code

demo/echo_conversation.py

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+import logging
+
+# Configure the root logger to WARNING to suppress debug messages from other libraries
+logging.basicConfig(level=logging.WARNING)
+
+# Create a console handler
+console_handler = logging.StreamHandler()
+console_handler.setLevel(logging.DEBUG)
+
+# Create a formatter
+formatter = logging.Formatter("%(name)s - %(levelname)s - %(message)s")
+console_handler.setFormatter(formatter)
+
+# Configure the logger for your specific library
+logger = logging.getLogger("gradio_webrtc")
+logger.setLevel(logging.DEBUG)
+logger.addHandler(console_handler)
+
+
+import time
+from queue import Queue
+
+import gradio as gr
+import numpy as np
+from gradio_webrtc import StreamHandler, WebRTC
+
+
+class EchoHandler(StreamHandler):
+    def __init__(self) -> None:
+        super().__init__()
+        self.queue = Queue()
+
+    def receive(self, frame: tuple[int, np.ndarray] | np.ndarray) -> None:
+        self.queue.put(frame)
+
+    def emit(self) -> None:
+        return self.queue.get()
+
+
+with gr.Blocks() as demo:
+    gr.HTML(
+        """
+    <h1 style='text-align: center'>
+    Conversational AI (Powered by WebRTC ⚡️)
+    </h1>
+    """
+    )
+    with gr.Column():
+        with gr.Group():
+            audio = WebRTC(
+                label="Stream",
+                rtc_configuration=None,
+                mode="send-receive",
+                modality="audio",
+            )
+
+        audio.stream(fn=EchoHandler(), inputs=[audio], outputs=[audio], time_limit=15)
+
+
+if __name__ == "__main__":
+    demo.launch()