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Merge pull request #602 from pipecat-ai/mb/adjust-logger-levels

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Adjust log levels for log messages
This commit is contained in:
Mark Backman
2024-10-16 18:00:35 -04:00
committed by GitHub
parent 4075b19f7c 55f1ae2564
commit bb48a81103
8 changed files with 29 additions and 38 deletions
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17
examples/storytelling-chatbot/src/bot.py
View File

@@ -1,11 +1,16 @@
import argparse
import asyncio
import aiohttp
import os
import sys
import aiohttp
from dotenv import load_dotenv
from loguru import logger
from processors import StoryImageProcessor, StoryProcessor
from prompts import CUE_USER_TURN, LLM_BASE_PROMPT, LLM_INTRO_PROMPT
from utils.helpers import load_images, load_sounds
from pipecat.frames.frames import LLMMessagesFrame, StopTaskFrame, EndFrame
from pipecat.frames.frames import EndFrame, LLMMessagesFrame, StopTaskFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineTask
@@ -22,14 +27,6 @@ from pipecat.transports.services.daily import (
DailyTransportMessageFrame,
)
from processors import StoryProcessor, StoryImageProcessor
from prompts import LLM_BASE_PROMPT, LLM_INTRO_PROMPT, CUE_USER_TURN
from utils.helpers import load_sounds, load_images
from loguru import logger
from dotenv import load_dotenv
load_dotenv(override=True)
logger.remove(0)

14
src/pipecat/processors/aggregators/openai_llm_context.py
View File

@@ -8,30 +8,26 @@ import base64
import copy
import io
import json
from dataclasses import dataclass
from typing import Any, Awaitable, Callable, List
from loguru import logger
from PIL import Image
from pipecat.frames.frames import (
Frame,
VisionImageRawFrame,
FunctionCallInProgressFrame,
FunctionCallResultFrame,
VisionImageRawFrame,
)
from pipecat.processors.frame_processor import FrameProcessor
from loguru import logger
try:
from openai._types import NOT_GIVEN, NotGiven
from openai.types.chat import (
ChatCompletionToolParam,
ChatCompletionToolChoiceOptionParam,
ChatCompletionMessageParam,
ChatCompletionToolChoiceOptionParam,
ChatCompletionToolParam,
)
except ModuleNotFoundError as e:
logger.error(f"Exception: {e}")
@@ -185,7 +181,7 @@ class OpenAILLMContext:
llm: FrameProcessor,
run_llm: bool = True,
) -> None:
logger.debug(f"Calling function {function_name} with arguments {arguments}")
logger.info(f"Calling function {function_name} with arguments {arguments}")
# Push a SystemFrame downstream. This frame will let our assistant context aggregator
# know that we are in the middle of a function call. Some contexts/aggregators may
# not need this. But some definitely do (Anthropic, for example).

12
src/pipecat/services/ai_services.py
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@@ -75,7 +75,7 @@ class AIService(FrameProcessor):
print("Update request for:", key, value)
if key in self._settings:
logger.debug(f"Updating LLM setting {key} to: [{value}]")
logger.info(f"Updating LLM setting {key} to: [{value}]")
self._settings[key] = value
elif key in SessionProperties.model_fields:
print("Attempting to update", key, value)
@@ -99,12 +99,12 @@ class AIService(FrameProcessor):
validated_properties = SessionProperties.model_validate(
current_properties.model_dump()
)
logger.debug(f"Updating LLM setting {key} to: [{value}]")
logger.info(f"Updating LLM setting {key} to: [{value}]")
self._session_properties = validated_properties.model_dump()
except Exception as e:
logger.warning(f"Unexpected error updating session property {key}: {e}")
elif key == "model":
logger.debug(f"Updating LLM setting {key} to: [{value}]")
logger.info(f"Updating LLM setting {key} to: [{value}]")
self.set_model_name(value)
else:
logger.warning(f"Unknown setting for {self.name} service: {key}")
@@ -271,7 +271,7 @@ class TTSService(AIService):
async def _update_settings(self, settings: Dict[str, Any]):
for key, value in settings.items():
if key in self._settings:
logger.debug(f"Updating TTS setting {key} to: [{value}]")
logger.info(f"Updating TTS setting {key} to: [{value}]")
self._settings[key] = value
if key == "language":
self._settings[key] = self.language_to_service_language(value)
@@ -470,10 +470,10 @@ class STTService(AIService):
pass
async def _update_settings(self, settings: Dict[str, Any]):
logger.debug(f"Updating STT settings: {self._settings}")
logger.info(f"Updating STT settings: {self._settings}")
for key, value in settings.items():
if key in self._settings:
logger.debug(f"Updating STT setting {key} to: [{value}]")
logger.info(f"Updating STT setting {key} to: [{value}]")
self._settings[key] = value
if key == "language":
await self.set_language(value)

3
src/pipecat/services/cartesia.py
View File

@@ -18,7 +18,6 @@ from pipecat.frames.frames import (
EndFrame,
ErrorFrame,
Frame,
LLMFullResponseEndFrame,
StartFrame,
StartInterruptionFrame,
TTSAudioRawFrame,
@@ -132,7 +131,7 @@ class CartesiaTTSService(WordTTSService):
async def set_model(self, model: str):
self._model_id = model
await super().set_model(model)
logger.debug(f"Switching TTS model to: [{model}]")
logger.info(f"Switching TTS model to: [{model}]")
def language_to_service_language(self, language: Language) -> str | None:
return language_to_cartesia_language(language)

8
src/pipecat/services/deepgram.py
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@@ -162,13 +162,13 @@ class DeepgramSTTService(STTService):
async def set_model(self, model: str):
await super().set_model(model)
logger.debug(f"Switching STT model to: [{model}]")
logger.info(f"Switching STT model to: [{model}]")
self._settings["model"] = model
await self._disconnect()
await self._connect()
async def set_language(self, language: Language):
logger.debug(f"Switching STT language to: [{language}]")
logger.info(f"Switching STT language to: [{language}]")
self._settings["language"] = language
await self._disconnect()
await self._connect()
@@ -191,14 +191,14 @@ class DeepgramSTTService(STTService):
async def _connect(self):
if await self._connection.start(self._settings):
logger.debug(f"{self}: Connected to Deepgram")
logger.info(f"{self}: Connected to Deepgram")
else:
logger.error(f"{self}: Unable to connect to Deepgram")
async def _disconnect(self):
if self._connection.is_connected:
await self._connection.finish()
logger.debug(f"{self}: Disconnected from Deepgram")
logger.info(f"{self}: Disconnected from Deepgram")
async def _on_speech_started(self, *args, **kwargs):
await self.start_ttfb_metrics()

6
src/pipecat/services/elevenlabs.py
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@@ -247,7 +247,7 @@ class ElevenLabsTTSService(WordTTSService):
async def set_model(self, model: str):
await super().set_model(model)
logger.debug(f"Switching TTS model to: [{model}]")
logger.info(f"Switching TTS model to: [{model}]")
await self._disconnect()
await self._connect()
@@ -257,7 +257,7 @@ class ElevenLabsTTSService(WordTTSService):
if not prev_voice == self._voice_id:
await self._disconnect()
await self._connect()
logger.debug(f"Switching TTS voice to: [{self._voice_id}]")
logger.info(f"Switching TTS voice to: [{self._voice_id}]")
async def start(self, frame: StartFrame):
await super().start(frame)
@@ -298,7 +298,7 @@ class ElevenLabsTTSService(WordTTSService):
if model == "eleven_turbo_v2_5":
url += f"&language_code={language}"
else:
logger.debug(
logger.warning(
f"Language code [{language}] not applied. Language codes can only be used with the 'eleven_turbo_v2_5' model."
)

2
src/pipecat/services/openai.py
View File

@@ -400,7 +400,7 @@ class OpenAITTSService(TTSService):
return True
async def set_model(self, model: str):
logger.debug(f"Switching TTS model to: [{model}]")
logger.info(f"Switching TTS model to: [{model}]")
self.set_model_name(model)
async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:

5
src/pipecat/vad/vad_analyzer.py
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@@ -7,12 +7,11 @@
from abc import abstractmethod
from enum import Enum
from loguru import logger
from pydantic.main import BaseModel
from pipecat.utils.audio import calculate_audio_volume, exp_smoothing
from loguru import logger
class VADState(Enum):
QUIET = 1
@@ -58,7 +57,7 @@ class VADAnalyzer:
pass
def set_params(self, params: VADParams):
logger.debug(f"Setting VAD params to: {params}")
logger.info(f"Setting VAD params to: {params}")
self._params = params
self._vad_frames = self.num_frames_required()
self._vad_frames_num_bytes = self._vad_frames * self._num_channels * 2