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updated the example to use stereo audio and pass in the context. also updated the service to send the transcripts if they're available

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This commit is contained in:
Adrian Cowham
2025-01-16 13:12:38 -08:00
parent 8b602a3f62
commit d0b48c95bb
2 changed files with 8 additions and 3 deletions
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3
examples/canonical-metrics/bot.py
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@@ -97,7 +97,7 @@ async def main():
call completion, CanonicalMetrics will send the audio buffer to Canonical for call completion, CanonicalMetrics will send the audio buffer to Canonical for
analysis. Visit https://voice.canonical.chat to learn more. analysis. Visit https://voice.canonical.chat to learn more.
""" """
audio_buffer_processor = AudioBufferProcessor() audio_buffer_processor = AudioBufferProcessor(num_channels=2)
canonical = CanonicalMetricsService( canonical = CanonicalMetricsService(
audio_buffer_processor=audio_buffer_processor, audio_buffer_processor=audio_buffer_processor,
aiohttp_session=session, aiohttp_session=session,
@@ -105,6 +105,7 @@ async def main():
call_id=str(uuid.uuid4()), call_id=str(uuid.uuid4()),
assistant="pipecat-chatbot", assistant="pipecat-chatbot",
assistant_speaks_first=True, assistant_speaks_first=True,
context=context,
) )
pipeline = Pipeline( pipeline = Pipeline(
[ [

8
src/pipecat/services/canonical.py
View File

@@ -15,10 +15,9 @@ import aiohttp
from loguru import logger from loguru import logger
from pipecat.frames.frames import CancelFrame, EndFrame, Frame from pipecat.frames.frames import CancelFrame, EndFrame, Frame
from pipecat.processors.audio import audio_buffer_processor from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.processors.audio.audio_buffer_processor import AudioBufferProcessor from pipecat.processors.audio.audio_buffer_processor import AudioBufferProcessor
from pipecat.processors.frame_processor import FrameDirection from pipecat.processors.frame_processor import FrameDirection
from pipecat.services.ai_services import AIService
try: try:
import aiofiles import aiofiles
@@ -69,6 +68,7 @@ class CanonicalMetricsService(AIService):
api_url: str = "https://voiceapp.canonical.chat/api/v1", api_url: str = "https://voiceapp.canonical.chat/api/v1",
assistant_speaks_first: bool = True, assistant_speaks_first: bool = True,
output_dir: str = "recordings", output_dir: str = "recordings",
context: OpenAILLMContext | None = None,
**kwargs, **kwargs,
): ):
super().__init__(**kwargs) super().__init__(**kwargs)
@@ -80,6 +80,7 @@ class CanonicalMetricsService(AIService):
self._assistant = assistant self._assistant = assistant
self._assistant_speaks_first = assistant_speaks_first self._assistant_speaks_first = assistant_speaks_first
self._output_dir = output_dir self._output_dir = output_dir
self._context = context
async def stop(self, frame: EndFrame): async def stop(self, frame: EndFrame):
await super().stop(frame) await super().stop(frame)
@@ -190,6 +191,9 @@ class CanonicalMetricsService(AIService):
"callId": self._call_id, "callId": self._call_id,
"assistant": {"id": self._assistant, "speaksFirst": self._assistant_speaks_first}, "assistant": {"id": self._assistant, "speaksFirst": self._assistant_speaks_first},
} }
if self._context is not None:
params["transcript"] = self._context.messages
logger.debug(f"Completing upload for {params['filename']}") logger.debug(f"Completing upload for {params['filename']}")
logger.debug(f"Slug: {params['slug']}") logger.debug(f"Slug: {params['slug']}")
response = await self._aiohttp_session.post( response = await self._aiohttp_session.post(