112341e162
Stabilize Windows+WSL setup by fixing script line-ending pitfalls, WSL Ollama host detection, and dashboard startup behavior so models are detected reliably in Mission Control. Co-authored-by: Cursor <cursoragent@cursor.com>
343 lines
12 KiB
Bash
Executable File
343 lines
12 KiB
Bash
Executable File
#!/bin/bash
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# ============================================================
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# TTS Setup - One-Shot Script for Fresh Laptop
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#
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# Sets up Orpheus TTS (via Ollama) and Qwen3-TTS (direct Python)
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# on macOS (Apple Silicon) or Linux (CUDA GPU / WSL2).
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#
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# What this does:
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# 1. Installs Python 3.12 (Homebrew on macOS, apt on Linux)
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# 2. Creates Python venv with TTS packages (MPS on macOS, CUDA on Linux)
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# 3. Pulls Orpheus TTS model via Ollama
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# 4. Downloads SNAC audio decoder
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# 5. (Optional) Downloads Qwen3-TTS 0.6B
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#
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# Prerequisites:
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# macOS: Homebrew + Ollama installed
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# Linux: apt + Ollama accessible at localhost:11434
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#
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# Usage:
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# bash setup-tts.sh
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# From WSL with Ollama on Windows: OLLAMA_HOST=http://<Windows_IP>:11434 bash setup-tts.sh
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#
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# After setup, test with:
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# .venv-qwen-tts/bin/python test_orpheus_tts.py
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# ============================================================
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set -e
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SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
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VENV="$SCRIPT_DIR/.venv-qwen-tts"
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MODELS_DIR="$SCRIPT_DIR/models"
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# HuggingFace mirror that works through corporate proxy
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# On personal machines, set HF_MIRROR=https://huggingface.co to download directly
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HF_MIRROR="${HF_MIRROR:-https://hf-mirror.com}"
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# Ollama API base URL (for WSL2 with Ollama on Windows, set OLLAMA_HOST=http://<Windows_IP>:11434)
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OLLAMA_BASE="${OLLAMA_HOST:-http://localhost:11434}"
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OLLAMA_BASE="${OLLAMA_BASE%/}"
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# WSL2: if localhost fails, try Windows host via default gateway (common when Ollama runs on Windows)
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if [ "$OLLAMA_BASE" = "http://localhost:11434" ] && ! curl -s --max-time 2 "$OLLAMA_BASE/api/tags" &>/dev/null; then
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if [ -r /proc/version ] && grep -qi microsoft /proc/version 2>/dev/null; then
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WIN_HOST=$(ip route show default 2>/dev/null | awk '{print $3}' | head -1)
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if [ -n "$WIN_HOST" ] && curl -s --max-time 2 "http://${WIN_HOST}:11434/api/tags" &>/dev/null; then
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OLLAMA_BASE="http://${WIN_HOST}:11434"
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export OLLAMA_HOST="${OLLAMA_BASE}"
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fi
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fi
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fi
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export OLLAMA_HOST="${OLLAMA_HOST:-$OLLAMA_BASE}"
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# Detect OS
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OS_TYPE="$(uname -s)"
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IS_MAC=false
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[ "$OS_TYPE" = "Darwin" ] && IS_MAC=true
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RED='\033[0;31m'
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GREEN='\033[0;32m'
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YELLOW='\033[1;33m'
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NC='\033[0m'
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ok() { echo -e "${GREEN}[OK]${NC} $1"; }
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warn() { echo -e "${YELLOW}[!!]${NC} $1"; }
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fail() { echo -e "${RED}[FAIL]${NC} $1"; exit 1; }
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step() { echo -e "\n${GREEN}=== $1 ===${NC}"; }
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echo "+------------------------------------------------------+"
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echo "| TTS Setup - Local Speech Generation |"
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echo "| Orpheus TTS (Ollama) + Qwen3-TTS (Python) |"
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echo "+------------------------------------------------------+"
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echo ""
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# -- 0. Check prerequisites -----------------------------------
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step "Checking prerequisites"
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if $IS_MAC; then
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# Homebrew
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if ! command -v brew &>/dev/null; then
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fail "Homebrew not found. Install: /bin/bash -c \"\$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)\""
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fi
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ok "Homebrew"
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# Ollama (install via Homebrew if missing)
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if ! command -v ollama &>/dev/null; then
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warn "Ollama not found. Installing..."
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brew install ollama
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fi
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else
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# Linux / WSL2 - Ollama should be installed on host or via install script
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if ! command -v ollama &>/dev/null; then
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# On WSL2 Ollama runs on the Windows side; check if reachable
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if ! curl -s --max-time 2 "$OLLAMA_BASE/api/tags" &>/dev/null; then
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fail "Ollama not reachable at $OLLAMA_BASE. From WSL set OLLAMA_HOST=http://<Windows_IP>:11434 (e.g. from /etc/resolv.conf nameserver)."
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fi
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ok "Ollama reachable at $OLLAMA_BASE (Windows host)"
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fi
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fi
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ok "Ollama installed"
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# Check if Ollama is running
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if ! curl -s --max-time 2 "$OLLAMA_BASE/api/tags" &>/dev/null; then
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warn "Ollama not running at $OLLAMA_BASE. Starting..."
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if command -v ollama &>/dev/null; then
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ollama serve &>/dev/null &
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sleep 3
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fi
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if ! curl -s --max-time 2 "$OLLAMA_BASE/api/tags" &>/dev/null; then
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fail "Could not start Ollama. Try manually: ollama serve (or from WSL set OLLAMA_HOST=http://<Windows_IP>:11434)"
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fi
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fi
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ok "Ollama running at $OLLAMA_BASE"
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# GPU check
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ARCH=$(uname -m)
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if $IS_MAC; then
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if [ "$ARCH" != "arm64" ]; then
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warn "Not Apple Silicon ($ARCH). MPS acceleration won't be available."
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else
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ok "Apple Silicon ($ARCH) - MPS acceleration available"
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fi
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else
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if command -v nvidia-smi &>/dev/null; then
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GPU_NAME=$(nvidia-smi --query-gpu=name --format=csv,noheader 2>/dev/null | head -1)
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ok "NVIDIA GPU detected: $GPU_NAME - CUDA acceleration available"
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else
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warn "nvidia-smi not found. CUDA acceleration won't be available (CPU fallback)."
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fi
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fi
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# -- 1. Install Python 3.12 -----------------------------------
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step "Python 3.12"
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PYTHON_CMD=""
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# Check various Python 3.12 locations
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for cmd in python3.12 /opt/homebrew/bin/python3.12 /usr/local/bin/python3.12 python3; do
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if command -v "$cmd" &>/dev/null; then
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PYTHON_CMD="$cmd"
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break
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fi
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done
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if [ -z "$PYTHON_CMD" ]; then
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if $IS_MAC; then
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warn "Python 3.12 not found. Installing via Homebrew..."
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brew install python@3.12
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PYTHON_CMD="/opt/homebrew/bin/python3.12"
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else
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warn "Python 3.12 not found. Installing via apt..."
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sudo apt update && sudo apt install -y python3.12 python3.12-venv python3-pip
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PYTHON_CMD="python3.12"
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fi
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fi
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PYTHON_VER=$("$PYTHON_CMD" --version 2>&1)
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ok "$PYTHON_VER at $PYTHON_CMD"
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# -- 2. Create venv --------------------------------------------
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step "Python virtual environment"
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if [ -f "$VENV/bin/python" ]; then
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ok "Venv exists at $VENV"
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else
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echo "Creating venv..."
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"$PYTHON_CMD" -m venv "$VENV"
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ok "Venv created at $VENV"
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fi
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# -- 3. Install Python packages --------------------------------
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step "Python packages"
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# Check if snac is installed (quick proxy for all packages)
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if "$VENV/bin/python" -c "import snac" &>/dev/null; then
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ok "Packages already installed (snac, torch, etc.)"
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else
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echo "Installing packages (this may take a few minutes)..."
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"$VENV/bin/pip" install -U pip --quiet
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if $IS_MAC; then
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# macOS: default PyTorch includes MPS support
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"$VENV/bin/pip" install -U snac qwen-tts --quiet
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else
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# Linux: install PyTorch with CUDA first, then snac/qwen-tts
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echo "Installing PyTorch with CUDA support..."
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"$VENV/bin/pip" install -U torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu124 --quiet
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"$VENV/bin/pip" install -U snac qwen-tts --quiet
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fi
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ok "Packages installed"
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fi
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# -- 4. Pull Orpheus TTS model ---------------------------------
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step "Orpheus TTS model (Ollama)"
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# Helper: use ollama CLI if available, otherwise use API (WSL2 where CLI is on Windows)
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ollama_list() {
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if command -v ollama &>/dev/null; then
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ollama list 2>/dev/null
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else
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curl -s "$OLLAMA_BASE/api/tags" 2>/dev/null | python3 -c "import sys,json; [print(m['name']) for m in json.load(sys.stdin).get('models',[])]" 2>/dev/null
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fi
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}
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ollama_pull() {
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local model="$1"
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if command -v ollama &>/dev/null; then
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ollama pull "$model"
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else
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echo " (Using Ollama API at $OLLAMA_BASE to pull model...)"
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curl -s -X POST "$OLLAMA_BASE/api/pull" -d "{\"name\":\"$model\",\"stream\":false}" --max-time 600
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echo ""
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fi
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}
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if ollama_list | grep -q "orpheus"; then
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ok "Orpheus TTS already downloaded"
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else
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echo "Pulling sematre/orpheus:en (4 GB)..."
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ollama_pull "sematre/orpheus:en"
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ok "Orpheus TTS downloaded"
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fi
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# -- 5. Download SNAC decoder ----------------------------------
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step "SNAC 24kHz audio decoder (~76 MB)"
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mkdir -p "$MODELS_DIR/snac_24khz"
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if [ -f "$MODELS_DIR/snac_24khz/pytorch_model.bin" ]; then
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if $IS_MAC; then
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SIZE=$(stat -f%z "$MODELS_DIR/snac_24khz/pytorch_model.bin" 2>/dev/null)
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else
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SIZE=$(stat -c%s "$MODELS_DIR/snac_24khz/pytorch_model.bin" 2>/dev/null)
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fi
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if [ "$SIZE" -gt 1000000 ]; then
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ok "SNAC decoder already downloaded ($(echo "scale=1; $SIZE/1048576" | bc) MB)"
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else
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warn "SNAC file looks corrupted (${SIZE} bytes). Re-downloading..."
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rm -f "$MODELS_DIR/snac_24khz/pytorch_model.bin"
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fi
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fi
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if [ ! -f "$MODELS_DIR/snac_24khz/pytorch_model.bin" ]; then
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echo "Downloading config.json..."
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curl -k -sL -o "$MODELS_DIR/snac_24khz/config.json" \
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"$HF_MIRROR/hubertsiuzdak/snac_24khz/raw/main/config.json"
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# Verify config is JSON (not an HTML block page)
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if ! python3 -c "import json; json.load(open('$MODELS_DIR/snac_24khz/config.json'))" &>/dev/null; then
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fail "Downloaded config.json is not valid JSON. The mirror may be blocked. Try from home network."
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fi
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ok "config.json downloaded"
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echo "Downloading pytorch_model.bin (~76 MB)..."
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curl -k -L --progress-bar -o "$MODELS_DIR/snac_24khz/pytorch_model.bin" \
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"$HF_MIRROR/hubertsiuzdak/snac_24khz/resolve/main/pytorch_model.bin"
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# Verify it's a real model file (zip/pytorch format), not HTML
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FILE_TYPE=$(file -b "$MODELS_DIR/snac_24khz/pytorch_model.bin" | head -c 20)
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if echo "$FILE_TYPE" | grep -qi "html"; then
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rm -f "$MODELS_DIR/snac_24khz/pytorch_model.bin"
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fail "Downloaded model is HTML (proxy block page). Try from home network."
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fi
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ok "SNAC decoder downloaded"
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fi
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# Verify SNAC loads in Python
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echo "Verifying SNAC decoder loads..."
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if "$VENV/bin/python" -c "
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import snac, torch
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model = snac.SNAC.from_pretrained('$MODELS_DIR/snac_24khz')
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print(f'SNAC: {sum(p.numel() for p in model.parameters())/1e6:.1f}M parameters')
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" 2>/dev/null; then
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ok "SNAC decoder verified"
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else
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fail "SNAC decoder failed to load. Delete models/snac_24khz/ and re-run."
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fi
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# -- 6. (Optional) Download Qwen3-TTS --------------------------
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step "Qwen3-TTS 0.6B (optional, ~1.7 GB total)"
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QWEN_TOKENIZER_DIR="$MODELS_DIR/Qwen3-TTS-Tokenizer-12Hz"
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QWEN_MODEL_DIR="$MODELS_DIR/Qwen3-TTS-12Hz-0.6B-CustomVoice"
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if [ -d "$QWEN_MODEL_DIR" ] && [ -f "$QWEN_MODEL_DIR/config.json" ]; then
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ok "Qwen3-TTS already downloaded"
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else
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echo "Qwen3-TTS 0.6B requires ~1.7 GB download (tokenizer + model)."
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echo "This is optional - Orpheus TTS (above) works without it."
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read -p "Download Qwen3-TTS? [y/N] " -n 1 -r
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echo
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if [[ $REPLY =~ ^[Yy]$ ]]; then
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# Tokenizer (~650 MB)
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echo "Downloading Qwen3-TTS Tokenizer (~650 MB)..."
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mkdir -p "$QWEN_TOKENIZER_DIR"
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for f in config.json configuration.json preprocessor_config.json; do
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curl -k -sL -o "$QWEN_TOKENIZER_DIR/$f" \
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"$HF_MIRROR/Qwen/Qwen3-TTS-Tokenizer-12Hz/resolve/main/$f" 2>/dev/null || true
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done
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curl -k -L --progress-bar -o "$QWEN_TOKENIZER_DIR/model.safetensors" \
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"$HF_MIRROR/Qwen/Qwen3-TTS-Tokenizer-12Hz/resolve/main/model.safetensors"
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ok "Tokenizer downloaded"
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# Model
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echo "Downloading Qwen3-TTS 0.6B (~1.2 GB)..."
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mkdir -p "$QWEN_MODEL_DIR"
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for f in config.json generation_config.json; do
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curl -k -sL -o "$QWEN_MODEL_DIR/$f" \
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"$HF_MIRROR/Qwen/Qwen3-TTS-12Hz-0.6B-CustomVoice/resolve/main/$f" 2>/dev/null || true
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done
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curl -k -L --progress-bar -o "$QWEN_MODEL_DIR/model.safetensors" \
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"$HF_MIRROR/Qwen/Qwen3-TTS-12Hz-0.6B-CustomVoice/resolve/main/model.safetensors"
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ok "Qwen3-TTS 0.6B downloaded"
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else
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warn "Skipped. You can re-run this script later to download."
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fi
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fi
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# -- Summary ---------------------------------------------------
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step "Setup Complete"
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echo ""
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echo "Installed components:"
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echo " Orpheus TTS (Ollama): $(ollama_list 2>/dev/null | grep orpheus | head -1 || echo 'ready')"
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echo " SNAC decoder: $MODELS_DIR/snac_24khz/"
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if [ -d "$QWEN_MODEL_DIR" ] && [ -f "$QWEN_MODEL_DIR/config.json" ]; then
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echo " Qwen3-TTS 0.6B: $QWEN_MODEL_DIR/"
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else
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echo " Qwen3-TTS 0.6B: (not installed - re-run setup to add)"
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fi
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echo ""
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echo "Disk usage:"
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du -sh "$MODELS_DIR"/* 2>/dev/null | sed 's/^/ /'
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echo ""
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echo "Test commands:"
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echo " $VENV/bin/python $SCRIPT_DIR/test_orpheus_tts.py"
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if $IS_MAC; then
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echo " afplay test_orpheus_tara.wav"
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else
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echo " aplay test_orpheus_tara.wav (or: ffplay -nodisp -autoexit test_orpheus_tara.wav)"
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fi
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if [ -d "$QWEN_MODEL_DIR" ]; then
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echo " $VENV/bin/python $SCRIPT_DIR/test_qwen_tts.py"
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fi
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echo ""
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echo "Voices: tara, leah, jess, leo, dan, mia, zac, zoe"
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echo "Emotion: <laugh>, <chuckle>, <sigh>, <cough>, <groan>, <yawn>, <gasp>"
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