Async API
Working with Asynchronous Agents in the Agentuity Python SDK
Async API
The Agentuity Python SDK now supports fully asynchronous operations, enabling more efficient handling of concurrent requests and streaming responses.
Agent Request
The AgentRequest class now uses async patterns to handle incoming data:
from agentuity.server import AgentRequest
async def run(request: AgentRequest, response, context):
# Access request data asynchronously
data = await request.data.text()
# Access request metadata
metadata = request.metadata
# Get the trigger type
trigger = request.trigger
# Return a response
return response.text(f"Received: {data}")Agent Response
The AgentResponse class supports async streaming and iteration:
from agentuity.server import AgentResponse
async def run(request, response: AgentResponse, context):
# Stream response data
async def data_generator():
for i in range(5):
yield f"Data chunk {i}\n"
# Return a streaming response
return response.stream(data_generator(), contentType="text/plain")Async Iteration
Responses can be iterated over asynchronously:
async def process_response(response):
async for chunk in response:
print(chunk)Data Streaming
The SDK provides several specialized stream readers for different data types:
from agentuity.server.data import (
StringStreamReader,
BytesStreamReader,
EmptyDataReader
)
# Create a stream from a string
string_stream = StringStreamReader("Hello, world!")
# Create a stream from bytes
bytes_stream = BytesStreamReader(b"Binary data")
# Create an empty stream
empty_stream = EmptyDataReader()Performance Benefits
The async implementation provides several advantages:
- Efficient handling of concurrent requests
- Streaming of large data payloads without blocking
- Reduced memory usage for processing large files
- Better integration with modern async Python applications
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