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examples: fix moondream-chatbot

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This commit is contained in:
Aleix Conchillo Flaqué
2024-05-13 15:28:11 -07:00
parent fdfcfd1d5e
commit 22cd1ac5f2
5 changed files with 82 additions and 92 deletions
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4
examples/moondream-chatbot/README.md
View File

@@ -10,8 +10,8 @@ This app connects you to a chatbot powered by GPT-4, complete with animations ge
## Get started
```python
python3 -m venv env
source env/bin/activate
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
cp env.example .env # and add your credentials

156
examples/moondream-chatbot/bot.py
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@@ -1,43 +1,46 @@
import asyncio
import aiohttp
import logging
import os
import sys
from PIL import Image
from typing import AsyncGenerator
from dailyai.pipeline.aggregators import (
LLMUserResponseAggregator,
ParallelPipeline,
VisionImageFrameAggregator,
SentenceAggregator
)
from dailyai.pipeline.frames import (
ImageFrame,
from pipecat.frames.frames import (
ImageRawFrame,
SpriteFrame,
Frame,
LLMMessagesFrame,
AudioFrame,
PipelineStartedFrame,
TTSEndFrame,
AudioRawFrame,
TTSStoppedFrame,
TextFrame,
UserImageFrame,
UserImageRawFrame,
UserImageRequestFrame,
)
from dailyai.services.moondream_ai_service import MoondreamService
from dailyai.pipeline.pipeline import FrameProcessor, Pipeline
from dailyai.transports.daily_transport import DailyTransport
from dailyai.services.open_ai_services import OpenAILLMService
from dailyai.services.elevenlabs_ai_service import ElevenLabsTTSService
from pipecat.pipeline.parallel_pipeline import ParallelPipeline
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
from pipecat.processors.aggregators.sentence import SentenceAggregator
from pipecat.processors.aggregators.vision_image_frame import VisionImageFrameAggregator
from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
from pipecat.services.elevenlabs import ElevenLabsTTSService
from pipecat.services.moondream import MoondreamService
from pipecat.services.openai import OpenAILLMService
from pipecat.transports.services.daily import DailyParams, DailyTransport
from pipecat.vad.silero import SileroVAD
from runner import configure
from loguru import logger
from dotenv import load_dotenv
load_dotenv(override=True)
logging.basicConfig(format=f"%(levelno)s %(asctime)s %(message)s")
logger = logging.getLogger("dailyai")
logger.setLevel(logging.DEBUG)
logger.remove(0)
logger.add(sys.stderr, level="DEBUG")
user_request_answer = "Let me take a look."
@@ -51,13 +54,13 @@ for i in range(1, 26):
# Get the filename without the extension to use as the dictionary key
# Open the image and convert it to bytes
with Image.open(full_path) as img:
sprites.append(img.tobytes())
sprites.append(ImageRawFrame(image=img.tobytes(), size=img.size, format=img.format))
flipped = sprites[::-1]
sprites.extend(flipped)
# When the bot isn't talking, show a static image of the cat listening
quiet_frame = ImageFrame(sprites[0], (1024, 576))
quiet_frame = sprites[0]
talking_frame = SpriteFrame(images=sprites)
@@ -71,37 +74,18 @@ class TalkingAnimation(FrameProcessor):
super().__init__()
self._is_talking = False
async def process_frame(self, frame: Frame) -> AsyncGenerator[Frame, None]:
if isinstance(frame, AudioFrame):
async def process_frame(self, frame: Frame, direction: FrameDirection):
if isinstance(frame, AudioRawFrame):
if not self._is_talking:
yield talking_frame
yield frame
await self.push_frame(talking_frame)
self._is_talking = True
else:
yield frame
elif isinstance(frame, TTSEndFrame):
yield quiet_frame
yield frame
elif isinstance(frame, TTSStoppedFrame):
await self.push_frame(quiet_frame)
self._is_talking = False
else:
yield frame
class AnimationInitializer(FrameProcessor):
def __init__(self):
super().__init__()
async def process_frame(self, frame: Frame) -> AsyncGenerator[Frame, None]:
if isinstance(frame, PipelineStartedFrame):
yield quiet_frame
yield frame
else:
yield frame
await self.push_frame(frame)
class UserImageRequester(FrameProcessor):
participant_id: str | None
def __init__(self):
super().__init__()
self.participant_id = None
@@ -109,33 +93,32 @@ class UserImageRequester(FrameProcessor):
def set_participant_id(self, participant_id: str):
self.participant_id = participant_id
async def process_frame(self, frame: Frame) -> AsyncGenerator[Frame, None]:
async def process_frame(self, frame: Frame, direction: FrameDirection):
if self.participant_id and isinstance(frame, TextFrame):
if frame.text == user_request_answer:
yield UserImageRequestFrame(self.participant_id)
yield TextFrame("Describe the image in a short sentence.")
elif isinstance(frame, UserImageFrame):
yield frame
await self.push_frame(UserImageRequestFrame(self.participant_id), FrameDirection.UPSTREAM)
await self.push_frame(TextFrame("Describe the image in a short sentence."))
elif isinstance(frame, UserImageRawFrame):
await self.push_frame(frame)
class TextFilterProcessor(FrameProcessor):
text: str
def __init__(self, text: str):
super().__init__()
self.text = text
async def process_frame(self, frame: Frame) -> AsyncGenerator[Frame, None]:
async def process_frame(self, frame: Frame, direction: FrameDirection):
if isinstance(frame, TextFrame):
if frame.text != self.text:
yield frame
await self.push_frame(frame)
else:
yield frame
await self.push_frame(frame)
class ImageFilterProcessor(FrameProcessor):
async def process_frame(self, frame: Frame) -> AsyncGenerator[Frame, None]:
if not isinstance(frame, ImageFrame):
yield frame
async def process_frame(self, frame: Frame, direction: FrameDirection):
if not isinstance(frame, ImageRawFrame):
await self.push_frame(frame)
async def main(room_url: str, token):
@@ -144,17 +127,18 @@ async def main(room_url: str, token):
room_url,
token,
"Chatbot",
duration_minutes=5,
start_transcription=True,
mic_enabled=True,
mic_sample_rate=16000,
camera_enabled=True,
camera_width=1024,
camera_height=576,
vad_enabled=True,
video_rendering_enabled=True
DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
camera_out_enabled=True,
camera_out_width=1024,
camera_out_height=576,
transcription_enabled=True
)
)
vad = SileroVAD()
tts = ElevenLabsTTSService(
aiohttp_session=session,
api_key=os.getenv("ELEVENLABS_API_KEY"),
@@ -166,11 +150,11 @@ async def main(room_url: str, token):
model="gpt-4-turbo-preview")
ta = TalkingAnimation()
ai = AnimationInitializer()
sa = SentenceAggregator()
ir = UserImageRequester()
va = VisionImageFrameAggregator()
# If you run into weird description, try with use_cpu=True
moondream = MoondreamService()
@@ -186,23 +170,25 @@ async def main(room_url: str, token):
ura = LLMUserResponseAggregator(messages)
pipeline = Pipeline([
ai, ura, llm, ParallelPipeline(
[[sa, ir, va, moondream], [tf, imgf]]
),
tts, ta
])
pipeline = Pipeline([transport.input(), vad, ura, llm,
ParallelPipeline(
[sa, ir, va, moondream],
[tf, imgf]),
tts, ta, transport.output()])
@transport.event_handler("on_first_other_participant_joined")
async def on_first_other_participant_joined(transport, participant):
transport.render_participant_video(participant["id"], framerate=0)
task = PipelineTask(pipeline)
await task.queue_frame(quiet_frame)
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant):
transport.capture_participant_transcription(participant["id"])
transport.capture_participant_video(participant["id"], framerate=0)
ir.set_participant_id(participant["id"])
await pipeline.queue_frames([LLMMessagesFrame(messages)])
await task.queue_frames([LLMMessagesFrame(messages)])
transport.transcription_settings["extra"]["endpointing"] = True
transport.transcription_settings["extra"]["punctuate"] = True
runner = PipelineRunner()
await asyncio.gather(transport.run(pipeline))
await runner.run(task)
if __name__ == "__main__":

2
examples/moondream-chatbot/requirements.txt
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@@ -2,4 +2,4 @@ python-dotenv
requests
fastapi[all]
uvicorn
dailyai[daily,moondream,openai,silero]
pipecat-ai[daily,moondream,openai,silero]

2
examples/moondream-chatbot/server.py
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@@ -7,7 +7,7 @@ from fastapi import FastAPI, Request, HTTPException
from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import JSONResponse, RedirectResponse
from utils.daily_helpers import create_room as _create_room, get_token, get_name_from_url
from utils.daily_helpers import create_room as _create_room, get_token
MAX_BOTS_PER_ROOM = 1

10
examples/simple-chatbot/bot.py
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@@ -21,6 +21,7 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
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 SileroVAD
from runner import configure
@@ -81,15 +82,17 @@ async def main(room_url: str, token):
token,
"Chatbot",
DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
camera_out_enabled=True,
camera_out_width=1024,
camera_out_height=576,
transcription_enabled=True,
vad_enabled=True
transcription_enabled=True
)
)
vad = SileroVAD()
tts = ElevenLabsTTSService(
aiohttp_session=session,
api_key=os.getenv("ELEVENLABS_API_KEY"),
@@ -111,7 +114,8 @@ async def main(room_url: str, token):
ta = TalkingAnimation()
pipeline = Pipeline([transport.input(), user_response, llm, tts, ta, transport.output()])
pipeline = Pipeline([transport.input(), vad, user_response,
llm, tts, ta, transport.output()])
task = PipelineTask(pipeline)
await task.queue_frame(quiet_frame)