Create Dockerfile

Dockerfile

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+# Lightweight Python image
+FROM python:3.10-slim
+
+# System deps: ffmpeg (for Whisper), git + g++ (some wheels may need it)
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    ffmpeg git build-essential \
+ && rm -rf /var/lib/apt/lists/*
+
+# For faster HF model caching inside the container
+ENV TRANSFORMERS_CACHE=/root/.cache/huggingface/transformers
+ENV HF_HOME=/root/.cache/huggingface
+ENV PYTHONDONTWRITEBYTECODE=1
+ENV PYTHONUNBUFFERED=1
+
+# Optional: choose Whisper size via env (tiny/base/small/medium)
+# You can override this in Space settings too.
+ENV WHISPER_MODEL=base
+
+# Copy files
+WORKDIR /app
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY app.py .
+COPY README.md .  
+
+# Hugging Face Spaces expects the app to listen on port 7860
+ENV PORT=7860
+
+# (Optional) Pre-download models on build to reduce cold-start
+# Comment out if build time becomes too long
+# RUN python -c "import nltk; \
+#     import whisper; \
+#     from nltk.sentiment.vader import SentimentIntensityAnalyzer as _; \
+#     import nltk; \
+#     nltk.download('vader_lexicon'); \
+#     whisper.load_model('${WHISPER_MODEL}')"
+
+# Start FastAPI with uvicorn
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]