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ai-agent-book 精选快照(<2MB 代码与文档,来自 github.com/bojieli/ai-agent-book)
2026-08-20 13:12:50 +00:00

74 lines
2.4 KiB
Python

#!/usr/bin/env python3
"""Test script to verify all fixes are working"""
import logging
from config import Config
from contextual_evaluator import ContextualMemoryEvaluator
# Set up detailed logging
logging.basicConfig(
level=logging.INFO,
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
)
def test_single_evaluation():
"""Test evaluation with a single simple test case"""
print("="*80)
print("TESTING CONTEXTUAL RETRIEVAL SYSTEM - VERBOSE MODE")
print("="*80)
config = Config.from_env()
evaluator = ContextualMemoryEvaluator(config)
# Load only layer1 test cases
test_cases = evaluator.load_test_cases("layer1")
print(f"\nLoaded {len(test_cases)} test cases")
if test_cases:
# Pick the first test case
test_id = test_cases[0]
test_case = evaluator.test_cases[test_id]
print(f"\n{'='*80}")
print(f"EVALUATING: {test_id}")
print(f"Title: {test_case.title}")
print(f"Question: {test_case.user_question}")
print(f"Conversations: {len(test_case.conversation_histories)}")
if test_case.conversation_histories:
first_conv = test_case.conversation_histories[0]
print(f"First conversation has {len(first_conv.get('messages', []))} messages")
print(f"{'='*80}\n")
# Run evaluation
try:
result = evaluator.evaluate_test_case(test_id)
print(f"\n{'='*80}")
print("EVALUATION RESULT")
print(f"{'='*80}")
print(f"Success: {result.success}")
print(f"Iterations: {result.iterations}")
print(f"Tool Calls: {result.tool_calls}")
print(f"Memory Cards Used: {len(result.memory_cards_used)}")
print(f"Chunks Retrieved: {len(result.chunks_retrieved)}")
print(f"Processing Time: {result.processing_time:.2f}s")
if result.agent_answer:
print(f"\nAgent Answer:")
print(result.agent_answer)
if result.error:
print(f"\nError: {result.error}")
print(f"{'='*80}\n")
except Exception as e:
print(f"\nERROR during evaluation: {e}")
import traceback
traceback.print_exc()
else:
print("No test cases available")
if __name__ == "__main__":
test_single_evaluation()