Add changelog for OpenRouter updates

.claude/skills/squash-commits/SKILL.md

@@ -1,91 +0,0 @@
----
-name: squash-commits
-description: Reorganize messy branch commits into a small set of logical, meaningful commits without changing any content. Drops merge-from-main commits. Safe: creates a backup branch first.
----
-
-Reorganize the commits on the current branch into a small number of logical commits. Do NOT change any file content — only the commit structure changes.
-
-## Instructions
-
-### 1. Safety check
-
-```bash
-git status --short
-```
-
-If there are uncommitted changes, stop and tell the user to commit or stash them first.
-
-### 2. Inspect the branch
-
-```bash
-git log main..HEAD --oneline
-git diff main..HEAD --name-only
-```
-
-List every file changed vs `main` and every commit on the branch (excluding merge commits from main).
-
-### 3. Create a backup branch
-
-```bash
-git branch backup/<current-branch-name>
-```
-
-Tell the user the backup exists so they can recover if needed.
-
-### 4. Soft-reset to main and unstage everything
-
-```bash
-git reset --soft main
-git restore --staged .
-```
-
-All branch changes are now in the working tree, unstaged. No content has changed.
-
-### 5. Plan the logical groups
-
-Read the changed files and the original commit messages to understand what the work covers. Group related files into logical commits. Typical groups:
-
-- Core feature or fix (new source files + modified core files)
-- Secondary features or fixes (each as its own commit if distinct)
-- Refactoring or renames
-- Tests
-- Changelogs / docs
-
-Use the changelog files (if any) as a strong hint — each changelog entry often maps to one commit.
-
-Present the proposed grouping to the user and ask for confirmation before committing.
-
-### 6. Commit in logical groups
-
-For each group, stage only the relevant files and commit with a clear message following the project's conventions:
-
-```bash
-git add <file1> <file2> ...
-git commit -m "..."
-```
-
-Use conventional commit prefixes if the project uses them (`feat:`, `fix:`, `refactor:`, `test:`, `chore:`).
-
-### 7. Verify
-
-```bash
-git log main..HEAD --oneline
-git diff main..HEAD --name-only
-git status --short
-```
-
-Confirm:
-- Commit count is small and each message is meaningful
-- The set of changed files vs `main` is identical to before
-- Working tree is clean
-
-### 8. Remind about force-push
-
-The branch history has been rewritten. Tell the user they will need to `git push --force-with-lease` when they are ready to update the remote. Do NOT push automatically.
-
-## Rules
-
-- Never change file contents. If you find yourself editing a file, stop.
-- Never skip the backup branch step.
-- Never force-push without explicit user instruction.
-- If any step fails or the result looks wrong, tell the user and suggest restoring from the backup: `git reset --hard backup/<branch-name>`.

.github/workflows/coverage.yaml

@@ -41,9 +41,7 @@ jobs:
             --extra google \
             --extra langchain \
             --extra livekit \
-            --extra pgmq \
             --extra piper \
-            --extra redis \
             --extra runner \
             --extra sagemaker \
             --extra tracing \

.github/workflows/tests.yaml

@@ -45,9 +45,7 @@ jobs:
             --extra google \
             --extra langchain \
             --extra livekit \
-            --extra pgmq \
             --extra piper \
-            --extra redis \
             --extra runner \
             --extra sagemaker \
             --extra tracing \

README.md

@@ -92,10 +92,10 @@ Catch new features, interviews, and how-tos on our [Pipecat TV](https://www.yout
 | Category            | Services                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
 | ------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
 | Speech-to-Text      | [AssemblyAI](https://docs.pipecat.ai/api-reference/server/services/stt/assemblyai), [AWS](https://docs.pipecat.ai/api-reference/server/services/stt/aws), [Azure](https://docs.pipecat.ai/api-reference/server/services/stt/azure), [Cartesia](https://docs.pipecat.ai/api-reference/server/services/stt/cartesia), [Deepgram](https://docs.pipecat.ai/api-reference/server/services/stt/deepgram), [ElevenLabs](https://docs.pipecat.ai/api-reference/server/services/stt/elevenlabs), [Fal Wizper](https://docs.pipecat.ai/api-reference/server/services/stt/fal), [Gladia](https://docs.pipecat.ai/api-reference/server/services/stt/gladia), [Google](https://docs.pipecat.ai/api-reference/server/services/stt/google), [Gradium](https://docs.pipecat.ai/api-reference/server/services/stt/gradium), [Groq (Whisper)](https://docs.pipecat.ai/api-reference/server/services/stt/groq), [Mistral](https://docs.pipecat.ai/api-reference/server/services/stt/mistral), [NVIDIA](https://docs.pipecat.ai/api-reference/server/services/stt/nvidia), [OpenAI (Whisper)](https://docs.pipecat.ai/api-reference/server/services/stt/openai), [Sarvam](https://docs.pipecat.ai/api-reference/server/services/stt/sarvam), [Soniox](https://docs.pipecat.ai/api-reference/server/services/stt/soniox), [Speechmatics](https://docs.pipecat.ai/api-reference/server/services/stt/speechmatics), [Whisper](https://docs.pipecat.ai/api-reference/server/services/stt/whisper), [xAI](https://docs.pipecat.ai/api-reference/server/services/stt/xai)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     |
-| LLMs                | [Anthropic](https://docs.pipecat.ai/api-reference/server/services/llm/anthropic), [AWS](https://docs.pipecat.ai/api-reference/server/services/llm/aws), [Azure](https://docs.pipecat.ai/api-reference/server/services/llm/azure), [Cerebras](https://docs.pipecat.ai/api-reference/server/services/llm/cerebras), [DeepSeek](https://docs.pipecat.ai/api-reference/server/services/llm/deepseek), [Fireworks AI](https://docs.pipecat.ai/api-reference/server/services/llm/fireworks), [Gemini](https://docs.pipecat.ai/api-reference/server/services/llm/gemini), [Grok](https://docs.pipecat.ai/api-reference/server/services/llm/grok), [Groq](https://docs.pipecat.ai/api-reference/server/services/llm/groq), [Inception](https://docs.pipecat.ai/api-reference/server/services/llm/inception), [Mistral](https://docs.pipecat.ai/api-reference/server/services/llm/mistral), [Nebius](https://docs.pipecat.ai/api-reference/server/services/llm/nebius), [Novita](https://docs.pipecat.ai/api-reference/server/services/llm/novita), [NVIDIA NIM](https://docs.pipecat.ai/api-reference/server/services/llm/nvidia), [Ollama](https://docs.pipecat.ai/api-reference/server/services/llm/ollama), [OpenAI](https://docs.pipecat.ai/api-reference/server/services/llm/openai), [OpenAI Responses](https://docs.pipecat.ai/api-reference/server/services/llm/openai-responses), [OpenRouter](https://docs.pipecat.ai/api-reference/server/services/llm/openrouter), [Perplexity](https://docs.pipecat.ai/api-reference/server/services/llm/perplexity), [Qwen](https://docs.pipecat.ai/api-reference/server/services/llm/qwen), [SambaNova](https://docs.pipecat.ai/api-reference/server/services/llm/sambanova), [Sarvam](https://docs.pipecat.ai/api-reference/server/services/llm/sarvam), [Together AI](https://docs.pipecat.ai/api-reference/server/services/llm/together)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    |
+| LLMs                | [Anthropic](https://docs.pipecat.ai/api-reference/server/services/llm/anthropic), [AWS](https://docs.pipecat.ai/api-reference/server/services/llm/aws), [Azure](https://docs.pipecat.ai/api-reference/server/services/llm/azure), [Cerebras](https://docs.pipecat.ai/api-reference/server/services/llm/cerebras), [DeepSeek](https://docs.pipecat.ai/api-reference/server/services/llm/deepseek), [Fireworks AI](https://docs.pipecat.ai/api-reference/server/services/llm/fireworks), [Gemini](https://docs.pipecat.ai/api-reference/server/services/llm/gemini), [Grok](https://docs.pipecat.ai/api-reference/server/services/llm/grok), [Groq](https://docs.pipecat.ai/api-reference/server/services/llm/groq), [Mistral](https://docs.pipecat.ai/api-reference/server/services/llm/mistral), [Nebius](https://docs.pipecat.ai/api-reference/server/services/llm/nebius), [Novita](https://docs.pipecat.ai/api-reference/server/services/llm/novita), [NVIDIA NIM](https://docs.pipecat.ai/api-reference/server/services/llm/nvidia), [Ollama](https://docs.pipecat.ai/api-reference/server/services/llm/ollama), [OpenAI](https://docs.pipecat.ai/api-reference/server/services/llm/openai), [OpenAI Responses](https://docs.pipecat.ai/api-reference/server/services/llm/openai-responses), [OpenRouter](https://docs.pipecat.ai/api-reference/server/services/llm/openrouter), [Perplexity](https://docs.pipecat.ai/api-reference/server/services/llm/perplexity), [Qwen](https://docs.pipecat.ai/api-reference/server/services/llm/qwen), [SambaNova](https://docs.pipecat.ai/api-reference/server/services/llm/sambanova), [Sarvam](https://docs.pipecat.ai/api-reference/server/services/llm/sarvam), [Together AI](https://docs.pipecat.ai/api-reference/server/services/llm/together)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    |
 | Text-to-Speech      | [Async](https://docs.pipecat.ai/api-reference/server/services/tts/asyncai), [AWS](https://docs.pipecat.ai/api-reference/server/services/tts/aws), [Azure](https://docs.pipecat.ai/api-reference/server/services/tts/azure), [Camb AI](https://docs.pipecat.ai/api-reference/server/services/tts/camb), [Cartesia](https://docs.pipecat.ai/api-reference/server/services/tts/cartesia), [Deepgram](https://docs.pipecat.ai/api-reference/server/services/tts/deepgram), [ElevenLabs](https://docs.pipecat.ai/api-reference/server/services/tts/elevenlabs), [Fish](https://docs.pipecat.ai/api-reference/server/services/tts/fish), [Google](https://docs.pipecat.ai/api-reference/server/services/tts/google), [Gradium](https://docs.pipecat.ai/api-reference/server/services/tts/gradium), [Groq](https://docs.pipecat.ai/api-reference/server/services/tts/groq), [Hume](https://docs.pipecat.ai/api-reference/server/services/tts/hume), [Inworld](https://docs.pipecat.ai/api-reference/server/services/tts/inworld), [Kokoro](https://docs.pipecat.ai/api-reference/server/services/tts/kokoro), [LMNT](https://docs.pipecat.ai/api-reference/server/services/tts/lmnt), [MiniMax](https://docs.pipecat.ai/api-reference/server/services/tts/minimax), [Mistral](https://docs.pipecat.ai/api-reference/server/services/tts/mistral), [Neuphonic](https://docs.pipecat.ai/api-reference/server/services/tts/neuphonic), [NVIDIA](https://docs.pipecat.ai/api-reference/server/services/tts/nvidia), [OpenAI](https://docs.pipecat.ai/api-reference/server/services/tts/openai), [Piper](https://docs.pipecat.ai/api-reference/server/services/tts/piper), [Resemble](https://docs.pipecat.ai/api-reference/server/services/tts/resemble), [Rime](https://docs.pipecat.ai/api-reference/server/services/tts/rime), [Sarvam](https://docs.pipecat.ai/api-reference/server/services/tts/sarvam), [Smallest](https://docs.pipecat.ai/api-reference/server/services/tts/smallest), [Soniox](https://docs.pipecat.ai/api-reference/server/services/tts/soniox), [Speechmatics](https://docs.pipecat.ai/api-reference/server/services/tts/speechmatics), [xAI](https://docs.pipecat.ai/api-reference/server/services/tts/xai), [XTTS](https://docs.pipecat.ai/api-reference/server/services/tts/xtts) |
 | Speech-to-Speech    | [AWS Nova Sonic](https://docs.pipecat.ai/api-reference/server/services/s2s/aws), [Gemini Multimodal Live](https://docs.pipecat.ai/api-reference/server/services/s2s/gemini), [Grok Voice Agent](https://docs.pipecat.ai/api-reference/server/services/s2s/grok), [OpenAI Realtime](https://docs.pipecat.ai/api-reference/server/services/s2s/openai), [Ultravox](https://docs.pipecat.ai/api-reference/server/services/s2s/ultravox),                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               |
-| Transport           | [Daily (WebRTC)](https://docs.pipecat.ai/api-reference/server/services/transport/daily), [FastAPI Websocket](https://docs.pipecat.ai/api-reference/server/services/transport/fastapi-websocket), [LiveKit (WebRTC)](https://docs.pipecat.ai/api-reference/server/services/transport/livekit), [SmallWebRTCTransport](https://docs.pipecat.ai/api-reference/server/services/transport/small-webrtc), [Vonage (WebRTC)](https://docs.pipecat.ai/api-reference/server/services/transport/vonage), [WebSocket Server](https://docs.pipecat.ai/api-reference/server/services/transport/websocket-server), [WhatsApp](https://docs.pipecat.ai/api-reference/server/services/transport/whatsapp), Local                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               |
+| Transport           | [Daily (WebRTC)](https://docs.pipecat.ai/api-reference/server/services/transport/daily), [FastAPI Websocket](https://docs.pipecat.ai/api-reference/server/services/transport/fastapi-websocket), [LiveKit (WebRTC)](https://docs.pipecat.ai/api-reference/server/services/transport/livekit), [SmallWebRTCTransport](https://docs.pipecat.ai/api-reference/server/services/transport/small-webrtc), [WebSocket Server](https://docs.pipecat.ai/api-reference/server/services/transport/websocket-server), [WhatsApp](https://docs.pipecat.ai/api-reference/server/services/transport/whatsapp), Local                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               |
 | Serializers         | [Exotel](https://docs.pipecat.ai/api-reference/server/services/serializers/exotel), [Genesys](https://docs.pipecat.ai/api-reference/server/services/serializers/genesys), [Plivo](https://docs.pipecat.ai/api-reference/server/services/serializers/plivo), [Twilio](https://docs.pipecat.ai/api-reference/server/services/serializers/twilio), [Telnyx](https://docs.pipecat.ai/api-reference/server/services/serializers/telnyx), [Vonage](https://docs.pipecat.ai/api-reference/server/services/serializers/vonage)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              |
 | Video               | [HeyGen](https://docs.pipecat.ai/api-reference/server/services/video/heygen), [LemonSlice](https://docs.pipecat.ai/api-reference/server/services/transport/lemonslice), [Tavus](https://docs.pipecat.ai/api-reference/server/services/video/tavus), [Simli](https://docs.pipecat.ai/api-reference/server/services/video/simli)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                      |
 | Memory              | [mem0](https://docs.pipecat.ai/api-reference/server/services/memory/mem0)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           |

changelog/4052.added.md

@@ -1 +0,0 @@
-- Added `VonageVideoConnectorTransport`, a new transport integration for real-time Vonage WebRTC sessions using the Vonage Video Connector library.

changelog/4306.fixed.md

@@ -1 +0,0 @@
-- Fixed Azure TTS last word being missed by observers and RTVI UI. The completion signal was racing with word timestamp processing, causing the final word's `TTSTextFrame` to arrive after `TTSStoppedFrame`. Completion is now routed through the word boundary queue to ensure all words are processed before signaling stream end.

changelog/4380.fixed.2.md

@@ -1 +0,0 @@
-- Fixed `BaseOutputTransport` reordering frames that share the same presentation timestamp. Frames with equal PTS values are now emitted in insertion order, preventing subtle audio/text sequencing bugs when multiple frames arrive at the same time.

changelog/4380.fixed.3.md

@@ -1 +0,0 @@
-- Fixed Cartesia word timestamps leaking SSML tag text (e.g. `<spell>`, `<emotion>`, `<break>`) into word entries. Tags are now stripped before processing, so word-to-text attribution remains accurate when SSML markup is present in the TTS input.

changelog/4380.fixed.4.md

@@ -1 +0,0 @@
-- Fixed `TTSTextFrame` entries losing their original text structure when word timestamps are enabled. Each `TTSTextFrame` now carries a `raw_text` field containing the corresponding span of the original LLM-produced text (including pattern delimiters such as `<card>4111 1111 1111 1111</card>`), so the assistant context receives properly-tagged content rather than the cleaned words returned by the TTS provider. Also handles words that straddle two sentence boundaries by splitting them and attributing each part to its correct source frame.

changelog/4380.fixed.md

@@ -1 +0,0 @@
-- Fixed skipped TTS frames (e.g. code blocks filtered via `skip_aggregator_types`) being emitted to the assistant context immediately instead of waiting for preceding spoken frames to finish. They now hold their position in the frame sequence and are flushed only after all earlier spoken sentences are complete, keeping context ordering correct.

changelog/4423.added.md

@@ -1 +0,0 @@
-- Added `InceptionLLMService` for Inception's Mercury 2 diffusion reasoning model, with support for `reasoning_effort` and `realtime` settings.

changelog/4493.added.md

@@ -1 +0,0 @@
-- Added `pipecat.workers`, a worker-based agent framework folded in from the standalone `pipecat-subagents` package. Workers inherit from `BaseWorker`, share a `WorkerBus`, register in a `WorkerRegistry`, and exchange typed work via `@job` handlers. `LLMWorker` and `LLMContextWorker` provide ready-made LLM-driven workers. `PipelineRunner.spawn(worker)` registers fire-and-forget workers alongside the main pipeline worker.

changelog/4493.changed.2.md

@@ -1 +0,0 @@
-- ⚠️ `FrameProcessorSetup.pipeline_worker` and `FunctionCallParams.pipeline_worker` are now mandatory fields, and `FrameProcessor.pipeline_worker` raises if read before `setup()` instead of returning `None`. Real-world code (frame processors set up by `PipelineWorker`, tool handlers invoked by `LLMService`) is unaffected; only callers that construct these dataclasses by hand (typically tests) now have to supply a `pipeline_worker` reference.

changelog/4493.changed.md

@@ -1 +0,0 @@
-- `PipelineWorker` now inherits from `BaseWorker`, so every pipeline worker is also a bus participant. It accepts a new optional `bridged=()` parameter that auto-wraps the pipeline with bus edge processors, letting the worker exchange frames with other bridged workers over the shared `WorkerBus`. The bus is supplied by `PipelineRunner` via `worker.attach(registry=..., bus=...)` instead of through the constructor.

changelog/4513.changed.2.md

@@ -0,0 +1 @@
+- OpenRouter LLM requests now convert `developer` messages to `user` messages by default for broader model compatibility. Override this by subclassing `OpenRouterLLMService` or setting `llm.supports_developer_role = True` for models that support the `developer` role.

changelog/4513.changed.md

@@ -0,0 +1 @@
+- OpenRouter LLM service now defaults to `openai/gpt-4.1`.

changelog/4514.fixed.md

@@ -1 +0,0 @@
-- Fixed websocket STT connection setup failures so services clear stale websocket state and emit non-fatal error frames, allowing `ServiceSwitcher` failover to keep agents running.

changelog/4521.added.md

@@ -1 +0,0 @@
-- Added `max_endpoint_delay_ms` to `SonioxSTTService.Settings`, controlling the maximum delay (500-3000 ms) before endpoint detection finalizes a turn.

changelog/4521.changed.md

@@ -1 +0,0 @@
-- `SonioxSTTService` now applies settings updates (e.g. via `STTUpdateSettingsFrame`) using a graceful reconnect instead of a hard disconnect/reconnect, preserving the service's reconnect retry behavior.

changelog/4521.removed.md

@@ -1 +0,0 @@
-- Removed the unsupported Georgian (`Language.KA`) language mapping from `SonioxSTTService`.

changelog/4522.changed.md

@@ -1 +0,0 @@
-- Updated the default p99 TTFS latency values for Smallest AI, Mistral, and XAI STT so turn stop timing uses measured values instead of the conservative fallback.

changelog/4524.changed.md

@@ -1 +0,0 @@
-- Updated the development runner startup banner to show the prebuilt client URL once and list enabled or disabled transports with install hints.

changelog/4524.fixed.md

@@ -1 +0,0 @@
-- Fixed the development runner so missing optional transport dependencies disable only their related routes instead of failing startup in all-transport mode.

changelog/4527.fixed.md

@@ -1 +0,0 @@
-- Fixed a race in `ElevenLabsTTSService` where the periodic keepalive could be sent for a new turn's context before that context's `voice_settings` initialization message, causing ElevenLabs to close the WebSocket with a 1008 policy violation (`voice_settings field must be provided in the first message ...`). The keepalive now only targets a context once its context-init has been sent.

changelog/4531.changed.md

@@ -1 +0,0 @@
-- Bumped `pipecat-ai-prebuilt` to 1.0.1 in the `runner` extra, updating the prebuilt client UI served by the development runner.

changelog/xxxx.added.2.md

@@ -1 +0,0 @@
-- Added `LLMService.append_system_instruction(...)`, which composes durable text onto a user-provided system instruction (alongside the turn-completion and async-tool-cancellation instructions) so it is prepended on every inference and survives context-message resets.

changelog/xxxx.added.md

@@ -1,3 +0,0 @@
-- Added `pipecat.workers.ui.UIWorker`, an `LLMContextWorker` that observes and drives a client GUI over the RTVI UI channel: it stores live accessibility snapshots, auto-injects `<ui_state>` into the LLM context before every inference (via the LLM's `on_before_process_frame` hook), dispatches client events to `@on_ui_event` handlers, and sends UI commands (`scroll_to`, `highlight`, `select_text`, `click`, `set_input_value`) back to the client. The optional `ReplyToolMixin` exposes a bundled `reply` tool, and `user_job_group(...)` surfaces fan-out work to the client as cancellable task cards. A native RTVI⇄bus UI bridge is built into `PipelineWorker` (active whenever RTVI is enabled), so no decorator or manual wiring is needed: inbound UI messages are broadcast on the bus as `BusUIEventMessage`, and outbound `BusUICommandMessage` / `BusUITask*` carriers are translated into RTVI frames for the client.
-
-- `UIWorker` auto-injects the UI wire-format guide (`UI_STATE_PROMPT_GUIDE`) into its LLM's system instruction by default, via a `prompt_guide` parameter — pass your own string to override the guide, or `None` to disable. Apps no longer need to concatenate `UI_STATE_PROMPT_GUIDE` into the LLM's `system_instruction` by hand.

env.example

@@ -91,9 +91,6 @@ HEYGEN_LIVE_AVATAR_API_KEY=...
 HUME_API_KEY=...
 HUME_VOICE_ID=...
 
-# Inception
-INCEPTION_API_KEY=...
-
 # Inworld
 INWORLD_API_KEY=...
 
@@ -214,11 +211,6 @@ TWILIO_AUTH_TOKEN=...
 # Ultravox Realtime
 ULTRAVOX_API_KEY=...
 
-# Vonage
-VONAGE_APPLICATION_ID=...
-VONAGE_SESSION_ID=...
-VONAGE_TOKEN=...
-
 # WhatsApp
 WHATSAPP_TOKEN=...
 WHATSAPP_WEBHOOK_VERIFICATION_TOKEN=...

examples/audio/audio-bot-background-sound.py

@@ -16,7 +16,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame, MixerEnableFrame, MixerUpdateSettingsFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -105,7 +105,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -120,27 +120,27 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         logger.info(f"Listening for background sound for a bit...")
         await asyncio.sleep(5.0)
         logger.info(f"Reducing volume...")
-        await worker.queue_frame(MixerUpdateSettingsFrame({"volume": 0.5}))
+        await task.queue_frame(MixerUpdateSettingsFrame({"volume": 0.5}))
         await asyncio.sleep(5.0)
         logger.info(f"Disabling background sound for a bit...")
-        await worker.queue_frame(MixerEnableFrame(False))
+        await task.queue_frame(MixerEnableFrame(False))
         await asyncio.sleep(5.0)
         logger.info(f"Re-enabling background sound and starting bot...")
-        await worker.queue_frame(MixerEnableFrame(True))
+        await task.queue_frame(MixerEnableFrame(True))
         # Kick off the conversation.
         context.add_message(
             {"role": "developer", "content": "Please introduce yourself to the user."}
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/audio/audio-recording.py

@@ -54,7 +54,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -146,7 +146,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -161,12 +161,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         # Start recording audio
         await audiobuffer.start_recording()
         # Start conversation - empty prompt to let LLM follow system instructions
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     # Handler for merged audio
     @audiobuffer.event_handler("on_audio_data")
@@ -191,7 +191,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         await save_audio_file(bot_audio, bot_filename, sample_rate, 1)
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/audio/audio-sound-effects.py

@@ -20,7 +20,7 @@ from pipecat.frames.frames import (
 )
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineWorker
+from pipecat.pipeline.task import PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -144,7 +144,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
@@ -153,17 +153,17 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     async def on_client_connected(transport, client):
         logger.info(f"Client connected")
         # Kick off the conversation.
-        await worker.queue_frame(TTSSpeakFrame("Hi, I'm listening!"))
+        await task.queue_frame(TTSSpeakFrame("Hi, I'm listening!"))
         await transport.send_audio(sounds["ding1.wav"])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/context-summarization/context-summarization-dedicated-llm.py

@@ -26,7 +26,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_context_summarizer import SummaryAppliedEvent
 from pipecat.processors.aggregators.llm_response_universal import (
@@ -198,7 +198,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -214,16 +214,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         context.add_message(
             {"role": "developer", "content": "Please introduce yourself to the user."}
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info("Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/context-summarization/context-summarization-google.py

@@ -24,7 +24,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_context_summarizer import SummaryAppliedEvent
 from pipecat.processors.aggregators.llm_response_universal import (
@@ -159,7 +159,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -175,16 +175,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         context.add_message(
             {"role": "developer", "content": "Please introduce yourself to the user."}
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info("Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/context-summarization/context-summarization-manual-openai.py

@@ -26,7 +26,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame, LLMSummarizeContextFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -133,7 +133,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -149,16 +149,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         context.add_message(
             {"role": "developer", "content": "Please introduce yourself to the user."}
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info("Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/context-summarization/context-summarization-openai.py

@@ -24,7 +24,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_context_summarizer import SummaryAppliedEvent
 from pipecat.processors.aggregators.llm_response_universal import (
@@ -159,7 +159,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -175,16 +175,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         context.add_message(
             {"role": "developer", "content": "Please introduce yourself to the user."}
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info("Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/features/features-add-tool-change-messages.py

@@ -56,7 +56,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame, LLMSetToolsFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import NOT_GIVEN, LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -163,7 +163,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(enable_metrics=True, enable_usage_metrics=True),
         idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
@@ -185,13 +185,13 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
                 "=== Phase 1: weather tool REMOVED. Keep asking about the weather "
                 "to exercise hallucination scenarios. ==="
             )
-            await worker.queue_frame(LLMSetToolsFrame(tools=NOT_GIVEN))
+            await task.queue_frame(LLMSetToolsFrame(tools=NOT_GIVEN))
         elif user_turn_count == READD_AT_TURN - 1:
             logger.info(
                 "=== Phase 2: weather tool RE-ADDED. Ask for the weather again — "
                 "does the LLM call it, or keep refusing? (THIS IS THE TEST.) ==="
             )
-            await worker.queue_frame(LLMSetToolsFrame(tools=weather_tools))
+            await task.queue_frame(LLMSetToolsFrame(tools=weather_tools))
 
     @transport.event_handler("on_client_connected")
     async def on_client_connected(transport, client):
@@ -209,15 +209,15 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
                 ),
             }
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info("Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/features/features-app-resources.py

@@ -4,27 +4,27 @@
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
-"""Example demonstrating ``PipelineWorker(app_resources=...)``.
+"""Example demonstrating ``PipelineTask(app_resources=...)``.
 
 ``app_resources`` is an application-defined bag of anything your
 application code may want to share across a session: database handles,
 HTTP clients, feature flags, per-user state, observability clients,
 in-memory caches — whatever fits your app. Pipecat passes it through
-untouched and exposes it as ``worker.app_resources``, so any code with a
-handle on the worker can read or mutate it.
+untouched and exposes it as ``task.app_resources``, so any code with a
+handle on the task can read or mutate it.
 
 Two of the convenience aliases exercised below:
 
 - Tool handlers read it from ``FunctionCallParams.app_resources``.
 - Custom ``FrameProcessor`` subclasses read it from
-  ``self.pipeline_worker.app_resources``.
+  ``self.pipeline_task.app_resources``.
 
 This example uses two small loggers as stand-ins for that "shared thing":
 ``ToolCallLogger`` (written from tool handlers) and
 ``TranscriptionLogger`` (written from a custom ``FrameProcessor`` that
 sits in the pipeline). A real app might just as easily pass a Postgres
 pool, a Redis client, a Stripe SDK instance, or any combination thereof.
-The mechanics shown here — construct once, hand to the worker, read it
+The mechanics shown here — construct once, hand to the task, read it
 from each site, inspect it after the session — are the same regardless
 of what you put in.
 
@@ -50,7 +50,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import Frame, LLMRunFrame, TranscriptionFrame, TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -131,7 +131,7 @@ class AppResources:
     get autocomplete and refactor safety:
 
     - In tools: ``cast(AppResources, params.app_resources)``.
-    - In custom processors: ``cast(AppResources, self.pipeline_worker.app_resources)``.
+    - In custom processors: ``cast(AppResources, self.pipeline_task.app_resources)``.
     """
 
     tool_call_logger: ToolCallLogger
@@ -155,8 +155,8 @@ class TranscriptionLoggingProcessor(FrameProcessor):
 
     Demonstrates the second read site for ``app_resources``: any custom
     ``FrameProcessor`` can reach the same bag every tool handler sees by
-    going through ``self.pipeline_worker.app_resources``. ``pipeline_worker``
-    is ``None`` until the worker sets the processor up, so we guard against
+    going through ``self.pipeline_task.app_resources``. ``pipeline_task``
+    is ``None`` until the task sets the processor up, so we guard against
     that case.
     """
 
@@ -164,8 +164,8 @@ class TranscriptionLoggingProcessor(FrameProcessor):
         """Forward all frames; log final user transcriptions on the way through."""
         await super().process_frame(frame, direction)
 
-        if isinstance(frame, TranscriptionFrame) and self.pipeline_worker is not None:
-            resources = cast(AppResources, self.pipeline_worker.app_resources)
+        if isinstance(frame, TranscriptionFrame) and self.pipeline_task is not None:
+            resources = cast(AppResources, self.pipeline_task.app_resources)
             resources.transcription_logger.log_transcription(frame.text)
 
         await self.push_frame(frame, direction)
@@ -282,7 +282,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         transcription_logger=transcription_logger,
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -299,16 +299,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         context.add_message(
             {"role": "developer", "content": "Please introduce yourself to the user."}
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
     # The session has ended; read whatever state the handlers built up.
     logger.info(f"Tool calls logged during session:\n{tool_call_logger.dump()}")

examples/features/features-before-and-after-events.py

@@ -14,7 +14,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import DataFrame, LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -97,7 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -124,18 +124,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
             {"role": "developer", "content": "Please introduce yourself to the user."}
         )
         # Custom frames are pushed in order so they can be used for synchronization purposes.
-        await worker.queue_frames(
-            [CustomBeforeProcessFrame(), LLMRunFrame(), CustomAfterPushFrame()]
-        )
+        await task.queue_frames([CustomBeforeProcessFrame(), LLMRunFrame(), CustomAfterPushFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/features/features-concurrent-llm-evaluation.py

@@ -15,7 +15,7 @@ from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.parallel_pipeline import ParallelPipeline
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -130,7 +130,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -149,16 +149,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         groq_context.add_message(
             {"role": "developer", "content": "Please introduce yourself to the user."}
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/features/features-concurrent-llm-rtvi-ignored-sources.py

@@ -21,7 +21,7 @@ from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.parallel_pipeline import ParallelPipeline
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -141,7 +141,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -160,16 +160,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         evaluator_context.add_message(
             {"role": "developer", "content": "Ready to evaluate user messages."}
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info("Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/features/features-custom-frame-processor.py

@@ -17,7 +17,7 @@ from pipecat.frames.frames import (
 )
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -128,7 +128,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -144,16 +144,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         context.add_message(
             {"role": "developer", "content": "Please introduce yourself to the user."}
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/features/features-gpu-container-local-bot.py

@@ -14,7 +14,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -95,7 +95,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -112,7 +112,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         context.add_message(
             {"role": "developer", "content": "Please introduce yourself to the user."}
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     # Handle "latency-ping" messages. The client will send app messages that look like
     # this:
@@ -128,13 +128,13 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
                 logger.debug(f"Received latency ping app message: {message}")
                 ts = message["latency-ping"]["ts"]
                 # Send immediately
-                await worker.queue_frame(
+                await task.queue_frame(
                     DailyOutputTransportMessageUrgentFrame(
                         message={"latency-pong-msg-handler": {"ts": ts}}, participant_id=sender
                     )
                 )
                 # And push to the pipeline for the Daily transport.output to send
-                await worker.queue_frame(
+                await task.queue_frame(
                     DailyOutputTransportMessageFrame(
                         message={"latency-pong-pipeline-delivery": {"ts": ts}},
                         participant_id=sender,
@@ -146,11 +146,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/features/features-live-translation.py

@@ -14,7 +14,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -99,7 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -111,7 +111,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     @transport.event_handler("on_client_connected")
     async def on_client_connected(transport, client):
         logger.info(f"Client connected")
-        await worker.queue_frames(
+        await task.queue_frames(
             [
                 TTSSpeakFrame(
                     text="Hello, welcome to live translation. Everything you say will be automatically translated to Spanish. Let's begin!",
@@ -123,11 +123,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/features/features-pattern-pair-voice-switching.py

@@ -48,7 +48,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -216,7 +216,7 @@ Remember: Use narrator voice for EVERYTHING except the actual quoted dialogue.""
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -229,15 +229,15 @@ Remember: Use narrator voice for EVERYTHING except the actual quoted dialogue.""
     async def on_client_connected(transport, client):
         logger.info(f"Client connected")
         # Start conversation - empty prompt to let LLM follow system instructions
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/features/features-service-switcher.py

@@ -18,7 +18,7 @@ from pipecat.pipeline.llm_switcher import LLMSwitcher
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.service_switcher import ServiceSwitcher
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -151,7 +151,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -167,25 +167,25 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         context.add_message(
             {"role": "developer", "content": "Please introduce yourself to the user."}
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
         await asyncio.sleep(15)
         print(f"Switching to {stt_deepgram}")
-        await worker.queue_frames([ManuallySwitchServiceFrame(service=stt_deepgram)])
+        await task.queue_frames([ManuallySwitchServiceFrame(service=stt_deepgram)])
         await asyncio.sleep(15)
         print(f"Switching to {llm_google}")
-        await worker.queue_frames([ManuallySwitchServiceFrame(service=llm_google)])
+        await task.queue_frames([ManuallySwitchServiceFrame(service=llm_google)])
         await asyncio.sleep(15)
         print(f"Switching to {tts_deepgram}")
-        await worker.queue_frames([ManuallySwitchServiceFrame(service=tts_deepgram)])
+        await task.queue_frames([ManuallySwitchServiceFrame(service=tts_deepgram)])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/features/features-switch-languages.py

@@ -17,7 +17,7 @@ from pipecat.frames.frames import Frame, LLMRunFrame
 from pipecat.pipeline.parallel_pipeline import ParallelPipeline
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -147,7 +147,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -166,16 +166,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
                 "content": f"Please introduce yourself to the user and let them know the languages you speak. Your initial responses should be in {tts.current_language}.",
             }
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/features/features-switch-voices.py

@@ -17,7 +17,7 @@ from pipecat.frames.frames import Frame, LLMRunFrame
 from pipecat.pipeline.parallel_pipeline import ParallelPipeline
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -157,7 +157,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -176,16 +176,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
                 "content": f"Please introduce yourself to the user and let them know the voices you can do. Your initial responses should be as if you were a {tts.current_voice}.",
             }
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/features/features-user-email-gathering.py

@@ -16,7 +16,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -125,7 +125,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -138,15 +138,15 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     async def on_client_connected(transport, client):
         logger.info(f"Client connected")
         # Start conversation - empty prompt to let LLM follow system instructions
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/features/features-voicemail-detection.py

@@ -14,7 +14,7 @@ from pipecat.extensions.voicemail.voicemail_detector import VoicemailDetector
 from pipecat.frames.frames import TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -91,7 +91,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -107,7 +107,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     @voicemail.event_handler("on_conversation_detected")
     async def on_conversation_detected(processor):
@@ -130,7 +130,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/features/features-wake-phrase.py

@@ -13,7 +13,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -107,7 +107,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -123,16 +123,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         context.add_message(
             {"role": "developer", "content": "Please introduce yourself to the user."}
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-anthropic-async-stream.py

@@ -38,7 +38,7 @@ from pipecat.frames.frames import (
 )
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -171,7 +171,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -186,16 +186,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         context.add_message(
             {"role": "developer", "content": "Please introduce yourself to the user."}
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-anthropic-async.py

@@ -16,7 +16,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -140,7 +140,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -156,16 +156,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         context.add_message(
             {"role": "developer", "content": "Please introduce yourself to the user."}
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-anthropic-video.py

@@ -15,7 +15,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame, UserImageRequestFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -143,7 +143,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -168,16 +168,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
                 "content": f"Please introduce yourself to the user. Use '{client_id}' as the user ID during function calls.",
             }
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-anthropic.py

@@ -16,7 +16,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -125,7 +125,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -141,16 +141,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         context.add_message(
             {"role": "developer", "content": "Please introduce yourself to the user."}
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-aws-video.py

@@ -15,7 +15,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame, UserImageRequestFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -148,7 +148,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -173,16 +173,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
                 "content": f"Please introduce yourself to the user briefly; don't mention the camera. Use '{client_id}' as the user ID during function calls.",
             }
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-aws.py

@@ -14,7 +14,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -134,7 +134,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -150,16 +150,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         context.add_message(
             {"role": "developer", "content": "Please introduce yourself to the user."}
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-azure.py

@@ -16,7 +16,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -120,7 +120,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -133,16 +133,19 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     async def on_client_connected(transport, client):
         logger.info(f"Client connected")
         # Kick off the conversation.
-        await worker.queue_frames([LLMRunFrame()])
+        context.add_message(
+            {"role": "developer", "content": "Please introduce yourself to the user."}
+        )
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-cerebras.py

@@ -16,7 +16,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -129,7 +129,7 @@ Start by asking me for my location. Then, use 'get_weather_current' to give me a
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -142,16 +142,19 @@ Start by asking me for my location. Then, use 'get_weather_current' to give me a
     async def on_client_connected(transport, client):
         logger.info(f"Client connected")
         # Kick off the conversation.
-        await worker.queue_frames([LLMRunFrame()])
+        context.add_message(
+            {"role": "developer", "content": "Please introduce yourself to the user."}
+        )
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-deepseek.py

@@ -16,7 +16,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -130,7 +130,7 @@ Start by asking me for my location. Then, use 'get_weather_current' to give me a
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -143,16 +143,19 @@ Start by asking me for my location. Then, use 'get_weather_current' to give me a
     async def on_client_connected(transport, client):
         logger.info(f"Client connected")
         # Kick off the conversation.
-        await worker.queue_frames([LLMRunFrame()])
+        context.add_message(
+            {"role": "developer", "content": "Please introduce yourself to the user."}
+        )
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-direct.py

@@ -15,7 +15,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -121,7 +121,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -134,16 +134,19 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     async def on_client_connected(transport, client):
         logger.info(f"Client connected")
         # Kick off the conversation.
-        await worker.queue_frames([LLMRunFrame()])
+        context.add_message(
+            {"role": "developer", "content": "Please introduce yourself to the user."}
+        )
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-fireworks.py

@@ -16,7 +16,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -123,7 +123,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -139,16 +139,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         context.add_message(
             {"role": "developer", "content": "Please introduce yourself to the user."}
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-google-async-stream.py

@@ -38,7 +38,7 @@ from pipecat.frames.frames import (
 )
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -175,7 +175,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -190,16 +190,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         context.add_message(
             {"role": "developer", "content": "Please introduce yourself to the user."}
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-google-async.py

@@ -16,7 +16,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame, UserImageRequestFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -208,7 +208,7 @@ indicate you should use the get_image tool are:
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -232,16 +232,16 @@ indicate you should use the get_image tool are:
                 "content": f"Please introduce yourself to the user. Use '{client_id}' as the user ID during function calls.",
             }
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-google-vertex.py

@@ -16,7 +16,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -121,7 +121,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -140,16 +140,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
                 "content": "Please introduce yourself to the user.",
             }
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-google-video.py

@@ -15,7 +15,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame, UserImageRequestFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -143,7 +143,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -168,16 +168,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
                 "content": f"Please introduce yourself to the user. Use '{client_id}' as the user ID during function calls.",
             }
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-google.py

@@ -16,7 +16,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame, UserImageRequestFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -200,7 +200,7 @@ indicate you should use the get_image tool are:
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -224,16 +224,16 @@ indicate you should use the get_image tool are:
                 "content": f"Please introduce yourself to the user. Use '{client_id}' as the user ID during function calls.",
             }
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-grok.py

@@ -17,7 +17,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -117,7 +117,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
             ]
         )
 
-        worker = PipelineWorker(
+        task = PipelineTask(
             pipeline,
             params=PipelineParams(
                 enable_metrics=True,
@@ -133,16 +133,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
             context.add_message(
                 {"role": "developer", "content": "Please introduce yourself to the user."}
             )
-            await worker.queue_frames([LLMRunFrame()])
+            await task.queue_frames([LLMRunFrame()])
 
         @transport.event_handler("on_client_disconnected")
         async def on_client_disconnected(transport, client):
             logger.info(f"Client disconnected")
-            await worker.cancel()
+            await task.cancel()
 
         runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-        await runner.run(worker)
+        await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-groq.py

@@ -16,7 +16,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -118,7 +118,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -131,16 +131,19 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     async def on_client_connected(transport, client):
         logger.info(f"Client connected")
         # Kick off the conversation.
-        await worker.queue_frames([LLMRunFrame()])
+        context.add_message(
+            {"role": "developer", "content": "Please introduce yourself to the user."}
+        )
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-inception.py

@@ -1,177 +0,0 @@
-#
-# Copyright (c) 2024-2026, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-
-import os
-
-from dotenv import load_dotenv
-from loguru import logger
-
-from pipecat.adapters.schemas.function_schema import FunctionSchema
-from pipecat.adapters.schemas.tools_schema import ToolsSchema
-from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame
-from pipecat.pipeline.pipeline import Pipeline
-from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
-from pipecat.processors.aggregators.llm_response_universal import (
-    LLMContextAggregatorPair,
-    LLMUserAggregatorParams,
-)
-from pipecat.runner.types import RunnerArguments
-from pipecat.runner.utils import create_transport
-from pipecat.services.cartesia.tts import CartesiaTTSService
-from pipecat.services.deepgram.stt import DeepgramSTTService
-from pipecat.services.inception.llm import InceptionLLMService
-from pipecat.services.llm_service import FunctionCallParams
-from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
-
-load_dotenv(override=True)
-
-
-async def fetch_weather_from_api(params: FunctionCallParams):
-    await params.result_callback({"conditions": "nice", "temperature": "75"})
-
-
-async def fetch_restaurant_recommendation(params: FunctionCallParams):
-    await params.result_callback({"name": "The Golden Dragon"})
-
-
-# We use lambdas to defer transport parameter creation until the transport
-# type is selected at runtime.
-transport_params = {
-    "daily": lambda: DailyParams(
-        audio_in_enabled=True,
-        audio_out_enabled=True,
-    ),
-    "twilio": lambda: FastAPIWebsocketParams(
-        audio_in_enabled=True,
-        audio_out_enabled=True,
-    ),
-    "webrtc": lambda: TransportParams(
-        audio_in_enabled=True,
-        audio_out_enabled=True,
-    ),
-}
-
-
-async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
-    logger.info(f"Starting bot")
-
-    stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
-
-    tts = CartesiaTTSService(
-        api_key=os.environ["CARTESIA_API_KEY"],
-        settings=CartesiaTTSService.Settings(
-            voice="71a7ad14-091c-4e8e-a314-022ece01c121",  # British Reading Lady
-        ),
-    )
-
-    llm = InceptionLLMService(
-        api_key=os.environ["INCEPTION_API_KEY"],
-        settings=InceptionLLMService.Settings(
-            reasoning_effort="instant",
-            system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
-        ),
-    )
-    # You can also register a function_name of None to get all functions
-    # sent to the same callback with an additional function_name parameter.
-    llm.register_function("get_current_weather", fetch_weather_from_api)
-    llm.register_function("get_restaurant_recommendation", fetch_restaurant_recommendation)
-
-    @llm.event_handler("on_function_calls_started")
-    async def on_function_calls_started(service, function_calls):
-        await tts.queue_frame(TTSSpeakFrame("Let me check on that."))
-
-    weather_function = FunctionSchema(
-        name="get_current_weather",
-        description="Get the current weather",
-        properties={
-            "location": {
-                "type": "string",
-                "description": "The city and state, e.g. San Francisco, CA",
-            },
-            "format": {
-                "type": "string",
-                "enum": ["celsius", "fahrenheit"],
-                "description": "The temperature unit to use. Infer this from the user's location.",
-            },
-        },
-        required=["location", "format"],
-    )
-
-    restaurant_function = FunctionSchema(
-        name="get_restaurant_recommendation",
-        description="Get a restaurant recommendation",
-        properties={
-            "location": {
-                "type": "string",
-                "description": "The city and state, e.g. San Francisco, CA",
-            },
-        },
-        required=["location"],
-    )
-    tools = ToolsSchema(standard_tools=[weather_function, restaurant_function])
-
-    context = LLMContext(tools=tools)
-    user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
-        context,
-        user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
-    )
-
-    pipeline = Pipeline(
-        [
-            transport.input(),
-            stt,
-            user_aggregator,
-            llm,
-            tts,
-            transport.output(),
-            assistant_aggregator,
-        ]
-    )
-
-    task = PipelineTask(
-        pipeline,
-        params=PipelineParams(
-            enable_metrics=True,
-            enable_usage_metrics=True,
-        ),
-        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
-    )
-
-    @transport.event_handler("on_client_connected")
-    async def on_client_connected(transport, client):
-        logger.info(f"Client connected")
-        # Kick off the conversation.
-        context.add_message(
-            {"role": "developer", "content": "Please introduce yourself to the user."}
-        )
-        await task.queue_frames([LLMRunFrame()])
-
-    @transport.event_handler("on_client_disconnected")
-    async def on_client_disconnected(transport, client):
-        logger.info(f"Client disconnected")
-        await task.cancel()
-
-    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
-
-    await runner.run(task)
-
-
-async def bot(runner_args: RunnerArguments):
-    """Main bot entry point compatible with Pipecat Cloud."""
-    transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport, runner_args)
-
-
-if __name__ == "__main__":
-    from pipecat.runner.run import main
-
-    main()

examples/function-calling/function-calling-missing-handler.py

@@ -48,7 +48,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -141,7 +141,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(enable_metrics=True, enable_usage_metrics=True),
         idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
@@ -164,15 +164,15 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
                 ),
             }
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info("Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-mistral.py

@@ -15,7 +15,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -131,7 +131,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -144,16 +144,19 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     async def on_client_connected(transport, client):
         logger.info(f"Client connected")
         # Kick off the conversation.
-        await worker.queue_frames([LLMRunFrame()])
+        context.add_message(
+            {"role": "developer", "content": "Please introduce yourself to the user."}
+        )
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-moondream-video.py

@@ -24,7 +24,7 @@ from pipecat.frames.frames import (
 from pipecat.pipeline.parallel_pipeline import ParallelPipeline
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineWorker
+from pipecat.pipeline.task import PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -185,7 +185,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
@@ -206,16 +206,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
                 "content": f"Please introduce yourself to the user. Use '{client_id}' as the user ID during function calls.",
             }
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-nebius.py

@@ -15,7 +15,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -135,7 +135,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -151,16 +151,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         context.add_message(
             {"role": "developer", "content": "Please introduce yourself to the user."}
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-novita.py

@@ -15,7 +15,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -136,7 +136,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -149,16 +149,19 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     async def on_client_connected(transport, client):
         logger.info(f"Client connected")
         # Kick off the conversation.
-        await worker.queue_frames([LLMRunFrame()])
+        context.add_message(
+            {"role": "developer", "content": "Please introduce yourself to the user."}
+        )
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-nvidia.py

@@ -16,7 +16,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -122,7 +122,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -135,16 +135,19 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     async def on_client_connected(transport, client):
         logger.info(f"Client connected")
         # Kick off the conversation.
-        await worker.queue_frames([LLMRunFrame()])
+        context.add_message(
+            {"role": "developer", "content": "Please introduce yourself to the user."}
+        )
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-ollama.py

@@ -16,7 +16,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -136,7 +136,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -149,16 +149,19 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     async def on_client_connected(transport, client):
         logger.info(f"Client connected")
         # Kick off the conversation.
-        await worker.queue_frames([LLMRunFrame()])
+        context.add_message(
+            {"role": "developer", "content": "Please introduce yourself to the user."}
+        )
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-openai-async-stream.py

@@ -38,7 +38,7 @@ from pipecat.frames.frames import (
 )
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -175,7 +175,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -190,16 +190,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         context.add_message(
             {"role": "developer", "content": "Please introduce yourself to the user."}
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-openai-async.py

@@ -19,7 +19,7 @@ from pipecat.frames.frames import (
 )
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -153,7 +153,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -168,16 +168,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         context.add_message(
             {"role": "developer", "content": "Please introduce yourself to the user."}
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-openai-responses-async-stream.py

@@ -38,7 +38,7 @@ from pipecat.frames.frames import (
 )
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -175,7 +175,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -187,16 +187,19 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     async def on_client_connected(transport, client):
         logger.info(f"Client connected")
         # Kick off the conversation.
-        await worker.queue_frames([LLMRunFrame()])
+        context.add_message(
+            {"role": "developer", "content": "Please introduce yourself to the user."}
+        )
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-openai-responses-async.py

@@ -16,7 +16,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -157,7 +157,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -173,16 +173,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         context.add_message(
             {"role": "developer", "content": "Please introduce yourself to the user."}
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-openai-responses-http.py

@@ -15,7 +15,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -135,7 +135,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -151,16 +151,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         context.add_message(
             {"role": "developer", "content": "Please introduce yourself to the user."}
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-openai-responses-video-http.py

@@ -16,7 +16,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame, UserImageRequestFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -143,7 +143,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -167,12 +167,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
                 "content": f"Please introduce yourself to the user. Use '{client_id}' as the user ID during function calls.",
             }
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     @tts.event_handler("on_tts_request")
     async def on_tts_request(tts, context_id: str, text: str):
@@ -180,7 +180,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-openai-responses-video.py

@@ -16,7 +16,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame, UserImageRequestFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -143,7 +143,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -167,12 +167,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
                 "content": f"Please introduce yourself to the user. Use '{client_id}' as the user ID during function calls.",
             }
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     @tts.event_handler("on_tts_request")
     async def on_tts_request(tts, context_id: str, text: str):
@@ -180,7 +180,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-openai-responses.py

@@ -15,7 +15,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -143,7 +143,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -159,16 +159,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         context.add_message(
             {"role": "developer", "content": "Please introduce yourself to the user."}
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-openai-video.py

@@ -16,7 +16,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame, UserImageRequestFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -143,7 +143,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -167,12 +167,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
                 "content": f"Please introduce yourself to the user. Use '{client_id}' as the user ID during function calls.",
             }
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     @tts.event_handler("on_tts_request")
     async def on_tts_request(tts, context_id: str, text: str):
@@ -180,7 +180,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-openai.py

@@ -15,7 +15,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -136,7 +136,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -148,16 +148,19 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     async def on_client_connected(transport, client):
         logger.info(f"Client connected")
         # Kick off the conversation.
-        await worker.queue_frames([LLMRunFrame()])
+        context.add_message(
+            {"role": "developer", "content": "Please introduce yourself to the user."}
+        )
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-openrouter.py

@@ -16,7 +16,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -76,7 +76,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     llm = OpenRouterLLMService(
         api_key=os.environ["OPENROUTER_API_KEY"],
         settings=OpenRouterLLMService.Settings(
-            model="openai/gpt-4o-2024-11-20",
             system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
         ),
     )
@@ -123,7 +122,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -136,16 +135,19 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     async def on_client_connected(transport, client):
         logger.info(f"Client connected")
         # Kick off the conversation.
-        await worker.queue_frames([LLMRunFrame()])
+        context.add_message(
+            {"role": "developer", "content": "Please introduce yourself to the user."}
+        )
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-perplexity.py

@@ -20,7 +20,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -92,7 +92,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -108,16 +108,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         context.add_message(
             {"role": "developer", "content": "Please introduce yourself to the user."}
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-qwen.py

@@ -16,7 +16,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -121,7 +121,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -134,16 +134,19 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     async def on_client_connected(transport, client):
         logger.info(f"Client connected")
         # Kick off the conversation.
-        await worker.queue_frames([LLMRunFrame()])
+        context.add_message(
+            {"role": "developer", "content": "Please introduce yourself to the user."}
+        )
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-sambanova.py

@@ -16,7 +16,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -120,7 +120,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -133,16 +133,19 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     async def on_client_connected(transport, client):
         logger.info(f"Client connected")
         # Kick off the conversation.
-        await worker.queue_frames([LLMRunFrame()])
+        context.add_message(
+            {"role": "developer", "content": "Please introduce yourself to the user."}
+        )
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-sarvam.py

@@ -15,7 +15,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -140,7 +140,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -156,16 +156,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         context.add_message(
             {"role": "developer", "content": "Please introduce yourself to the user."}
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/function-calling/function-calling-together.py

@@ -16,7 +16,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -118,7 +118,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -134,16 +134,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         context.add_message(
             {"role": "developer", "content": "Please introduce yourself to the user."}
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/getting-started/01-say-one-thing.py

@@ -12,7 +12,7 @@ from loguru import logger
 from pipecat.frames.frames import EndFrame, TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineWorker
+from pipecat.pipeline.task import PipelineTask
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.cartesia.tts import CartesiaTTSService
@@ -42,7 +42,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ),
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         Pipeline([tts, transport.output()]),
         idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
@@ -50,11 +50,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     # Register an event handler so we can play the audio when the client joins
     @transport.event_handler("on_client_connected")
     async def on_client_connected(transport, client):
-        await worker.queue_frames([TTSSpeakFrame(f"Hello there!"), EndFrame()])
+        await task.queue_frames([TTSSpeakFrame(f"Hello there!"), EndFrame()])
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/getting-started/01a-local-audio.py

@@ -14,7 +14,7 @@ from loguru import logger
 from pipecat.frames.frames import EndFrame, TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineWorker
+from pipecat.pipeline.task import PipelineTask
 from pipecat.services.cartesia.tts import CartesiaTTSService
 from pipecat.transports.local.audio import LocalAudioTransport, LocalAudioTransportParams
 
@@ -36,15 +36,15 @@ async def main():
 
     pipeline = Pipeline([tts, transport.output()])
 
-    worker = PipelineWorker(pipeline)
+    task = PipelineTask(pipeline)
 
     async def say_something():
         await asyncio.sleep(1)
-        await worker.queue_frames([TTSSpeakFrame("Hello there, how is it going!"), EndFrame()])
+        await task.queue_frames([TTSSpeakFrame("Hello there, how is it going!"), EndFrame()])
 
     runner = PipelineRunner(handle_sigint=False if sys.platform == "win32" else True)
 
-    await asyncio.gather(runner.run(worker), say_something())
+    await asyncio.gather(runner.run(task), say_something())
 
 
 if __name__ == "__main__":

examples/getting-started/02-llm-say-one-thing.py

@@ -12,7 +12,7 @@ from loguru import logger
 from pipecat.frames.frames import EndFrame, LLMContextFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineWorker
+from pipecat.pipeline.task import PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
@@ -51,7 +51,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ),
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         Pipeline([llm, tts, transport.output()]),
         idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
@@ -61,11 +61,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     async def on_client_connected(transport, client):
         context = LLMContext()
         context.add_message({"role": "developer", "content": "Say hello to the world."})
-        await worker.queue_frames([LLMContextFrame(context), EndFrame()])
+        await task.queue_frames([LLMContextFrame(context), EndFrame()])
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/getting-started/03-still-frame.py

@@ -12,7 +12,7 @@ from loguru import logger
 from pipecat.frames.frames import TextFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.google.image import GoogleImageGenService
@@ -45,7 +45,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         api_key=os.environ["GOOGLE_API_KEY"],
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         Pipeline([imagegen, transport.output()]),
         params=PipelineParams(
             enable_metrics=True,
@@ -57,18 +57,18 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     # Register an event handler so we can play the audio when the client joins
     @transport.event_handler("on_client_connected")
     async def on_client_connected(transport, client):
-        await worker.queue_frame(TextFrame("a cat in the style of picasso"))
-        await worker.queue_frame(TextFrame("a dog in the style of picasso"))
-        await worker.queue_frame(TextFrame("a fish in the style of picasso"))
+        await task.queue_frame(TextFrame("a cat in the style of picasso"))
+        await task.queue_frame(TextFrame("a dog in the style of picasso"))
+        await task.queue_frame(TextFrame("a fish in the style of picasso"))
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/getting-started/03a-local-still-frame.py

@@ -16,7 +16,7 @@ from loguru import logger
 from pipecat.frames.frames import TextFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineWorker
+from pipecat.pipeline.task import PipelineTask
 from pipecat.services.fal.image import FalImageGenService
 from pipecat.transports.local.tk import TkLocalTransport, TkTransportParams
 
@@ -46,18 +46,18 @@ async def main():
 
         pipeline = Pipeline([imagegen, transport.output()])
 
-        worker = PipelineWorker(pipeline)
-        await worker.queue_frames([TextFrame("a cat in the style of picasso")])
+        task = PipelineTask(pipeline)
+        await task.queue_frames([TextFrame("a cat in the style of picasso")])
 
         runner = PipelineRunner()
 
         async def run_tk():
-            while not worker.has_finished():
+            while not task.has_finished():
                 tk_root.update()
                 tk_root.update_idletasks()
                 await asyncio.sleep(0.1)
 
-        await asyncio.gather(runner.run(worker), run_tk())
+        await asyncio.gather(runner.run(task), run_tk())
 
 
 if __name__ == "__main__":

examples/getting-started/04-sync-speech-and-image.py

@@ -22,7 +22,7 @@ from pipecat.frames.frames import (
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.sync_parallel_pipeline import FrameOrder, SyncParallelPipeline
-from pipecat.pipeline.worker import PipelineWorker
+from pipecat.pipeline.task import PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.sentence import SentenceAggregator
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
@@ -186,7 +186,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
             frames.append(MonthFrame(month=month))
             frames.append(LLMContextFrame(LLMContext(messages)))
 
-        worker = PipelineWorker(
+        task = PipelineTask(
             pipeline,
             idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
         )
@@ -196,16 +196,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         async def on_client_connected(transport, client):
             logger.info(f"Client connected")
             # Start the month narration once connected
-            await worker.queue_frames(frames)
+            await task.queue_frames(frames)
 
         @transport.event_handler("on_client_disconnected")
         async def on_client_disconnected(transport, client):
             logger.info(f"Client disconnected")
-            await worker.cancel()
+            await task.cancel()
 
         # Run the pipeline
         runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
-        await runner.run(worker)
+        await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/getting-started/05-speaking-state.py

@@ -20,7 +20,7 @@ from pipecat.frames.frames import (
 )
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -136,7 +136,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -149,15 +149,15 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     async def on_client_connected(transport, client):
         logger.info(f"Client connected")
         # Kick off the conversation.
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):

examples/getting-started/06-voice-agent.py

@@ -13,7 +13,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.worker import PipelineParams, PipelineWorker
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response_universal import (
     LLMContextAggregatorPair,
@@ -85,7 +85,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         ]
     )
 
-    worker = PipelineWorker(
+    task = PipelineTask(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -101,16 +101,16 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         context.add_message(
             {"role": "developer", "content": "Please introduce yourself to the user."}
         )
-        await worker.queue_frames([LLMRunFrame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await worker.cancel()
+        await task.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(worker)
+    await runner.run(task)
 
 
 async def bot(runner_args: RunnerArguments):