From aec93b7103b3ca102e4d1b2dba9430ea9067e2a1 Mon Sep 17 00:00:00 2001 From: Chad Bailey Date: Thu, 23 May 2024 14:26:42 +0000 Subject: [PATCH 01/20] added function calling code back --- examples/foundational/06a-image-sync.py | 15 +-- examples/foundational/10-wake-word.py | 70 ++++++++++---- examples/foundational/11-sound-effects.py | 18 ++-- src/pipecat/frames/frames.py | 24 ++++- .../processors/aggregators/llm_response.py | 91 ++++++++++++------- src/pipecat/services/openai.py | 26 +++++- 6 files changed, 174 insertions(+), 70 deletions(-) diff --git a/examples/foundational/06a-image-sync.py b/examples/foundational/06a-image-sync.py index 4c9925b20..3ec2752b4 100644 --- a/examples/foundational/06a-image-sync.py +++ b/examples/foundational/06a-image-sync.py @@ -15,14 +15,15 @@ from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineTask -from pipecat.processors.aggregators.llm_context import ( - LLMAssistantContextAggregator, - LLMUserContextAggregator, +from pipecat.processors.aggregators.llm_response import ( + LLMAssistantResponseAggregator, + LLMUserResponseAggregator, ) from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.services.openai import OpenAILLMService from pipecat.services.elevenlabs import ElevenLabsTTSService from pipecat.transports.services.daily import DailyTransport +from pipecat.vad.silero import SileroVADAnalyzer from pipecat.transports.services.daily import DailyParams from runner import configure @@ -66,7 +67,9 @@ async def main(room_url: str, token): audio_out_enabled=True, camera_out_width=1024, camera_out_height=1024, - transcription_enabled=True + transcription_enabled=True, + vad_enabled=True, + vad_analyzer=SileroVADAnalyzer() ) ) @@ -87,8 +90,8 @@ async def main(room_url: str, token): }, ] - tma_in = LLMUserContextAggregator(messages) - tma_out = LLMAssistantContextAggregator(messages) + tma_in = LLMUserResponseAggregator(messages) + tma_out = LLMAssistantResponseAggregator(messages) image_sync_aggregator = ImageSyncAggregator( os.path.join(os.path.dirname(__file__), "assets", "speaking.png"), diff --git a/examples/foundational/10-wake-word.py b/examples/foundational/10-wake-word.py index 4d0c0a16d..310b13d75 100644 --- a/examples/foundational/10-wake-word.py +++ b/examples/foundational/10-wake-word.py @@ -12,19 +12,26 @@ from PIL import Image -from pipecat.frames.frames import Frame, ImageRawFrame, SpriteFrame +from pipecat.frames.frames import ( + Frame, + SystemFrame, + TextFrame, + ImageRawFrame, + SpriteFrame, + TranscriptionFrame, +) from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineTask -from pipecat.processors.aggregators.llm_context import ( - LLMUserContextAggregator, - LLMAssistantContextAggregator, +from pipecat.processors.aggregators.llm_response import ( + LLMUserResponseAggregator, + LLMAssistantResponseAggregator, ) -from pipecat.processors.filters.wake_check_filter import WakeCheckFilter from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.services.openai import OpenAILLMService from pipecat.services.elevenlabs import ElevenLabsTTSService from pipecat.transports.services.daily import DailyParams, DailyTransport +from pipecat.vad.silero import SileroVADAnalyzer from runner import configure @@ -78,6 +85,33 @@ thinking_frame = SpriteFrame(thinking_list) +class NameCheckFilter(FrameProcessor): + def __init__(self, names: list[str]): + super().__init__() + self._names = names + self._sentence = "" + + async def process_frame(self, frame: Frame, direction: FrameDirection): + if isinstance(frame, SystemFrame): + await self.push_frame(frame, direction) + return + + content: str = "" + + # TODO: split up transcription by participant + if isinstance(frame, TranscriptionFrame): + content = frame.text + self._sentence += content + if self._sentence.endswith((".", "?", "!")): + if any(name in self._sentence for name in self._names): + await self.push_frame(TextFrame(self._sentence)) + self._sentence = "" + else: + self._sentence = "" + else: + await self.push_frame(frame, direction) + + class ImageSyncAggregator(FrameProcessor): async def process_frame(self, frame: Frame, direction: FrameDirection): @@ -98,7 +132,9 @@ async def main(room_url: str, token): camera_out_width=720, camera_out_height=1280, camera_out_framerate=10, - transcription_enabled=True + transcription_enabled=True, + vad_enabled=True, + vad_analyzer=SileroVADAnalyzer() ) ) @@ -120,19 +156,19 @@ async def main(room_url: str, token): }, ] - tma_in = LLMUserContextAggregator(messages) - tma_out = LLMAssistantContextAggregator(messages) - wcf = WakeCheckFilter(["Santa Cat", "Santa"]) + tma_in = LLMUserResponseAggregator(messages) + tma_out = LLMAssistantResponseAggregator(messages) + ncf = NameCheckFilter(["Santa Cat", "Santa"]) pipeline = Pipeline([ - transport.input(), # Transport user input - isa, # Cat talking/quiet images - wcf, # Filter out speech not directed at Santa Cat - tma_in, # User responses - llm, # LLM - tts, # TTS - transport.output(), # Transport bot output - tma_out # Santa Cat spoken responses + transport.input(), + isa, + ncf, + tma_in, + llm, + tts, + transport.output(), + tma_out ]) @transport.event_handler("on_first_participant_joined") diff --git a/examples/foundational/11-sound-effects.py b/examples/foundational/11-sound-effects.py index c8d113c30..1ca568bf0 100644 --- a/examples/foundational/11-sound-effects.py +++ b/examples/foundational/11-sound-effects.py @@ -19,15 +19,16 @@ from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineTask -from pipecat.processors.aggregators.llm_context import ( - LLMUserContextAggregator, - LLMAssistantContextAggregator, +from pipecat.processors.aggregators.llm_response import ( + LLMUserResponseAggregator, + LLMAssistantResponseAggregator, ) from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.processors.logger import FrameLogger from pipecat.services.elevenlabs import ElevenLabsTTSService from pipecat.services.openai import OpenAILLMService from pipecat.transports.services.daily import DailyParams, DailyTransport +from pipecat.vad.silero import SileroVADAnalyzer from runner import configure @@ -84,7 +85,12 @@ async def main(room_url: str, token): room_url, token, "Respond bot", - DailyParams(audio_out_enabled=True, transcription_enabled=True) + DailyParams( + audio_out_enabled=True, + transcription_enabled=True, + vad_enabled=True, + vad_analyzer=SileroVADAnalyzer() + ) ) llm = OpenAILLMService( @@ -104,8 +110,8 @@ async def main(room_url: str, token): }, ] - tma_in = LLMUserContextAggregator(messages) - tma_out = LLMAssistantContextAggregator(messages) + tma_in = LLMUserResponseAggregator(messages) + tma_out = LLMAssistantResponseAggregator(messages) out_sound = OutboundSoundEffectWrapper() in_sound = InboundSoundEffectWrapper() fl = FrameLogger("LLM Out") diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index ab772edb6..c960b99b8 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -110,6 +110,24 @@ def __str__(self): return f"{self.name}(size: {len(self.images)})" +@dataclass() +class LLMFunctionStartFrame(Frame): + """Emitted when the LLM receives the beginning of a function call + completion. A frame processor can use this frame to indicate that it should + start preparing to make a function call, if it can do so in the absence of + any arguments.""" + function_name: str + tool_call_id: str + + +@dataclass() +class LLMFunctionCallFrame(Frame): + """Emitted when the LLM has received an entire function call completion.""" + function_name: str + tool_call_id: str + arguments: str + + @dataclass class TextFrame(DataFrame): """A chunk of text. Emitted by LLM services, consumed by TTS services, can @@ -119,7 +137,7 @@ class TextFrame(DataFrame): text: str def __str__(self): - return f"{self.name}(text: [{self.text}])" + return f"{self.name}(text: {self.text})" @dataclass @@ -132,7 +150,7 @@ class TranscriptionFrame(TextFrame): timestamp: str def __str__(self): - return f"{self.name}(user_id: {self.user_id}, text: [{self.text}], timestamp: {self.timestamp})" + return f"{self.name}(user: {self.user_id}, text: {self.text}, timestamp: {self.timestamp})" @dataclass @@ -143,7 +161,7 @@ class InterimTranscriptionFrame(TextFrame): timestamp: str def __str__(self): - return f"{self.name}(user: {self.user_id}, text: [{self.text}], timestamp: {self.timestamp})" + return f"{self.name}(user: {self.user_id}, text: {self.text}, timestamp: {self.timestamp})" @dataclass diff --git a/src/pipecat/processors/aggregators/llm_response.py b/src/pipecat/processors/aggregators/llm_response.py index 8739c8ab3..5a5c01482 100644 --- a/src/pipecat/processors/aggregators/llm_response.py +++ b/src/pipecat/processors/aggregators/llm_response.py @@ -11,13 +11,16 @@ Frame, InterimTranscriptionFrame, LLMFullResponseEndFrame, - LLMFullResponseStartFrame, LLMMessagesFrame, + LLMResponseStartFrame, StartInterruptionFrame, - TranscriptionFrame, TextFrame, + LLMResponseEndFrame, + TranscriptionFrame, UserStartedSpeakingFrame, - UserStoppedSpeakingFrame) + UserStoppedSpeakingFrame +) +from pipecat.services.openai import OpenAILLMContext, OpenAILLMContextFrame class LLMResponseAggregator(FrameProcessor): @@ -30,30 +33,21 @@ def __init__( start_frame, end_frame, accumulator_frame: TextFrame, - interim_accumulator_frame: TextFrame | None = None, - handle_interruptions: bool = False + interim_accumulator_frame: TextFrame | None = None ): super().__init__() - self._messages = messages + if messages: + self._messages = messages self._role = role self._start_frame = start_frame self._end_frame = end_frame self._accumulator_frame = accumulator_frame self._interim_accumulator_frame = interim_accumulator_frame - self._handle_interruptions = handle_interruptions # Reset our accumulator state. self._reset() - @property - def messages(self): - return self._messages - - @property - def role(self): - return self._role - # # Frame processor # @@ -76,16 +70,11 @@ def role(self): async def process_frame(self, frame: Frame, direction: FrameDirection): send_aggregation = False - if isinstance(frame, self._start_frame): - self._aggregation = "" - self._aggregating = True self._seen_start_frame = True - self._seen_end_frame = False - self._seen_interim_results = False + self._aggregating = True elif isinstance(frame, self._end_frame): self._seen_end_frame = True - self._seen_start_frame = False # We might have received the end frame but we might still be # aggregating (i.e. we have seen interim results but not the final @@ -107,9 +96,7 @@ async def process_frame(self, frame: Frame, direction: FrameDirection): self._seen_interim_results = False elif self._interim_accumulator_frame and isinstance(frame, self._interim_accumulator_frame): self._seen_interim_results = True - elif self._handle_interruptions and isinstance(frame, StartInterruptionFrame): - await self._push_aggregation() - # Reset anyways + elif isinstance(frame, StartInterruptionFrame): self._reset() await self.push_frame(frame, direction) else: @@ -121,14 +108,12 @@ async def process_frame(self, frame: Frame, direction: FrameDirection): async def _push_aggregation(self): if len(self._aggregation) > 0: self._messages.append({"role": self._role, "content": self._aggregation}) - - # Reset the aggregation. Reset it before pushing it down, otherwise - # if the tasks gets cancelled we won't be able to clear things up. - self._aggregation = "" - frame = LLMMessagesFrame(self._messages) await self.push_frame(frame) + # Reset our accumulator state. + self._reset() + def _reset(self): self._aggregation = "" self._aggregating = False @@ -142,10 +127,9 @@ def __init__(self, messages: List[dict] = []): super().__init__( messages=messages, role="assistant", - start_frame=LLMFullResponseStartFrame, - end_frame=LLMFullResponseEndFrame, - accumulator_frame=TextFrame, - handle_interruptions=True + start_frame=LLMResponseStartFrame, + end_frame=LLMResponseEndFrame, + accumulator_frame=TextFrame ) @@ -211,3 +195,44 @@ async def process_frame(self, frame: Frame, direction: FrameDirection): self._aggregation = "" else: await self.push_frame(frame, direction) + + +class LLMContextAggregator(LLMResponseAggregator): + def __init__(self, *, context: OpenAILLMContext, **kwargs): + + self._context = context + super().__init__(**kwargs) + + async def _push_aggregation(self): + if len(self._aggregation) > 0: + self._context.add_message({"role": self._role, "content": self._aggregation}) + frame = OpenAILLMContextFrame(self._context) + await self.push_frame(frame) + + # Reset our accumulator state. + self._reset() + + +class LLMAssistantContextAggregator(LLMContextAggregator): + def __init__(self, context: OpenAILLMContext): + super().__init__( + messages=[], + context=context, + role="assistant", + start_frame=LLMResponseStartFrame, + end_frame=LLMResponseEndFrame, + accumulator_frame=TextFrame + ) + + +class LLMUserContextAggregator(LLMContextAggregator): + def __init__(self, context: OpenAILLMContext): + super().__init__( + messages=[], + context=context, + role="user", + start_frame=UserStartedSpeakingFrame, + end_frame=UserStoppedSpeakingFrame, + accumulator_frame=TranscriptionFrame, + interim_accumulator_frame=InterimTranscriptionFrame + ) diff --git a/src/pipecat/services/openai.py b/src/pipecat/services/openai.py index 51e4f1dad..dacc4cecd 100644 --- a/src/pipecat/services/openai.py +++ b/src/pipecat/services/openai.py @@ -5,6 +5,7 @@ # import io +import json import time import aiohttp import base64 @@ -16,8 +17,10 @@ from pipecat.frames.frames import ( ErrorFrame, Frame, + LLMFunctionCallFrame, LLMFullResponseEndFrame, LLMFullResponseStartFrame, + LLMFunctionStartFrame, LLMMessagesFrame, LLMResponseEndFrame, LLMResponseStartFrame, @@ -35,6 +38,7 @@ from openai import AsyncOpenAI, AsyncStream from openai.types.chat import ( + ChatCompletion, ChatCompletionChunk, ChatCompletionMessageParam, ) @@ -97,9 +101,19 @@ async def _stream_chat_completions( return chunks + async def _chat_completions(self, messages) -> str | None: + response: ChatCompletion = await self._client.chat.completions.create( + model=self._model, stream=False, messages=messages + ) + if response and len(response.choices) > 0: + return response.choices[0].message.content + else: + return None + async def _process_context(self, context: OpenAILLMContext): function_name = "" arguments = "" + tool_call_id = "" chunk_stream: AsyncStream[ChatCompletionChunk] = ( await self._stream_chat_completions(context) @@ -125,8 +139,10 @@ async def _process_context(self, context: OpenAILLMContext): tool_call = chunk.choices[0].delta.tool_calls[0] if tool_call.function and tool_call.function.name: + print(f"!!! !!! !!! OMG TOOL CALL {tool_call}") function_name += tool_call.function.name - # yield LLMFunctionStartFrame(function_name=tool_call.function.name) + tool_call_id = tool_call.id + await self.push_frame(LLMFunctionStartFrame(function_name=tool_call.function.name, tool_call_id=tool_call_id)) if tool_call.function and tool_call.function.arguments: # Keep iterating through the response to collect all the argument fragments and # yield a complete LLMFunctionCallFrame after run_llm_async @@ -137,12 +153,12 @@ async def _process_context(self, context: OpenAILLMContext): await self.push_frame(TextFrame(chunk.choices[0].delta.content)) await self.push_frame(LLMResponseEndFrame()) - await self.push_frame(LLMFullResponseEndFrame()) - # if we got a function name and arguments, yield the frame with all the info so # frame consumers can take action based on the function call. - # if function_name and arguments: - # yield LLMFunctionCallFrame(function_name=function_name, arguments=arguments) + if function_name and arguments: + await self.push_frame(LLMFunctionCallFrame(function_name=function_name, arguments=arguments, tool_call_id=tool_call_id)) + + await self.push_frame(LLMFullResponseEndFrame()) async def process_frame(self, frame: Frame, direction: FrameDirection): context = None From aeeea64aeaa81b3d3bfe8ada25c579c22605b4bb Mon Sep 17 00:00:00 2001 From: Chad Bailey Date: Thu, 23 May 2024 14:27:17 +0000 Subject: [PATCH 02/20] removed old llm_context file --- .../processors/aggregators/llm_context.py | 82 ------------------- 1 file changed, 82 deletions(-) delete mode 100644 src/pipecat/processors/aggregators/llm_context.py diff --git a/src/pipecat/processors/aggregators/llm_context.py b/src/pipecat/processors/aggregators/llm_context.py deleted file mode 100644 index 06e91b8c3..000000000 --- a/src/pipecat/processors/aggregators/llm_context.py +++ /dev/null @@ -1,82 +0,0 @@ -# -# Copyright (c) 2024, Daily -# -# SPDX-License-Identifier: BSD 2-Clause License -# - -from pipecat.frames.frames import Frame, InterimTranscriptionFrame, LLMMessagesFrame, TextFrame -from pipecat.processors.frame_processor import FrameDirection, FrameProcessor - - -class LLMContextAggregator(FrameProcessor): - def __init__( - self, - messages: list[dict], - role: str, - complete_sentences=True, - pass_through=True, - ): - super().__init__() - self._messages = messages - self._role = role - self._sentence = "" - self._complete_sentences = complete_sentences - self._pass_through = pass_through - - async def process_frame(self, frame: Frame, direction: FrameDirection): - # We don't do anything with non-text frames, pass it along to next in - # the pipeline. - if not isinstance(frame, TextFrame): - await self.push_frame(frame, direction) - return - - # If we get interim results, we ignore them. - if isinstance(frame, InterimTranscriptionFrame): - return - - # The common case for "pass through" is receiving frames from the LLM that we'll - # use to update the "assistant" LLM messages, but also passing the text frames - # along to a TTS service to be spoken to the user. - if self._pass_through: - await self.push_frame(frame, direction) - - # TODO: split up transcription by participant - if self._complete_sentences: - # 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 = "" - await self.push_frame(LLMMessagesFrame(self._messages)) - else: - # 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}) - await self.push_frame(LLMMessagesFrame(self._messages)) - - -class LLMUserContextAggregator(LLMContextAggregator): - def __init__( - self, - messages: list[dict], - complete_sentences=True): - super().__init__( - messages, - "user", - complete_sentences, - pass_through=False) - - -class LLMAssistantContextAggregator(LLMContextAggregator): - def __init__( - self, - messages: list[dict], - complete_sentences=True): - super().__init__( - messages, - "assistant", - complete_sentences, - pass_through=True, - ) From f39b20d4621fdb4260d58f33a0f86b61e3bdbc19 Mon Sep 17 00:00:00 2001 From: Chad Bailey Date: Thu, 23 May 2024 20:29:55 +0000 Subject: [PATCH 03/20] added integration testing for openai --- src/pipecat/services/openai.py | 1 - src/pipecat/utils/test_frame_processor.py | 41 ++++++++++++++++++ tests/integration/integration_openai_llm.py | 47 ++++++++++++++++----- 3 files changed, 77 insertions(+), 12 deletions(-) create mode 100644 src/pipecat/utils/test_frame_processor.py diff --git a/src/pipecat/services/openai.py b/src/pipecat/services/openai.py index dacc4cecd..512f037b0 100644 --- a/src/pipecat/services/openai.py +++ b/src/pipecat/services/openai.py @@ -139,7 +139,6 @@ async def _process_context(self, context: OpenAILLMContext): tool_call = chunk.choices[0].delta.tool_calls[0] if tool_call.function and tool_call.function.name: - print(f"!!! !!! !!! OMG TOOL CALL {tool_call}") function_name += tool_call.function.name tool_call_id = tool_call.id await self.push_frame(LLMFunctionStartFrame(function_name=tool_call.function.name, tool_call_id=tool_call_id)) diff --git a/src/pipecat/utils/test_frame_processor.py b/src/pipecat/utils/test_frame_processor.py new file mode 100644 index 000000000..f4a6674aa --- /dev/null +++ b/src/pipecat/utils/test_frame_processor.py @@ -0,0 +1,41 @@ +from typing import List +from pipecat.processors.frame_processor import FrameProcessor + + +class TestException(BaseException): + pass + + +class TestFrameProcessor(FrameProcessor): + def __init__(self, test_frames): + self.test_frames = test_frames + self._list_counter = 0 + super().__init__() + + async def process_frame(self, frame, direction): + if not self.test_frames[0]: # then we've run out of required frames but the generator is still going? + raise TestException(f"Oops, got an extra frame, {frame}") + if isinstance(self.test_frames[0], List): + # We need to consume frames until we see the next frame type after this + next_frame = self.test_frames[1] + if isinstance(frame, next_frame): + # we're done iterating the list I guess + print(f"TestFrameProcessor got expected list exit frame: {frame}") + # pop twice to get rid of the list, as well as the next frame + self.test_frames.pop(0) + self.test_frames.pop(0) + self.list_counter = 0 + else: + fl = self.test_frames[0] + fl_el = fl[self._list_counter % len(fl)] + if isinstance(frame, fl_el): + print(f"TestFrameProcessor got expected list frame: {frame}") + self._list_counter += 1 + else: + raise TestException(f"Inside a list, expected {fl_el} but got {frame}") + + else: + if not isinstance(frame, self.test_frames[0]): + raise TestException(f"Expected {self.test_frames[0]}, but got {frame}") + print(f"TestFrameProcessor got expected frame: {frame}") + self.test_frames.pop(0) diff --git a/tests/integration/integration_openai_llm.py b/tests/integration/integration_openai_llm.py index 6f87b7fec..bc011c3eb 100644 --- a/tests/integration/integration_openai_llm.py +++ b/tests/integration/integration_openai_llm.py @@ -1,15 +1,27 @@ import asyncio import os -from pipecat.pipeline.openai_frames import OpenAILLMContextFrame -from pipecat.services.openai_llm_context import OpenAILLMContext +from typing import List +from pipecat.services.openai import OpenAILLMContextFrame, OpenAILLMContext +from pipecat.processors.frame_processor import FrameDirection, FrameProcessor +from pipecat.frames.frames import ( + LLMFullResponseStartFrame, + LLMFullResponseEndFrame, + LLMResponseEndFrame, + LLMResponseStartFrame, + LLMFunctionCallFrame, + LLMFunctionStartFrame, + TextFrame +) +from pipecat.utils.test_frame_processor import TestFrameProcessor from openai.types.chat import ( ChatCompletionSystemMessageParam, ChatCompletionToolParam, ChatCompletionUserMessageParam, ) -from pipecat.services.openai_api_llm_service import BaseOpenAILLMService +from pipecat.services.openai import OpenAILLMService + if __name__ == "__main__": async def test_functions(): @@ -42,10 +54,19 @@ async def test_functions(): api_key = os.getenv("OPENAI_API_KEY") - llm = BaseOpenAILLMService( + t = TestFrameProcessor([ + LLMFullResponseStartFrame, + LLMFunctionStartFrame, + LLMFunctionCallFrame, + LLMFullResponseEndFrame + ]) + + llm = OpenAILLMService( api_key=api_key or "", model="gpt-4-1106-preview", ) + llm.link(t) + context = OpenAILLMContext(tools=tools) system_message: ChatCompletionSystemMessageParam = ChatCompletionSystemMessageParam( content="Ask the user to ask for a weather report", name="system", role="system" @@ -58,23 +79,27 @@ async def test_functions(): context.add_message(system_message) context.add_message(user_message) frame = OpenAILLMContextFrame(context) - async for s in llm.process_frame(frame): - print(s) + await llm.process_frame(frame, FrameDirection.DOWNSTREAM) async def test_chat(): api_key = os.getenv("OPENAI_API_KEY") - - llm = BaseOpenAILLMService( + t = TestFrameProcessor([ + LLMFullResponseStartFrame, + [LLMResponseStartFrame, TextFrame, LLMResponseEndFrame], + LLMFullResponseEndFrame + ]) + llm = OpenAILLMService( api_key=api_key or "", - model="gpt-4-1106-preview", + model="gpt-4o", ) + llm.link(t) context = OpenAILLMContext() message: ChatCompletionSystemMessageParam = ChatCompletionSystemMessageParam( content="Please tell the world hello.", name="system", role="system") context.add_message(message) frame = OpenAILLMContextFrame(context) - async for s in llm.process_frame(frame): - print(s) + print(f"starting chattest") + await llm.process_frame(frame, FrameDirection.DOWNSTREAM) async def run_tests(): await test_functions() From 729aca3a0248153c789c26d337c2a6b925865c99 Mon Sep 17 00:00:00 2001 From: Chad Bailey Date: Fri, 24 May 2024 17:52:11 +0000 Subject: [PATCH 04/20] added function calling example --- examples/foundational/15-function-calling.py | 195 +++++++++++++++++++ tests/integration/integration_openai_llm.py | 1 - 2 files changed, 195 insertions(+), 1 deletion(-) create mode 100644 examples/foundational/15-function-calling.py diff --git a/examples/foundational/15-function-calling.py b/examples/foundational/15-function-calling.py new file mode 100644 index 000000000..94c3d939c --- /dev/null +++ b/examples/foundational/15-function-calling.py @@ -0,0 +1,195 @@ +# +# Copyright (c) 2024, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import aiohttp +import os +import json +import sys + +from pipecat.frames.frames import LLMMessagesFrame, Frame +from pipecat.processors.frame_processor import FrameDirection, FrameProcessor +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineTask +from pipecat.processors.aggregators.llm_response import ( + LLMAssistantContextAggregator, + LLMUserContextAggregator, +) +from pipecat.services.openai import OpenAILLMContextFrame, OpenAILLMContext +from pipecat.processors.logger import FrameLogger +from pipecat.services.elevenlabs import ElevenLabsTTSService +from pipecat.services.openai import OpenAILLMService +from pipecat.transports.services.daily import DailyParams, DailyTransport +from pipecat.vad.silero import SileroVADAnalyzer +from openai.types.chat import ( + ChatCompletionSystemMessageParam, + ChatCompletionFunctionMessageParam, + ChatCompletionToolParam, + ChatCompletionUserMessageParam, +) +from pipecat.frames.frames import ( + LLMFullResponseStartFrame, + LLMFullResponseEndFrame, + LLMResponseEndFrame, + LLMResponseStartFrame, + LLMFunctionCallFrame, + LLMFunctionStartFrame, + TextFrame +) + +from runner import configure + +from loguru import logger + +from dotenv import load_dotenv +load_dotenv(override=True) + +logger.remove(0) +logger.add(sys.stderr, level="DEBUG") + + +class FunctionCaller(FrameProcessor): + def __init__(self, context): + self._context = context + super().__init__() + + async def process_frame(self, frame: Frame, direction: FrameDirection): + # When we receive function call frames, we need to ask the LLM to run a completion + # again so it actually talks to the user + if isinstance(frame, LLMFunctionCallFrame): + tool_call = ChatCompletionFunctionMessageParam({ + "role": "assistant", + "tool_calls": [ + { + "id": frame.tool_call_id, + "function": { + "arguments": frame.arguments, + "name": frame.function_name + }, + "type": "function" + } + ] + + }) + self._context.add_message(tool_call) + + # This is where you'd actually call the function + weather_result = { + "city": "San Francisco, CA", + "conditions": "Sunny and beautiful", + "temperature": "75 degrees Fahrenheit" + } + print(f"weather_result: {weather_result}") + result = ChatCompletionToolParam({ + "tool_call_id": frame.tool_call_id, + "role": "tool", + "content": json.dumps(weather_result) + }) + print(f"result: {result}") + try: + self._context.add_message(result) + except Exception as e: + print(f"got exception: {e}") + print(f"context now includes: {self._context.messages}") + await self.push_frame(OpenAILLMContextFrame(self._context), FrameDirection.UPSTREAM) + else: + print(f"!!! Got a frame I'm forwarding: {frame}") + await self.push_frame(frame) + + +async def main(room_url: str, token): + async with aiohttp.ClientSession() as session: + transport = DailyTransport( + room_url, + token, + "Respond bot", + DailyParams( + audio_out_enabled=True, + transcription_enabled=True, + vad_enabled=True, + vad_analyzer=SileroVADAnalyzer() + ) + ) + + tts = ElevenLabsTTSService( + aiohttp_session=session, + api_key=os.getenv("ELEVENLABS_API_KEY"), + voice_id=os.getenv("ELEVENLABS_VOICE_ID"), + ) + + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + model="gpt-4-turbo-preview") + + fl_in = FrameLogger("Inner") + fl_out = FrameLogger("Outer") + + tools = [ + ChatCompletionToolParam( + type="function", + function={ + "name": "get_current_weather", + "description": "Get the current weather", + "parameters": { + "type": "object", + "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 users location.", + }, + }, + "required": [ + "location", + "format"], + }, + })] + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = OpenAILLMContext(messages, tools) + tma_in = LLMUserContextAggregator(context) + tma_out = LLMAssistantContextAggregator(context) + caller = FunctionCaller(context) + pipeline = Pipeline([ + fl_in, + transport.input(), + tma_in, + llm, + caller, + fl_out, + tts, + transport.output(), + tma_out + ]) + + task = PipelineTask(pipeline) + + @ transport.event_handler("on_first_participant_joined") + async def on_first_participant_joined(transport, participant): + transport.capture_participant_transcription(participant["id"]) + # Kick off the conversation. + await tts.say("Hi! Ask me about the weather in San Francisco.") + + runner = PipelineRunner() + + await runner.run(task) + + +if __name__ == "__main__": + (url, token) = configure() + asyncio.run(main(url, token)) diff --git a/tests/integration/integration_openai_llm.py b/tests/integration/integration_openai_llm.py index bc011c3eb..3f4a1105d 100644 --- a/tests/integration/integration_openai_llm.py +++ b/tests/integration/integration_openai_llm.py @@ -98,7 +98,6 @@ async def test_chat(): content="Please tell the world hello.", name="system", role="system") context.add_message(message) frame = OpenAILLMContextFrame(context) - print(f"starting chattest") await llm.process_frame(frame, FrameDirection.DOWNSTREAM) async def run_tests(): From 5027cb4122c07d2e4eee7c7841c87003e1eae95d Mon Sep 17 00:00:00 2001 From: Chad Bailey Date: Tue, 28 May 2024 16:12:23 +0000 Subject: [PATCH 05/20] added function callbacks --- .../{14-wake-phrase.py => 10-wake-phrase.py} | 0 examples/foundational/10-wake-word.py | 192 ------------------ ...tion-calling.py => 14-function-calling.py} | 0 src/pipecat/services/openai.py | 71 ++++++- tests/integration/integration_openai_llm.py | 32 ++- 5 files changed, 85 insertions(+), 210 deletions(-) rename examples/foundational/{14-wake-phrase.py => 10-wake-phrase.py} (100%) delete mode 100644 examples/foundational/10-wake-word.py rename examples/foundational/{15-function-calling.py => 14-function-calling.py} (100%) diff --git a/examples/foundational/14-wake-phrase.py b/examples/foundational/10-wake-phrase.py similarity index 100% rename from examples/foundational/14-wake-phrase.py rename to examples/foundational/10-wake-phrase.py diff --git a/examples/foundational/10-wake-word.py b/examples/foundational/10-wake-word.py deleted file mode 100644 index 310b13d75..000000000 --- a/examples/foundational/10-wake-word.py +++ /dev/null @@ -1,192 +0,0 @@ -# -# Copyright (c) 2024, Daily -# -# SPDX-License-Identifier: BSD 2-Clause License -# - -import asyncio -import aiohttp -import os -import random -import sys - -from PIL import Image - -from pipecat.frames.frames import ( - Frame, - SystemFrame, - TextFrame, - ImageRawFrame, - SpriteFrame, - TranscriptionFrame, -) -from pipecat.pipeline.pipeline import Pipeline -from pipecat.pipeline.runner import PipelineRunner -from pipecat.pipeline.task import PipelineTask -from pipecat.processors.aggregators.llm_response import ( - LLMUserResponseAggregator, - LLMAssistantResponseAggregator, -) -from pipecat.processors.frame_processor import FrameDirection, FrameProcessor -from pipecat.services.openai import OpenAILLMService -from pipecat.services.elevenlabs import ElevenLabsTTSService -from pipecat.transports.services.daily import DailyParams, DailyTransport -from pipecat.vad.silero import SileroVADAnalyzer - -from runner import configure - -from loguru import logger - -from dotenv import load_dotenv -load_dotenv(override=True) - -logger.remove(0) -logger.add(sys.stderr, level="DEBUG") - - -sprites = {} -image_files = [ - "sc-default.png", - "sc-talk.png", - "sc-listen-1.png", - "sc-think-1.png", - "sc-think-2.png", - "sc-think-3.png", - "sc-think-4.png", -] - -script_dir = os.path.dirname(__file__) - -for file in image_files: - # Build the full path to the image file - full_path = os.path.join(script_dir, "assets", file) - # Get the filename without the extension to use as the dictionary key - filename = os.path.splitext(os.path.basename(full_path))[0] - # Open the image and convert it to bytes - with Image.open(full_path) as img: - sprites[file] = ImageRawFrame(image=img.tobytes(), size=img.size, format=img.format) - -# When the bot isn't talking, show a static image of the cat listening -quiet_frame = sprites["sc-listen-1.png"] - -# When the bot is talking, build an animation from two sprites -talking_list = [sprites["sc-default.png"], sprites["sc-talk.png"]] -talking = [random.choice(talking_list) for x in range(30)] -talking_frame = SpriteFrame(talking) - -# TODO: Support "thinking" as soon as we get a valid transcript, while LLM -# is processing -thinking_list = [ - sprites["sc-think-1.png"], - sprites["sc-think-2.png"], - sprites["sc-think-3.png"], - sprites["sc-think-4.png"], -] -thinking_frame = SpriteFrame(thinking_list) - - -class NameCheckFilter(FrameProcessor): - def __init__(self, names: list[str]): - super().__init__() - self._names = names - self._sentence = "" - - async def process_frame(self, frame: Frame, direction: FrameDirection): - if isinstance(frame, SystemFrame): - await self.push_frame(frame, direction) - return - - content: str = "" - - # TODO: split up transcription by participant - if isinstance(frame, TranscriptionFrame): - content = frame.text - self._sentence += content - if self._sentence.endswith((".", "?", "!")): - if any(name in self._sentence for name in self._names): - await self.push_frame(TextFrame(self._sentence)) - self._sentence = "" - else: - self._sentence = "" - else: - await self.push_frame(frame, direction) - - -class ImageSyncAggregator(FrameProcessor): - - async def process_frame(self, frame: Frame, direction: FrameDirection): - await self.push_frame(talking_frame) - await self.push_frame(frame) - await self.push_frame(quiet_frame) - - -async def main(room_url: str, token): - async with aiohttp.ClientSession() as session: - transport = DailyTransport( - room_url, - token, - "Santa Cat", - DailyParams( - audio_out_enabled=True, - camera_out_enabled=True, - camera_out_width=720, - camera_out_height=1280, - camera_out_framerate=10, - transcription_enabled=True, - vad_enabled=True, - vad_analyzer=SileroVADAnalyzer() - ) - ) - - llm = OpenAILLMService( - api_key=os.getenv("OPENAI_API_KEY"), - model="gpt-4-turbo-preview") - - tts = ElevenLabsTTSService( - aiohttp_session=session, - api_key=os.getenv("ELEVENLABS_API_KEY"), - voice_id="jBpfuIE2acCO8z3wKNLl", - ) - isa = ImageSyncAggregator() - - messages = [ - { - "role": "system", - "content": "You are Santa Cat, a cat that lives in Santa's workshop at the North Pole. You should be clever, and a bit sarcastic. You should also tell jokes every once in a while. Your responses should only be a few sentences long.", - }, - ] - - tma_in = LLMUserResponseAggregator(messages) - tma_out = LLMAssistantResponseAggregator(messages) - ncf = NameCheckFilter(["Santa Cat", "Santa"]) - - pipeline = Pipeline([ - transport.input(), - isa, - ncf, - tma_in, - llm, - tts, - transport.output(), - tma_out - ]) - - @transport.event_handler("on_first_participant_joined") - async def on_first_participant_joined(transport, participant): - # Send some greeting at the beginning. - await tts.say("Hi! If you want to talk to me, just say 'hey Santa Cat'.") - transport.capture_participant_transcription(participant["id"]) - - async def starting_image(): - await transport.send_image(quiet_frame) - - runner = PipelineRunner() - - task = PipelineTask(pipeline) - - await asyncio.gather(runner.run(task), starting_image()) - - -if __name__ == "__main__": - (url, token) = configure() - asyncio.run(main(url, token)) diff --git a/examples/foundational/15-function-calling.py b/examples/foundational/14-function-calling.py similarity index 100% rename from examples/foundational/15-function-calling.py rename to examples/foundational/14-function-calling.py diff --git a/src/pipecat/services/openai.py b/src/pipecat/services/openai.py index 512f037b0..40cc12d86 100644 --- a/src/pipecat/services/openai.py +++ b/src/pipecat/services/openai.py @@ -31,7 +31,12 @@ from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext, OpenAILLMContextFrame from pipecat.processors.frame_processor import FrameDirection from pipecat.services.ai_services import LLMService, ImageGenService - +from openai.types.chat import ( + ChatCompletionSystemMessageParam, + ChatCompletionFunctionMessageParam, + ChatCompletionToolParam, + ChatCompletionUserMessageParam, +) from loguru import logger try: @@ -63,10 +68,18 @@ def __init__(self, model: str, api_key=None, base_url=None): super().__init__() self._model: str = model self._client = self.create_client(api_key=api_key, base_url=base_url) + self._callbacks = {} def create_client(self, api_key=None, base_url=None): return AsyncOpenAI(api_key=api_key, base_url=base_url) + # TODO-CB: callback function type + def register_function(self, function_name, callback): + self._callbacks[function_name] = callback + + def unregister_function(self, function_name): + del self._callbacks[function_name] + async def _stream_chat_completions( self, context: OpenAILLMContext ) -> AsyncStream[ChatCompletionChunk]: @@ -119,8 +132,6 @@ async def _process_context(self, context: OpenAILLMContext): await self._stream_chat_completions(context) ) - await self.push_frame(LLMFullResponseStartFrame()) - async for chunk in chunk_stream: if len(chunk.choices) == 0: continue @@ -141,7 +152,9 @@ async def _process_context(self, context: OpenAILLMContext): if tool_call.function and tool_call.function.name: function_name += tool_call.function.name tool_call_id = tool_call.id - await self.push_frame(LLMFunctionStartFrame(function_name=tool_call.function.name, tool_call_id=tool_call_id)) + # only send a function start frame if we're not handling the function call + if function_name not in self._callbacks.keys(): + await self.push_frame(LLMFunctionStartFrame(function_name=tool_call.function.name, tool_call_id=tool_call_id)) if tool_call.function and tool_call.function.arguments: # Keep iterating through the response to collect all the argument fragments and # yield a complete LLMFunctionCallFrame after run_llm_async @@ -152,12 +165,50 @@ async def _process_context(self, context: OpenAILLMContext): await self.push_frame(TextFrame(chunk.choices[0].delta.content)) await self.push_frame(LLMResponseEndFrame()) - # if we got a function name and arguments, yield the frame with all the info so - # frame consumers can take action based on the function call. + # if we got a function name and arguments, check to see if it's a function with + # a registered handler. If so, run the registered callback, save the result to + # the context, and re-prompt to get a chat answer. If we don't have a registered + # handler, push an LLMFunctionCallFrame and let the pipeline deal with it. if function_name and arguments: - await self.push_frame(LLMFunctionCallFrame(function_name=function_name, arguments=arguments, tool_call_id=tool_call_id)) - - await self.push_frame(LLMFullResponseEndFrame()) + if function_name in self._callbacks.keys(): + print(f"got a function call that im handling, {function_name}") + await self._handle_function_call(context, tool_call_id, function_name, arguments) + + else: + print(f"got a function call im NOT handling: {function_name}") + await self.push_frame(LLMFunctionCallFrame(function_name=function_name, arguments=arguments, tool_call_id=tool_call_id)) + + async def _handle_function_call(self, context, tool_call_id, function_name, arguments): + print("using a callback to handle this one") + result = await self._callbacks[function_name](arguments) + print(f"result is {result}") + + tool_call = ChatCompletionFunctionMessageParam({ + "role": "assistant", + "tool_calls": [ + { + "id": tool_call_id, + "function": { + "arguments": arguments, + "name": function_name + }, + "type": "function" + } + ] + + }) + context.add_message(tool_call) + if isinstance(result, List): + result = json.dumps(result) + tool_result = ChatCompletionToolParam({ + "tool_call_id": tool_call_id, + "role": "tool", + "content": result + }) + context.add_message(tool_result) + # re-prompt to get a human answer + print(f"about to re-prompt with {context}, {context.messages}") + await self._process_context(context) async def process_frame(self, frame: Frame, direction: FrameDirection): context = None @@ -171,7 +222,9 @@ async def process_frame(self, frame: Frame, direction: FrameDirection): await self.push_frame(frame, direction) if context: + await self.push_frame(LLMFullResponseStartFrame()) await self._process_context(context) + await self.push_frame(LLMFullResponseEndFrame()) class OpenAILLMService(BaseOpenAILLMService): diff --git a/tests/integration/integration_openai_llm.py b/tests/integration/integration_openai_llm.py index 3f4a1105d..42f8e58ba 100644 --- a/tests/integration/integration_openai_llm.py +++ b/tests/integration/integration_openai_llm.py @@ -1,4 +1,5 @@ import asyncio +import json import os from typing import List @@ -24,7 +25,7 @@ if __name__ == "__main__": - async def test_functions(): + async def test_functions(handle=False): tools = [ ChatCompletionToolParam( type="function", @@ -52,19 +53,31 @@ async def test_functions(): }, })] - api_key = os.getenv("OPENAI_API_KEY") + async def get_weather_from_api(args): + print(f"get_weather_from_api called with {args}") + return json.dumps({"conditions": "nice", "temperature": "75"}) - t = TestFrameProcessor([ - LLMFullResponseStartFrame, - LLMFunctionStartFrame, - LLMFunctionCallFrame, - LLMFullResponseEndFrame - ]) + api_key = os.getenv("OPENAI_API_KEY") llm = OpenAILLMService( api_key=api_key or "", model="gpt-4-1106-preview", ) + + if (handle): + llm.register_function("get_current_weather", get_weather_from_api) + t = TestFrameProcessor([ + LLMFullResponseStartFrame, + [LLMResponseStartFrame, TextFrame, LLMResponseEndFrame], + LLMFullResponseEndFrame + ]) + else: + t = TestFrameProcessor([ + LLMFullResponseStartFrame, + LLMFunctionStartFrame, + LLMFunctionCallFrame, + LLMFullResponseEndFrame + ]) llm.link(t) context = OpenAILLMContext(tools=tools) @@ -101,7 +114,8 @@ async def test_chat(): await llm.process_frame(frame, FrameDirection.DOWNSTREAM) async def run_tests(): - await test_functions() + await test_functions(True) + await test_functions(False) await test_chat() asyncio.run(run_tests()) From e13d8caddafab916232934879fbcb8b349677f4f Mon Sep 17 00:00:00 2001 From: Chad Bailey Date: Tue, 28 May 2024 16:49:51 +0000 Subject: [PATCH 06/20] added function start callback --- examples/foundational/14-function-calling.py | 14 ++++++++++++-- src/pipecat/services/openai.py | 16 ++++++++++++---- tests/integration/integration_openai_llm.py | 3 +-- 3 files changed, 25 insertions(+), 8 deletions(-) diff --git a/examples/foundational/14-function-calling.py b/examples/foundational/14-function-calling.py index 94c3d939c..295ad139f 100644 --- a/examples/foundational/14-function-calling.py +++ b/examples/foundational/14-function-calling.py @@ -101,6 +101,14 @@ async def process_frame(self, frame: Frame, direction: FrameDirection): await self.push_frame(frame) +async def start_fetch_weather(llm): + await llm.push_frame(TextFrame("Let me think.")) + + +async def fetch_weather_from_api(llm, args): + return ({"conditions": "nice", "temperature": "75"}) + + async def main(room_url: str, token): async with aiohttp.ClientSession() as session: transport = DailyTransport( @@ -124,6 +132,10 @@ async def main(room_url: str, token): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4-turbo-preview") + llm.register_function( + "get_current_weather", + fetch_weather_from_api, + start_callback=start_fetch_weather) fl_in = FrameLogger("Inner") fl_out = FrameLogger("Outer") @@ -164,13 +176,11 @@ async def main(room_url: str, token): context = OpenAILLMContext(messages, tools) tma_in = LLMUserContextAggregator(context) tma_out = LLMAssistantContextAggregator(context) - caller = FunctionCaller(context) pipeline = Pipeline([ fl_in, transport.input(), tma_in, llm, - caller, fl_out, tts, transport.output(), diff --git a/src/pipecat/services/openai.py b/src/pipecat/services/openai.py index 40cc12d86..44b05e4b0 100644 --- a/src/pipecat/services/openai.py +++ b/src/pipecat/services/openai.py @@ -69,16 +69,21 @@ def __init__(self, model: str, api_key=None, base_url=None): self._model: str = model self._client = self.create_client(api_key=api_key, base_url=base_url) self._callbacks = {} + self._start_callbacks = {} def create_client(self, api_key=None, base_url=None): return AsyncOpenAI(api_key=api_key, base_url=base_url) # TODO-CB: callback function type - def register_function(self, function_name, callback): + def register_function(self, function_name, callback, *, start_callback=None): self._callbacks[function_name] = callback + if start_callback: + self._start_callbacks[function_name] = start_callback def unregister_function(self, function_name): del self._callbacks[function_name] + if self._start_callbacks[function_name]: + del self._start_callbacks[function_name] async def _stream_chat_completions( self, context: OpenAILLMContext @@ -153,7 +158,10 @@ async def _process_context(self, context: OpenAILLMContext): function_name += tool_call.function.name tool_call_id = tool_call.id # only send a function start frame if we're not handling the function call - if function_name not in self._callbacks.keys(): + if function_name in self._callbacks.keys(): + if function_name in self._start_callbacks.keys(): + await self._start_callbacks[function_name](self) + else: await self.push_frame(LLMFunctionStartFrame(function_name=tool_call.function.name, tool_call_id=tool_call_id)) if tool_call.function and tool_call.function.arguments: # Keep iterating through the response to collect all the argument fragments and @@ -180,7 +188,7 @@ async def _process_context(self, context: OpenAILLMContext): async def _handle_function_call(self, context, tool_call_id, function_name, arguments): print("using a callback to handle this one") - result = await self._callbacks[function_name](arguments) + result = await self._callbacks[function_name](self, arguments) print(f"result is {result}") tool_call = ChatCompletionFunctionMessageParam({ @@ -198,7 +206,7 @@ async def _handle_function_call(self, context, tool_call_id, function_name, argu }) context.add_message(tool_call) - if isinstance(result, List): + if not isinstance(result, str): result = json.dumps(result) tool_result = ChatCompletionToolParam({ "tool_call_id": tool_call_id, diff --git a/tests/integration/integration_openai_llm.py b/tests/integration/integration_openai_llm.py index 42f8e58ba..a7a1ed186 100644 --- a/tests/integration/integration_openai_llm.py +++ b/tests/integration/integration_openai_llm.py @@ -53,8 +53,7 @@ async def test_functions(handle=False): }, })] - async def get_weather_from_api(args): - print(f"get_weather_from_api called with {args}") + async def get_weather_from_api(llm, args): return json.dumps({"conditions": "nice", "temperature": "75"}) api_key = os.getenv("OPENAI_API_KEY") From 55421b1e0ddf00ddc73532db7f5ca8cdf67ec8f0 Mon Sep 17 00:00:00 2001 From: Chad Bailey Date: Tue, 28 May 2024 17:01:01 +0000 Subject: [PATCH 07/20] fixup --- examples/foundational/14-function-calling.py | 49 -------------------- src/pipecat/services/openai.py | 7 +-- 2 files changed, 1 insertion(+), 55 deletions(-) diff --git a/examples/foundational/14-function-calling.py b/examples/foundational/14-function-calling.py index 295ad139f..2bc21885a 100644 --- a/examples/foundational/14-function-calling.py +++ b/examples/foundational/14-function-calling.py @@ -52,55 +52,6 @@ logger.add(sys.stderr, level="DEBUG") -class FunctionCaller(FrameProcessor): - def __init__(self, context): - self._context = context - super().__init__() - - async def process_frame(self, frame: Frame, direction: FrameDirection): - # When we receive function call frames, we need to ask the LLM to run a completion - # again so it actually talks to the user - if isinstance(frame, LLMFunctionCallFrame): - tool_call = ChatCompletionFunctionMessageParam({ - "role": "assistant", - "tool_calls": [ - { - "id": frame.tool_call_id, - "function": { - "arguments": frame.arguments, - "name": frame.function_name - }, - "type": "function" - } - ] - - }) - self._context.add_message(tool_call) - - # This is where you'd actually call the function - weather_result = { - "city": "San Francisco, CA", - "conditions": "Sunny and beautiful", - "temperature": "75 degrees Fahrenheit" - } - print(f"weather_result: {weather_result}") - result = ChatCompletionToolParam({ - "tool_call_id": frame.tool_call_id, - "role": "tool", - "content": json.dumps(weather_result) - }) - print(f"result: {result}") - try: - self._context.add_message(result) - except Exception as e: - print(f"got exception: {e}") - print(f"context now includes: {self._context.messages}") - await self.push_frame(OpenAILLMContextFrame(self._context), FrameDirection.UPSTREAM) - else: - print(f"!!! Got a frame I'm forwarding: {frame}") - await self.push_frame(frame) - - async def start_fetch_weather(llm): await llm.push_frame(TextFrame("Let me think.")) diff --git a/src/pipecat/services/openai.py b/src/pipecat/services/openai.py index 44b05e4b0..68a133660 100644 --- a/src/pipecat/services/openai.py +++ b/src/pipecat/services/openai.py @@ -75,7 +75,7 @@ def create_client(self, api_key=None, base_url=None): return AsyncOpenAI(api_key=api_key, base_url=base_url) # TODO-CB: callback function type - def register_function(self, function_name, callback, *, start_callback=None): + def register_function(self, function_name, callback, start_callback=None): self._callbacks[function_name] = callback if start_callback: self._start_callbacks[function_name] = start_callback @@ -179,17 +179,13 @@ async def _process_context(self, context: OpenAILLMContext): # handler, push an LLMFunctionCallFrame and let the pipeline deal with it. if function_name and arguments: if function_name in self._callbacks.keys(): - print(f"got a function call that im handling, {function_name}") await self._handle_function_call(context, tool_call_id, function_name, arguments) else: - print(f"got a function call im NOT handling: {function_name}") await self.push_frame(LLMFunctionCallFrame(function_name=function_name, arguments=arguments, tool_call_id=tool_call_id)) async def _handle_function_call(self, context, tool_call_id, function_name, arguments): - print("using a callback to handle this one") result = await self._callbacks[function_name](self, arguments) - print(f"result is {result}") tool_call = ChatCompletionFunctionMessageParam({ "role": "assistant", @@ -215,7 +211,6 @@ async def _handle_function_call(self, context, tool_call_id, function_name, argu }) context.add_message(tool_result) # re-prompt to get a human answer - print(f"about to re-prompt with {context}, {context.messages}") await self._process_context(context) async def process_frame(self, frame: Frame, direction: FrameDirection): From a518c3d0ce1e9a1214a4a8ce5f249b5071e8ccaa Mon Sep 17 00:00:00 2001 From: Chad Bailey Date: Tue, 28 May 2024 17:05:08 +0000 Subject: [PATCH 08/20] fixup --- .../processors/aggregators/llm_response.py | 54 +++++++++++++------ 1 file changed, 37 insertions(+), 17 deletions(-) diff --git a/src/pipecat/processors/aggregators/llm_response.py b/src/pipecat/processors/aggregators/llm_response.py index 5a5c01482..289296487 100644 --- a/src/pipecat/processors/aggregators/llm_response.py +++ b/src/pipecat/processors/aggregators/llm_response.py @@ -6,21 +6,22 @@ from typing import List +from pipecat.services.openai import OpenAILLMContextFrame, OpenAILLMContext + from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.frames.frames import ( Frame, InterimTranscriptionFrame, LLMFullResponseEndFrame, - LLMMessagesFrame, + LLMFullResponseStartFrame, + LLMResponseEndFrame, LLMResponseStartFrame, + LLMMessagesFrame, StartInterruptionFrame, - TextFrame, - LLMResponseEndFrame, TranscriptionFrame, + TextFrame, UserStartedSpeakingFrame, - UserStoppedSpeakingFrame -) -from pipecat.services.openai import OpenAILLMContext, OpenAILLMContextFrame + UserStoppedSpeakingFrame) class LLMResponseAggregator(FrameProcessor): @@ -33,21 +34,30 @@ def __init__( start_frame, end_frame, accumulator_frame: TextFrame, - interim_accumulator_frame: TextFrame | None = None + interim_accumulator_frame: TextFrame | None = None, + handle_interruptions: bool = False ): super().__init__() - if messages: - self._messages = messages + self._messages = messages self._role = role self._start_frame = start_frame self._end_frame = end_frame self._accumulator_frame = accumulator_frame self._interim_accumulator_frame = interim_accumulator_frame + self._handle_interruptions = handle_interruptions # Reset our accumulator state. self._reset() + @property + def messages(self): + return self._messages + + @property + def role(self): + return self._role + # # Frame processor # @@ -70,11 +80,16 @@ def __init__( async def process_frame(self, frame: Frame, direction: FrameDirection): send_aggregation = False + if isinstance(frame, self._start_frame): - self._seen_start_frame = True + self._aggregation = "" self._aggregating = True + self._seen_start_frame = True + self._seen_end_frame = False + self._seen_interim_results = False elif isinstance(frame, self._end_frame): self._seen_end_frame = True + self._seen_start_frame = False # We might have received the end frame but we might still be # aggregating (i.e. we have seen interim results but not the final @@ -96,7 +111,9 @@ async def process_frame(self, frame: Frame, direction: FrameDirection): self._seen_interim_results = False elif self._interim_accumulator_frame and isinstance(frame, self._interim_accumulator_frame): self._seen_interim_results = True - elif isinstance(frame, StartInterruptionFrame): + elif self._handle_interruptions and isinstance(frame, StartInterruptionFrame): + await self._push_aggregation() + # Reset anyways self._reset() await self.push_frame(frame, direction) else: @@ -108,12 +125,14 @@ async def process_frame(self, frame: Frame, direction: FrameDirection): async def _push_aggregation(self): if len(self._aggregation) > 0: self._messages.append({"role": self._role, "content": self._aggregation}) + + # Reset the aggregation. Reset it before pushing it down, otherwise + # if the tasks gets cancelled we won't be able to clear things up. + self._aggregation = "" + frame = LLMMessagesFrame(self._messages) await self.push_frame(frame) - # Reset our accumulator state. - self._reset() - def _reset(self): self._aggregation = "" self._aggregating = False @@ -127,9 +146,10 @@ def __init__(self, messages: List[dict] = []): super().__init__( messages=messages, role="assistant", - start_frame=LLMResponseStartFrame, - end_frame=LLMResponseEndFrame, - accumulator_frame=TextFrame + start_frame=LLMFullResponseStartFrame, + end_frame=LLMFullResponseEndFrame, + accumulator_frame=TextFrame, + handle_interruptions=True ) From 4a1e032c4c953a0622d08fcf7dad4cfc54fb44f3 Mon Sep 17 00:00:00 2001 From: Chad Bailey Date: Tue, 28 May 2024 20:20:07 +0000 Subject: [PATCH 09/20] added different return type support for function calling --- src/pipecat/services/openai.py | 69 +++++++----- tests/integration/integration_openai_llm.py | 112 ++++++++++++-------- 2 files changed, 112 insertions(+), 69 deletions(-) diff --git a/src/pipecat/services/openai.py b/src/pipecat/services/openai.py index 68a133660..c696f6723 100644 --- a/src/pipecat/services/openai.py +++ b/src/pipecat/services/openai.py @@ -184,34 +184,51 @@ async def _process_context(self, context: OpenAILLMContext): else: await self.push_frame(LLMFunctionCallFrame(function_name=function_name, arguments=arguments, tool_call_id=tool_call_id)) - async def _handle_function_call(self, context, tool_call_id, function_name, arguments): + async def _handle_function_call( + self, + context, + tool_call_id, + function_name, + arguments + ): result = await self._callbacks[function_name](self, arguments) - tool_call = ChatCompletionFunctionMessageParam({ - "role": "assistant", - "tool_calls": [ - { - "id": tool_call_id, - "function": { - "arguments": arguments, - "name": function_name - }, - "type": "function" - } - ] - - }) - context.add_message(tool_call) - if not isinstance(result, str): - result = json.dumps(result) - tool_result = ChatCompletionToolParam({ - "tool_call_id": tool_call_id, - "role": "tool", - "content": result - }) - context.add_message(tool_result) - # re-prompt to get a human answer - await self._process_context(context) + if isinstance(result, (str, dict)): + # Handle it in "full magic mode" + tool_call = ChatCompletionFunctionMessageParam({ + "role": "assistant", + "tool_calls": [ + { + "id": tool_call_id, + "function": { + "arguments": arguments, + "name": function_name + }, + "type": "function" + } + ] + + }) + context.add_message(tool_call) + if not isinstance(result, str): + result = json.dumps(result) + tool_result = ChatCompletionToolParam({ + "tool_call_id": tool_call_id, + "role": "tool", + "content": result + }) + context.add_message(tool_result) + # re-prompt to get a human answer + await self._process_context(context) + elif isinstance(result, list): + # reduced magic + for msg in result: + context.add_message(msg) + await self._process_context(context) + elif isinstance(result, None): + pass + else: + raise BaseException(f"Unknown return type from function callback: {type(result)}") async def process_frame(self, frame: Frame, direction: FrameDirection): context = None diff --git a/tests/integration/integration_openai_llm.py b/tests/integration/integration_openai_llm.py index a7a1ed186..bad4d651a 100644 --- a/tests/integration/integration_openai_llm.py +++ b/tests/integration/integration_openai_llm.py @@ -23,35 +23,35 @@ from pipecat.services.openai import OpenAILLMService +tools = [ + ChatCompletionToolParam( + type="function", + function={ + "name": "get_current_weather", + "description": "Get the current weather", + "parameters": { + "type": "object", + "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 users location.", + }, + }, + "required": [ + "location", + "format"], + }, + })] if __name__ == "__main__": - async def test_functions(handle=False): - tools = [ - ChatCompletionToolParam( - type="function", - function={ - "name": "get_current_weather", - "description": "Get the current weather", - "parameters": { - "type": "object", - "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 users location.", - }, - }, - "required": [ - "location", - "format"], - }, - })] + async def test_simple_functions(): async def get_weather_from_api(llm, args): return json.dumps({"conditions": "nice", "temperature": "75"}) @@ -63,20 +63,46 @@ async def get_weather_from_api(llm, args): model="gpt-4-1106-preview", ) - if (handle): - llm.register_function("get_current_weather", get_weather_from_api) - t = TestFrameProcessor([ - LLMFullResponseStartFrame, - [LLMResponseStartFrame, TextFrame, LLMResponseEndFrame], - LLMFullResponseEndFrame - ]) - else: - t = TestFrameProcessor([ - LLMFullResponseStartFrame, - LLMFunctionStartFrame, - LLMFunctionCallFrame, - LLMFullResponseEndFrame - ]) + llm.register_function("get_current_weather", get_weather_from_api) + t = TestFrameProcessor([ + LLMFullResponseStartFrame, + [LLMResponseStartFrame, TextFrame, LLMResponseEndFrame], + LLMFullResponseEndFrame + ]) + llm.link(t) + + context = OpenAILLMContext(tools=tools) + system_message: ChatCompletionSystemMessageParam = ChatCompletionSystemMessageParam( + content="Ask the user to ask for a weather report", name="system", role="system" + ) + user_message: ChatCompletionUserMessageParam = ChatCompletionUserMessageParam( + content="Could you tell me the weather for Boulder, Colorado", + name="user", + role="user", + ) + context.add_message(system_message) + context.add_message(user_message) + frame = OpenAILLMContextFrame(context) + await llm.process_frame(frame, FrameDirection.DOWNSTREAM) + + async def test_advanced_functions(): + + async def get_weather_from_api(llm, args): + return [{"role": "system", "content": "The user has asked for live weather. Respond by telling them we don't currently support live weather for that area, but it's coming soon."}] + + api_key = os.getenv("OPENAI_API_KEY") + + llm = OpenAILLMService( + api_key=api_key or "", + model="gpt-4-1106-preview", + ) + + llm.register_function("get_current_weather", get_weather_from_api) + t = TestFrameProcessor([ + LLMFullResponseStartFrame, + [LLMResponseStartFrame, TextFrame, LLMResponseEndFrame], + LLMFullResponseEndFrame + ]) llm.link(t) context = OpenAILLMContext(tools=tools) @@ -113,8 +139,8 @@ async def test_chat(): await llm.process_frame(frame, FrameDirection.DOWNSTREAM) async def run_tests(): - await test_functions(True) - await test_functions(False) + await test_simple_functions() + await test_advanced_functions() await test_chat() asyncio.run(run_tests()) From d048525a8b15bf2a8e4887d632b279b312ae62e4 Mon Sep 17 00:00:00 2001 From: Chad Bailey Date: Wed, 29 May 2024 17:06:37 +0000 Subject: [PATCH 10/20] intake example working --- examples/patient-intake/Dockerfile | 16 + examples/patient-intake/README.md | 37 ++ .../assets/clack-short-quiet.wav | Bin 0 -> 66522 bytes .../patient-intake/assets/clack-short.wav | Bin 0 -> 66522 bytes examples/patient-intake/assets/clack.wav | Bin 0 -> 105166 bytes examples/patient-intake/assets/ding.wav | Bin 0 -> 59154 bytes examples/patient-intake/assets/ding2.wav | Bin 0 -> 36980 bytes examples/patient-intake/assets/ding3.wav | Bin 0 -> 16696 bytes examples/patient-intake/bot.py | 361 ++++++++++++++++++ examples/patient-intake/env.example | 4 + examples/patient-intake/image.png | Bin 0 -> 750370 bytes examples/patient-intake/requirements.txt | 5 + examples/patient-intake/runner.py | 58 +++ examples/patient-intake/server.py | 124 ++++++ .../patient-intake/utils/daily_helpers.py | 109 ++++++ src/pipecat/services/openai.py | 4 +- 16 files changed, 717 insertions(+), 1 deletion(-) create mode 100644 examples/patient-intake/Dockerfile create mode 100644 examples/patient-intake/README.md create mode 100644 examples/patient-intake/assets/clack-short-quiet.wav create mode 100644 examples/patient-intake/assets/clack-short.wav create mode 100644 examples/patient-intake/assets/clack.wav create mode 100644 examples/patient-intake/assets/ding.wav create mode 100644 examples/patient-intake/assets/ding2.wav create mode 100644 examples/patient-intake/assets/ding3.wav create mode 100644 examples/patient-intake/bot.py create mode 100644 examples/patient-intake/env.example create mode 100644 examples/patient-intake/image.png create mode 100644 examples/patient-intake/requirements.txt create mode 100644 examples/patient-intake/runner.py create mode 100644 examples/patient-intake/server.py create mode 100644 examples/patient-intake/utils/daily_helpers.py diff --git a/examples/patient-intake/Dockerfile b/examples/patient-intake/Dockerfile new file mode 100644 index 000000000..704080eec --- /dev/null +++ b/examples/patient-intake/Dockerfile @@ -0,0 +1,16 @@ +FROM python:3.10-bullseye + +RUN mkdir /app +RUN mkdir /app/assets +RUN mkdir /app/utils +COPY *.py /app/ +COPY requirements.txt /app/ +copy assets/* /app/assets/ +copy utils/* /app/utils/ + +WORKDIR /app +RUN pip3 install -r requirements.txt + +EXPOSE 7860 + +CMD ["python3", "server.py"] \ No newline at end of file diff --git a/examples/patient-intake/README.md b/examples/patient-intake/README.md new file mode 100644 index 000000000..13c0b31e0 --- /dev/null +++ b/examples/patient-intake/README.md @@ -0,0 +1,37 @@ +# Simple Chatbot + + + +This app connects you to a chatbot powered by GPT-4, complete with animations generated by Stable Video Diffusion. + +See a video of it in action: https://x.com/kwindla/status/1778628911817183509 + +And a quick video walkthrough of the code: https://www.loom.com/share/13df1967161f4d24ade054e7f8753416 + +ℹ️ The first time, things might take extra time to get started since VAD (Voice Activity Detection) model needs to be downloaded. + +## Get started + +```python +python3 -m venv venv +source venv/bin/activate +pip install -r requirements.txt + +cp env.example .env # and add your credentials + +``` + +## Run the server + +```bash +python server.py +``` + +Then, visit `http://localhost:7860/start` in your browser to start a chatbot session. + +## Build and test the Docker image + +``` +docker build -t chatbot . +docker run --env-file .env -p 7860:7860 chatbot +``` diff --git a/examples/patient-intake/assets/clack-short-quiet.wav b/examples/patient-intake/assets/clack-short-quiet.wav new file mode 100644 index 0000000000000000000000000000000000000000..f0580d11e76b41e4ebff89f3f97ded6e12f2fe0e GIT binary patch literal 66522 zcmXV(1z1(f*T!e|Ig|(jq9}HE7k1aRyRbX4>w4|JcDG_(ySux)I}t_2B2Vm@@3;AX z&v}63IXh-nyz5CbEc7kzV-m6DoZ9otaMp zMF!z7Qi+Uw?k&88(n&f&$MO@e9lZa=`&j)|N9o`C4}X)iTibRM<`4z@ZQR$+l~OZaYa9W*QZv_Jk%k{{W}lJSXW(}hkx671xkNs+kwfGcxkXMs z$;v0Wc$XcmWfLJB7b4Q}vgQ|z&I0-C)&WS;lB&Tgj*(lsv-F~nrpXw*_$~R)#dkK5 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Creating room") + room_url, room_name = _create_room() + print(f"!!! Room URL: {room_url}") + # Ensure the room property is present + if not room_url: + raise HTTPException( + status_code=500, + detail="Missing 'room' property in request data. Cannot start agent without a target room!") + + # Check if there is already an existing process running in this room + num_bots_in_room = sum( + 1 for proc in bot_procs.values() if proc[1] == room_url and proc[0].poll() is None) + if num_bots_in_room >= MAX_BOTS_PER_ROOM: + raise HTTPException( + status_code=500, detail=f"Max bot limited reach for room: {room_url}") + + # Get the token for the room + token = get_token(room_url) + + if not token: + raise HTTPException( + status_code=500, detail=f"Failed to get token for room: {room_url}") + + # Spawn a new agent, and join the user session + # Note: this is mostly for demonstration purposes (refer to 'deployment' in README) + try: + proc = subprocess.Popen( + [ + f"python3 -m bot -u {room_url} -t {token}" + ], + shell=True, + bufsize=1, + cwd=os.path.dirname(os.path.abspath(__file__)) + ) + bot_procs[proc.pid] = (proc, room_url) + except Exception as e: + raise HTTPException( + status_code=500, detail=f"Failed to start subprocess: {e}") + + return RedirectResponse(room_url) + + +@app.get("/status/{pid}") +def get_status(pid: int): + # Look up the subprocess + proc = bot_procs.get(pid) + + # If the subprocess doesn't exist, return an error + if not proc: + raise HTTPException( + status_code=404, detail=f"Bot with process id: {pid} not found") + + # Check the status of the subprocess + if proc[0].poll() is None: + status = "running" + else: + status = "finished" + + return JSONResponse({"bot_id": pid, "status": status}) + + +if __name__ == "__main__": + import uvicorn + + default_host = os.getenv("HOST", "0.0.0.0") + default_port = int(os.getenv("FAST_API_PORT", "7860")) + + parser = argparse.ArgumentParser( + description="Daily Storyteller FastAPI server") + parser.add_argument("--host", type=str, + default=default_host, help="Host address") + parser.add_argument("--port", type=int, + default=default_port, help="Port number") + parser.add_argument("--reload", action="store_true", + help="Reload code on change") + + config = parser.parse_args() + print(f"to join a test room, visit http://localhost:{config.port}/start") + uvicorn.run( + "server:app", + host=config.host, + port=config.port, + reload=config.reload, + ) diff --git a/examples/patient-intake/utils/daily_helpers.py b/examples/patient-intake/utils/daily_helpers.py new file mode 100644 index 000000000..140f710e4 --- /dev/null +++ b/examples/patient-intake/utils/daily_helpers.py @@ -0,0 +1,109 @@ + +import urllib.parse +import os +import time +import urllib +import requests + +from dotenv import load_dotenv +load_dotenv() + + +daily_api_path = os.getenv("DAILY_API_URL") or "api.daily.co/v1" +daily_api_key = os.getenv("DAILY_API_KEY") + + +def create_room() -> tuple[str, str]: + """ + Helper function to create a Daily room. + # See: https://docs.daily.co/reference/rest-api/rooms + + Returns: + tuple: A tuple containing the room URL and room name. + + Raises: + Exception: If the request to create the room fails or if the response does not contain the room URL or room name. + """ + room_props = { + "exp": time.time() + 60 * 60, # 1 hour + "enable_chat": True, + "enable_emoji_reactions": True, + "eject_at_room_exp": True, + "enable_prejoin_ui": False, # Important for the bot to be able to join headlessly + } + res = requests.post( + f"https://{daily_api_path}/rooms", + headers={"Authorization": f"Bearer {daily_api_key}"}, + json={ + "properties": room_props + }, + ) + if res.status_code != 200: + raise Exception(f"Unable to create room: {res.text}") + + data = res.json() + room_url: str = data.get("url") + room_name: str = data.get("name") + if room_url is None or room_name is None: + raise Exception("Missing room URL or room name in response") + + return room_url, room_name + + +def get_name_from_url(room_url: str) -> str: + """ + Extracts the name from a given room URL. + + Args: + room_url (str): The URL of the room. + + Returns: + str: The extracted name from the room URL. + """ + return urllib.parse.urlparse(room_url).path[1:] + + +def get_token(room_url: str) -> str: + """ + Retrieves a meeting token for the specified Daily room URL. + # See: https://docs.daily.co/reference/rest-api/meeting-tokens + + Args: + room_url (str): The URL of the Daily room. + + Returns: + str: The meeting token. + + Raises: + Exception: If no room URL is specified or if no Daily API key is specified. + Exception: If there is an error creating the meeting token. + """ + if not room_url: + raise Exception( + "No Daily room specified. You must specify a Daily room in order a token to be generated.") + + if not daily_api_key: + raise Exception( + "No Daily API key specified. set DAILY_API_KEY in your environment to specify a Daily API key, available from https://dashboard.daily.co/developers.") + + expiration: float = time.time() + 60 * 60 + room_name = get_name_from_url(room_url) + + res: requests.Response = requests.post( + f"https://{daily_api_path}/meeting-tokens", + headers={ + "Authorization": f"Bearer {daily_api_key}"}, + json={ + "properties": { + "room_name": room_name, + "is_owner": True, # Owner tokens required for transcription + "exp": expiration}}, + ) + + if res.status_code != 200: + raise Exception( + f"Failed to create meeting token: {res.status_code} {res.text}") + + token: str = res.json()["token"] + + return token diff --git a/src/pipecat/services/openai.py b/src/pipecat/services/openai.py index c696f6723..6162c2108 100644 --- a/src/pipecat/services/openai.py +++ b/src/pipecat/services/openai.py @@ -191,6 +191,7 @@ async def _handle_function_call( function_name, arguments ): + arguments = json.loads(arguments) result = await self._callbacks[function_name](self, arguments) if isinstance(result, (str, dict)): @@ -225,12 +226,13 @@ async def _handle_function_call( for msg in result: context.add_message(msg) await self._process_context(context) - elif isinstance(result, None): + elif isinstance(result, type(None)): pass else: raise BaseException(f"Unknown return type from function callback: {type(result)}") async def process_frame(self, frame: Frame, direction: FrameDirection): + print(f"@@@ in process frame with: {frame}") context = None if isinstance(frame, OpenAILLMContextFrame): context: OpenAILLMContext = frame.context From 8cb0ee307031b065aef33ec93837495ed9367369 Mon Sep 17 00:00:00 2001 From: Chad Bailey Date: Wed, 29 May 2024 19:47:28 +0000 Subject: [PATCH 11/20] added frame loggers --- examples/patient-intake/bot.py | 13 ++++++++----- 1 file changed, 8 insertions(+), 5 deletions(-) diff --git a/examples/patient-intake/bot.py b/examples/patient-intake/bot.py index 4517f1a97..e2033dbf6 100644 --- a/examples/patient-intake/bot.py +++ b/examples/patient-intake/bot.py @@ -303,7 +303,7 @@ async def main(room_url: str, token): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - model="gpt-4-turbo") + model="gpt-4o") messages = [] context = OpenAILLMContext( @@ -330,20 +330,23 @@ async def main(room_url: str, token): "list_visit_reasons", intake.save_data, start_callback=intake.start_visit_reasons) - fl = FrameLogger("after transport output") - fltts = FrameLogger("### out of tts") + fl = FrameLogger("!!! after LLM") + fltts = FrameLogger("@@@ out of tts") + flend = FrameLogger("### out of the end") pipeline = Pipeline([ transport.input(), user_context, llm, + fl, tts, - # fltts, + fltts, transport.output(), assistant_context, + flend # fl ]) - task = PipelineTask(pipeline, allow_interruptions=True) + task = PipelineTask(pipeline, allow_interruptions=False) @transport.event_handler("on_first_participant_joined") async def on_first_participant_joined(transport, participant): From 7bde9c8dcc5289a8956d410346dd06dbe3f341fa Mon Sep 17 00:00:00 2001 From: Chad Bailey Date: Thu, 30 May 2024 14:33:36 +0000 Subject: [PATCH 12/20] cleanup --- examples/foundational/06-listen-and-respond.py | 14 ++++++++------ examples/patient-intake/bot.py | 8 ++------ src/pipecat/processors/logger.py | 17 +++++++++++------ src/pipecat/services/azure.py | 2 +- src/pipecat/services/elevenlabs.py | 2 +- src/pipecat/transports/base_output.py | 3 ++- 6 files changed, 25 insertions(+), 21 deletions(-) diff --git a/examples/foundational/06-listen-and-respond.py b/examples/foundational/06-listen-and-respond.py index a0475bd4b..480b64996 100644 --- a/examples/foundational/06-listen-and-respond.py +++ b/examples/foundational/06-listen-and-respond.py @@ -56,10 +56,11 @@ async def main(room_url: str, token): llm = OpenAILLMService( api_key=os.getenv("OPENAI_API_KEY"), - model="gpt-4-turbo-preview") + model="gpt-4o") - fl_in = FrameLogger("Inner") - fl_out = FrameLogger("Outer") + fl = FrameLogger("!!! after LLM", "red") + fltts = FrameLogger("@@@ out of tts", "green") + flend = FrameLogger("### out of the end", "magenta") messages = [ { @@ -71,14 +72,15 @@ async def main(room_url: str, token): tma_out = LLMAssistantResponseAggregator(messages) pipeline = Pipeline([ - fl_in, transport.input(), tma_in, llm, - fl_out, + fl, tts, + fltts, transport.output(), - tma_out + tma_out, + flend ]) task = PipelineTask(pipeline) diff --git a/examples/patient-intake/bot.py b/examples/patient-intake/bot.py index e2033dbf6..48adf6e0e 100644 --- a/examples/patient-intake/bot.py +++ b/examples/patient-intake/bot.py @@ -330,20 +330,16 @@ async def main(room_url: str, token): "list_visit_reasons", intake.save_data, start_callback=intake.start_visit_reasons) - fl = FrameLogger("!!! after LLM") - fltts = FrameLogger("@@@ out of tts") - flend = FrameLogger("### out of the end") + fl = FrameLogger("LLM Output") + pipeline = Pipeline([ transport.input(), user_context, llm, fl, tts, - fltts, transport.output(), assistant_context, - flend - # fl ]) task = PipelineTask(pipeline, allow_interruptions=False) diff --git a/src/pipecat/processors/logger.py b/src/pipecat/processors/logger.py index c8b2f10dc..6f07548af 100644 --- a/src/pipecat/processors/logger.py +++ b/src/pipecat/processors/logger.py @@ -6,17 +6,22 @@ from pipecat.frames.frames import Frame from pipecat.processors.frame_processor import FrameDirection, FrameProcessor +from loguru import logger +from typing import Optional +logger = logger.opt(ansi=True) class FrameLogger(FrameProcessor): - def __init__(self, prefix="Frame"): + def __init__(self, prefix="Frame", color: Optional[str] = None): super().__init__() self._prefix = prefix + self._color = color async def process_frame(self, frame: Frame, direction: FrameDirection): - match direction: - case FrameDirection.UPSTREAM: - print(f"< {self._prefix}: {frame}") - case FrameDirection.DOWNSTREAM: - print(f"> {self._prefix}: {frame}") + dir = "<" if direction is FrameDirection.UPSTREAM else ">" + msg = f"{dir} {self._prefix}: {frame}" + if self._color: + msg = f"<{self._color}>{msg}" + logger.debug(msg) + await self.push_frame(frame, direction) diff --git a/src/pipecat/services/azure.py b/src/pipecat/services/azure.py index 080e3680e..216d0555b 100644 --- a/src/pipecat/services/azure.py +++ b/src/pipecat/services/azure.py @@ -46,7 +46,7 @@ def __init__(self, *, api_key: str, region: str, voice="en-US-SaraNeural", **kwa self._voice = voice async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: - logger.debug(f"Transcribing text: {text}") + logger.debug(f"Generating TTS: {text}") ssml = ( " AsyncGenerator[Frame, None]: - logger.debug(f"Transcribing text: [{text}]") + logger.debug(f"Generating TTS: [{text}]") url = f"https://api.elevenlabs.io/v1/text-to-speech/{self._voice_id}/stream" diff --git a/src/pipecat/transports/base_output.py b/src/pipecat/transports/base_output.py index 6106eaefa..146c58496 100644 --- a/src/pipecat/transports/base_output.py +++ b/src/pipecat/transports/base_output.py @@ -158,7 +158,6 @@ def _sink_thread_handler(self): while self._running: try: frame = self._sink_queue.get(timeout=1) - if not self._is_interrupted.is_set(): if isinstance(frame, AudioRawFrame): if self._params.audio_out_enabled: @@ -252,6 +251,8 @@ def _camera_out_thread_handler(self): image = next(self._camera_images) self._draw_image(image) time.sleep(1.0 / self._params.camera_out_framerate) + else: + time.sleep(1.0 / self._params.camera_out_framerate) except queue.Empty: pass except Exception as e: From fcbe4804edab0e5196adb662e7e0776256fef0f1 Mon Sep 17 00:00:00 2001 From: Chad Bailey Date: Thu, 30 May 2024 14:43:40 +0000 Subject: [PATCH 13/20] fixup --- examples/patient-intake/bot.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/examples/patient-intake/bot.py b/examples/patient-intake/bot.py index 48adf6e0e..dae366fe2 100644 --- a/examples/patient-intake/bot.py +++ b/examples/patient-intake/bot.py @@ -106,7 +106,6 @@ def __init__( ] async def verify_birthday(self, llm, args): - print(f"!!! checking birthday! Happy birthday! the user said {args}, {type(args)}") if args["birthday"] == "1983-01-01": self._context.set_tools( [ @@ -137,6 +136,8 @@ async def verify_birthday(self, llm, args): }, }, }]) + # It's a bit weird to push this to the LLM, but it gets it into the pipeline + await llm.push_frame(sounds["ding2.wav"], FrameDirection.DOWNSTREAM) # We don't need the function call in the context, so just return a new # system message and let the framework re-prompt return [{"role": "system", "content": "Next, thank the user for confirming their identity, then ask the user to list their current prescriptions. Each prescription needs to have a medication name and a dosage. Do not call the list_prescriptions function with any unknown dosages."}] From c4d01a23f45f7f5d6924d4a27e0aaf7f3396bb37 Mon Sep 17 00:00:00 2001 From: chadbailey59 Date: Thu, 30 May 2024 10:50:31 -0500 Subject: [PATCH 14/20] Update openai.py --- src/pipecat/services/openai.py | 1 - 1 file changed, 1 deletion(-) diff --git a/src/pipecat/services/openai.py b/src/pipecat/services/openai.py index 6162c2108..8219f3711 100644 --- a/src/pipecat/services/openai.py +++ b/src/pipecat/services/openai.py @@ -232,7 +232,6 @@ async def _handle_function_call( raise BaseException(f"Unknown return type from function callback: {type(result)}") async def process_frame(self, frame: Frame, direction: FrameDirection): - print(f"@@@ in process frame with: {frame}") context = None if isinstance(frame, OpenAILLMContextFrame): context: OpenAILLMContext = frame.context From d2351823ab001884e9bcb8ef55726b9ed292f402 Mon Sep 17 00:00:00 2001 From: Chad Bailey Date: Thu, 30 May 2024 16:21:29 +0000 Subject: [PATCH 15/20] removed function call frame types --- examples/foundational/14-function-calling.py | 2 -- examples/patient-intake/bot.py | 2 -- src/pipecat/frames/frames.py | 17 ----------------- src/pipecat/services/openai.py | 19 +++++++++---------- tests/integration/integration_openai_llm.py | 2 -- 5 files changed, 9 insertions(+), 33 deletions(-) diff --git a/examples/foundational/14-function-calling.py b/examples/foundational/14-function-calling.py index 2bc21885a..124e9648f 100644 --- a/examples/foundational/14-function-calling.py +++ b/examples/foundational/14-function-calling.py @@ -36,8 +36,6 @@ LLMFullResponseEndFrame, LLMResponseEndFrame, LLMResponseStartFrame, - LLMFunctionCallFrame, - LLMFunctionStartFrame, TextFrame ) diff --git a/examples/patient-intake/bot.py b/examples/patient-intake/bot.py index dae366fe2..a24161e1a 100644 --- a/examples/patient-intake/bot.py +++ b/examples/patient-intake/bot.py @@ -22,8 +22,6 @@ from pipecat.frames.frames import ( Frame, LLMMessagesFrame, - LLMFunctionCallFrame, - LLMFunctionStartFrame, AudioRawFrame, ) from pipecat.processors.frame_processor import FrameDirection, FrameProcessor diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index c960b99b8..16989741f 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -110,23 +110,6 @@ def __str__(self): return f"{self.name}(size: {len(self.images)})" -@dataclass() -class LLMFunctionStartFrame(Frame): - """Emitted when the LLM receives the beginning of a function call - completion. A frame processor can use this frame to indicate that it should - start preparing to make a function call, if it can do so in the absence of - any arguments.""" - function_name: str - tool_call_id: str - - -@dataclass() -class LLMFunctionCallFrame(Frame): - """Emitted when the LLM has received an entire function call completion.""" - function_name: str - tool_call_id: str - arguments: str - @dataclass class TextFrame(DataFrame): diff --git a/src/pipecat/services/openai.py b/src/pipecat/services/openai.py index 8219f3711..c1a5f8a2f 100644 --- a/src/pipecat/services/openai.py +++ b/src/pipecat/services/openai.py @@ -17,10 +17,8 @@ from pipecat.frames.frames import ( ErrorFrame, Frame, - LLMFunctionCallFrame, LLMFullResponseEndFrame, LLMFullResponseStartFrame, - LLMFunctionStartFrame, LLMMessagesFrame, LLMResponseEndFrame, LLMResponseStartFrame, @@ -54,6 +52,10 @@ raise Exception(f"Missing module: {e}") +class OpenAIUnhandledFunctionException(BaseException): + pass + + class BaseOpenAILLMService(LLMService): """This is the base for all services that use the AsyncOpenAI client. @@ -161,12 +163,8 @@ async def _process_context(self, context: OpenAILLMContext): if function_name in self._callbacks.keys(): if function_name in self._start_callbacks.keys(): await self._start_callbacks[function_name](self) - else: - await self.push_frame(LLMFunctionStartFrame(function_name=tool_call.function.name, tool_call_id=tool_call_id)) if tool_call.function and tool_call.function.arguments: - # Keep iterating through the response to collect all the argument fragments and - # yield a complete LLMFunctionCallFrame after run_llm_async - # completes + # Keep iterating through the response to collect all the argument fragments arguments += tool_call.function.arguments elif chunk.choices[0].delta.content: await self.push_frame(LLMResponseStartFrame()) @@ -176,13 +174,14 @@ async def _process_context(self, context: OpenAILLMContext): # if we got a function name and arguments, check to see if it's a function with # a registered handler. If so, run the registered callback, save the result to # the context, and re-prompt to get a chat answer. If we don't have a registered - # handler, push an LLMFunctionCallFrame and let the pipeline deal with it. + # handler, raise an exception. if function_name and arguments: if function_name in self._callbacks.keys(): await self._handle_function_call(context, tool_call_id, function_name, arguments) else: - await self.push_frame(LLMFunctionCallFrame(function_name=function_name, arguments=arguments, tool_call_id=tool_call_id)) + raise OpenAIUnhandledFunctionException( + f"The LLM tried to call a function named '{function_name}', but there isn't a callback registered for that function.") async def _handle_function_call( self, @@ -193,7 +192,7 @@ async def _handle_function_call( ): arguments = json.loads(arguments) result = await self._callbacks[function_name](self, arguments) - + arguments = json.dumps(arguments) if isinstance(result, (str, dict)): # Handle it in "full magic mode" tool_call = ChatCompletionFunctionMessageParam({ diff --git a/tests/integration/integration_openai_llm.py b/tests/integration/integration_openai_llm.py index bad4d651a..c993a9adb 100644 --- a/tests/integration/integration_openai_llm.py +++ b/tests/integration/integration_openai_llm.py @@ -10,8 +10,6 @@ LLMFullResponseEndFrame, LLMResponseEndFrame, LLMResponseStartFrame, - LLMFunctionCallFrame, - LLMFunctionStartFrame, TextFrame ) from pipecat.utils.test_frame_processor import TestFrameProcessor From 89fe4ab2bfc7bc7c99b2c03176bcb9b4ebc47b53 Mon Sep 17 00:00:00 2001 From: Chad Bailey Date: Thu, 30 May 2024 16:38:58 +0000 Subject: [PATCH 16/20] fixup --- src/pipecat/services/openai.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/pipecat/services/openai.py b/src/pipecat/services/openai.py index c1a5f8a2f..5c9298d69 100644 --- a/src/pipecat/services/openai.py +++ b/src/pipecat/services/openai.py @@ -210,7 +210,7 @@ async def _handle_function_call( }) context.add_message(tool_call) - if not isinstance(result, str): + if isinstance(result, dict): result = json.dumps(result) tool_result = ChatCompletionToolParam({ "tool_call_id": tool_call_id, From c384720d1708fe0f82b940b6c01df03025386586 Mon Sep 17 00:00:00 2001 From: Chad Bailey Date: Thu, 30 May 2024 16:42:21 +0000 Subject: [PATCH 17/20] re-added example --- examples/foundational/14-wake-phrase.py | 94 +++++++++++++++++++++++++ 1 file changed, 94 insertions(+) create mode 100644 examples/foundational/14-wake-phrase.py diff --git a/examples/foundational/14-wake-phrase.py b/examples/foundational/14-wake-phrase.py new file mode 100644 index 000000000..853bac4e3 --- /dev/null +++ b/examples/foundational/14-wake-phrase.py @@ -0,0 +1,94 @@ +# +# Copyright (c) 2024, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import aiohttp +import os +import sys + +from pipecat.processors.filters.wake_check_filter import WakeCheckFilter +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_response import ( + LLMAssistantResponseAggregator, LLMUserResponseAggregator) +from pipecat.services.elevenlabs import ElevenLabsTTSService +from pipecat.services.openai import OpenAILLMService +from pipecat.transports.services.daily import DailyParams, DailyTransport +from pipecat.vad.silero import SileroVADAnalyzer + +from runner import configure + +from loguru import logger + +from dotenv import load_dotenv +load_dotenv(override=True) + +logger.remove(0) +logger.add(sys.stderr, level="DEBUG") + + +async def main(room_url: str, token): + + async with aiohttp.ClientSession() as session: + transport = DailyTransport( + room_url, + token, + "Robot", + DailyParams( + audio_out_enabled=True, + transcription_enabled=True, + vad_enabled=True, + vad_analyzer=SileroVADAnalyzer() + ) + ) + + tts = ElevenLabsTTSService( + aiohttp_session=session, + api_key=os.getenv("ELEVENLABS_API_KEY"), + voice_id=os.getenv("ELEVENLABS_VOICE_ID"), + ) + + llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + model="gpt-4o") + + messages = [ + { + "role": "system", + "content": "You are a helpful assistant. Respond to what the user said in a creative and helpful way. Keep your responses brief.", + }, + ] + + hey_robot_filter = WakeCheckFilter(["hey robot", "hey, robot"]) + tma_in = LLMUserResponseAggregator(messages) + tma_out = LLMAssistantResponseAggregator(messages) + + pipeline = Pipeline([ + transport.input(), # Transport user input + hey_robot_filter, # Filter out speech not directed at the robot + tma_in, # User responses + llm, # LLM + tts, # TTS + transport.output(), # Transport bot output + tma_out # Assistant spoken responses + ]) + + task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True)) + + @transport.event_handler("on_first_participant_joined") + async def on_first_participant_joined(transport, participant): + transport.capture_participant_transcription(participant["id"]) + await tts.say("Hi! If you want to talk to me, just say 'Hey Robot'.") + + runner = PipelineRunner() + + await runner.run(task) + + +if __name__ == "__main__": + (url, token) = configure() + asyncio.run(main(url, token)) From ed70c71311458b4eb12521cc413a4378844402fe Mon Sep 17 00:00:00 2001 From: Chad Bailey Date: Thu, 30 May 2024 16:42:37 +0000 Subject: [PATCH 18/20] renumbered wake phrase --- examples/foundational/14-wake-phrase.py | 94 ------------------------- 1 file changed, 94 deletions(-) delete mode 100644 examples/foundational/14-wake-phrase.py diff --git a/examples/foundational/14-wake-phrase.py b/examples/foundational/14-wake-phrase.py deleted file mode 100644 index 853bac4e3..000000000 --- a/examples/foundational/14-wake-phrase.py +++ /dev/null @@ -1,94 +0,0 @@ -# -# Copyright (c) 2024, Daily -# -# SPDX-License-Identifier: BSD 2-Clause License -# - -import asyncio -import aiohttp -import os -import sys - -from pipecat.processors.filters.wake_check_filter import WakeCheckFilter -from pipecat.pipeline.pipeline import Pipeline -from pipecat.pipeline.runner import PipelineRunner -from pipecat.pipeline.task import PipelineParams, PipelineTask -from pipecat.processors.aggregators.llm_response import ( - LLMAssistantResponseAggregator, LLMUserResponseAggregator) -from pipecat.services.elevenlabs import ElevenLabsTTSService -from pipecat.services.openai import OpenAILLMService -from pipecat.transports.services.daily import DailyParams, DailyTransport -from pipecat.vad.silero import SileroVADAnalyzer - -from runner import configure - -from loguru import logger - -from dotenv import load_dotenv -load_dotenv(override=True) - -logger.remove(0) -logger.add(sys.stderr, level="DEBUG") - - -async def main(room_url: str, token): - - async with aiohttp.ClientSession() as session: - transport = DailyTransport( - room_url, - token, - "Robot", - DailyParams( - audio_out_enabled=True, - transcription_enabled=True, - vad_enabled=True, - vad_analyzer=SileroVADAnalyzer() - ) - ) - - tts = ElevenLabsTTSService( - aiohttp_session=session, - api_key=os.getenv("ELEVENLABS_API_KEY"), - voice_id=os.getenv("ELEVENLABS_VOICE_ID"), - ) - - llm = OpenAILLMService( - api_key=os.getenv("OPENAI_API_KEY"), - model="gpt-4o") - - messages = [ - { - "role": "system", - "content": "You are a helpful assistant. Respond to what the user said in a creative and helpful way. Keep your responses brief.", - }, - ] - - hey_robot_filter = WakeCheckFilter(["hey robot", "hey, robot"]) - tma_in = LLMUserResponseAggregator(messages) - tma_out = LLMAssistantResponseAggregator(messages) - - pipeline = Pipeline([ - transport.input(), # Transport user input - hey_robot_filter, # Filter out speech not directed at the robot - tma_in, # User responses - llm, # LLM - tts, # TTS - transport.output(), # Transport bot output - tma_out # Assistant spoken responses - ]) - - task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True)) - - @transport.event_handler("on_first_participant_joined") - async def on_first_participant_joined(transport, participant): - transport.capture_participant_transcription(participant["id"]) - await tts.say("Hi! If you want to talk to me, just say 'Hey Robot'.") - - runner = PipelineRunner() - - await runner.run(task) - - -if __name__ == "__main__": - (url, token) = configure() - asyncio.run(main(url, token)) From 9ee9010397bec5d06c584cd64bf4bcc521600a52 Mon Sep 17 00:00:00 2001 From: Chad Bailey Date: Thu, 30 May 2024 17:22:56 +0000 Subject: [PATCH 19/20] fixup for autopep8 --- src/pipecat/frames/frames.py | 1 - 1 file changed, 1 deletion(-) diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index 16989741f..8eb32664c 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -110,7 +110,6 @@ def __str__(self): return f"{self.name}(size: {len(self.images)})" - @dataclass class TextFrame(DataFrame): """A chunk of text. Emitted by LLM services, consumed by TTS services, can From f97ab3dc8ae9f395f194676cedd24225944fa09a Mon Sep 17 00:00:00 2001 From: Chad Bailey Date: Thu, 30 May 2024 17:25:17 +0000 Subject: [PATCH 20/20] remove unused imports --- examples/foundational/14-function-calling.py | 11 +---------- 1 file changed, 1 insertion(+), 10 deletions(-) diff --git a/examples/foundational/14-function-calling.py b/examples/foundational/14-function-calling.py index 124e9648f..aab799ae9 100644 --- a/examples/foundational/14-function-calling.py +++ b/examples/foundational/14-function-calling.py @@ -10,8 +10,6 @@ import json import sys -from pipecat.frames.frames import LLMMessagesFrame, Frame -from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineTask @@ -19,23 +17,16 @@ LLMAssistantContextAggregator, LLMUserContextAggregator, ) -from pipecat.services.openai import OpenAILLMContextFrame, OpenAILLMContext +from pipecat.services.openai import OpenAILLMContext from pipecat.processors.logger import FrameLogger from pipecat.services.elevenlabs import ElevenLabsTTSService from pipecat.services.openai import OpenAILLMService from pipecat.transports.services.daily import DailyParams, DailyTransport from pipecat.vad.silero import SileroVADAnalyzer from openai.types.chat import ( - ChatCompletionSystemMessageParam, - ChatCompletionFunctionMessageParam, ChatCompletionToolParam, - ChatCompletionUserMessageParam, ) from pipecat.frames.frames import ( - LLMFullResponseStartFrame, - LLMFullResponseEndFrame, - LLMResponseEndFrame, - LLMResponseStartFrame, TextFrame )