llm user and assistant aggregator renames

This commit is contained in:
Aleix Conchillo Flaqué
2024-04-09 08:31:48 -07:00
parent d7b2e67c35
commit 97b923e37e
4 changed files with 21 additions and 21 deletions

View File

@@ -3,8 +3,8 @@ import aiohttp
import logging
import os
from dailyai.pipeline.aggregators import (
LLMResponseAggregator,
UserResponseAggregator,
LLMAssistantResponseAggregator,
LLMUserResponseAggregator,
)
from dailyai.pipeline.pipeline import Pipeline
@@ -63,8 +63,8 @@ async def main(room_url: str, token):
await transport.run_interruptible_pipeline(
pipeline,
post_processor=LLMResponseAggregator(messages),
pre_processor=UserResponseAggregator(messages),
post_processor=LLMAssistantResponseAggregator(messages),
pre_processor=LLMUserResponseAggregator(messages),
)
transport.transcription_settings["extra"]["punctuate"] = False

View File

@@ -6,8 +6,8 @@ from PIL import Image
from typing import AsyncGenerator
from dailyai.pipeline.aggregators import (
LLMResponseAggregator,
UserResponseAggregator,
LLMAssistantResponseAggregator,
LLMUserResponseAggregator,
)
from dailyai.pipeline.frames import (
ImageFrame,
@@ -135,8 +135,8 @@ async def main(room_url: str, token):
await transport.run_interruptible_pipeline(
pipeline,
post_processor=LLMResponseAggregator(messages),
pre_processor=UserResponseAggregator(messages),
post_processor=LLMAssistantResponseAggregator(messages),
pre_processor=LLMUserResponseAggregator(messages),
)
transport.transcription_settings["extra"]["endpointing"] = True

View File

@@ -19,8 +19,8 @@ from dailyai.services.deepgram_ai_services import DeepgramTTSService
from dailyai.services.elevenlabs_ai_service import ElevenLabsTTSService
from dailyai.pipeline.aggregators import (
LLMAssistantContextAggregator,
UserResponseAggregator,
LLMResponseAggregator,
LLMAssistantResponseAggregator,
LLMUserResponseAggregator,
)
from dailyai.pipeline.frames import (
EndPipeFrame,
@@ -209,8 +209,8 @@ async def main(room_url: str, token):
key_id=os.getenv("FAL_KEY_ID"),
key_secret=os.getenv("FAL_KEY_SECRET"),
)
lra = LLMResponseAggregator(messages)
ura = UserResponseAggregator(messages)
lra = LLMAssistantResponseAggregator(messages)
ura = LLMUserResponseAggregator(messages)
sp = StoryProcessor(messages, story)
sig = StoryImageGenerator(story, llm, img)

View File

@@ -21,7 +21,7 @@ from dailyai.services.ai_services import AIService
from typing import AsyncGenerator, Coroutine, List
class BasicResponseAggregator(FrameProcessor):
class ResponseAggregator(FrameProcessor):
"""This frame processor aggregates frames between a start and an end frame
into complete text frame sentences.
@@ -37,10 +37,10 @@ class BasicResponseAggregator(FrameProcessor):
... if isinstance(frame, TextFrame):
... print(frame.text)
>>> aggregator = BasicResponseAggregator(start_frame = UserStartedSpeakingFrame,
... end_frame=UserStoppedSpeakingFrame,
... accumulator_frame=TranscriptionFrame,
... pass_through=False)
>>> aggregator = ResponseAggregator(start_frame = UserStartedSpeakingFrame,
... end_frame=UserStoppedSpeakingFrame,
... accumulator_frame=TranscriptionFrame,
... pass_through=False)
>>> asyncio.run(print_frames(aggregator, UserStartedSpeakingFrame()))
>>> asyncio.run(print_frames(aggregator, TranscriptionFrame("Hello,", 1, 1)))
>>> asyncio.run(print_frames(aggregator, TranscriptionFrame("world.", 1, 2)))
@@ -84,7 +84,7 @@ class BasicResponseAggregator(FrameProcessor):
yield frame
class UserTranscriptionAggregator(BasicResponseAggregator):
class UserResponseAggregator(ResponseAggregator):
def __init__(self):
super().__init__(
start_frame=UserStartedSpeakingFrame,
@@ -94,7 +94,7 @@ class UserTranscriptionAggregator(BasicResponseAggregator):
)
class ResponseAggregator(FrameProcessor):
class LLMResponseAggregator(FrameProcessor):
def __init__(
self,
@@ -139,7 +139,7 @@ class ResponseAggregator(FrameProcessor):
yield frame
class LLMResponseAggregator(ResponseAggregator):
class LLMAssistantResponseAggregator(LLMResponseAggregator):
def __init__(self, messages: list[dict]):
super().__init__(
messages=messages,
@@ -150,7 +150,7 @@ class LLMResponseAggregator(ResponseAggregator):
)
class UserResponseAggregator(ResponseAggregator):
class LLMUserResponseAggregator(LLMResponseAggregator):
def __init__(self, messages: list[dict]):
super().__init__(
messages=messages,