Additional LLM and TTS metrics (#343)
* added llm and tts usage metrics * Metrics debug logging * cleanup
This commit is contained in:
@@ -9,14 +9,15 @@ import aiohttp
|
|||||||
import os
|
import os
|
||||||
import sys
|
import sys
|
||||||
|
|
||||||
from pipecat.frames.frames import LLMMessagesFrame
|
from pipecat.frames.frames import Frame, LLMMessagesFrame, MetricsFrame
|
||||||
from pipecat.pipeline.pipeline import Pipeline
|
from pipecat.pipeline.pipeline import Pipeline
|
||||||
from pipecat.pipeline.runner import PipelineRunner
|
from pipecat.pipeline.runner import PipelineRunner
|
||||||
from pipecat.pipeline.task import PipelineTask
|
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||||
from pipecat.processors.aggregators.llm_response import (
|
from pipecat.processors.aggregators.llm_response import (
|
||||||
LLMAssistantResponseAggregator,
|
LLMAssistantResponseAggregator,
|
||||||
LLMUserResponseAggregator,
|
LLMUserResponseAggregator,
|
||||||
)
|
)
|
||||||
|
from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
|
||||||
from pipecat.processors.logger import FrameLogger
|
from pipecat.processors.logger import FrameLogger
|
||||||
from pipecat.services.elevenlabs import ElevenLabsTTSService
|
from pipecat.services.elevenlabs import ElevenLabsTTSService
|
||||||
from pipecat.services.openai import OpenAILLMService
|
from pipecat.services.openai import OpenAILLMService
|
||||||
@@ -34,6 +35,14 @@ logger.remove(0)
|
|||||||
logger.add(sys.stderr, level="DEBUG")
|
logger.add(sys.stderr, level="DEBUG")
|
||||||
|
|
||||||
|
|
||||||
|
class MetricsLogger(FrameProcessor):
|
||||||
|
async def process_frame(self, frame: Frame, direction: FrameDirection):
|
||||||
|
if isinstance(frame, MetricsFrame):
|
||||||
|
print(
|
||||||
|
f"!!! MetricsFrame: {frame}, ttfb: {frame.ttfb}, processing: {frame.processing}, tokens: {frame.tokens}, characters: {frame.characters}")
|
||||||
|
await self.push_frame(frame, direction)
|
||||||
|
|
||||||
|
|
||||||
async def main():
|
async def main():
|
||||||
async with aiohttp.ClientSession() as session:
|
async with aiohttp.ClientSession() as session:
|
||||||
(room_url, token) = await configure(session)
|
(room_url, token) = await configure(session)
|
||||||
@@ -58,11 +67,10 @@ async def main():
|
|||||||
|
|
||||||
llm = OpenAILLMService(
|
llm = OpenAILLMService(
|
||||||
api_key=os.getenv("OPENAI_API_KEY"),
|
api_key=os.getenv("OPENAI_API_KEY"),
|
||||||
model="gpt-4o")
|
model="gpt-4o"
|
||||||
|
)
|
||||||
|
|
||||||
fl = FrameLogger("!!! after LLM", "red")
|
ml = MetricsLogger()
|
||||||
fltts = FrameLogger("@@@ out of tts", "green")
|
|
||||||
flend = FrameLogger("### out of the end", "magenta")
|
|
||||||
|
|
||||||
messages = [
|
messages = [
|
||||||
{
|
{
|
||||||
@@ -77,15 +85,18 @@ async def main():
|
|||||||
transport.input(),
|
transport.input(),
|
||||||
tma_in,
|
tma_in,
|
||||||
llm,
|
llm,
|
||||||
fl,
|
|
||||||
tts,
|
tts,
|
||||||
fltts,
|
ml,
|
||||||
transport.output(),
|
transport.output(),
|
||||||
tma_out,
|
tma_out,
|
||||||
flend
|
|
||||||
])
|
])
|
||||||
|
|
||||||
task = PipelineTask(pipeline)
|
task = PipelineTask(pipeline)
|
||||||
|
task = PipelineTask(pipeline, PipelineParams(
|
||||||
|
allow_interruptions=True,
|
||||||
|
enable_metrics=True,
|
||||||
|
report_only_initial_ttfb=False,
|
||||||
|
))
|
||||||
|
|
||||||
@transport.event_handler("on_first_participant_joined")
|
@transport.event_handler("on_first_participant_joined")
|
||||||
async def on_first_participant_joined(transport, participant):
|
async def on_first_participant_joined(transport, participant):
|
||||||
|
|||||||
@@ -276,6 +276,8 @@ class MetricsFrame(SystemFrame):
|
|||||||
"""
|
"""
|
||||||
ttfb: List[Mapping[str, Any]] | None = None
|
ttfb: List[Mapping[str, Any]] | None = None
|
||||||
processing: List[Mapping[str, Any]] | None = None
|
processing: List[Mapping[str, Any]] | None = None
|
||||||
|
tokens: List[Mapping[str, Any]] | None = None
|
||||||
|
characters: List[Mapping[str, Any]] | None = None
|
||||||
|
|
||||||
#
|
#
|
||||||
# Control frames
|
# Control frames
|
||||||
|
|||||||
@@ -537,7 +537,11 @@ class RTVIProcessor(FrameProcessor):
|
|||||||
processors.extend(pipeline.processors_with_metrics())
|
processors.extend(pipeline.processors_with_metrics())
|
||||||
ttfb = [{"processor": p.name, "value": 0.0} for p in processors]
|
ttfb = [{"processor": p.name, "value": 0.0} for p in processors]
|
||||||
processing = [{"processor": p.name, "value": 0.0} for p in processors]
|
processing = [{"processor": p.name, "value": 0.0} for p in processors]
|
||||||
await self.push_frame(MetricsFrame(ttfb=ttfb, processing=processing))
|
tokens = [{"processor": p.name, "value": {"prompt_tokens": 0,
|
||||||
|
"completion_tokens": 0,
|
||||||
|
"total_tokens": 0}} for p in processors]
|
||||||
|
characters = [{"processor": p.name, "value": 0} for p in processors]
|
||||||
|
await self.push_frame(MetricsFrame(ttfb=ttfb, processing=processing, tokens=tokens, characters=characters))
|
||||||
|
|
||||||
self._pipeline = pipeline
|
self._pipeline = pipeline
|
||||||
|
|
||||||
|
|||||||
@@ -18,6 +18,7 @@ from pipecat.frames.frames import (
|
|||||||
EndFrame,
|
EndFrame,
|
||||||
ErrorFrame,
|
ErrorFrame,
|
||||||
Frame,
|
Frame,
|
||||||
|
MetricsFrame,
|
||||||
StartFrame,
|
StartFrame,
|
||||||
SystemFrame,
|
SystemFrame,
|
||||||
TranscriptionFrame,
|
TranscriptionFrame,
|
||||||
@@ -87,7 +88,13 @@ class AzureTTSService(TTSService):
|
|||||||
|
|
||||||
async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
|
async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
|
||||||
logger.debug(f"Generating TTS: [{text}]")
|
logger.debug(f"Generating TTS: [{text}]")
|
||||||
|
if self.can_generate_metrics() and self.metrics_enabled:
|
||||||
|
characters = {
|
||||||
|
"processor": self.name,
|
||||||
|
"value": len(text),
|
||||||
|
}
|
||||||
|
logger.debug(f"{self.name} Characters: {characters['value']}")
|
||||||
|
await self.push_frame(MetricsFrame(characters=[characters]))
|
||||||
await self.start_ttfb_metrics()
|
await self.start_ttfb_metrics()
|
||||||
|
|
||||||
ssml = (
|
ssml = (
|
||||||
|
|||||||
@@ -21,6 +21,7 @@ from pipecat.frames.frames import (
|
|||||||
StartFrame,
|
StartFrame,
|
||||||
EndFrame,
|
EndFrame,
|
||||||
TextFrame,
|
TextFrame,
|
||||||
|
MetricsFrame,
|
||||||
LLMFullResponseEndFrame
|
LLMFullResponseEndFrame
|
||||||
)
|
)
|
||||||
from pipecat.services.ai_services import TTSService
|
from pipecat.services.ai_services import TTSService
|
||||||
@@ -200,6 +201,13 @@ class CartesiaTTSService(TTSService):
|
|||||||
|
|
||||||
async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
|
async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
|
||||||
logger.debug(f"Generating TTS: [{text}]")
|
logger.debug(f"Generating TTS: [{text}]")
|
||||||
|
if self.can_generate_metrics() and self.metrics_enabled:
|
||||||
|
characters = {
|
||||||
|
"processor": self.name,
|
||||||
|
"value": len(text),
|
||||||
|
}
|
||||||
|
logger.debug(f"{self.name} Characters: {characters['value']}")
|
||||||
|
await self.push_frame(MetricsFrame(characters=[characters]))
|
||||||
|
|
||||||
try:
|
try:
|
||||||
if not self._websocket:
|
if not self._websocket:
|
||||||
|
|||||||
@@ -15,6 +15,7 @@ from pipecat.frames.frames import (
|
|||||||
ErrorFrame,
|
ErrorFrame,
|
||||||
Frame,
|
Frame,
|
||||||
InterimTranscriptionFrame,
|
InterimTranscriptionFrame,
|
||||||
|
MetricsFrame,
|
||||||
StartFrame,
|
StartFrame,
|
||||||
SystemFrame,
|
SystemFrame,
|
||||||
TranscriptionFrame)
|
TranscriptionFrame)
|
||||||
@@ -70,7 +71,13 @@ class DeepgramTTSService(TTSService):
|
|||||||
|
|
||||||
async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
|
async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
|
||||||
logger.debug(f"Generating TTS: [{text}]")
|
logger.debug(f"Generating TTS: [{text}]")
|
||||||
|
if self.can_generate_metrics() and self.metrics_enabled:
|
||||||
|
characters = {
|
||||||
|
"processor": self.name,
|
||||||
|
"value": len(text),
|
||||||
|
}
|
||||||
|
logger.debug(f"{self.name} Characters: {characters['value']}")
|
||||||
|
await self.push_frame(MetricsFrame(characters=[characters]))
|
||||||
base_url = self._base_url
|
base_url = self._base_url
|
||||||
request_url = f"{base_url}?model={self._voice}&encoding={self._encoding}&container=none&sample_rate={self._sample_rate}"
|
request_url = f"{base_url}?model={self._voice}&encoding={self._encoding}&container=none&sample_rate={self._sample_rate}"
|
||||||
headers = {"authorization": f"token {self._api_key}"}
|
headers = {"authorization": f"token {self._api_key}"}
|
||||||
|
|||||||
@@ -8,7 +8,7 @@ import aiohttp
|
|||||||
|
|
||||||
from typing import AsyncGenerator
|
from typing import AsyncGenerator
|
||||||
|
|
||||||
from pipecat.frames.frames import AudioRawFrame, ErrorFrame, Frame
|
from pipecat.frames.frames import AudioRawFrame, ErrorFrame, Frame, MetricsFrame
|
||||||
from pipecat.services.ai_services import TTSService
|
from pipecat.services.ai_services import TTSService
|
||||||
|
|
||||||
from loguru import logger
|
from loguru import logger
|
||||||
@@ -40,7 +40,13 @@ class ElevenLabsTTSService(TTSService):
|
|||||||
|
|
||||||
async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
|
async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
|
||||||
logger.debug(f"Generating TTS: [{text}]")
|
logger.debug(f"Generating TTS: [{text}]")
|
||||||
|
if self.can_generate_metrics() and self.metrics_enabled:
|
||||||
|
characters = {
|
||||||
|
"processor": self.name,
|
||||||
|
"value": len(text),
|
||||||
|
}
|
||||||
|
logger.debug(f"{self.name} Characters: {characters['value']}")
|
||||||
|
await self.push_frame(MetricsFrame(characters=[characters]))
|
||||||
url = f"https://api.elevenlabs.io/v1/text-to-speech/{self._voice_id}/stream"
|
url = f"https://api.elevenlabs.io/v1/text-to-speech/{self._voice_id}/stream"
|
||||||
|
|
||||||
payload = {"text": text, "model_id": self._model}
|
payload = {"text": text, "model_id": self._model}
|
||||||
|
|||||||
@@ -23,6 +23,7 @@ from pipecat.frames.frames import (
|
|||||||
LLMFullResponseStartFrame,
|
LLMFullResponseStartFrame,
|
||||||
LLMMessagesFrame,
|
LLMMessagesFrame,
|
||||||
LLMModelUpdateFrame,
|
LLMModelUpdateFrame,
|
||||||
|
MetricsFrame,
|
||||||
TextFrame,
|
TextFrame,
|
||||||
URLImageRawFrame,
|
URLImageRawFrame,
|
||||||
VisionImageRawFrame
|
VisionImageRawFrame
|
||||||
@@ -95,6 +96,7 @@ class BaseOpenAILLMService(LLMService):
|
|||||||
messages=messages,
|
messages=messages,
|
||||||
tools=context.tools,
|
tools=context.tools,
|
||||||
tool_choice=context.tool_choice,
|
tool_choice=context.tool_choice,
|
||||||
|
stream_options={"include_usage": True}
|
||||||
)
|
)
|
||||||
return chunks
|
return chunks
|
||||||
|
|
||||||
@@ -132,6 +134,19 @@ class BaseOpenAILLMService(LLMService):
|
|||||||
)
|
)
|
||||||
|
|
||||||
async for chunk in chunk_stream:
|
async for chunk in chunk_stream:
|
||||||
|
if chunk.usage:
|
||||||
|
if self.can_generate_metrics() and self.metrics_enabled:
|
||||||
|
tokens = {
|
||||||
|
"processor": self.name,
|
||||||
|
"prompt_tokens": chunk.usage.prompt_tokens,
|
||||||
|
"completion_tokens": chunk.usage.completion_tokens,
|
||||||
|
"total_tokens": chunk.usage.total_tokens
|
||||||
|
}
|
||||||
|
logger.debug(
|
||||||
|
f"{self.name} prompt tokens: {tokens['prompt_tokens']}, completion tokens: {tokens['completion_tokens']}")
|
||||||
|
|
||||||
|
await self.push_frame(MetricsFrame(tokens=[tokens]))
|
||||||
|
|
||||||
if len(chunk.choices) == 0:
|
if len(chunk.choices) == 0:
|
||||||
continue
|
continue
|
||||||
|
|
||||||
@@ -323,7 +338,13 @@ class OpenAITTSService(TTSService):
|
|||||||
|
|
||||||
async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
|
async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
|
||||||
logger.debug(f"Generating TTS: [{text}]")
|
logger.debug(f"Generating TTS: [{text}]")
|
||||||
|
if self.can_generate_metrics() and self.metrics_enabled:
|
||||||
|
characters = {
|
||||||
|
"processor": self.name,
|
||||||
|
"value": len(text),
|
||||||
|
}
|
||||||
|
logger.debug(f"{self.name} Characters: {characters['value']}")
|
||||||
|
await self.push_frame(MetricsFrame(characters=[characters]))
|
||||||
try:
|
try:
|
||||||
await self.start_ttfb_metrics()
|
await self.start_ttfb_metrics()
|
||||||
|
|
||||||
|
|||||||
@@ -9,7 +9,7 @@ import struct
|
|||||||
|
|
||||||
from typing import AsyncGenerator
|
from typing import AsyncGenerator
|
||||||
|
|
||||||
from pipecat.frames.frames import AudioRawFrame, Frame
|
from pipecat.frames.frames import AudioRawFrame, Frame, MetricsFrame
|
||||||
from pipecat.services.ai_services import TTSService
|
from pipecat.services.ai_services import TTSService
|
||||||
|
|
||||||
from loguru import logger
|
from loguru import logger
|
||||||
@@ -48,7 +48,13 @@ class PlayHTTTSService(TTSService):
|
|||||||
|
|
||||||
async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
|
async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
|
||||||
logger.debug(f"Generating TTS: [{text}]")
|
logger.debug(f"Generating TTS: [{text}]")
|
||||||
|
if self.can_generate_metrics() and self.metrics_enabled:
|
||||||
|
characters = {
|
||||||
|
"processor": self.name,
|
||||||
|
"value": len(text),
|
||||||
|
}
|
||||||
|
logger.debug(f"{self.name} Characters: {characters['value']}")
|
||||||
|
await self.push_frame(MetricsFrame(characters=[characters]))
|
||||||
try:
|
try:
|
||||||
b = bytearray()
|
b = bytearray()
|
||||||
in_header = True
|
in_header = True
|
||||||
|
|||||||
@@ -8,7 +8,7 @@ import aiohttp
|
|||||||
|
|
||||||
from typing import Any, AsyncGenerator, Dict
|
from typing import Any, AsyncGenerator, Dict
|
||||||
|
|
||||||
from pipecat.frames.frames import AudioRawFrame, ErrorFrame, Frame, StartFrame
|
from pipecat.frames.frames import AudioRawFrame, ErrorFrame, Frame, MetricsFrame, StartFrame
|
||||||
from pipecat.services.ai_services import TTSService
|
from pipecat.services.ai_services import TTSService
|
||||||
|
|
||||||
from loguru import logger
|
from loguru import logger
|
||||||
@@ -70,7 +70,13 @@ class XTTSService(TTSService):
|
|||||||
|
|
||||||
async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
|
async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
|
||||||
logger.debug(f"Generating TTS: [{text}]")
|
logger.debug(f"Generating TTS: [{text}]")
|
||||||
|
if self.can_generate_metrics() and self.metrics_enabled:
|
||||||
|
characters = {
|
||||||
|
"processor": self.name,
|
||||||
|
"value": len(text),
|
||||||
|
}
|
||||||
|
logger.debug(f"{self.name} Characters: {characters['value']}")
|
||||||
|
await self.push_frame(MetricsFrame(characters=[characters]))
|
||||||
if not self._studio_speakers:
|
if not self._studio_speakers:
|
||||||
logger.error(f"{self} no studio speakers available")
|
logger.error(f"{self} no studio speakers available")
|
||||||
return
|
return
|
||||||
|
|||||||
@@ -699,6 +699,10 @@ class DailyOutputTransport(BaseOutputTransport):
|
|||||||
metrics["ttfb"] = frame.ttfb
|
metrics["ttfb"] = frame.ttfb
|
||||||
if frame.processing:
|
if frame.processing:
|
||||||
metrics["processing"] = frame.processing
|
metrics["processing"] = frame.processing
|
||||||
|
if frame.tokens:
|
||||||
|
metrics["tokens"] = frame.tokens
|
||||||
|
if frame.characters:
|
||||||
|
metrics["characters"] = frame.characters
|
||||||
|
|
||||||
message = DailyTransportMessageFrame(message={
|
message = DailyTransportMessageFrame(message={
|
||||||
"type": "pipecat-metrics",
|
"type": "pipecat-metrics",
|
||||||
|
|||||||
Reference in New Issue
Block a user