Upload aco/cli.py

aco/cli.py

@@ -0,0 +1,123 @@
+"""CLI for Agent Cost Optimizer."""
+
+import argparse
+import json
+import sys
+from pathlib import Path
+
+from aco.optimizer import AgentCostOptimizer
+from aco.config import ACOConfig
+from aco.benchmarks.benchmark_suite import BenchmarkSuite
+
+
+def main():
+    parser = argparse.ArgumentParser(description="Agent Cost Optimizer")
+    subparsers = parser.add_subparsers(dest="command", help="Command to run")
+    
+    # Optimize command
+    opt_parser = subparsers.add_parser("optimize", help="Optimize an agent request")
+    opt_parser.add_argument("--config", "-c", default="config.yaml", help="Config file path")
+    opt_parser.add_argument("--request", "-r", required=True, help="User request text")
+    opt_parser.add_argument("--output", "-o", default="-", help="Output file (default: stdout)")
+    
+    # Benchmark command
+    bench_parser = subparsers.add_parser("benchmark", help="Run benchmark suite")
+    bench_parser.add_argument("--config", "-c", default="config.yaml", help="Config file path")
+    bench_parser.add_argument("--tasks", "-n", type=int, default=1000, help="Number of tasks")
+    bench_parser.add_argument("--output", "-o", default="benchmark_results.json", help="Output path")
+    bench_parser.add_argument("--ablations", action="store_true", help="Run ablation study")
+    
+    # Report command
+    report_parser = subparsers.add_parser("report", help="Generate report from benchmark results")
+    report_parser.add_argument("--input", "-i", required=True, help="Benchmark results JSON")
+    report_parser.add_argument("--output", "-o", default="-", help="Output file")
+    
+    args = parser.parse_args()
+    
+    if args.command == "optimize":
+        _cmd_optimize(args)
+    elif args.command == "benchmark":
+        _cmd_benchmark(args)
+    elif args.command == "report":
+        _cmd_report(args)
+    else:
+        parser.print_help()
+        sys.exit(1)
+
+
+def _cmd_optimize(args):
+    config = ACOConfig.from_yaml(args.config) if Path(args.config).exists() else ACOConfig()
+    optimizer = AgentCostOptimizer(config)
+    result = optimizer.optimize(args.request)
+    
+    output = {
+        "trace_id": result.trace_id,
+        "model": result.routing_decision.model_id,
+        "tier": result.routing_decision.tier,
+        "estimated_cost": result.estimated_cost,
+        "estimated_latency_ms": result.estimated_latency_ms,
+        "confidence": result.confidence,
+        "reasoning": result.reasoning,
+        "tool_decisions": [
+            {"tool": d.tool_name, "decision": d.decision.value, "cost": d.estimated_cost}
+            for d in result.tool_decisions
+        ],
+        "verifier": result.verifier_decision.decision.value if result.verifier_decision else None,
+        "doom_score": result.doom_assessment.confidence if result.doom_assessment else None,
+        "meta_tool_match": result.meta_tool_match is not None,
+    }
+    
+    json_str = json.dumps(output, indent=2)
+    if args.output == "-":
+        print(json_str)
+    else:
+        with open(args.output, "w") as f:
+            f.write(json_str)
+
+
+def _cmd_benchmark(args):
+    config = ACOConfig.from_yaml(args.config) if Path(args.config).exists() else ACOConfig()
+    suite = BenchmarkSuite(config)
+    
+    print(f"Generating {args.tasks} synthetic traces...")
+    traces = suite.generate_benchmark_data(args.tasks)
+    
+    print("Running baselines...")
+    results = suite.run_all_baselines(traces)
+    
+    if args.ablations:
+        print("Running ablations...")
+        ablation_results = suite.run_ablations(traces)
+        results.update(ablation_results)
+    
+    suite.export(results, args.output)
+    
+    # Print report
+    report = suite.report(results)
+    print(report)
+    
+    print(f"\nResults saved to {args.output}")
+
+
+def _cmd_report(args):
+    with open(args.input, "r") as f:
+        data = json.load(f)
+    
+    # Reconstruct BenchmarkResults for reporting
+    from aco.benchmarks.benchmark_suite import BenchmarkResult
+    results = {}
+    for name, d in data.items():
+        results[name] = BenchmarkResult(**d)
+    
+    suite = BenchmarkSuite()
+    report = suite.report(results)
+    
+    if args.output == "-":
+        print(report)
+    else:
+        with open(args.output, "w") as f:
+            f.write(report)
+
+
+if __name__ == "__main__":
+    main()