Create app.py

app.py

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+import gradio as gr
+import os
+import subprocess
+import tempfile
+import shutil
+from zipfile import ZipFile
+import logging
+import json
+import threading
+import psutil
+
+# Configure logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+connected_cpus = {}
+
+# Function to donate CPU
+def donate_cpu(data):
+    host = data['host']
+    cpu_count = data['cpu_count']
+    connected_cpus[host] = {"cpu_count": cpu_count, "usage": 0.0}
+    logger.info(f"CPU donated by {host} with {cpu_count} CPUs.")
+    return {"status": "success", "message": f"CPU donated by {host}"}
+
+# Function to update CPU usage
+def update_cpu_usage(data):
+    host = data['host']
+    usage = data['usage']
+    if host in connected_cpus:
+        connected_cpus[host]['usage'] = usage
+        logger.info(f"Updated CPU usage for {host}: {usage}%")
+    return {"status": "success"}
+
+# Function to run the provided Python script using MPI
+def run_script(script_name, folder_path):
+    output_log = tempfile.TemporaryFile(mode='w+t')
+    try:
+        # Collect all available CPUs
+        total_cpus = sum(cpu['cpu_count'] for cpu in connected_cpus.values())
+        
+        # Run the script using MPI
+        result = subprocess.run(['mpiexec', '-n', str(total_cpus), 'python', script_name], cwd=folder_path, stdout=output_log, stderr=subprocess.STDOUT)
+        output_log.seek(0)
+        log_output = output_log.read()
+    except Exception as e:
+        log_output = str(e)
+    finally:
+        output_log.close()
+    
+    return log_output
+
+# Function to handle file uploads and script execution
+def handle_upload(folder, script_name):
+    # Create a temporary directory to store uploaded files
+    temp_dir = tempfile.mkdtemp()
+    
+    # Save the uploaded folder contents to the temporary directory
+    folder_path = os.path.join(temp_dir, 'uploaded_folder')
+    os.makedirs(folder_path, exist_ok=True)
+    for file_name, file_obj in folder.items():
+        with open(os.path.join(folder_path, file_name), 'wb') as f:
+            f.write(file_obj.read())
+
+    # Run the script
+    log_output = run_script(script_name, folder_path)
+    
+    # Create a zip file of the entire folder (including any new files created by the script)
+    zip_path = os.path.join(temp_dir, 'output_folder.zip')
+    with ZipFile(zip_path, 'w') as zipf:
+        for root, _, files in os.walk(folder_path):
+            for file in files:
+                zipf.write(os.path.join(root, file), os.path.relpath(os.path.join(root, file), folder_path))
+    
+    return log_output, zip_path
+
+# Function to get connected CPUs information
+def get_cpu_info():
+    info = []
+    for host, data in connected_cpus.items():
+        info.append(f"{host}: {data['cpu_count']} CPUs, {data['usage']}% usage")
+    return "\n".join(info)
+
+# Gradio interface
+def gradio_interface():
+    with gr.Blocks() as demo:
+        gr.Markdown("## Python Script Executor with Distributed Computing")
+        
+        with gr.Row():
+            folder = gr.File(label="Upload Folder", file_count="multiple", file_types=['file'])
+            script_name = gr.Textbox(label="Python Script Name")
+        
+        log_output = gr.Textbox(label="Log Output", interactive=False)
+        output_folder = gr.File(label="Download Output Folder")
+        cpu_info = gr.Textbox(label="Connected CPUs Info", interactive=False)
+        
+        run_button = gr.Button("Run Script")
+        refresh_button = gr.Button("Refresh CPU Info")
+        
+        run_button.click(fn=handle_upload, inputs=[folder, script_name], outputs=[log_output, output_folder])
+        refresh_button.click(fn=get_cpu_info, inputs=[], outputs=[cpu_info])
+        
+        # Define the donate CPU endpoint
+        demo.api(donate_cpu, inputs=gr.JSON(), outputs=gr.JSON(), name="donate_cpu")
+    
+    demo.launch()
+
+if __name__ == "__main__":
+    gradio_interface()