learningcircuit--local-deep-research/examples/benchmarks/run_simpleqa.py

#!/usr/bin/env python
"""
SimpleQA Benchmark Runner for Local Deep Research.

This script provides a convenient way to run the SimpleQA benchmark.

Usage:
    # Install dependencies with PDM
    cd /path/to/local-deep-research
    pdm install

    # Run the script with PDM
    pdm run python examples/benchmarks/run_simpleqa.py --help
"""

import argparse
import sys
from pathlib import Path

# Import the benchmark functionality
from local_deep_research.benchmarks.benchmark_functions import evaluate_simpleqa


def main():
    """Run the SimpleQA benchmark with the specified parameters."""
    parser = argparse.ArgumentParser(description="Run SimpleQA benchmark")
    parser.add_argument(
        "--examples", type=int, default=10, help="Number of examples to run"
    )
    parser.add_argument(
        "--iterations", type=int, default=3, help="Number of search iterations"
    )
    parser.add_argument(
        "--questions", type=int, default=3, help="Questions per iteration"
    )
    parser.add_argument(
        "--search-tool", type=str, default="searxng", help="Search tool to use"
    )
    parser.add_argument(
        "--output-dir",
        type=str,
        default=str(Path("examples") / "benchmarks" / "results" / "simpleqa"),
        help="Output directory",
    )
    parser.add_argument(
        "--no-eval", action="store_true", help="Skip evaluation"
    )

    # Optional evaluation parameters
    parser.add_argument(
        "--human-eval", action="store_true", help="Use human evaluation"
    )
    parser.add_argument(
        "--eval-model", type=str, help="Model to use for evaluation"
    )
    parser.add_argument(
        "--eval-provider", type=str, help="Provider to use for evaluation"
    )

    # Add model configuration options
    parser.add_argument(
        "--search-model", type=str, help="Model to use for the search system"
    )
    parser.add_argument(
        "--search-provider",
        type=str,
        help="Provider to use for the search system",
    )
    parser.add_argument(
        "--endpoint-url",
        type=str,
        help="Endpoint URL for OpenRouter or other API services",
    )
    parser.add_argument(
        "--search-strategy",
        type=str,
        default="source_based",
        choices=[
            "source_based",
            "standard",
            "rapid",
            "parallel",
            "iterdrag",
            "modular",
        ],
        help="Search strategy to use (default: source_based)",
    )
    parser.add_argument("--api-key", type=str, help="API key for LLM provider")

    args = parser.parse_args()

    print(f"Starting SimpleQA benchmark with {args.examples} examples...")

    # Run the benchmark
    results = evaluate_simpleqa(
        num_examples=args.examples,
        search_iterations=args.iterations,
        questions_per_iteration=args.questions,
        search_tool=args.search_tool,
        human_evaluation=args.human_eval,
        evaluation_model=args.eval_model,
        evaluation_provider=args.eval_provider,
        output_dir=args.output_dir,
    )

    # Print summary
    print("\nSimpleQA Benchmark Results:")
    print(f"  Accuracy: {results.get('accuracy', 0):.3f}")
    print(f"  Total examples: {results.get('total_examples', 0)}")
    print(f"  Report saved to: {results.get('report_path', '')}")

    return 0


if __name__ == "__main__":
    sys.exit(main())