* Add Inworld Realtime LLM service
Adds a WebSocket-based realtime service for Inworld's cascade
STT/LLM/TTS API with semantic VAD, function calling, and streaming
transcription support.
New files:
- src/pipecat/services/inworld/realtime/ (service, events)
- src/pipecat/adapters/services/inworld_realtime_adapter.py
- examples/foundational/19zb-inworld-realtime.py
Also includes:
- websockets dependency for inworld extra in pyproject.toml
- Adapter and settings tests matching OpenAI/Grok realtime patterns
- Fix for double-response when server-side VAD is enabled
* Prefer init-provided system instruction in Inworld Realtime
Adopt _resolve_system_instruction() from BaseLLMAdapter, matching the
pattern applied to OpenAI Realtime, Grok Realtime, Gemini Live, and
Nova Sonic in the pk/realtime-services-init-v-context-system-instructions-cleanup
branch.
* Update changelog entry with PR number
* Fix changelog format to use bullet point
* Polish PR: default model, example cleanup, changelog update
- Change default model from gpt-4.1-nano to gpt-4.1-mini
- Add function calling demo to example
- Remove demo-testing artifact from system instruction
- Mention Router support in changelog
* Address PR review feedback for Inworld Realtime
- Move example to examples/realtime/realtime-inworld.py
- Change initial context role from "user" to "developer"
- Remove explicit sample rates from example; sync them in
_ensure_audio_config so Inworld gets the transport's actual rates
- Add audio race condition guard in _handle_evt_audio_delta (matches
OpenAI realtime pattern)
- Convert remaining "system"/"developer" messages to "user" in adapter
- Add clarifying comment for local-VAD vs server-VAD metrics paths
* Simplify example, add provider tracking, remove local VAD path
- Remove function calling from example, switch model to xai/grok-4-1-fast-non-reasoning
- Add pipecat-realtime session key prefix and provider_data metadata
for Inworld traffic attribution
- Remove local VAD code path (Inworld only supports server-side VAD)
- Use typed InputAudioBufferAppendEvent for audio sends
* Default TTS model to inworld-tts-1.5-max
* Remove dead shimmed tools code, set STT/VAD defaults
- Remove non-functional AdapterType.SHIM custom tools code from adapter
- Default STT model to assemblyai/u3-rt-pro
- Default VAD eagerness to low
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).
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
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.
OpenPipe was acquired by CoreWeave in September 2025. The Python package
hasn't been updated since June 2025 and the repo since 2024. The openpipe
package caps openai<=1.97.1, creating dependency conflicts with other
extras. Remove the dead integration to clean up the codebase.