Dockerfile

# ============================================================
# VoiceVault — Docker Image for Hugging Face Spaces
# ============================================================
# Base: Python 3.11-slim (stable, widely supported on HF)
# Runtime: CPU-only (Groq cloud API for transcription + LLM)
# Port: 7860 (HF Spaces default)
# ============================================================

FROM python:3.11-slim

WORKDIR /app

# ── System dependencies ────────────────────────────────────────────────
# build-essential : compiles C extensions (chromadb, numpy, etc.)
# git             : some pip packages clone during install
# tesseract-ocr   : OCR fallback for scanned PDFs (pytesseract)
# libsndfile1     : soundfile audio I/O library (WAV reading for VAD)
RUN apt-get update && apt-get install -y --no-install-recommends \
        build-essential \
        git \
        tesseract-ocr \
        libsndfile1 \
    && rm -rf /var/lib/apt/lists/*

# ── Python: CPU-only PyTorch FIRST ────────────────────────────────────
# Install before requirements.txt so pip reuses this install (~650MB)
# instead of the CUDA wheel from PyPI (~2.5GB).
RUN pip install --no-cache-dir \
    torch==2.5.1 \
    --index-url https://download.pytorch.org/whl/cpu

# ── Python: all other dependencies ────────────────────────────────────
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

# ── spaCy language model ───────────────────────────────────────────────
# Required by SemanticChunker for sentence tokenization during ingestion.
RUN python -m spacy download en_core_web_sm

# ── Pre-download ML models ────────────────────────────────────────────
# Baking models into the image avoids slow cold-start downloads in prod.
# Embedding model  (~90 MB) — used for vector search
# Cross-encoder    (~67 MB) — used for reranking retrieved chunks
ENV HF_HOME=/app/cache
ENV TRANSFORMERS_CACHE=/app/cache
ENV SENTENCE_TRANSFORMERS_HOME=/app/cache

RUN python -c "\
from sentence_transformers import SentenceTransformer, CrossEncoder; \
SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2'); \
CrossEncoder('cross-encoder/ms-marco-MiniLM-L12-v2'); \
print('Models pre-downloaded successfully.')"

# ── Application code ──────────────────────────────────────────────────
COPY . .

# ── Runtime directories ───────────────────────────────────────────────
RUN mkdir -p data/uploads models

# ── Environment ───────────────────────────────────────────────────────
# Force CPU — avoids CUDA errors on HF CPU-only hardware
ENV CUDA_VISIBLE_DEVICES=-1
# Suppress Windows-only symlink warning (harmless, reduces log noise)
ENV HF_HUB_DISABLE_SYMLINKS_WARNING=1
# Ensure Python output is unbuffered (logs appear immediately)
ENV PYTHONUNBUFFERED=1
# Server binding — HF Spaces requires 0.0.0.0:7860
ENV HOST=0.0.0.0
ENV PORT=7860

EXPOSE 7860

# ── Entrypoint ────────────────────────────────────────────────────────
CMD ["python", "server.py"]