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agent-framework/python/samples/concepts
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Eduard van Valkenburg 35097d8c75 Python: Add long-running agents and background responses support (#3808)
* Python: Add long-running agents and background responses support

- Add ContinuationToken TypedDict to core types
- Add continuation_token field to ChatResponse, ChatResponseUpdate,
  AgentResponse, and AgentResponseUpdate
- Add background and continuation_token options to OpenAIResponsesOptions
- Implement polling via responses.retrieve() and streaming resumption
  in RawOpenAIResponsesClient
- Propagate continuation tokens through agent run() and
  map_chat_to_agent_update
- Fix streaming telemetry 'Failed to detach context' error in both
  ChatTelemetryLayer and AgentTelemetryLayer by avoiding
  trace.use_span() context attachment for async-managed spans
- Add 14 unit tests for continuation token types and background flows
- Add background_responses sample showing polling and stream resumption

Fixes #2478

* Python: Add A2A long-running task support via ContinuationToken

- Make ContinuationToken provider-agnostic (total=False, optional task_id/context_id fields)
- Add background param to A2AAgent.run() controlling token emission
- Add poll_task() for single-request task state retrieval
- Add resubscribe support via continuation_token param on run()
- Extract _updates_from_task() and _map_a2a_stream() for cleaner code
- Streamline run()/streaming by removing intermediate _stream_updates wrapper
- Update A2A sample to show background=False (default) with link to background_responses sample
- Remove stale BareAgent from __all__
- Add 12 new A2A continuation token tests

* fix logic for overriding continuation token when done

* refactored ContinuationToken setup
35097d8c75 ยท 2026-02-10 20:37:43 +00:00
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Concept Samples

This folder contains samples that dive deep into specific Agent Framework concepts.

Samples

Sample Description
response_stream.py Deep dive into ResponseStream - the streaming abstraction for AI responses. Covers the four hook types (transform hooks, cleanup hooks, finalizer, result hooks), two consumption patterns (iteration vs direct finalization), and the wrap() API for layering streams without double-consumption.
typed_options.py Demonstrates TypedDict-based chat options for type-safe configuration with IDE autocomplete support.