Rename BaseTask → BaseWorker and reserve "task" for asyncio

Replaces every "task" identifier that referred to the BaseTask
abstraction with "worker". Asyncio task plumbing (asyncio.Task,
BaseTaskManager, TaskManager, create_task, cancel_task, etc.) stays
untouched. Highlights:

- Classes: BaseTask → BaseWorker, PipelineTask → PipelineWorker,
  LLMTask → LLMWorker, LLMContextTask → LLMContextWorker, TaskBus →
  WorkerBus, TaskRegistry → WorkerRegistry, TaskActivationArgs →
  WorkerActivationArgs, TaskReadyData → WorkerReadyData,
  TaskRegistryEntry → WorkerRegistryEntry, TaskObserver →
  WorkerObserver, all Bus*TaskMessage → Bus*WorkerMessage,
  BusAddTaskMessage.task field → worker, BusWorkerRegistryMessage.tasks
  field → workers.
- Methods/decorators: activate_task → activate_worker, deactivate_task
  → deactivate_worker, add_task → add_worker, watch_task →
  watch_worker, @task_ready → @worker_ready, setup_pipeline_task hook
  → setup_pipeline_worker.
- Params/fields: FrameProcessorSetup.pipeline_task and
  FunctionCallParams.pipeline_task → pipeline_worker. Parameter names
  like task_name → worker_name; spawn/run accept worker:.
- Files: pipeline/base_task.py → base_worker.py, pipeline/task.py →
  worker.py (plus a re-export shim at pipeline/task.py),
  task_observer.py → worker_observer.py, task_ready_decorator.py →
  worker_ready_decorator.py, pipecat.tasks → pipecat.workers,
  llm_task.py → llm_worker.py, llm_context_task.py →
  llm_context_worker.py, examples/multi-task → examples/multi-worker.

Back-compat:
- PipelineTask kept as a deprecated subclass of PipelineWorker that
  warns on construction.
- pipecat.pipeline.task re-exports PipelineWorker/PipelineTask/etc. so
  existing user imports keep working.
- FrameProcessor.pipeline_task kept as a deprecated property that
  forwards to pipeline_worker.

Local variables in examples that hold a worker (task = PipelineTask(...))
are renamed to worker = PipelineWorker(...). Asyncio-task locals
(runner_task, etc.) are preserved.

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.task import PipelineParams, PipelineTask
+from pipecat.pipeline.worker import PipelineParams, PipelineWorker
 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):
         ]
     )
 
-    task = PipelineTask(
+    worker = PipelineWorker(
         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 task.queue_frame(LLMSetToolsFrame(tools=NOT_GIVEN))
+            await worker.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 task.queue_frame(LLMSetToolsFrame(tools=weather_tools))
+            await worker.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 task.queue_frames([LLMRunFrame()])
+        await worker.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info("Client disconnected")
-        await task.cancel()
+        await worker.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
-    await runner.run(task)
+    await runner.run(worker)
 
 
 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 ``PipelineTask(app_resources=...)``.
+"""Example demonstrating ``PipelineWorker(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 ``task.app_resources``, so any code with a
-handle on the task can read or mutate it.
+untouched and exposes it as ``worker.app_resources``, so any code with a
+handle on the worker 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_task.app_resources``.
+  ``self.pipeline_worker.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 task, read it
+The mechanics shown here — construct once, hand to the worker, 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.task import PipelineParams, PipelineTask
+from pipecat.pipeline.worker import PipelineParams, PipelineWorker
 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_task.app_resources)``.
+    - In custom processors: ``cast(AppResources, self.pipeline_worker.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_task.app_resources``. ``pipeline_task``
-    is ``None`` until the task sets the processor up, so we guard against
+    going through ``self.pipeline_worker.app_resources``. ``pipeline_worker``
+    is ``None`` until the worker 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_task is not None:
-            resources = cast(AppResources, self.pipeline_task.app_resources)
+        if isinstance(frame, TranscriptionFrame) and self.pipeline_worker is not None:
+            resources = cast(AppResources, self.pipeline_worker.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,
     )
 
-    task = PipelineTask(
+    worker = PipelineWorker(
         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 task.queue_frames([LLMRunFrame()])
+        await worker.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await task.cancel()
+        await worker.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(task)
+    await runner.run(worker)
 
     # 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.task import PipelineParams, PipelineTask
+from pipecat.pipeline.worker import PipelineParams, PipelineWorker
 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):
         ]
     )
 
-    task = PipelineTask(
+    worker = PipelineWorker(
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
@@ -124,16 +124,18 @@ 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 task.queue_frames([CustomBeforeProcessFrame(), LLMRunFrame(), CustomAfterPushFrame()])
+        await worker.queue_frames(
+            [CustomBeforeProcessFrame(), LLMRunFrame(), CustomAfterPushFrame()]
+        )
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await task.cancel()
+        await worker.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(task)
+    await runner.run(worker)
 
 
 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.task import PipelineParams, PipelineTask
+from pipecat.pipeline.worker import PipelineParams, PipelineWorker
 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):
         ]
     )
 
-    task = PipelineTask(
+    worker = PipelineWorker(
         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 task.queue_frames([LLMRunFrame()])
+        await worker.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await task.cancel()
+        await worker.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(task)
+    await runner.run(worker)
 
 
 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.task import PipelineParams, PipelineTask
+from pipecat.pipeline.worker import PipelineParams, PipelineWorker
 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):
         ]
     )
 
-    task = PipelineTask(
+    worker = PipelineWorker(
         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 task.queue_frames([LLMRunFrame()])
+        await worker.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info("Client disconnected")
-        await task.cancel()
+        await worker.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(task)
+    await runner.run(worker)
 
 
 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.task import PipelineParams, PipelineTask
+from pipecat.pipeline.worker import PipelineParams, PipelineWorker
 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):
         ]
     )
 
-    task = PipelineTask(
+    worker = PipelineWorker(
         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 task.queue_frames([LLMRunFrame()])
+        await worker.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await task.cancel()
+        await worker.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(task)
+    await runner.run(worker)
 
 
 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.task import PipelineParams, PipelineTask
+from pipecat.pipeline.worker import PipelineParams, PipelineWorker
 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):
         ]
     )
 
-    task = PipelineTask(
+    worker = PipelineWorker(
         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 task.queue_frames([LLMRunFrame()])
+        await worker.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 task.queue_frame(
+                await worker.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 task.queue_frame(
+                await worker.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 task.cancel()
+        await worker.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(task)
+    await runner.run(worker)
 
 
 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.task import PipelineParams, PipelineTask
+from pipecat.pipeline.worker import PipelineParams, PipelineWorker
 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):
         ]
     )
 
-    task = PipelineTask(
+    worker = PipelineWorker(
         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 task.queue_frames(
+        await worker.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 task.cancel()
+        await worker.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(task)
+    await runner.run(worker)
 
 
 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.task import PipelineParams, PipelineTask
+from pipecat.pipeline.worker import PipelineParams, PipelineWorker
 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.""
         ]
     )
 
-    task = PipelineTask(
+    worker = PipelineWorker(
         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 task.queue_frames([LLMRunFrame()])
+        await worker.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await task.cancel()
+        await worker.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
-    await runner.run(task)
+    await runner.run(worker)
 
 
 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.task import PipelineParams, PipelineTask
+from pipecat.pipeline.worker import PipelineParams, PipelineWorker
 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):
         ]
     )
 
-    task = PipelineTask(
+    worker = PipelineWorker(
         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 task.queue_frames([LLMRunFrame()])
+        await worker.queue_frames([LLMRunFrame()])
         await asyncio.sleep(15)
         print(f"Switching to {stt_deepgram}")
-        await task.queue_frames([ManuallySwitchServiceFrame(service=stt_deepgram)])
+        await worker.queue_frames([ManuallySwitchServiceFrame(service=stt_deepgram)])
         await asyncio.sleep(15)
         print(f"Switching to {llm_google}")
-        await task.queue_frames([ManuallySwitchServiceFrame(service=llm_google)])
+        await worker.queue_frames([ManuallySwitchServiceFrame(service=llm_google)])
         await asyncio.sleep(15)
         print(f"Switching to {tts_deepgram}")
-        await task.queue_frames([ManuallySwitchServiceFrame(service=tts_deepgram)])
+        await worker.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 task.cancel()
+        await worker.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(task)
+    await runner.run(worker)
 
 
 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.task import PipelineParams, PipelineTask
+from pipecat.pipeline.worker import PipelineParams, PipelineWorker
 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):
         ]
     )
 
-    task = PipelineTask(
+    worker = PipelineWorker(
         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 task.queue_frames([LLMRunFrame()])
+        await worker.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await task.cancel()
+        await worker.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(task)
+    await runner.run(worker)
 
 
 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.task import PipelineParams, PipelineTask
+from pipecat.pipeline.worker import PipelineParams, PipelineWorker
 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):
         ]
     )
 
-    task = PipelineTask(
+    worker = PipelineWorker(
         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 task.queue_frames([LLMRunFrame()])
+        await worker.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await task.cancel()
+        await worker.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(task)
+    await runner.run(worker)
 
 
 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.task import PipelineParams, PipelineTask
+from pipecat.pipeline.worker import PipelineParams, PipelineWorker
 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):
         ]
     )
 
-    task = PipelineTask(
+    worker = PipelineWorker(
         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 task.queue_frames([LLMRunFrame()])
+        await worker.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await task.cancel()
+        await worker.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
-    await runner.run(task)
+    await runner.run(worker)
 
 
 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.task import PipelineParams, PipelineTask
+from pipecat.pipeline.worker import PipelineParams, PipelineWorker
 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):
         ]
     )
 
-    task = PipelineTask(
+    worker = PipelineWorker(
         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 task.cancel()
+        await worker.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(task)
+    await runner.run(worker)
 
 
 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.task import PipelineParams, PipelineTask
+from pipecat.pipeline.worker import PipelineParams, PipelineWorker
 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):
         ]
     )
 
-    task = PipelineTask(
+    worker = PipelineWorker(
         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 task.queue_frames([LLMRunFrame()])
+        await worker.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
         logger.info(f"Client disconnected")
-        await task.cancel()
+        await worker.cancel()
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 
-    await runner.run(task)
+    await runner.run(worker)
 
 
 async def bot(runner_args: RunnerArguments):