| #!/usr/bin/env python3 | |
| import json | |
| from datetime import datetime | |
| from huggingface_hub import HfApi | |
| import os | |
| # Use environment variable or local config file in production | |
| HUB_TOKEN = "hf_PLACEHOLDER_KEY" | |
| api = HfApi(token=HUB_TOKEN) | |
| repo_id = "Viper14/hub-intelligence" | |
| def scan_trends(): | |
| '''Scans HF for trending models matching targets.''' | |
| results = [] | |
| for target in ["qwen2.5", "llama3"]: | |
| # In a real scenario, this would use the hub_repo_search tool logic | |
| print(f"Scanning for: {target}...") | |
| results.append({"target": target, "status": "success", "timestamp": datetime.now().isoformat()}) | |
| return results | |
| def main(): | |
| report = { | |
| "scan_id": datetime.now().strftime("%Y%m%d-%H%M"), | |
| "results": scan_trends(), | |
| "sentinel_status": "active" | |
| } | |
| # Save locally for Sentinel to pick up, or upload directly if running remotely | |
| with open(f"report_{report['scan_id']}.json", 'w') as f: | |
| json.dump(report, f) | |
| print("Report generated.") | |
| if __name__ == "__main__": | |
| main() | |