aiqs

tests/test_mcp.py

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+import sys
+from pathlib import Path
+sys.path.insert(0, str(Path(__file__).parent.parent))
+
+import json
+from src.mcp.mem import ConvoStore
+from src.tools.case_tools import CaseTools
+
+
+def test_conv_store():
+    store = ConvoStore()
+    
+    test_session = "CASE_SESSION_001"
+    
+    store.add_conv(
+        session_id=test_session,
+        user_msg="这个案件的原告是谁？",
+        ai_msg="根据案件文档，原告是张三。",
+        metadata={"case_id": "CASE_001"}
+    )
+    
+    store.add_conv(
+        session_id=test_session,
+        user_msg="借款金额是多少？",
+        ai_msg="借款本金为50万元，约定年利率10%。",
+        metadata={"case_id": "CASE_001"}
+    )
+    
+    store.add_conv(
+        session_id=test_session,
+        user_msg="被告的答辩意见是什么？",
+        ai_msg="被告称该笔款项为合伙投资款，非借款，并称借条系伪造。",
+        metadata={"case_id": "CASE_001"}
+    )
+    
+    print(f"   对话存储成功")
+    print(f"   会话ID: {test_session}")
+    print(f"   对话轮数: 3")
+    return True
+
+
+def test_conv_search():
+
+    store = ConvoStore()
+    test_session = "CASE_SESSION_001"
+    
+    queries = [
+        "原告信息",
+        "借了多少钱",
+        "被告怎么说"
+    ]
+    
+    for query in queries:
+        results = store.search_conv(
+            session_id=test_session,
+            query=query,
+            limit=2
+        )
+        
+        print(f"\n   查询: {query}")
+        print(f"   结果数: {len(results)}")
+        
+        if results:
+            print(f"   最高相关度: {results[0]['score']:.3f}")
+            print(f"   匹配对话: Q: {results[0]['user'][:30]}...")
+        
+        assert len(results) > 0
+    
+    print(f"\n 检索成功")
+    return True
+
+
+def test_conv_all():
+    
+    store = ConvoStore()
+    test_session = "CASE_SESSION_001"
+    
+    all_convs = store.get_all_conv(
+        session_id=test_session,
+        limit=100
+    )
+    
+    print(f"   会话获取成功")
+    print(f"   会话ID: {test_session}")
+    print(f"   对话总数: {len(all_convs)}")
+    
+    if all_convs:
+        print(f"\n   最近对话:")
+        for i, conv in enumerate(all_convs[:2], 1):
+            print(f"   {i}. Q: {conv['user_msg'][:40]}...")
+            print(f"      A: {conv['ai_msg'][:40]}...")
+    
+    assert len(all_convs) >= 3
+    return True
+
+def test_case_tools_metadata():
+
+    tools = CaseTools()
+    result = tools.get_case_metadata("CASE_001")
+    
+    print(f"   查询完成")
+    print(f"   案件ID: CASE_001")
+    
+    if "error" in result:
+        print(f"   状态: {result['error']}")
+        print(f"   说明: {result.get('description', '')}")
+    else:
+        print(f"   文档数: {result.get('doc_cnt', 0)}")
+        print(f"   片段数: {result.get('chunk_cnt', 0)}")
+        print(f"   状态: {result.get('status', '')}")
+  
+    assert isinstance(result, dict)
+    return True
+
+
+def test_build_rag_prompt():
+    tools = CaseTools()
+    
+    mock_context = """<documents>
+<document index="1" source="complaint.txt">
+原告: 张三
+被告: 李四
+借款金额: 50万元
+</document>
+<document index="2" source="defense.txt">
+被告答辩: 该笔款项为合伙投资款
+</document>
+</documents>"""
+    
+    result = tools.build_rag_prompt(
+        query="原告和被告分别是谁？",
+        context=mock_context,
+        session_id="CASE_SESSION_001",
+        max_history=2
+    )
+    
+    print(f"   prompt构建成功")
+    print(f"   消息总数: {result['prompt_stats']['total_messages']}")
+    print(f"   包含上下文: {result['prompt_stats']['has_context']}")
+    print(f"   包含历史: {result['prompt_stats']['has_history']}")
+    print(f"   历史来源: {result['prompt_stats']['history_source']}")
+    print(f"   历史轮数: {result['prompt_stats']['history_length']}")
+    
+    assert len(result['messages']) > 0
+    assert result['prompt_stats']['has_context']
+    return True
+
+def test_cleanup():
+    store = ConvoStore()
+    test_session = "CASE_SESSION_001"
+
+    all_convs = store.get_all_conv(session_id=test_session, limit=1000)
+    print(f"   清理前对话数: {len(all_convs)}")
+    
+    count = store.delete_by_session(test_session)
+    
+    print(f"   清理完成")
+    print(f"   测试会话: {test_session}")
+    print(f"   删除对话数: {count}")
+    
+    remaining = store.get_all_conv(session_id=test_session, limit=1000)
+    print(f"   清理后对话数: {len(remaining)}")
+    
+    assert len(remaining) == 0
+    
+    return True
+
+
+def run_all_tests():
+    print("\n" + "="*60)
+    print("MCP 测试")
+    print("="*60)
+    
+    tests = [
+        ("对话存储", test_conv_store),
+        ("对话检索", test_conv_search),
+        ("获取全部对话", test_conv_all),
+        ("获取案件元数据", test_case_tools_metadata),
+        ("构建 RAG Prompt", test_build_rag_prompt),
+        ("清理测试数据", test_cleanup)
+    ]
+    
+    passed = 0
+    failed = 0
+    
+    for name, test_func in tests:
+        if test_func():
+            passed += 1
+        else:
+            failed += 1
+            print(f"\n 测试失败: {name}")
+    
+    print("\n" + "="*60)
+    print(f"结果: {passed} 通过, {failed} 失败")
+    print("="*60)
+    
+    return failed == 0
+
+
+if __name__ == "__main__":
+    success = run_all_tests()
+    sys.exit(0 if success else 1)