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+# Use the specified RunPod base image with CUDA support and Python 3.8
+FROM python:3.8-slim
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    build-essential \
+    python3-dev \
+    ffmpeg \
+    aria2 \
+    git \
+    git-lfs \
+    && rm -rf /var/lib/apt/lists/*
+
+# Clone the repository into the container
+ARG CACHEBUST=1
+RUN git clone https://huggingface.co/spaces/smjain/Advanced-RVC-Inference /app
+
+# Set the working directory to the cloned repository to run commands inside it
+WORKDIR /app
+
+# Install Git Large File Storage (LFS), then pull LFS files
+RUN git lfs install && git lfs pull
+
+# Create a virtual environment named 'infer' and activate it
+#RUN python3 -m venv /venv/infer
+#ENV PATH="/venv/infer/bin:$PATH"
+
+# Upgrade pip and install Python dependencies from the project's requirements.txt
+# Also, install Flask and av as specified
+RUN pip install --upgrade pip && \
+    pip install --upgrade -r requirements.txt --no-cache-dir && \
+    pip install flask av boto3 flask_dance
+
+# Move PyTorch model weights into the weights directory if necessary
+RUN mv *.pth weights/ || echo "No weights to move"
+
+# Setting Flask application
+# Expose the port Flask is running on
+EXPOSE 5000
+
+# Command to directly run the Flask application script
+CMD ["python", "myinfer_latest.py"]

download.py

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+from flask import Flask, send_file, request, jsonify
+import boto3
+import os
+
+app = Flask(__name__)
+
+# AWS / DigitalOcean Spaces credentials
+ACCESS_ID = os.getenv('ACCESS_ID', 'DO0026WEQUG4WF6WQNJ9')
+SECRET_KEY = os.getenv('SECRET_KEY', 'UG7kQicGgWmkfVmESWK889RxZG49UqV7vRfYUJDFFUo')
+
+@app.route('/download/<filename>', methods=['GET'])
+def download_file(filename):
+    # Configure the client with your credentials
+    session = boto3.session.Session()
+    client = session.client('s3',
+                            region_name='nyc3',
+                            endpoint_url='https://nyc3.digitaloceanspaces.com',
+                            aws_access_key_id=ACCESS_ID,
+                            aws_secret_access_key=SECRET_KEY)
+    
+    # Define the bucket and object key
+    bucket_name = 'sing'  # Your bucket name
+    object_key = f'{filename}'  # Construct the object key
+
+    # Define the local path to save the file
+    local_file_path = os.path.join('weights', filename)
+
+    # Download the file from the bucket
+    try:
+        client.download_file(bucket_name, object_key, local_file_path)
+    except client.exceptions.NoSuchKey:
+        return jsonify({'error': 'File not found in the bucket'}), 404
+    except Exception as e:
+        return jsonify({'error': str(e)}), 500
+
+    # Optional: Send the file directly to the client
+    # return send_file(local_file_path, as_attachment=True)
+
+    return jsonify({'success': True, 'message': 'File downloaded successfully', 'file_path': local_file_path})
+
+if __name__ == '__main__':
+    app.run(debug=True)