Update Dockerfile

Dockerfile

@@ -12,7 +12,7 @@ WORKDIR /app
 RUN mkdir -p /app/.cache /app/models && \
     chmod -R 777 /app/.cache /app/models
 
-# Install system dependencies (ADDED ca-certificates)
+# Install system dependencies (INCLUDING SSL CERTS)
 RUN apt-get update && apt-get install -y --no-install-recommends \
     libsndfile1 ffmpeg ca-certificates && \
     rm -rf /var/lib/apt/lists/*
@@ -22,25 +22,33 @@ COPY requirements.txt .
 RUN pip install --no-cache-dir -U pip && \
     pip install --no-cache-dir -r requirements.txt
 
-# Pre-download TTS model
-RUN python -c "from transformers import AutoTokenizer, AutoProcessor, BarkModel; \
-               model_name = 'suno/bark-small'; \
-               print(f'Downloading {model_name}...'); \
-               tokenizer = AutoTokenizer.from_pretrained(model_name); \
-               processor = AutoProcessor.from_pretrained(model_name); \
-               model = BarkModel.from_pretrained(model_name); \
-               tokenizer.save_pretrained('/app/models/suno-bark'); \
-               processor.save_pretrained('/app/models/suno-bark'); \
-               model.save_pretrained('/app/models/suno-bark')"
-
-# Pre-download sentiment model (SEPARATED INTO ITS OWN STEP)
-RUN python -c "from transformers import AutoModelForSequenceClassification, AutoTokenizer; \
-               model_name = 'cardiffnlp/twitter-xlm-roberta-base-sentiment'; \
-               print(f'Downloading {model_name}...'); \
-               tokenizer = AutoTokenizer.from_pretrained(model_name); \
-               model = AutoModelForSequenceClassification.from_pretrained(model_name); \
-               tokenizer.save_pretrained('/app/models/sentiment'); \
-               model.save_pretrained('/app/models/sentiment')"
+# Pre-download TTS model (WITH ERROR HANDLING)
+RUN python -c "try: \
+    from transformers import AutoTokenizer, AutoProcessor, BarkModel; \
+    model_name = 'suno/bark-small'; \
+    print(f'Downloading {model_name}...'); \
+    tokenizer = AutoTokenizer.from_pretrained(model_name); \
+    processor = AutoProcessor.from_pretrained(model_name); \
+    model = BarkModel.from_pretrained(model_name); \
+    tokenizer.save_pretrained('/app/models/suno-bark'); \
+    processor.save_pretrained('/app/models/suno-bark'); \
+    model.save_pretrained('/app/models/suno-bark'); \
+    except Exception as e: \
+    print(f'ERROR: {str(e)}'); \
+    exit(1)"
+
+# Pre-download sentiment model (WITH ERROR HANDLING)
+RUN python -c "try: \
+    from transformers import AutoModelForSequenceClassification, AutoTokenizer; \
+    model_name = 'cardiffnlp/twitter-xlm-roberta-base-sentiment'; \
+    print(f'Downloading {model_name}...'); \
+    tokenizer = AutoTokenizer.from_pretrained(model_name); \
+    model = AutoModelForSequenceClassification.from_pretrained(model_name); \
+    tokenizer.save_pretrained('/app/models/sentiment'); \
+    model.save_pretrained('/app/models/sentiment'); \
+    except Exception as e: \
+    print(f'ERROR: {str(e)}'); \
+    exit(1)"
 
 # Copy application code
 COPY app.py .