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Signed-off-by: Filinto Duran <[email protected]>
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‎examples/conversation/test_streaming_async.py‎

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#!/usr/bin/env python3
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"""
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Example demonstrating asynchronous streaming conversation API.
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This example shows how to use the Dapr async conversation streaming API with the echo component
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for testing purposes. In production, you would replace 'echo' with an actual LLM component
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like 'openai', 'anthropic', etc.
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Prerequisites:
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- Dapr sidecar running with conversation components
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- Use tools/run_dapr_dev.py to start a development sidecar with echo component
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"""
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import asyncio
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from dapr.aio.clients import DaprClient
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from dapr.clients.grpc._request import ConversationInput
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async def main():
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print('🧪 Testing asynchronous streaming conversation with echo component...')
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try:
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async with DaprClient() as d:
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print('✓ Connected to Dapr sidecar (async)')
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# Test basic async streaming conversation
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print('\n📡 Testing async streaming conversation...')
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inputs = [
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ConversationInput(content="Hello from async Python SDK streaming test!", role='user')
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]
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chunks_received = []
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final_usage = None
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async for chunk in d.converse_stream_alpha1(
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name='echo',
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inputs=inputs,
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context_id='async-test-session-456'
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):
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if chunk.result and chunk.result.result:
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print(f'📦 Async chunk: "{chunk.result.result}"')
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chunks_received.append(chunk.result.result)
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if chunk.context_id:
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print(f'🆔 Async context ID: {chunk.context_id}')
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if chunk.usage:
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print(f'📊 Async usage: {chunk.usage.prompt_tokens} prompt + {chunk.usage.completion_tokens} completion = {chunk.usage.total_tokens} total tokens')
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final_usage = chunk.usage
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print(f'\n✅ Async success! Received {len(chunks_received)} chunks')
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print(f'📝 Full async response: {"".join(chunks_received)}')
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if final_usage:
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print(f'💰 Total async usage: {final_usage.total_tokens} tokens')
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else:
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print('ℹ️ No usage information available (echo component doesn\'t provide token counts)')
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# Test multiple concurrent conversations
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print('\n🔄 Testing concurrent conversations...')
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async def run_conversation(message, session_id):
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inputs = [ConversationInput(content=message, role='user')]
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chunks = []
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async for chunk in d.converse_stream_alpha1(
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name='echo',
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inputs=inputs,
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context_id=session_id
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):
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if chunk.result and chunk.result.result:
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chunks.append(chunk.result.result)
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return f"Session {session_id}: {''.join(chunks)}"
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# Run 3 conversations concurrently
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tasks = [
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run_conversation("First conversation", "session-1"),
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run_conversation("Second conversation", "session-2"),
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run_conversation("Third conversation", "session-3")
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]
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results = await asyncio.gather(*tasks)
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for result in results:
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print(f'🎯 {result}')
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except Exception as e:
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print(f'❌ Async error: {e}')
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print('\n💡 Make sure to start the Dapr sidecar with:')
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print(' python tools/run_dapr_dev.py')
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if __name__ == '__main__':
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asyncio.run(main())

‎examples/conversation/test_streaming_sync.py‎

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#!/usr/bin/env python3
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"""
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Comprehensive example demonstrating the Dapr streaming conversation API.
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This example demonstrates all features of the streaming conversation API including:
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- Basic streaming conversation
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- Usage tracking (token consumption)
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- PII scrubbing
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- Temperature control
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- Error handling
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Prerequisites:
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- Dapr sidecar running with conversation components
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- Use tools/run_dapr_dev.py to start a development sidecar with echo component
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"""
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import time
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from dapr.clients import DaprClient
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from dapr.clients.grpc._request import ConversationInput
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def main():
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print('🚀 Demonstrating Dapr streaming conversation API features...')
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try:
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with DaprClient() as d:
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print('✓ Connected to Dapr sidecar')
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# Test basic streaming conversation
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print('\n📡 Testing basic streaming conversation...')
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inputs = [
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ConversationInput(content="Hello from Python SDK streaming test!", role='user')
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]
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chunks_received = []
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final_usage = None
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for chunk in d.converse_stream_alpha1(
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name='echo',
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inputs=inputs,
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context_id='sync-test-session-123'
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):
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if chunk.result and chunk.result.result:
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print(f'📦 Chunk: "{chunk.result.result}"')
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chunks_received.append(chunk.result.result)
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if chunk.context_id:
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print(f'🆔 Context ID: {chunk.context_id}')
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if chunk.usage:
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print(f'📊 Usage: {chunk.usage.prompt_tokens} prompt + {chunk.usage.completion_tokens} completion = {chunk.usage.total_tokens} total tokens')
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final_usage = chunk.usage
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print(f'\n✅ Success! Received {len(chunks_received)} chunks')
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print(f'📝 Full response: {"".join(chunks_received)}')
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if final_usage:
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print(f'💰 Total usage: {final_usage.total_tokens} tokens')
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else:
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print('ℹ️ No usage information available (echo component doesn\'t provide token counts)')
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# Test with PII scrubbing
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print('\n🔒 Testing PII scrubbing...')
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pii_inputs = [
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ConversationInput(content="My phone number is +1234567890", role='user', scrub_pii=True)
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]
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scrubbed_chunks = []
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for chunk in d.converse_stream_alpha1(
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name='echo',
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inputs=pii_inputs,
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scrub_pii=True
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):
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if chunk.result and chunk.result.result:
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print(f'📦 Scrubbed chunk: "{chunk.result.result}"')
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scrubbed_chunks.append(chunk.result.result)
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scrubbed_response = "".join(scrubbed_chunks)
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print(f'📝 Scrubbed response: {scrubbed_response}')
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if "<PHONE_NUMBER>" in scrubbed_response:
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print('✅ PII scrubbing working correctly!')
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else:
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print('⚠️ PII scrubbing may not be working as expected')
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# Test with temperature parameter
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print('\n🌡️ Testing with temperature parameter...')
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temp_inputs = [
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ConversationInput(content="Test with temperature setting", role='user')
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]
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temp_chunks = []
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for chunk in d.converse_stream_alpha1(
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name='echo',
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inputs=temp_inputs,
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temperature=0.7
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):
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if chunk.result and chunk.result.result:
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temp_chunks.append(chunk.result.result)
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print(f'📝 Temperature test response: {"".join(temp_chunks)}')
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except Exception as e:
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print(f'❌ Error: {e}')
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print('\n💡 Make sure to start the Dapr sidecar with:')
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print(' python tools/run_dapr_dev.py')
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if __name__ == '__main__':
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main()

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