Upload app.py with huggingface_hub

app.py

@@ -5,6 +5,7 @@ Based on the original liquid-audio demo
 
 from queue import Queue
 from threading import Thread
+import os
 
 import gradio as gr
 import numpy as np
@@ -13,6 +14,25 @@ from fastrtc import AdditionalOutputs, ReplyOnPause, WebRTC
 
 from liquid_audio import ChatState, LFM2AudioModel, LFM2AudioProcessor, LFMModality
 
+# Configure WebRTC with STUN/TURN servers
+# This is CRITICAL for WebRTC connections to work through firewalls/NAT
+rtc_configuration = {
+    "iceServers": [
+        {
+            "urls": [
+                "stun:stun.l.google.com:19302",
+                "stun:stun1.l.google.com:19302",
+            ]
+        }
+    ]
+}
+
+# For production deployment on Hugging Face Spaces, you can use Cloudflare TURN:
+# Uncomment these lines and set TURN_KEY_ID and TURN_KEY_API_TOKEN as Secrets
+# from fastrtc import get_cloudflare_turn_credentials_async
+# if os.getenv("TURN_KEY_ID") and os.getenv("TURN_KEY_API_TOKEN"):
+#     rtc_configuration = get_cloudflare_turn_credentials_async()
+
 # Load models
 HF_REPO = "LiquidAI/LFM2-Audio-1.5B"
 
@@ -163,6 +183,7 @@ with gr.Blocks(title="LFM2-Audio Real-time Speech-to-Speech") as demo:
                 modality="audio",
                 mode="send-receive",
                 full_screen=False,
+                rtc_configuration=rtc_configuration,
             )
 
             with gr.Row():