Reshape the helper module so AsyncToolMessagePayload is the canonical
in-memory form and the on-the-wire JSON is always derived from it
(never stored). This eliminates a drift risk that came with caching
the JSON in raw_content, and it lets prepare_message_payload_for_realtime
edit the payload (graft the re-invocation reminder into 'description')
and then serialize cleanly — which fixes a 'Tool Response parsing error'
from AWS Nova Sonic that was caused by wrapping the JSON with extra
prose.
Other changes:
- Builders construct an AsyncToolMessagePayload internally and convert
via shared private _payload_to_message and _payload_to_json helpers
(centralizing field-omission rules, e.g. no 'result' on 'started').
- prepare_message_payload_for_realtime replaces format_text_for_provider,
dispatching to per-kind helpers. Reminder is now appended after the
canonical description so the model reads the protocol explanation
first and the directive flows from it.
- Final-result payloads are pass-through; the task is done at that
point and re-invocation is no longer a mistake.
- Stream-tool example: lengthen intermediate sleeps 10s → 20s for more
interesting empirical testing.
Add support to AWSNovaSonicLLMService for the new "async tool call"
mechanism activated by `cancel_on_interruption=False`, which includes:
- delivering results asynchronously
- delivering result streams
- cancelling running async tools
Note that the introduction of the new mechanism had actually caused a
regression in AWS Nova Sonic, which previously supported
`cancel_on_interruption=False` with the old mechanism (simply avoiding
discarding tool calls on interruptions).
Support for the other major realtime services (`GeminiLiveLLMService`,
`OpenAIRealtimeLLMService`) will follow in a separate PR — Gemini Live
in particular needs more work before it can support long-running tool
calls reliably.
