The UI Agent Protocol lets server-side AI agents observe and drive
a GUI app on the client side through structured RTVI messages.
Five new top-level RTVI types in kebab-case, in line with the rest
of the protocol:
ui-event client → server (named event with payload)
ui-command server → client (named command with payload)
ui-snapshot client → server (accessibility tree of the page)
ui-cancel-task client → server (cancel an in-flight task group)
ui-task server → client (task lifecycle envelope)
Each ships paired ``*Data`` / ``*Message`` pydantic models in
``rtvi.models``, following the existing RTVI envelope convention
(``BotReady`` / ``BotReadyData``, ``Error`` / ``ErrorData``, etc.).
Built-in command payload models (``Toast``, ``Navigate``,
``ScrollTo``, ``Highlight``, ``Focus``, ``Click``, ``SetInputValue``,
``SelectText``) ship alongside; matching default React handlers
live in ``@pipecat-ai/client-react``.
Bumps the RTVI ``PROTOCOL_VERSION`` from ``1.2.0`` to ``1.3.0``.
Purely additive: only new top-level message types are introduced;
no existing wire shapes are changed. The major-version
compatibility check on ``client-ready`` still passes for older
1.x clients, so old clients continue to connect without warning;
they simply will not exercise the new types.
The ``RTVIProcessor`` registers a new ``on_ui_message`` event
handler that fires for inbound ``ui-event`` / ``ui-snapshot`` /
``ui-cancel-task`` with the parsed Message envelope, mirroring how
``on_client_message`` works for ``client-message``.
Five new pipeline frames let pipeline observers and processors see
UI traffic the same way they see other RTVI messages, mirroring
the frame-and-event pattern used by ``client-message``:
RTVIUICommandFrame(command_name, payload)
Pushed by downstream code (e.g. ``pipecat-ai-subagents``'s
bridge) to send a UI command to the client. Wrapped by the
observer into a ``UICommandMessage`` envelope.
RTVIUITaskFrame(data: UITaskData)
Same shape but for ``ui-task``; wrapped into ``UITaskMessage``.
``UITaskData`` is a discriminated union of the four lifecycle
kinds (group_started / task_update / task_completed /
group_completed).
RTVIUIEventFrame(msg_id, event_name, payload)
RTVIUISnapshotFrame(msg_id, tree)
RTVIUICancelTaskFrame(msg_id, task_id, reason)
Pushed by ``RTVIProcessor._handle_message`` whenever the
matching inbound message arrives, alongside firing
``on_ui_message``. Pipeline observers and processors can match
on the frame; subscribers like the subagents bridge keep using
the event handler.
The data layer is the canonical authority for the wire format:
higher-level frameworks like ``pipecat-ai-subagents`` build the
agent abstractions on top, and single-LLM Pipecat apps can target
the same wire format directly via custom tools that emit these
typed messages.
A second pass over the low-error-count files in the ignore list. Drops
10 files (77 → 67) and full-pyright errors from 580 → 555. Default
pyright stays clean.
Three coherent shapes plus a handful of one-offs:
`Language | str | None` → `Language | None` at STT frame boundaries.
`assert_given(self._settings.language)` returns `Language | str | None`
(strips `_NotGiven`, keeps the rest), but `TranscriptionFrame.language`
expects `Language | None`. In practice both `_settings.language` and
SDK-supplied codes resolve to a `Language` enum value, but technically
they could be raw strings — and `Language` is a StrEnum, so downstream
consumers (which mostly compare/serialize as strings) handle either.
Used `cast("Language | None", ...)` at each call site rather than a
runtime-validating helper, so an unrecognised code (e.g. one we
haven't added to the enum yet) still flows through unchanged. Cleared
azure/stt.py, aws/stt.py, gradium/stt.py; mistral/stt.py keeps the
cast at the SDK boundary (storing under `_detected_language: Language
| None`) but stays in the ignore list because of two unrelated
Optional-access errors.
aiobotocore `async with` stub gap. `aioboto3.Session().client(...)`
is an async context manager at runtime but its stubs don't advertise
`__aenter__`/`__aexit__` to pyright. Scoped
`# pyright: ignore[reportGeneralTypeIssues]` on the two affected
sites: aws/agent_core.py and aws/tts.py. aws/tts.py also had a latent
bug on the no-`AudioStream` path: the original code set
`audio_data = None` and then crashed in `resample(...)` and
`len(audio_data)` below; replaced with an early `return` after
logging — matches the convention elsewhere (OpenAI TTS, etc.) of not
recording usage metrics on the error path.
heygen `event_id: str | None` → `str` at transport→client boundary.
Three call sites in transports/heygen/transport.py passed `self._event_id`
(`str | None`) into client methods that take `str`. Added a guard at
each: `agent_speak_end` and `interrupt` only fire when `_event_id` is
set; `write_audio_frame` warn-and-drops when there's no active bot
event rather than sending a malformed message.
`OpenAIResponsesLLMInvocationParams` TypedDict.
`get_llm_invocation_params` always sets both `input` and `tools` in
the same dict literal, but the TypedDict was `total=False` so direct
subscript access (`invocation_params["input"]`) tripped
`reportTypedDictNotRequiredAccess` in services/openai/responses/llm.py.
Marked both keys `Required[...]`; `instructions` stays non-required
since it's only added when a system instruction is present.
Latent bug in heygen/api_interactive_avatar.py: the code accessed
`request_data.voice.voiceId` and `request_data.voice.elevenlabsSettings`,
but those names are Pydantic *aliases*; the actual attribute names
(used for attribute access) are `voice_id` and `elevenlabs_settings`.
Switched to the field names — those camelCase accesses would have
raised AttributeError at runtime if `voice` was set.
Other small fixes:
- assemblyai/stt.py: the deprecated `connection_params=` init path
was reading `formatted_finals` and `word_finalization_max_wait_time`
off `AssemblyAIConnectionParams`, but those fields were never on
the deprecated input model — they were added to Settings later.
Removed the reads (with a comment noting they're only available
via the canonical `settings=...` API); the deprecated input model
is unchanged.
- rtvi/processor.py: two `about: Mapping[str, Any] = None` parameter
signatures — declared `Mapping`, defaulted to `None`, and both
function bodies already handled the None case. Widened to
`Mapping[str, Any] | None = None`.
- aws/stt.py: `subprotocols=["mqtt"]` failed against websockets'
`Sequence[Subprotocol] | None` (Subprotocol is a NewType wrapper).
Wrapped: `subprotocols=[Subprotocol("mqtt")]`.
Files dropped from the ignore list (77 → 67):
processors/frameworks/rtvi/processor.py, services/assemblyai/stt.py,
services/aws/agent_core.py, services/aws/stt.py, services/aws/tts.py,
services/azure/stt.py, services/gradium/stt.py,
services/heygen/api_interactive_avatar.py,
services/openai/responses/llm.py, transports/heygen/transport.py.
Replace the monolithic rtvi.py with a proper package split by concern
protocol version:
- models_v0.py: deprecated pre-1.0 Pydantic models
- models_v1.py: current RTVI protocol v1 message models
- frames.py: RTVI pipeline frame dataclasses
- observer.py: RTVIObserver and RTVIObserverParams
- processor.py: RTVIProcessor (now lean, imports from submodules)
- __init__.py: re-exports full public API for backward compatability
