/build.py) for build options.
+</details>

packages/speech/speaches/model_aliases.json

@@ -1,5 +1,6 @@
 {
     "tts-1": "hexgrad/Kokoro-82M",
     "tts-1-hd": "hexgrad/Kokoro-82M",
+    "gpt-4o-mini-tts": "hexgrad/Kokoro-82M",
     "whisper-1": "Systran/faster-whisper-large-v3"
-}
+}