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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 psutil
from flask import Flask, request, jsonify
# Configure logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
# Initialize Flask app
app = Flask(__name__)
connected_cpus = {}
# Endpoint to donate CPU resources
@app.route('/donate_cpu', methods=['POST'])
def donate_cpu_handler():
data = request.get_json()
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 jsonify({"status": "success", "message": f"CPU donated by {host}"})
# Endpoint to update CPU usage
@app.route('/update_cpu_usage', methods=['POST'])
def update_cpu_usage_handler():
data = request.get_json()
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 jsonify({"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():
interface_inputs = [
gr.File(label="Upload Folder", file_count="multiple", file_types=['file']),
gr.Textbox(label="Python Script Name")
]
interface_outputs = [
gr.Textbox(label="Log Output", interactive=False),
gr.File(label="Download Output Folder"),
gr.Textbox(label="Connected CPUs Info", interactive=False)
]
iface = gr.Interface(
fn=handle_upload,
inputs=interface_inputs,
outputs=interface_outputs,
live=True,
theme="light" # Specify a theme that works, "light" is an example
)
iface.launch(port=7860) # Specify the port directly here
# Launch the Gradio interface using Flask's run method
if __name__ == "__main__":
app.run(host='0.0.0.0', port=7860)
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