72d0fb418a
Before the new async-tool mechanism landed, AWSNovaSonicLLMService and OpenAIRealtimeLLMService honored cancel_on_interruption=False by simply not cancelling in-flight function calls on interruption — the eventual result then flowed through the same channel as any synchronous tool result. The new mechanism (which appends started/intermediate/final messages to the LLM context as the underlying task progresses) broke that path: the realtime services didn't know how to interpret those messages, and the eventual result was never delivered to the provider. Restore the flag's behavior by teaching both services to detect async-tool messages in the context and route them appropriately: - started → skipped silently. The provider already issued the tool call and natively awaits a result; nothing to send for the started marker. - final → delivered via the formal tool-result channel. Same path as a synchronous tool result, just delayed. Streamed intermediate results (FunctionCallResultProperties(is_final= False)) are not supported on these realtime services. An intermediate result is logged as an error and surfaced via push_error, then dropped. Use a non-realtime LLM service if a tool needs to stream intermediate results. (Docstrings on register_function, register_direct_function, and FunctionCallResultProperties.is_final updated to call this out.) A new shared module pipecat.processors.aggregators.async_tool_messages is the single source of truth for the on-the-wire payload shape: the aggregator uses its build_*_message functions when injecting messages, and the realtime services use parse_message when scanning the context. Adds two example files exercising a network-delayed weather tool with each service. The plain realtime-aws-nova-sonic.py example is also reverted to a synchronous tool call now that the async variant lives in its own file. Similar fixes for other realtime services are forthcoming.
9.0 KiB
9.0 KiB