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39 lines
1.6 KiB
Python
39 lines
1.6 KiB
Python
"""Offline demonstration of Experiment 9-2."""
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from __future__ import annotations
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import argparse
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import json
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from pathlib import Path
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from experience_documents import build_documents, evaluate_retrieval_baselines, write_documents
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ROOT = Path(__file__).parent
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def main() -> None:
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parser = argparse.ArgumentParser(description="Experiment 9-2 experience-document extraction")
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parser.add_argument("--extractor", choices=("fixture", "llm"), default="fixture")
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parser.add_argument("--model", help="real LLM model; defaults to LLM_MODEL or gpt-5.6")
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args = parser.parse_args()
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dataset = json.loads((ROOT / "sample_trajectories.json").read_text(encoding="utf-8"))
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records = dataset["learning_trajectories"]
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if args.extractor == "llm":
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from llm_extractor import OpenAIExperienceExtractor
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records = OpenAIExperienceExtractor(args.model).extract_all(records)
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documents = build_documents(records, validated_on="2026-07-24")
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output_paths = write_documents(documents, ROOT / "output" / "experience_documents")
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report = evaluate_retrieval_baselines(records, documents, dataset["transfer_cases"])
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print(f"Experiment 9-2: evaluated trajectories -> Markdown experience documents (extractor={args.extractor})\n")
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for document, path in zip(documents, output_paths):
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print(f"{document.task_family:<18} sources={len(document.sources)} "
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f"recommendations={len(document.recommended_strategies)} -> {path.relative_to(ROOT)}")
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print("\nThree-baseline transfer report:")
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print(json.dumps(report, ensure_ascii=False, indent=2))
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if __name__ == "__main__":
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main()
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