Conversar com um fluxo do Amazon Bedrock - Amazon Bedrock

Conversar com um fluxo do Amazon Bedrock

O exemplo de código a seguir mostra como usar o InvokeFlow para conversar com um fluxo do Amazon Bedrock que inclui um nó do agente.

Para ter mais informações, consulte Conversar com um fluxo do Amazon Bedrock.

Python
SDK para Python (Boto3).
nota

Há mais no GitHub. Encontre o exemplo completo e saiba como configurar e executar no AWSCode Examples Repository.

""" Shows how to run an Amazon Bedrock flow with InvokeFlow and handle muli-turn interaction for a single conversation. For more information, see https://docs.aws.amazon.com/bedrock/latest/userguide/flows-multi-turn-invocation.html. """ import logging import boto3 import botocore import botocore.exceptions logging.basicConfig(level=logging.INFO) logger = logging.getLogger(__name__) def invoke_flow(client, flow_id, flow_alias_id, input_data, execution_id): """ Invoke an Amazon Bedrock flow and handle the response stream. Args: client: Boto3 client for Amazon Bedrock agent runtime. flow_id: The ID of the flow to invoke. flow_alias_id: The alias ID of the flow. input_data: Input data for the flow. execution_id: Execution ID for continuing a flow. Use the value None on first run. Returns: Dict containing flow_complete status, input_required info, and execution_id """ response = None request_params = None if execution_id is None: # Don't pass execution ID for first run. request_params = { "flowIdentifier": flow_id, "flowAliasIdentifier": flow_alias_id, "inputs": [input_data], "enableTrace": True } else: request_params = { "flowIdentifier": flow_id, "flowAliasIdentifier": flow_alias_id, "executionId": execution_id, "inputs": [input_data], "enableTrace": True } response = client.invoke_flow(**request_params) if "executionId" not in request_params: execution_id = response['executionId'] input_required = None flow_status = "" # Process the streaming response for event in response['responseStream']: # Check if flow is complete. if 'flowCompletionEvent' in event: flow_status = event['flowCompletionEvent']['completionReason'] # Check if more input us needed from user. elif 'flowMultiTurnInputRequestEvent' in event: input_required = event # Print the model output. elif 'flowOutputEvent' in event: print(event['flowOutputEvent']['content']['document']) # Log trace events. elif 'flowTraceEvent' in event: logger.info("Flow trace: %s", event['flowTraceEvent']) return { "flow_status": flow_status, "input_required": input_required, "execution_id": execution_id } def converse_with_flow(bedrock_agent_client, flow_id, flow_alias_id): """ Run a conversation with the supplied flow. Args: bedrock_agent_client: Boto3 client for Amazon Bedrock agent runtime. flow_id: The ID of the flow to run. flow_alias_id: The alias ID of the flow. """ flow_execution_id = None finished = False # Get the intial prompt from the user. user_input = input("Enter input: ") # Use prompt to create input data. flow_input_data = { "content": { "document": user_input }, "nodeName": "FlowInputNode", "nodeOutputName": "document" } try: while not finished: # Invoke the flow until successfully finished. result = invoke_flow( bedrock_agent_client, flow_id, flow_alias_id, flow_input_data, flow_execution_id) status = result['flow_status'] flow_execution_id = result['execution_id'] more_input = result['input_required'] if status == "INPUT_REQUIRED": # The flow needs more information from the user. logger.info("The flow %s requires more input", flow_id) user_input = input( more_input['flowMultiTurnInputRequestEvent']['content']['document'] + ": ") flow_input_data = { "content": { "document": user_input }, "nodeName": more_input['flowMultiTurnInputRequestEvent']['nodeName'], "nodeInputName": "agentInputText" } elif status == "SUCCESS": # The flow completed successfully. finished = True logger.info("The flow %s successfully completed.", flow_id) except botocore.exceptions.ClientError as e: print(f"Client error: {str(e)}") logger.error("Client error: %s", {str(e)}) except Exception as e: print(f"An error occurred: {str(e)}") logger.error("An error occurred: %s", {str(e)}) logger.error("Error type: %s", {type(e)}) def main(): """ Main entry point for the script. """ # Replace these with your actual flow ID and flow alias ID. FLOW_ID = 'YOUR_FLOW_ID' FLOW_ALIAS_ID = 'YOUR_FLOW_ALIAS_ID' logger.info("Starting conversation with FLOW: %s ID: %s", FLOW_ID, FLOW_ALIAS_ID) # Get the Bedrock agent runtime client. session = boto3.Session(profile_name='default') bedrock_agent_client = session.client('bedrock-agent-runtime') # Start the conversation. converse_with_flow(bedrock_agent_client, FLOW_ID, FLOW_ALIAS_ID) logger.info("Conversation with FLOW: %s ID: %s finished", FLOW_ID, FLOW_ALIAS_ID) if __name__ == "__main__": main()
  • Para ver detalhes da API, consulte InvokeFlow na Referência de API do AWS SDK para Python (Boto3).

Para ver uma lista completa dos guias de desenvolvedor e exemplos de código do SDK da AWS, consulte Usar o Amazon Bedrock com um SDK da AWS. Este tópico também inclui informações sobre como começar e detalhes sobre versões anteriores do SDK.