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Python: Use InvokeFlow for a turn by turn conversation. (#7210)
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‎.doc_gen/metadata/bedrock-agent-runtime_metadata.yaml

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@@ -32,3 +32,24 @@ bedrock-agent-runtime_InvokeFlow:
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- javascriptv3/example_code/bedrock-agent-runtime/actions/invoke-flow.js
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services:
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bedrock-agent-runtime: {InvokeFlow}
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bedrock-agent-runtime_Scenario_ConverseWithFlow:
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title: Converse with an &BRlong; flow
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synopsis: use InvokeFlow to converse with an &BRlong; flow that includes an agent node.
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category: Basics
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guide_topic:
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title: Converse with an &BRlong; flow
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url: bedrock/latest/userguide/flows-multi-turn-invocation.html
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languages:
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Python:
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versions:
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- sdk_version: 3
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github: python/example_code/bedrock-agent-runtime
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sdkguide:
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excerpts:
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- description:
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snippet_tags:
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- python.example_code.bedrock-agent-runtime.flow_conversation.complete
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services:
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bedrock-agent-runtime: {InvokeFlow}

‎python/example_code/bedrock-agent-runtime/README.md

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@@ -34,6 +34,13 @@ python -m pip install -r requirements.txt
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<!--custom.prerequisites.start-->
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<!--custom.prerequisites.end-->
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### Basics
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Code examples that show you how to perform the essential operations within a service.
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- [Learn the basics](flows/flow-conversation.py)
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### Single actions
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Code excerpts that show you how to call individual service functions.
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<!--custom.instructions.end-->
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#### Learn the basics
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This example shows you how to use InvokeFlow to converse with an Amazon Bedrock flow that includes an agent node.
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<!--custom.basic_prereqs.bedrock-agent-runtime_Scenario_ConverseWithFlow.start-->
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<!--custom.basic_prereqs.bedrock-agent-runtime_Scenario_ConverseWithFlow.end-->
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Start the example by running the following at a command prompt:
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```
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python flows/flow-conversation.py
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```
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<!--custom.basics.bedrock-agent-runtime_Scenario_ConverseWithFlow.start-->
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<!--custom.basics.bedrock-agent-runtime_Scenario_ConverseWithFlow.end-->
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### Tests
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Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
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SPDX-License-Identifier: Apache-2.0
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SPDX-License-Identifier: Apache-2.0

‎python/example_code/bedrock-agent-runtime/flows/flow-conversation.py

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# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
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# SPDX-License-Identifier: Apache-2.0
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# snippet-start:[python.example_code.bedrock-agent-runtime.flow_conversation.complete]
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"""
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Shows how to run an Amazon Bedrock flow with InvokeFlow and handle muli-turn interaction
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for a single conversation.
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For more information, see https://docs.aws.amazon.com/bedrock/latest/userguide/flows-multi-turn-invocation.html.
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"""
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import logging
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import boto3
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import botocore
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import botocore.exceptions
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logging.basicConfig(level=logging.INFO)
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logger = logging.getLogger(__name__)
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def invoke_flow(client, flow_id, flow_alias_id, input_data, execution_id):
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"""
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Invoke an Amazon Bedrock flow and handle the response stream.
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Args:
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client: Boto3 client for Amazon Bedrock agent runtime.
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flow_id: The ID of the flow to invoke.
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flow_alias_id: The alias ID of the flow.
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input_data: Input data for the flow.
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execution_id: Execution ID for continuing a flow. Use the value None on first run.
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Returns:
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Dict containing flow_complete status, input_required info, and execution_id
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"""
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response = None
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request_params = None
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if execution_id is None:
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# Don't pass execution ID for first run.
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request_params = {
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"flowIdentifier": flow_id,
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"flowAliasIdentifier": flow_alias_id,
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"inputs": [input_data],
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"enableTrace": True
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}
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else:
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request_params = {
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"flowIdentifier": flow_id,
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"flowAliasIdentifier": flow_alias_id,
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"executionId": execution_id,
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"inputs": [input_data],
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"enableTrace": True
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}
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response = client.invoke_flow(**request_params)
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if "executionId" not in request_params:
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execution_id = response['executionId']
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input_required = None
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flow_status = ""
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# Process the streaming response
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for event in response['responseStream']:
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# Check if flow is complete.
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if 'flowCompletionEvent' in event:
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flow_status = event['flowCompletionEvent']['completionReason']
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# Check if more input us needed from user.
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elif 'flowMultiTurnInputRequestEvent' in event:
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input_required = event
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# Print the model output.
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elif 'flowOutputEvent' in event:
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print(event['flowOutputEvent']['content']['document'])
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# Log trace events.
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elif 'flowTraceEvent' in event:
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logger.info("Flow trace: %s", event['flowTraceEvent'])
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return {
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"flow_status": flow_status,
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"input_required": input_required,
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"execution_id": execution_id
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}
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def converse_with_flow(bedrock_agent_client, flow_id, flow_alias_id):
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"""
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Run a conversation with the supplied flow.
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Args:
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bedrock_agent_client: Boto3 client for Amazon Bedrock agent runtime.
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flow_id: The ID of the flow to run.
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flow_alias_id: The alias ID of the flow.
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"""
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flow_execution_id = None
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finished = False
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# Get the intial prompt from the user.
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user_input = input("Enter input: ")
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# Use prompt to create input data.
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flow_input_data = {
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"content": {
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"document": user_input
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},
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"nodeName": "FlowInputNode",
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"nodeOutputName": "document"
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}
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try:
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while not finished:
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# Invoke the flow until successfully finished.
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result = invoke_flow(
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bedrock_agent_client, flow_id, flow_alias_id, flow_input_data, flow_execution_id)
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status = result['flow_status']
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flow_execution_id = result['execution_id']
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more_input = result['input_required']
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if status == "INPUT_REQUIRED":
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# The flow needs more information from the user.
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logger.info("The flow %s requires more input", flow_id)
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user_input = input(
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more_input['flowMultiTurnInputRequestEvent']['content']['document'] + ": ")
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flow_input_data = {
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"content": {
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"document": user_input
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},
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"nodeName": more_input['flowMultiTurnInputRequestEvent']['nodeName'],
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"nodeInputName": "agentInputText"
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}
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elif status == "SUCCESS":
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# The flow completed successfully.
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finished = True
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logger.info("The flow %s successfully completed.", flow_id)
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except botocore.exceptions.ClientError as e:
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print(f"Client error: {str(e)}")
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logger.error("Client error: %s", {str(e)})
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except Exception as e:
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print(f"An error occurred: {str(e)}")
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logger.error("An error occurred: %s", {str(e)})
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logger.error("Error type: %s", {type(e)})
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def main():
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"""
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Main entry point for the script.
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"""
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# Replace these with your actual flow ID and flow alias ID.
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FLOW_ID = 'YOUR_FLOW_ID'
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FLOW_ALIAS_ID = 'YOUR_FLOW_ALIAS_ID'
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logger.info("Starting conversation with FLOW: %s ID: %s",
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FLOW_ID, FLOW_ALIAS_ID)
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# Get the Bedrock agent runtime client.
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session = boto3.Session(profile_name='default')
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bedrock_agent_client = session.client('bedrock-agent-runtime')
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# Start the conversation.
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converse_with_flow(bedrock_agent_client, FLOW_ID, FLOW_ALIAS_ID)
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logger.info("Conversation with FLOW: %s ID: %s finished",
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FLOW_ID, FLOW_ALIAS_ID)
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if __name__ == "__main__":
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main()
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# snippet-end:[python.example_code.bedrock-agent-runtime.flow_conversation.complete]

‎python/example_code/bedrock-agent-runtime/test/test_flow_conversation.py

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# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
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# SPDX-License-Identifier: Apache-2.0
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import pytest
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import subprocess
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import sys
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files_under_test = [
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"flows/flow-conversation.py"
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]
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@pytest.mark.integ
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@pytest.mark.parametrize("file", files_under_test)
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def test_flow_conversation(file):
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# Simulate user input - each string represents one input() call
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# If you're using the docs at https://docs.aws.amazon.com/bedrock/latest/userguide/flows-multi-turn-invocation.html,
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# "Create a playlist\n 3\n pop, castles\n" should work with Antropic Haiku.
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test_input = "Hello\n"
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result = subprocess.run(
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[sys.executable, file],
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input=test_input,
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capture_output=True,
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text=True,
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)
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print(f"STDOUT: {result.stdout}") # For debugging
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print(f"STDERR: {result.stderr}") # For debugging
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assert result.stdout != ""
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assert result.returncode == 0

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