Spaces:
Sleeping
Sleeping
File size: 5,293 Bytes
8c1f582 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 |
#!/usr/bin/env python3
"""
Chunked UN Motion Simulation Runner
Processes countries in batches to allow incremental saving and better control.
"""
import argparse
import json
import sys
from pathlib import Path
from datetime import datetime
# Add project root to path
PROJECT_ROOT = Path(__file__).parent.parent
sys.path.insert(0, str(PROJECT_ROOT))
from run_motion import MotionRunner
def run_chunked_simulation(motion_id: str, chunk_size: int = 20, provider: str = "cloud", model: str = None):
"""Run simulation in chunks and save incrementally"""
runner = MotionRunner(provider=provider, model=model)
motion = runner.load_motion(motion_id)
countries = runner.get_country_list()
print(f"\n{'='*60}")
print(f"Chunked Motion Runner")
print(f"Motion: {motion_id}")
print(f"Total Countries: {len(countries)}")
print(f"Chunk Size: {chunk_size}")
print(f"Provider: {provider} | Model: {runner.model}")
print(f"{'='*60}\n")
# Initialize results
all_votes = []
vote_counts = {"yes": 0, "no": 0, "abstain": 0}
# Process in chunks
total_chunks = (len(countries) + chunk_size - 1) // chunk_size
for chunk_idx in range(total_chunks):
start_idx = chunk_idx * chunk_size
end_idx = min(start_idx + chunk_size, len(countries))
chunk = countries[start_idx:end_idx]
print(f"\n{'─'*60}")
print(f"Processing Chunk {chunk_idx + 1}/{total_chunks}")
print(f"Countries {start_idx + 1}-{end_idx} of {len(countries)}")
print(f"{'─'*60}\n")
for i, country in enumerate(chunk, start=start_idx + 1):
print(f"[{i}/{len(countries)}] Querying {country['name']}...", end=" ", flush=True)
result = runner.query_agent(country, motion)
vote_counts[result["vote"]] += 1
all_votes.append({
"country": country['name'],
"country_slug": country['slug'],
"vote": result["vote"],
"statement": result["statement"],
"error": result.get("error")
})
vote_emoji = {"yes": "✅", "no": "❌", "abstain": "⚪"}
print(f"{vote_emoji[result['vote']]} {result['vote'].upper()}")
# Save intermediate results after each chunk
intermediate_results = {
"motion_id": motion_id,
"motion_path": motion['path'],
"timestamp": datetime.utcnow().isoformat() + "Z",
"provider": provider,
"model": runner.model,
"total_votes": len(all_votes),
"vote_summary": vote_counts.copy(),
"votes": all_votes,
"status": f"In progress: {len(all_votes)}/{len(countries)} countries processed"
}
# Save to intermediate file
intermediate_path = runner.results_dir / f"{motion_id}_partial.json"
runner.results_dir.mkdir(parents=True, exist_ok=True)
with open(intermediate_path, 'w', encoding='utf-8') as f:
json.dump(intermediate_results, f, indent=2, ensure_ascii=False)
print(f"\n💾 Saved intermediate results: {len(all_votes)}/{len(countries)} countries")
print(f" File: {intermediate_path}")
# Final results
print(f"\n{'='*60}")
print(f"Final Vote Summary:")
print(f" YES: {vote_counts['yes']:3d} ({vote_counts['yes']/len(countries)*100:.1f}%)")
print(f" NO: {vote_counts['no']:3d} ({vote_counts['no']/len(countries)*100:.1f}%)")
print(f" ABSTAIN: {vote_counts['abstain']:3d} ({vote_counts['abstain']/len(countries)*100:.1f}%)")
print(f"{'='*60}\n")
final_results = {
"motion_id": motion_id,
"motion_path": motion['path'],
"timestamp": datetime.utcnow().isoformat() + "Z",
"provider": provider,
"model": runner.model,
"total_votes": len(countries),
"vote_summary": vote_counts,
"votes": all_votes
}
# Save final results
runner.save_results(final_results)
# Clean up partial file
intermediate_path = runner.results_dir / f"{motion_id}_partial.json"
if intermediate_path.exists():
intermediate_path.unlink()
return final_results
def main():
parser = argparse.ArgumentParser(description="Run UN motion simulation in chunks")
parser.add_argument("motion_id", help="ID of the motion to run")
parser.add_argument("--chunk-size", type=int, default=20, help="Countries per chunk (default: 20)")
parser.add_argument("--provider", choices=["cloud", "local"], default="cloud", help="AI provider")
parser.add_argument("--model", help="Model name (optional)")
args = parser.parse_args()
try:
run_chunked_simulation(
args.motion_id,
chunk_size=args.chunk_size,
provider=args.provider,
model=args.model
)
print("\n✓ Chunked simulation complete!")
except KeyboardInterrupt:
print("\n\n⚠ Simulation interrupted by user")
print("💾 Partial results saved in *_partial.json file")
sys.exit(130)
except Exception as e:
print(f"\n❌ Error: {e}", file=sys.stderr)
import traceback
traceback.print_exc()
sys.exit(1)
if __name__ == "__main__":
main()
|