Merge pull request #93 from daily-co/frame-name-cleanup

Cleanup the last few badly-named Frame types

examples/foundational/02-llm-say-one-thing.py

@@ -4,7 +4,7 @@
 
 import aiohttp
 
-from dailyai.pipeline.frames import EndFrame, LLMMessagesQueueFrame
+from dailyai.pipeline.frames import EndFrame, LLMMessagesFrame
 from dailyai.pipeline.pipeline import Pipeline
 from dailyai.transports.daily_transport import DailyTransport
 from dailyai.services.elevenlabs_ai_service import ElevenLabsTTSService
@@ -49,7 +49,7 @@ async def main(room_url):
 
         @transport.event_handler("on_first_other_participant_joined")
         async def on_first_other_participant_joined(transport):
-            await pipeline.queue_frames([LLMMessagesQueueFrame(messages), EndFrame()])
+            await pipeline.queue_frames([LLMMessagesFrame(messages), EndFrame()])
 
         await transport.run(pipeline)
 

examples/foundational/04-utterance-and-speech.py

@@ -9,7 +9,7 @@
 from dailyai.transports.daily_transport import DailyTransport
 from dailyai.services.azure_ai_services import AzureLLMService, AzureTTSService
 from dailyai.services.deepgram_ai_services import DeepgramTTSService
-from dailyai.pipeline.frames import EndPipeFrame, LLMMessagesQueueFrame, TextFrame
+from dailyai.pipeline.frames import EndPipeFrame, LLMMessagesFrame, TextFrame
 from dailyai.services.elevenlabs_ai_service import ElevenLabsTTSService
 
 from runner import configure
@@ -60,7 +60,7 @@ async def main(room_url: str):
         # will run in parallel with generating and speaking the audio for static text, so there's no delay to
         # speak the LLM response.
         llm_pipeline = Pipeline([llm, elevenlabs_tts])
-        await llm_pipeline.queue_frames([LLMMessagesQueueFrame(messages), EndPipeFrame()])
+        await llm_pipeline.queue_frames([LLMMessagesFrame(messages), EndPipeFrame()])
 
         simple_tts_pipeline = Pipeline([azure_tts])
         await simple_tts_pipeline.queue_frames(

examples/foundational/05-sync-speech-and-image.py

@@ -17,7 +17,7 @@
     TextFrame,
     EndFrame,
     ImageFrame,
-    LLMMessagesQueueFrame,
+    LLMMessagesFrame,
     LLMResponseStartFrame,
 )
 from dailyai.pipeline.frame_processor import FrameProcessor
@@ -133,7 +133,7 @@ async def main(room_url):
                 }
             ]
             frames.append(MonthFrame(month))
-            frames.append(LLMMessagesQueueFrame(messages))
+            frames.append(LLMMessagesFrame(messages))
 
         frames.append(EndFrame())
         await pipeline.queue_frames(frames)

examples/foundational/06-listen-and-respond.py

@@ -2,7 +2,7 @@
 import aiohttp
 import logging
 import os
-from dailyai.pipeline.frames import LLMMessagesQueueFrame
+from dailyai.pipeline.frames import LLMMessagesFrame
 from dailyai.pipeline.pipeline import Pipeline
 
 from dailyai.transports.daily_transport import DailyTransport
@@ -76,7 +76,7 @@ async def on_first_other_participant_joined(transport):
             # Kick off the conversation.
             messages.append(
                 {"role": "system", "content": "Please introduce yourself to the user."})
-            await pipeline.queue_frames([LLMMessagesQueueFrame(messages)])
+            await pipeline.queue_frames([LLMMessagesFrame(messages)])
 
         transport.transcription_settings["extra"]["endpointing"] = True
         transport.transcription_settings["extra"]["punctuate"] = True

examples/foundational/08-bots-arguing.py

@@ -10,7 +10,7 @@
 from dailyai.services.azure_ai_services import AzureLLMService, AzureTTSService
 from dailyai.services.elevenlabs_ai_service import ElevenLabsTTSService
 from dailyai.services.fal_ai_services import FalImageGenService
-from dailyai.pipeline.frames import AudioFrame, EndFrame, ImageFrame, LLMMessagesQueueFrame, TextFrame
+from dailyai.pipeline.frames import AudioFrame, EndFrame, ImageFrame, LLMMessagesFrame, TextFrame
 
 from runner import configure
 
@@ -80,7 +80,7 @@ async def get_text_and_audio(messages) -> Tuple[str, bytearray]:
                 [llm, sentence_aggregator, tts1], source_queue, sink_queue
             )
 
-            await source_queue.put(LLMMessagesQueueFrame(messages))
+            await source_queue.put(LLMMessagesFrame(messages))
             await source_queue.put(EndFrame())
             await pipeline.run_pipeline()
 

examples/foundational/10-wake-word.py

@@ -18,7 +18,7 @@
     TextFrame,
     ImageFrame,
     SpriteFrame,
-    TranscriptionQueueFrame,
+    TranscriptionFrame,
 )
 from dailyai.services.ai_services import AIService
 
@@ -76,7 +76,7 @@ def __init__(self, bot_participant_id=None):
         self.bot_participant_id = bot_participant_id
 
     async def process_frame(self, frame: Frame) -> AsyncGenerator[Frame, None]:
-        if isinstance(frame, TranscriptionQueueFrame):
+        if isinstance(frame, TranscriptionFrame):
             if frame.participantId != self.bot_participant_id:
                 yield frame
 

examples/foundational/11-sound-effects.py

@@ -16,7 +16,7 @@
     Frame,
     AudioFrame,
     LLMResponseEndFrame,
-    LLMMessagesQueueFrame,
+    LLMMessagesFrame,
 )
 from typing import AsyncGenerator
 
@@ -62,7 +62,7 @@ def __init__(self):
         pass
 
     async def process_frame(self, frame: Frame) -> AsyncGenerator[Frame, None]:
-        if isinstance(frame, LLMMessagesQueueFrame):
+        if isinstance(frame, LLMMessagesFrame):
             yield AudioFrame(sounds["ding2.wav"])
             # In case anything else up the stack needs it
             yield frame

examples/foundational/13a-whisper-local.py

@@ -1,7 +1,7 @@
 import argparse
 import asyncio
 import logging
-from dailyai.pipeline.frames import EndFrame, TranscriptionQueueFrame
+from dailyai.pipeline.frames import EndFrame, TranscriptionFrame
 
 from dailyai.transports.local_transport import LocalTransport
 from dailyai.services.whisper_ai_services import WhisperSTTService
@@ -32,7 +32,7 @@ async def handle_transcription():
         while not transport_done.is_set():
             item = await transcription_output_queue.get()
             print("got item from queue", item)
-            if isinstance(item, TranscriptionQueueFrame):
+            if isinstance(item, TranscriptionFrame):
                 print(item.text)
             elif isinstance(item, EndFrame):
                 break

examples/foundational/websocket-server/sample.py

@@ -3,7 +3,7 @@
 import logging
 import os
 from dailyai.pipeline.frame_processor import FrameProcessor
-from dailyai.pipeline.frames import TextFrame, TranscriptionQueueFrame
+from dailyai.pipeline.frames import TextFrame, TranscriptionFrame
 from dailyai.pipeline.pipeline import Pipeline
 from dailyai.services.elevenlabs_ai_service import ElevenLabsTTSService
 from dailyai.transports.websocket_transport import WebsocketTransport
@@ -16,7 +16,7 @@
 
 class WhisperTranscriber(FrameProcessor):
     async def process_frame(self, frame):
-        if isinstance(frame, TranscriptionQueueFrame):
+        if isinstance(frame, TranscriptionFrame):
             print(f"Transcribed: {frame.text}")
         else:
             yield frame

examples/internal/11a-dial-out.py

@@ -7,7 +7,7 @@
 from dailyai.services.azure_ai_services import AzureLLMService, AzureTTSService
 from dailyai.pipeline.aggregators import LLMContextAggregator
 from dailyai.services.ai_services import AIService, FrameLogger
-from dailyai.pipeline.frames import Frame, AudioFrame, LLMResponseEndFrame, LLMMessagesQueueFrame
+from dailyai.pipeline.frames import Frame, AudioFrame, LLMResponseEndFrame, LLMMessagesFrame
 from typing import AsyncGenerator
 
 from runner import configure
@@ -51,7 +51,7 @@ def __init__(self):
         pass
 
     async def process_frame(self, frame: Frame) -> AsyncGenerator[Frame, None]:
-        if isinstance(frame, LLMMessagesQueueFrame):
+        if isinstance(frame, LLMMessagesFrame):
             yield AudioFrame(sounds["ding2.wav"])
             # In case anything else up the stack needs it
             yield frame

examples/starter-apps/chatbot.py

@@ -14,7 +14,7 @@
     SpriteFrame,
     Frame,
     LLMResponseEndFrame,
-    LLMMessagesQueueFrame,
+    LLMMessagesFrame,
     AudioFrame,
     PipelineStartedFrame,
 )
@@ -129,7 +129,7 @@ async def main(room_url: str, token):
         @transport.event_handler("on_first_other_participant_joined")
         async def on_first_other_participant_joined(transport):
             print(f"!!! in here, pipeline.source is {pipeline.source}")
-            await pipeline.queue_frames([LLMMessagesQueueFrame(messages)])
+            await pipeline.queue_frames([LLMMessagesFrame(messages)])
 
         async def run_conversation():
 

examples/starter-apps/storybot.py

@@ -24,7 +24,7 @@
 )
 from dailyai.pipeline.frames import (
     EndPipeFrame,
-    LLMMessagesQueueFrame,
+    LLMMessagesFrame,
     Frame,
     TextFrame,
     LLMResponseEndFrame,
@@ -172,7 +172,7 @@ async def process_frame(self, frame: Frame) -> AsyncGenerator[Frame, None]:
                 prompt = f"You are an illustrator for a children's story book. Here is the story so far:\n\n\"{' '.join(self._story[:-1])}\"\n\nGenerate a prompt for DALL-E to create an illustration for the next page. Here's the sentence for the next page:\n\n\"{self._story[-1:][0]}\"\n\n Your response should start with the phrase \"Children's book illustration of\"."
             msgs = [{"role": "system", "content": prompt}]
             image_prompt = ""
-            async for f in self._llm.process_frame(LLMMessagesQueueFrame(msgs)):
+            async for f in self._llm.process_frame(LLMMessagesFrame(msgs)):
                 if isinstance(f, TextFrame):
                     image_prompt += f.text
             async for f in self._img.process_frame(TextFrame(image_prompt)):
@@ -253,7 +253,7 @@ async def storytime():
             await local_pipeline.queue_frames(
                 [
                     ImageFrame(None, images["grandma-listening.png"]),
-                    LLMMessagesQueueFrame(intro_messages),
+                    LLMMessagesFrame(intro_messages),
                     AudioFrame(sounds["listening.wav"]),
                     EndPipeFrame(),
                 ]

examples/starter-apps/translator.py

@@ -7,7 +7,7 @@
 from dailyai.pipeline.aggregators import (
     SentenceAggregator,
 )
-from dailyai.pipeline.frames import Frame, LLMMessagesQueueFrame, TextFrame
+from dailyai.pipeline.frames import Frame, LLMMessagesFrame, TextFrame
 from dailyai.pipeline.frame_processor import FrameProcessor
 from dailyai.pipeline.pipeline import Pipeline
 from dailyai.transports.daily_transport import DailyTransport
@@ -44,7 +44,7 @@ async def process_frame(self, frame: Frame) -> AsyncGenerator[Frame, None]:
                 },
                 {"role": "user", "content": frame.text},
             ]
-            yield LLMMessagesQueueFrame(context)
+            yield LLMMessagesFrame(context)
         else:
             yield frame
 

src/dailyai/pipeline/aggregators.py

@@ -7,11 +7,11 @@
     EndFrame,
     EndPipeFrame,
     Frame,
-    LLMMessagesQueueFrame,
+    LLMMessagesFrame,
     LLMResponseEndFrame,
     LLMResponseStartFrame,
     TextFrame,
-    TranscriptionQueueFrame,
+    TranscriptionFrame,
     UserStartedSpeakingFrame,
     UserStoppedSpeakingFrame,
 )
@@ -57,7 +57,7 @@ async def process_frame(self, frame: Frame) -> AsyncGenerator[Frame, None]:
                     {"role": self._role, "content": self.aggregation})
                 self.aggregation = ""
                 yield self._end_frame()
-                yield LLMMessagesQueueFrame(self.messages)
+                yield LLMMessagesFrame(self.messages)
         elif isinstance(frame, self._accumulator_frame) and self.aggregating:
             self.aggregation += f" {frame.text}"
             if self._pass_through:
@@ -84,7 +84,7 @@ def __init__(self, messages: list[dict]):
             role="user",
             start_frame=UserStartedSpeakingFrame,
             end_frame=UserStoppedSpeakingFrame,
-            accumulator_frame=TranscriptionQueueFrame,
+            accumulator_frame=TranscriptionFrame,
             pass_through=False,
         )
 
@@ -114,7 +114,7 @@ async def process_frame(self, frame: Frame) -> AsyncGenerator[Frame, None]:
             return
 
         # Ignore transcription frames from the bot
-        if isinstance(frame, TranscriptionQueueFrame):
+        if isinstance(frame, TranscriptionFrame):
             if frame.participantId == self.bot_participant_id:
                 return
 
@@ -126,19 +126,19 @@ async def process_frame(self, frame: Frame) -> AsyncGenerator[Frame, None]:
 
         # TODO: split up transcription by participant
         if self.complete_sentences:
-            # type: ignore -- the linter thinks this isn't a TextQueueFrame, even
+            # type: ignore -- the linter thinks this isn't a TextFrame, even
             # though we check it above
             self.sentence += frame.text
             if self.sentence.endswith((".", "?", "!")):
                 self.messages.append(
                     {"role": self.role, "content": self.sentence})
                 self.sentence = ""
-                yield LLMMessagesQueueFrame(self.messages)
+                yield LLMMessagesFrame(self.messages)
         else:
-            # type: ignore -- the linter thinks this isn't a TextQueueFrame, even
+            # type: ignore -- the linter thinks this isn't a TextFrame, even
             # though we check it above
             self.messages.append({"role": self.role, "content": frame.text})
-            yield LLMMessagesQueueFrame(self.messages)
+            yield LLMMessagesFrame(self.messages)
 
 
 class LLMUserContextAggregator(LLMContextAggregator):
@@ -334,7 +334,7 @@ async def process_frame(self, frame: Frame) -> AsyncGenerator[Frame, None]:
                 continue
             seen_ids.add(id(frame))
 
-            # Skip passing along EndParallelPipeQueueFrame, because we use them
+            # Skip passing along EndPipeFrame, because we use them
             # for our own flow control.
             if not isinstance(frame, EndPipeFrame):
                 yield frame

src/dailyai/pipeline/frame_processor.py

@@ -12,9 +12,9 @@ class FrameProcessor:
 
     By convention, FrameProcessors should immediately yield any frames they don't process.
 
-    Stateful FrameProcessors should watch for the EndStreamQueueFrame and finalize their
+    Stateful FrameProcessors should watch for the EndFrame and finalize their
     output, eg. yielding an unfinished sentence if they're aggregating LLM output to full
-    sentences. EndStreamQueueFrame is also a chance to clean up any services that need to
+    sentences. EndFrame is also a chance to clean up any services that need to
     be closed, del'd, etc.
     """
 

src/dailyai/pipeline/frames.py

@@ -102,7 +102,7 @@ def __str__(self):
 
 
 @dataclass()
-class TranscriptionQueueFrame(TextFrame):
+class TranscriptionFrame(TextFrame):
     """A text frame with transcription-specific data. Will be placed in the
     transport's receive queue when a participant speaks."""
     participantId: str
@@ -126,7 +126,7 @@ class TTSEndFrame(ControlFrame):
 
 
 @dataclass()
-class LLMMessagesQueueFrame(Frame):
+class LLMMessagesFrame(Frame):
     """A frame containing a list of LLM messages. Used to signal that an LLM
     service should run a chat completion and emit an LLMStartFrames, TextFrames
     and an LLMEndFrame.
@@ -137,7 +137,7 @@ class LLMMessagesQueueFrame(Frame):
 
 @dataclass()
 class OpenAILLMContextFrame(Frame):
-    """Like an LLMMessagesQueueFrame, but with extra context specific to the
+    """Like an LLMMessagesFrame, but with extra context specific to the
     OpenAI API. The context in this message is also mutable, and will be
     changed by the OpenAIContextAggregator frame processor."""
     context: OpenAILLMContext

src/dailyai/pipeline/opeanai_llm_aggregator.py

@@ -6,7 +6,7 @@
     LLMResponseStartFrame,
     OpenAILLMContextFrame,
     TextFrame,
-    TranscriptionQueueFrame,
+    TranscriptionFrame,
     UserStartedSpeakingFrame,
     UserStoppedSpeakingFrame,
 )
@@ -90,7 +90,7 @@ def __init__(self, context: OpenAILLMContext):
             role="user",
             start_frame=UserStartedSpeakingFrame,
             end_frame=UserStoppedSpeakingFrame,
-            accumulator_frame=TranscriptionQueueFrame,
+            accumulator_frame=TranscriptionFrame,
             pass_through=False,
         )
 

src/dailyai/pipeline/pipeline.py

@@ -81,8 +81,8 @@ async def run_pipeline(self):
 
         The source and sink queues must be set before calling this method.
 
-        This method will exit when an EndStreamQueueFrame is placed on the sink queue.
-        No more frames will be placed on the sink queue after an EndStreamQueueFrame, even
+        This method will exit when an EndFrame is placed on the sink queue.
+        No more frames will be placed on the sink queue after an EndFrame, even
         if it's not the last frame yielded by the last frame_processor in the pipeline..
         """