After a reconnect, _ready_for_realtime_input was never set back to True
because _create_initial_response (which sets the flag) is only called on
initial connection. This caused all audio/video/text to be silently
dropped after reconnecting, making the bot appear to hang.
Set the flag in _handle_session_ready when we detect a reconnect, either
via session_resumption_handle (server restores state) or via existing
context (rare case where connection drops before first resumption handle).
After a reconnect, _ready_for_realtime_input was never set back to True
because _create_initial_response (which sets the flag) is only called on
initial connection. This caused all audio/video/text to be silently
dropped after reconnecting, making the bot appear to hang.
Set the flag in _handle_session_ready when context already exists
(i.e. reconnect case) since we don't need to go through
_create_initial_response again.
Remove the deprecation proxy infrastructure that allowed old-style flat
imports (e.g. `from pipecat.services.openai import OpenAILLMService`).
Users must now import from specific submodules
(`from pipecat.services.openai.llm import OpenAILLMService`), which is
already the established pattern across all internal code and 179+ examples.
- Strip 32 proxy `__init__.py` files to empty
- Strip 3 non-proxy files with bare star imports (minimax, sambanova, sarvam)
- Strip google/gemini_live `__init__.py` re-exports
- Remove DeprecatedModuleProxy class and helpers from services/__init__.py
- Remove ruff per-file ignore for services/__init__.py
- Fix 2 examples using old-style imports
Patch Pydantic's DICT_TYPES check in conf.py to accept Union-wrapped
dict types, fixing the autodoc import failure for models using
ConfigDict(extra="allow").
Make -W (warnings as errors) opt-in via --strict flag instead of
default, and update README to reflect uv-based workflow and current
directory structure.
Add tests for LLMRunFrame, LLMMessagesAppendFrame, LLMMessagesUpdateFrame,
and LLMMessagesTransformFrame sent upstream to LLMAssistantAggregator,
mirroring the existing LLMUserAggregator downstream tests. Add
frames_to_send_direction param to run_test helper to support this.
The previous approach required the caller to directly grab a reference to the context object, grab a "snapshot" of its messages *at that point in time*, transform the messages, and then push an `LLMMessagesUpdateFrame` with the transformed messages. This approach can lead to problems: what if there had already been a change to the context queued in the pipeline? The transformed messages would simply overwrite it without consideration.
Napoleon's Attributes section creates class-level attribute docs that
duplicate the __init__ parameter docs when napoleon_include_init_with_doc
is enabled. Using Parameters avoids the duplication.
- Remove expect_stripped_words from LLMAssistantAggregatorParams and related warnings
- Remove old multi-parameter on_push_frame observer signature support in TaskObserver
- Remove deprecated context field from UserImageRequestFrame
- Remove deprecated LiveKitTransportMessageFrame and LiveKitTransportMessageUrgentFrame
- Remove deprecated pipecat.turns.mute shim module
Replace Markdown code blocks with RST syntax in genesys.py, fix
deprecated directive transitions in nvidia and summarization modules,
remove stray bullet prefix in whisper arg docs, restructure code block
in turn completion mixin, and add deepgram mock to Sphinx conf.
Remove stale riva mock imports from autodoc_mock_imports since the riva
service was removed and nvidia-riva-client is installed during doc builds.
Add pipecat.turns and pipecat.extensions to import_core_modules() and
add Turns to the index.rst toctree. Regenerate uv.lock to reflect the
riva extra removal from pyproject.toml.
Move the FastAPI instance to module level so other packages can import
it and register routes before main() is called. main() now configures
the existing app with transport-specific routes instead of creating a
new one.
Deepgram's built-in VAD events were deprecated in 0.0.99 in favor of
Silero VAD. This removes vad_events from settings and LiveOptions,
the should_interrupt parameter, the vad_enabled property,
_on_speech_started/_on_utterance_end handlers, and simplifies
_on_message and process_frame accordingly.
Remove the send_transcription_frames parameter from OpenAI Realtime LLM
(deprecated since 0.0.92). Also fix undefined _warn_deprecated_param
calls in both OpenAI and xAI realtime services, replacing them with the
existing _warn_init_param_moved_to_settings method.
UserBotLatencyLogObserver (deprecated 0.0.102) is replaced by
UserBotLatencyObserver. UserIdleProcessor (deprecated 0.0.100) is
replaced by LLMUserAggregator with user_idle_timeout.
The _self_queued_frames set and _internal_queue_frame wrapper were used
to prevent re-processing SpeechControlParamsFrame that the aggregator
queued to itself. Now that the frame is no longer special-cased, this
tracking is unnecessary. Also removes unused FrameCallback import.
Adds `enable_prompt_caching` setting to `AWSBedrockLLMSettings`. When
enabled, appends `cachePoint` markers to system prompts and tool
definitions in ConverseStream requests.
This can reduce TTFT by up to 85% for multi-turn conversations where
the system prompt stays constant (e.g. voice agents, chat assistants).
Follows the same pattern as `AnthropicLLMService.enable_prompt_caching`.
Usage:
```python
llm = AWSBedrockLLMService(
settings=AWSBedrockLLMSettings(
model="au.anthropic.claude-haiku-4-5-20251001-v1:0",
enable_prompt_caching=True,
),
)
```
See: https://docs.aws.amazon.com/bedrock/latest/userguide/prompt-caching.html
