Remove log

examples/foundational/18b-gstreamer.py

@@ -0,0 +1,165 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import argparse
+from typing import Optional
+
+from dotenv import load_dotenv
+from loguru import logger
+
+from pipecat.frames.frames import (
+    EndFrame,
+    Frame,
+    InputImageRawFrame,
+    OutputImageRawFrame,
+    TextFrame,
+    TTSTextFrame,
+    UserImageRequestFrame,
+    UserStartedSpeakingFrame,
+)
+from pipecat.observers.loggers.debug_log_observer import DebugLogObserver, FrameEndpoint
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineTask
+from pipecat.processors.aggregators.vision_image_frame import VisionImageFrameAggregator
+from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
+from pipecat.processors.frameworks.rtvi import (
+    RTVIConfig,
+    RTVIObserver,
+    RTVIProcessor,
+    RTVIServerMessageFrame,
+)
+from pipecat.processors.gstreamer.pipeline_source import GStreamerPipelineSource
+from pipecat.services.moondream.vision import MoondreamService
+from pipecat.transports.base_input import BaseInputTransport
+from pipecat.transports.base_output import BaseOutputTransport
+from pipecat.transports.base_transport import TransportParams
+from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
+from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
+
+load_dotenv(override=True)
+
+
+class AlertProcessor(FrameProcessor):
+    def __init__(self, connection: SmallWebRTCConnection):
+        super().__init__()
+        self._connection = connection
+
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        await super().process_frame(frame, direction)
+
+        if isinstance(frame, TextFrame):
+            text = frame.text.strip().upper()
+            message_frame = RTVIServerMessageFrame(data=text)
+            await self.push_frame(message_frame)
+
+        await self.push_frame(frame, direction)
+
+
+class UserImageRequester(FrameProcessor):
+    def __init__(self, participant_id: Optional[str] = None):
+        super().__init__()
+
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        await super().process_frame(frame, direction)
+
+        if isinstance(frame, OutputImageRawFrame):
+            await self.push_frame(frame)
+            # logger.info(f"UserImageRequester received image frame with size: {frame.size}")
+            text_frame = TextFrame(
+                "Are there people in the bottom right corner of the image? Only answer with YES or NO."
+            )
+            await self.push_frame(text_frame)
+            input_frame = InputImageRawFrame(
+                image=frame.image,
+                size=frame.size,
+                format=frame.format,
+            )
+            await self.push_frame(input_frame)
+        else:
+            await self.push_frame(frame, direction)
+
+
+async def run_bot(webrtc_connection: SmallWebRTCConnection, args: argparse.Namespace):
+    logger.info(f"Starting bot with video input: {args.input}")
+
+    transport = SmallWebRTCTransport(
+        webrtc_connection=webrtc_connection,
+        params=TransportParams(
+            audio_out_enabled=True,
+            video_out_enabled=True,
+            video_out_is_live=True,
+            video_out_width=1280,
+            video_out_height=720,
+        ),
+    )
+
+    gst = GStreamerPipelineSource(
+        pipeline=(f"rtspsrc location={args.input} ! decodebin ! autovideosink"),
+        out_params=GStreamerPipelineSource.OutputParams(
+            video_width=1280,
+            video_height=720,
+        ),
+    )
+
+    rtvi = RTVIProcessor(config=RTVIConfig(config=[]))
+
+    # If you run into weird description, try with use_cpu=True
+    moondream = MoondreamService()
+
+    ir = UserImageRequester()
+    va = VisionImageFrameAggregator()
+    alert = AlertProcessor(connection=webrtc_connection)
+
+    pipeline = Pipeline(
+        [
+            gst,  # GStreamer file source
+            rtvi,
+            ir,
+            # debug,
+            va,
+            moondream,
+            alert,  # Send an email alert or something if the door is open
+            transport.output(),  # Transport bot output
+        ]
+    )
+
+    task = PipelineTask(
+        pipeline,
+        observers=[
+            RTVIObserver(rtvi),
+            DebugLogObserver(
+                frame_types={
+                    # TextFrame: None,
+                    TextFrame: (MoondreamService, FrameEndpoint.SOURCE),
+                    # InputImageRawFrame: None,
+                    EndFrame: None,
+                }
+            ),
+        ],
+    )
+
+    @rtvi.event_handler("on_client_ready")
+    async def on_client_ready(rtvi):
+        logger.info(f"Bot ready: {rtvi}")
+        await rtvi.set_bot_ready()
+
+    @transport.event_handler("on_client_connected")
+    async def on_client_connected(transport, client):
+        logger.info(f"Client connected: {client}")
+
+    runner = PipelineRunner(handle_sigint=False)
+
+    await runner.run(task)
+
+
+if __name__ == "__main__":
+    from run import main
+
+    parser = argparse.ArgumentParser(description="Pipecat Bot Runner")
+    parser.add_argument("-i", "--input", type=str, required=True, help="Input video file")
+
+    main(parser)