examples(foundational): add 12d-describe-image-moondream

This commit is contained in:
Aleix Conchillo Flaqué
2025-10-30 13:06:12 -07:00
parent ec95618b94
commit 19f046a338
3 changed files with 140 additions and 15 deletions

View File

@@ -240,8 +240,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
### Other
- Updated all vision 12-series foundational examples to load images from a file
and push `LLMMessagesAppendFrame` with the loaded image.
- Updated all vision 12-series foundational examples to load images from a file.
- Added 14-series video examples for different services. These new examples
request an image from the user camera through a function call.

View File

@@ -0,0 +1,122 @@
#
# Copyright (c) 20242025, Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#
import os
from dotenv import load_dotenv
from loguru import logger
from PIL import Image
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
from pipecat.frames.frames import UserImageRawFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.moondream.vision import MoondreamService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
load_dotenv(override=True)
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
"webrtc": lambda: TransportParams(
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
),
}
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot")
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
)
vision = MoondreamService()
pipeline = Pipeline(
[
vision, # Vision
tts, # TTS
transport.output(), # Transport bot output
]
)
task = PipelineTask(
pipeline,
params=PipelineParams(
enable_metrics=True,
enable_usage_metrics=True,
),
idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
)
@transport.event_handler("on_client_connected")
async def on_client_connected(transport, client):
logger.info(f"Client connected")
if not runner_args.body:
script_dir = os.path.dirname(__file__)
runner_args.body = {
"image_path": os.path.join(script_dir, "assets", "cat.jpg"),
"question": "Describe this image",
}
image_path = runner_args.body["image_path"]
question = runner_args.body["question"]
# Describe the image.
image = Image.open(image_path)
await task.queue_frames(
[
UserImageRawFrame(
image=image.tobytes(),
format="RGB",
size=image.size,
text=question,
)
]
)
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
await task.cancel()
runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
await runner.run(task)
async def bot(runner_args: RunnerArguments):
"""Main bot entry point compatible with Pipecat Cloud."""
transport = await create_transport(runner_args, transport_params)
await run_bot(transport, runner_args)
if __name__ == "__main__":
from pipecat.runner.run import main
main()

View File

@@ -49,15 +49,18 @@ EVAL_VISION_CAMERA = EvalConfig(
eval="The user provides a cat description.",
)
EVAL_VISION_IMAGE = EvalConfig(
prompt="Briefly describe this image.",
eval="The user provides a cat description.",
eval_speaks_first=True,
runner_args_body={
"image_path": ASSETS_DIR / "cat.jpg",
"question": "Briefly describe this image.",
},
)
def EVAL_VISION_IMAGE(*, eval_speaks_first: bool = False):
return EvalConfig(
prompt="Briefly describe this image.",
eval="The user provides a cat description.",
eval_speaks_first=eval_speaks_first,
runner_args_body={
"image_path": ASSETS_DIR / "cat.jpg",
"question": "Briefly describe this image.",
},
)
EVAL_VOICEMAIL = EvalConfig(
prompt="Please leave a message.",
@@ -117,10 +120,11 @@ TESTS_07 = [
]
TESTS_12 = [
("12-describe-image-openai.py", EVAL_VISION_IMAGE),
("12a-describe-image-anthropic.py", EVAL_VISION_IMAGE),
("12b-describe-image-aws.py", EVAL_VISION_IMAGE),
("12c-describe-image-gemini-flash.py", EVAL_VISION_IMAGE),
("12-describe-image-openai.py", EVAL_VISION_IMAGE(eval_speaks_first=True)),
("12a-describe-image-anthropic.py", EVAL_VISION_IMAGE(eval_speaks_first=True)),
("12b-describe-image-aws.py", EVAL_VISION_IMAGE(eval_speaks_first=True)),
("12c-describe-image-gemini-flash.py", EVAL_VISION_IMAGE(eval_speaks_first=True)),
("12d-describe-image-moondream.py", EVAL_VISION_IMAGE()),
]
TESTS_14 = [