Docstring cleanup, fix missing examples imports

examples/daily-multi-translation/requirements.txt

@@ -2,4 +2,4 @@ aiofiles
 python-dotenv
 fastapi[all]
 uvicorn
-pipecat-ai[daily,deepgram,openai,silero,cartesia]
+pipecat-ai[daily,deepgram,openai,silero,cartesia,soundfile]

examples/open-telemetry/jaeger/requirements.txt

@@ -1,6 +1,6 @@
 fastapi
 uvicorn
 python-dotenv
-pipecat-ai[webrtc,silero,cartesia,deepgram,openai,tracing]
+pipecat-ai[daily,webrtc,silero,cartesia,deepgram,openai,tracing]
 pipecat-ai-small-webrtc-prebuilt
 opentelemetry-exporter-otlp-proto-grpc

examples/open-telemetry/langfuse/requirements.txt

@@ -1,6 +1,6 @@
 fastapi
 uvicorn
 python-dotenv
-pipecat-ai[webrtc,silero,cartesia,deepgram,openai,tracing]
+pipecat-ai[daily,webrtc,silero,cartesia,deepgram,openai,tracing]
 pipecat-ai-small-webrtc-prebuilt
 opentelemetry-exporter-otlp-proto-http

examples/phone-chatbot/daily-twilio-sip-dial-in/requirements.txt

@@ -1,4 +1,4 @@
-pipecat-ai[daily,elevenlabs,openai,silero]
+pipecat-ai[daily,cartesia,openai,silero]
 fastapi==0.115.6
 uvicorn
 python-dotenv

src/pipecat/observers/loggers/debug_log_observer.py

@@ -47,7 +47,7 @@ class DebugLogObserver(BaseObserver):
 
         Log specific frame types from any source/destination::
 
-            from pipecat.frames.frames import TranscriptionFrame, InterimTranscriptionFrame
+            from pipecat.frames.frames import LLMTextFrame, TranscriptionFrame
             observers=[
                 DebugLogObserver(frame_types=(LLMTextFrame,TranscriptionFrame,)),
             ]
@@ -55,7 +55,8 @@ class DebugLogObserver(BaseObserver):
         Log frames with specific source/destination filters::
 
             from pipecat.frames.frames import StartInterruptionFrame, UserStartedSpeakingFrame, LLMTextFrame
-            from pipecat.transports.base_output_transport import BaseOutputTransport
+            from pipecat.observers.loggers.debug_log_observer import DebugLogObserver, FrameEndpoint
+            from pipecat.transports.base_output import BaseOutputTransport
             from pipecat.services.stt_service import STTService
 
             observers=[

src/pipecat/processors/aggregators/gated.py

@@ -26,29 +26,6 @@ class GatedAggregator(FrameProcessor):
     until and not including the gate-closed frame. The aggregator maintains an
     internal gate state that controls whether frames are passed through immediately
     or accumulated for later release.
-
-    Doctest: FIXME to work with asyncio
-    >>> from pipecat.frames.frames import ImageRawFrame
-
-    >>> async def print_frames(aggregator, frame):
-    ...     async for frame in aggregator.process_frame(frame):
-    ...         if isinstance(frame, TextFrame):
-    ...             print(frame.text)
-    ...         else:
-    ...             print(frame.__class__.__name__)
-
-    >>> aggregator = GatedAggregator(
-    ...     gate_close_fn=lambda x: isinstance(x, LLMResponseStartFrame),
-    ...     gate_open_fn=lambda x: isinstance(x, ImageRawFrame),
-    ...     start_open=False)
-    >>> asyncio.run(print_frames(aggregator, TextFrame("Hello")))
-    >>> asyncio.run(print_frames(aggregator, TextFrame("Hello again.")))
-    >>> asyncio.run(print_frames(aggregator, ImageRawFrame(image=bytes([]), size=(0, 0))))
-    ImageRawFrame
-    Hello
-    Hello again.
-    >>> asyncio.run(print_frames(aggregator, TextFrame("Goodbye.")))
-    Goodbye.
     """
 
     def __init__(

src/pipecat/processors/aggregators/sentence.py

@@ -23,20 +23,10 @@ class SentenceAggregator(FrameProcessor):
     Useful for ensuring downstream processors receive coherent, complete sentences
     rather than fragmented text.
 
-    Frame input/output:
+    Frame input/output::
+
         TextFrame("Hello,") -> None
         TextFrame(" world.") -> TextFrame("Hello, world.")
-
-    Doctest: FIXME to work with asyncio
-    >>> import asyncio
-    >>> async def print_frames(aggregator, frame):
-    ...     async for frame in aggregator.process_frame(frame):
-    ...         print(frame.text)
-
-    >>> aggregator = SentenceAggregator()
-    >>> asyncio.run(print_frames(aggregator, TextFrame("Hello,")))
-    >>> asyncio.run(print_frames(aggregator, TextFrame(" world.")))
-    Hello, world.
     """
 
     def __init__(self):

src/pipecat/processors/aggregators/vision_image_frame.py

@@ -20,17 +20,6 @@ class VisionImageFrameAggregator(FrameProcessor):
     This aggregator waits for a consecutive TextFrame and an InputImageRawFrame.
     After the InputImageRawFrame arrives it will output a VisionImageRawFrame
     combining both the text and image data for multimodal processing.
-
-    >>> from pipecat.frames.frames import ImageFrame
-
-    >>> async def print_frames(aggregator, frame):
-    ...     async for frame in aggregator.process_frame(frame):
-    ...         print(frame)
-
-    >>> aggregator = VisionImageFrameAggregator()
-    >>> asyncio.run(print_frames(aggregator, TextFrame("What do you see?")))
-    >>> asyncio.run(print_frames(aggregator, ImageFrame(image=bytes([]), size=(0, 0))))
-    VisionImageFrame, text: What do you see?, image size: 0x0, buffer size: 0 B
     """
 
     def __init__(self):

src/pipecat/processors/text_transformer.py

@@ -18,14 +18,6 @@ class StatelessTextTransformer(FrameProcessor):
     This processor intercepts TextFrame objects and applies a user-provided
     transformation function to the text content. The function can be either
     synchronous or asynchronous (coroutine).
-
-    >>> async def print_frames(aggregator, frame):
-    ...     async for frame in aggregator.process_frame(frame):
-    ...         print(frame.text)
-
-    >>> aggregator = StatelessTextTransformer(lambda x: x.upper())
-    >>> asyncio.run(print_frames(aggregator, TextFrame("Hello")))
-    HELLO
     """
 
     def __init__(

src/pipecat/utils/utils.py

@@ -25,15 +25,6 @@ def obj_id() -> int:
 
     Returns:
         A unique integer identifier that increments globally across all objects.
-
-    Examples::
-
-        >>> obj_id()
-        0
-        >>> obj_id()
-        1
-        >>> obj_id()
-        2
     """
     with _ID_LOCK:
         return next(_ID)
@@ -47,16 +38,6 @@ def obj_count(obj) -> int:
 
     Returns:
         A unique integer count that increments per class type.
-
-    Examples::
-
-        >>> obj_count(object())
-        0
-        >>> obj_count(object())
-        1
-        >>> new_type = type('NewType', (object,), {})
-        >>> obj_count(new_type())
-        0
     """
     with _COUNTS_LOCK:
         return next(_COUNTS[obj.__class__.__name__])