65 lines
2.2 KiB
Python
65 lines
2.2 KiB
Python
"""Quick test — full domain-aware bilingual pipeline."""
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import asyncio
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import logging
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from app.graph.state import ReportState
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from app.pipeline.orchestrator import PipelineOrchestrator
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logging.basicConfig(
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level=logging.INFO,
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format="%(asctime)s [%(name)s] %(levelname)s: %(message)s",
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)
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async def main():
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state = ReportState(
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requirement="分析全球半导体行业2025年发展趋势，重点关注：1）全球供应链重构（美日欧中各自布局），2）中国半导体自主化进展与瓶颈，3）AI芯片竞争格局，4）投资建议",
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report_type="行业分析报告",
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output_formats=["docx"],
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output_languages=["zh", "en"], # bilingual output
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)
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print(f"[test] Task ID: {state.id}")
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print(f"[test] Requirement: {state.requirement[:80]}...")
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print(f"[test] Languages: {state.output_languages}")
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print()
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orchestrator = PipelineOrchestrator()
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state = await orchestrator.run(state)
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print()
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print(f"[test] Final node: {state.current_node}")
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print(f"[test] Error: {state.error or 'None'}")
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print(f"[test] Revisions: {state.revision_count}")
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print()
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# Execution trace
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print("[test] Execution trace:")
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for entry in state.node_history:
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print(f" {entry['timestamp'][:19]} | {entry['node']:20s} | {entry['status']:10s} | {entry.get('detail', '')}")
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# Parallel research — show domain/language/model allocation
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if state.research_results:
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print()
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print(f"[test] Research tracks: {len(state.research_results)}")
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for r in state.research_results:
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ms = f" ({r.duration_ms}ms)" if r.duration_ms else ""
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print(f" [{r.status.value:9s}] [{r.domain.value:6s}] [{r.native_language}] {r.description}{ms}")
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# Output files
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if state.generated_files:
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print()
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print(f"[test] Generated files ({len(state.generated_files)}):")
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for f in state.generated_files:
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print(f" → {f}")
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# Review verdict
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if state.review:
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print()
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print(f"[test] Review: score={state.review.get('overall_score')}, verdict={state.review.get('verdict')}")
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if __name__ == "__main__":
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asyncio.run(main())
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