Update Dockerfile

Dockerfile

@@ -1,39 +1,36 @@
 # Lightweight Python image
 FROM python:3.10-slim
 
-# System deps: ffmpeg (for Whisper), git + g++ (some wheels may need it)
+# System deps
 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
+# Make writable dirs for caches and NLTK
+RUN mkdir -p /data/nltk_data \
+    /data/huggingface/transformers \
+    /data/huggingface/datasets \
+    /data/tmp && chmod -R 777 /data
 
-# Optional: choose Whisper size via env (tiny/base/small/medium)
-# You can override this in Space settings too.
+# Point all caches to /data (writable)
+ENV NLTK_DATA=/data/nltk_data
+ENV HF_HOME=/data/huggingface
+ENV TRANSFORMERS_CACHE=/data/huggingface/transformers
+ENV HF_DATASETS_CACHE=/data/huggingface/datasets
+ENV TMPDIR=/data/tmp
+
+# Optional: choose Whisper size via env (ignored now if using SpeechRecognition)
 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 .  
+COPY README.md . 
 
-# Hugging Face Spaces expects the app to listen on port 7860
+# Spaces expects 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; \
-    from nltk.sentiment.vader import SentimentIntensityAnalyzer as _; \
-    import nltk; \
-    nltk.download('vader_lexicon'); \
-    whisper.load_model('${WHISPER_MODEL}')"
-
-# Start FastAPI with uvicorn
+# Start FastAPI
 CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]