๐ง Hybrid and Local AI WorkspacesJuly 7, 2026โ
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Local AI Workspace Validator
A Python-based validation tool designed to ensure that local AI workspaces are correctly configured for hybrid workflows. It checks for missing dependencies, hardware compatibility (e.g., GPU/CPU), and ensures proper configuration of local and remote endpoints. This assists developers in troubleshooting and optimizing their AI environments.
What It Does
The Local AI Workspace Validator is a Python-based tool designed to ensure that local AI workspaces are correctly configured for hybrid workflows. It checks for:
- Missing dependencies
- Hardware compatibility (e.g., GPU/CPU)
- Proper configuration of local and remote endpoints
This tool assists developers in troubleshooting and validating their AI workspace environments.
Installation
Install the required dependencies using pip:
pip install psutil requestsUsage
python local_ai_workspace_validator.py --workspace ./my_workspace --output ./report.jsonSource Code
import os
import json
import argparse
import psutil
import requests
def validate_dependencies(workspace_path):
"""Check if required dependencies are installed in the workspace."""
requirements_file = os.path.join(workspace_path, 'requirements.txt')
if not os.path.exists(requirements_file):
return {'status': 'error', 'message': 'requirements.txt not found in workspace.'}
missing_dependencies = []
with open(requirements_file, 'r') as f:
for line in f:
package = line.strip()
if not package:
continue
try:
__import__(package.split('==')[0])
except ModuleNotFoundError:
missing_dependencies.append(package)
if missing_dependencies:
return {'status': 'error', 'missing_dependencies': missing_dependencies}
return {'status': 'success', 'message': 'All dependencies are installed.'}
def validate_hardware():
"""Check hardware compatibility for AI workloads."""
gpu_available = any('nvidia' in partition.device.lower() for partition in psutil.disk_partitions(all=False))
cpu_cores = psutil.cpu_count(logical=True)
return {
'gpu_available': gpu_available,
'cpu_cores': cpu_cores,
'status': 'success' if gpu_available and cpu_cores >= 4 else 'warning',
'message': 'Hardware compatibility check completed.'
}
def validate_endpoints():
"""Check if local and remote endpoints are reachable."""
endpoints = ['http://localhost:5000', 'https://api.example.com']
unreachable_endpoints = []
for endpoint in endpoints:
try:
response = requests.get(endpoint, timeout=5)
if response.status_code != 200:
unreachable_endpoints.append(endpoint)
except requests.RequestException:
unreachable_endpoints.append(endpoint)
if unreachable_endpoints:
return {'status': 'error', 'unreachable_endpoints': unreachable_endpoints}
return {'status': 'success', 'message': 'All endpoints are reachable.'}
def main():
"""Local AI Workspace Validator"""
parser = argparse.ArgumentParser(description='Local AI Workspace Validator')
parser.add_argument('--workspace', required=True, type=str, help='Path to the AI workspace.')
parser.add_argument('--output', type=str, help='Path to save the validation report as JSON.')
args = parser.parse_args()
report = {
'dependencies': validate_dependencies(args.workspace),
'hardware': validate_hardware(),
'endpoints': validate_endpoints()
}
if args.output:
with open(args.output, 'w') as f:
json.dump(report, f, indent=4)
print(f'Report saved to {args.output}')
else:
print(json.dumps(report, indent=4))
if __name__ == '__main__':
main()
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Details
- Tool Name
- local_ai_workspace_validator
- Category
- Hybrid and Local AI Workspaces
- Generated
- July 7, 2026
- Tests
- Passing โ
- Fix Loops
- 5
Quick Install
Clone just this tool:
git clone --depth 1 --filter=blob:none --sparse \ https://github.com/ptulin/autoaiforge.git cd autoaiforge git sparse-checkout set generated_tools/2026-07-07/local_ai_workspace_validator cd generated_tools/2026-07-07/local_ai_workspace_validator pip install -r requirements.txt 2>/dev/null || true python local_ai_workspace_validator.py