File size: 2,761 Bytes
c7e434a 2195b13 5395cd1 c7e434a 5395cd1 c7e434a 5395cd1 c7e434a 2195b13 c7e434a 897c408 c7e434a 2195b13 c7e434a 2195b13 c7e434a 2195b13 c7e434a |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 |
# Hugging Face Spaces - Single Container Dockerfile
FROM python:3.10-slim
WORKDIR /app
# Install system dependencies including Redis
RUN apt-get update && apt-get install -y \
ffmpeg \
libsndfile1 \
git \
redis-server \
curl \
&& rm -rf /var/lib/apt/lists/*
# Copy requirements
COPY requirements.txt .
# Install Python dependencies
RUN pip install --no-cache-dir -r requirements.txt
# Create cache directory for models BEFORE copying code
# This ensures model downloads are cached even when code changes
RUN mkdir -p /.cache && chmod -R 777 /.cache
RUN mkdir -p /data/.cache && chmod -R 777 /data/.cache
ENV HF_HOME=/.cache
ENV TORCH_HOME=/data/.cache
ENV XDG_CACHE_HOME=/.cache
ENV WHISPER_CACHE=/data/.cache
# Pre-download models during build (HF Pro with persistent storage)
# These layers will be CACHED and won't rebuild when only code changes
# 1. Download Structure Model from HF Hub (~475MB)
RUN python -c "from transformers import AutoTokenizer, AutoModelForSequenceClassification; \
print('📥 Downloading Structure Model from HF Hub...'); \
AutoTokenizer.from_pretrained('Cyberlace/swara-structure-model', cache_dir='/.cache'); \
AutoModelForSequenceClassification.from_pretrained('Cyberlace/swara-structure-model', cache_dir='/.cache'); \
print('✅ Structure Model cached!')" && chmod -R 777 /.cache
# 2. Whisper medium: LAZY LOADING on first request
# Build OOM - HF Space build container has RAM limit
# Will download to /data/.cache on FIRST REQUEST (~2-3 min)
# With HF Pro persistent storage, download persists across restarts
# Subsequent requests will be fast using cached model
# 3. Download Sentence Transformer for Keywords (~420MB)
RUN python -c "from sentence_transformers import SentenceTransformer; \
print('📥 Downloading Sentence Transformer...'); \
SentenceTransformer('paraphrase-multilingual-MiniLM-L12-v2', cache_folder='/.cache'); \
print('✅ Sentence Transformer cached!')" && chmod -R 777 /.cache
# 4. Download Silero VAD (~10MB)
RUN python -c "import torch; \
print('📥 Downloading Silero VAD model...'); \
torch.hub.load(repo_or_dir='snakers4/silero-vad', model='silero_vad', force_reload=False); \
print('✅ Silero VAD cached!')" && chmod -R 777 /.cache
# Copy application code LAST (after model downloads)
# This way, code changes don't invalidate model cache layers
COPY . .
# Fix all cache permissions after code copy (in case any new cache created)
RUN chmod -R 777 /.cache || true
# Create uploads directory with proper permissions
RUN mkdir -p uploads && chmod 777 uploads
# Make start script executable
RUN chmod +x start.sh
# Expose Hugging Face Spaces port
EXPOSE 7860
# Start script (Redis + Worker + API)
CMD ["./start.sh"]
|