121 lines
4.5 KiB
Python
121 lines
4.5 KiB
Python
"""
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测试 kb_search_dynamic 工具 - 课程咨询场景
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"""
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import asyncio
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import sys
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from pathlib import Path
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sys.path.insert(0, str(Path(__file__).parent.parent))
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from sqlalchemy.ext.asyncio import AsyncSession, create_async_engine
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from sqlalchemy.orm import sessionmaker
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from app.services.mid.kb_search_dynamic_tool import (
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KbSearchDynamicTool,
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KbSearchDynamicConfig,
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StepKbConfig,
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)
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from app.core.config import get_settings
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async def test_kb_search():
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"""测试知识库搜索 - 课程咨询场景"""
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settings = get_settings()
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engine = create_async_engine(settings.database_url)
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async_session = sessionmaker(engine, class_=AsyncSession, expire_on_commit=False)
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async with async_session() as session:
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config = KbSearchDynamicConfig(
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enabled=True,
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top_k=10,
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timeout_ms=15000,
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min_score_threshold=0.3,
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)
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tool = KbSearchDynamicTool(session=session, config=config)
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course_kb_id = "75c465fe-277d-455d-a30b-4b168adcc03b"
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step_kb_config = StepKbConfig(
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allowed_kb_ids=[course_kb_id],
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preferred_kb_ids=[course_kb_id],
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step_id="test_course_query",
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)
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test_params = {
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"query": "课程介绍",
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"tenant_id": "szmp@ash@2026",
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"top_k": 10,
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"context": {
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"grade": "五年级",
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},
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"step_kb_config": step_kb_config,
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}
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print(f"\n{'='*80}")
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print(f"测试: kb_search_dynamic - 课程知识库")
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print(f"{'='*80}")
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print(f"参数: query={test_params['query']}")
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print(f" tenant_id={test_params['tenant_id']}")
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print(f" context={test_params['context']}")
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print(f" step_kb_config.allowed_kb_ids={step_kb_config.allowed_kb_ids}")
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print(f"超时设置: {config.timeout_ms}ms")
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print(f"最低分数阈值: {config.min_score_threshold}")
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try:
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result = await tool.execute(**test_params)
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print(f"\n结果:")
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print(f" success: {result.success}")
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print(f" hits count: {len(result.hits)}")
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print(f" applied_filter: {result.applied_filter}")
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print(f" fallback_reason_code: {result.fallback_reason_code}")
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print(f" duration_ms: {result.duration_ms}")
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if result.filter_debug:
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print(f" filter_debug: {result.filter_debug}")
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if result.step_kb_binding:
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print(f" step_kb_binding: {result.step_kb_binding}")
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if result.tool_trace:
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print(f"\n Tool Trace:")
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print(f" tool_name: {result.tool_trace.tool_name}")
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print(f" status: {result.tool_trace.status}")
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print(f" duration_ms: {result.tool_trace.duration_ms}")
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print(f" args_digest: {result.tool_trace.args_digest}")
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print(f" result_digest: {result.tool_trace.result_digest}")
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if hasattr(result.tool_trace, 'arguments') and result.tool_trace.arguments:
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print(f" arguments: {result.tool_trace.arguments}")
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if result.hits:
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print(f"\n 检索结果 (共 {len(result.hits)} 条):")
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for i, hit in enumerate(result.hits, 1):
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text = hit.get('text', '')
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text_preview = text[:200] + '...' if len(text) > 200 else text
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score = hit.get('score', 0)
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metadata = hit.get('metadata', {})
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collection = hit.get('collection', 'unknown')
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kb_id = hit.get('kb_id', 'unknown')
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print(f"\n [{i}] score={score:.4f}")
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print(f" collection: {collection}")
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print(f" kb_id: {kb_id}")
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print(f" metadata: {metadata}")
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print(f" text: {text_preview}")
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else:
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print(f"\n ⚠️ 没有命中任何结果")
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print(f" 请检查:")
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print(f" 1. 知识库是否有数据")
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print(f" 2. 向量是否正确生成")
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print(f" 3. 过滤条件是否过于严格")
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except Exception as e:
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print(f"\n ❌ 错误: {e}")
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import traceback
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traceback.print_exc()
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if __name__ == "__main__":
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asyncio.run(test_kb_search())
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