revert

app.py

@@ -1,13 +1,34 @@
 import gradio as gr
+from asr import transcribe_audio
+from llm_agent import get_llm_reply
+from tts import generate_speech
 
-with gr.Blocks(fill_height=True) as demo:
-    with gr.Sidebar():
-        gr.Markdown("# Inference Provider")
-        gr.Markdown("This Space showcases the nari-labs/Dia-1.6B model, served by the fal-ai API. Sign in with your Hugging Face account to use this API.")
-        button = gr.LoginButton("Sign in")
-    gr.load("models/nari-labs/Dia-1.6B", accept_token=button, provider="fal-ai")
+def voice_agent(audio):
+    if audio is None:
+        return "No audio received!", "...", None
     
+    # ASR
+    user_text = transcribe_audio(audio)
+    
+    # LLM
+    bot_reply = get_llm_reply(user_text)
+    
+    # TTS
+    audio_reply = generate_speech(bot_reply)
+    
+    return user_text, bot_reply, audio_reply
 
+ui = gr.Interface(
+    fn=voice_agent,
+    inputs=gr.Audio(type="filepath", label="🎙️ Upload Voice (.wav or .mp3)"),
+    outputs=[
+        gr.Textbox(label="📝 Transcribed Text"),
+        gr.Textbox(label="🤖 LLM Reply"),
+        gr.Audio(type="filepath", label="🔊 AI Voice Response")
+    ],
+    title="VoiceFreight AI v1.0",
+    description="Upload a voice file. Get a spoken reply from an AI freight agent!"
+)
 
 if __name__ == "__main__":
-    demo.launch()
+    ui.launch()