这是一个简单但有用的测试脚本，可帮助您快速测试和验证您的 aws bedrock + kb 设置。如果不同，只需更新您的 aws 区域，然后插入您的 bedrock kb id。
import boto3import jsonimport timefrom datetime import datetimedef test_kb_setup(): """Test function to verify Bedrock Knowledge Base setup and queries""" # Initialize clients bedrock_agent = boto3.client('bedrock-agent-runtime', region_name='us-east-1') bedrock_runtime = boto3.client('bedrock-runtime', region_name='us-east-1') # Your Knowledge Base ID kb_id = "**your-knowledge-base-id**" # Replace with your actual KB ID def test_kb_query(query_text): """Test a single knowledge base query""" print(f"nTesting query: '{query_text}'") print("-" * 50) try: # Query the knowledge base response = bedrock_agent.retrieve( knowledgeBaseId=kb_id, retrievalQuery={'text': query_text}, retrievalConfiguration={ 'vectorSearchConfiguration': { 'numberOfResults': 3 } } ) # Print raw response for debugging print("nRaw Response:") print(json.dumps(response, indent=2, default=str)) # Process and print retrieved results print("nProcessed Results:") if 'retrievalResults' in response: for i, result in enumerate(response['retrievalResults'], 1): print(f"nResult {i}:") print(f"Score: {result.get('score', 'N/A')}") print(f"Content: {result.get('content', {}).get('text', 'N/A')}") print(f"Location: {result.get('location', 'N/A')}") else: print("No results found in response") return True except Exception as e: print(f"Error during query: {str(e)}") return False def test_kb_with_bedrock(query_text): """Test knowledge base integration with Bedrock""" print(f"nTesting KB + Bedrock integration for: '{query_text}'") print("-" * 50) try: # First get KB results kb_response = bedrock_agent.retrieve( knowledgeBaseId=kb_id, retrievalQuery={'text': query_text}, retrievalConfiguration={ 'vectorSearchConfiguration': { 'numberOfResults': 3 } } ) # Format context from KB results context = "" if 'retrievalResults' in kb_response: context = "n".join([ f"Reference {i+1}:n{result.get('content', {}).get('text', '')}n" for i, result in enumerate(kb_response['retrievalResults']) ]) # Prepare Bedrock prompt enhanced_prompt = ( f"Using the following references:nn{context}nn" f"Please answer this question: {query_text}n" "Base your response on the provided references and clearly cite them when used." ) # Get Bedrock response bedrock_response = bedrock_runtime.invoke_model( modelId="anthropic.claude-v2", body=json.dumps({ "prompt": f"nnHuman: {enhanced_prompt}nnAssistant:", "max_tokens_to_sample": 500, "temperature": 0.7, "top_p": 1, }), contentType="application/json", accept="application/json", ) response_body = json.loads(bedrock_response.get('body').read()) final_response = response_body.get('completion', '').strip() print("nBedrock Response:") print(final_response) return True except Exception as e: print(f"Error during KB + Bedrock integration: {str(e)}") return False # Run test queries test_queries = [ "What are our company's remote work policies?", "Tell me about employee benefits", "What is the vacation policy?", "How does the performance review process work?", "What are the working hours?" ] print("Starting Knowledge Base Tests") print("=" * 50) # Test 1: Basic KB Queries print("nTest 1: Basic Knowledge Base Queries") for query in test_queries: success = test_kb_query(query) if not success: print(f"Failed on query: {query}") # Test 2: KB + Bedrock Integration print("nTest 2: Knowledge Base + Bedrock Integration") for query in test_queries: success = test_kb_with_bedrock(query) if not success: print(f"Failed on integration test: {query}")if __name__ == "__main__": test_kb_setup()
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