Update app.py

app.py

@@ -1,13 +1,9 @@
 import gradio as gr
 import torch
 from transformers import (
-    AutoTokenizer,
-    AutoModelForCausalLM,
-    SpeechT5Processor,
-    SpeechT5ForTextToSpeech,
-    SpeechT5HifiGan,
-    WhisperProcessor,
-    WhisperForConditionalGeneration
+    AutoTokenizer, AutoModelForCausalLM,
+    SpeechT5Processor, SpeechT5ForTextToSpeech, SpeechT5HifiGan,
+    WhisperProcessor, WhisperForConditionalGeneration
 )
 from datasets import load_dataset
 import os
@@ -17,7 +13,7 @@ import soundfile as sf
 import librosa
 import yaml
 
-# --- Configuration ---
+# ================== Configuration ==================
 HUGGINGFACE_MODEL_ID = "HuggingFaceH4/Qwen2.5-1.5B-Instruct-gkd"
 TORCH_DTYPE = torch.bfloat16
 MAX_NEW_TOKENS = 512
@@ -30,7 +26,7 @@ TTS_MODEL_ID = "microsoft/speecht5_tts"
 TTS_VOCODER_ID = "microsoft/speecht5_hifigan"
 STT_MODEL_ID = "openai/whisper-small"
 
-# --- Global Variables ---
+# ================== Global Variables ==================
 tokenizer = None
 llm_model = None
 tts_processor = None
@@ -41,9 +37,12 @@ whisper_processor = None
 whisper_model = None
 first_load = True
 
+# ================== UI Helpers ==================
 def generate_pretty_html(data):
     html = """
-    <div style="font-family: Arial, sans-serif; max-width: 600px; margin: auto; background-color: #f9f9f9; border-radius: 10px; padding: 20px; box-shadow: 0 4px 12px rgba(0,0,0,0.1);">
+    <div style="font-family: Arial, sans-serif; max-width: 600px; margin: auto; 
+                background-color: #f9f9f9; border-radius: 10px; padding: 20px;
+                box-shadow: 0 4px 12px rgba(0,0,0,0.1);">
       <h2 style="color: #2c3e50; border-bottom: 2px solid #ddd; padding-bottom: 10px;">Model Info</h2>
     """
     for key, value in data.items():
@@ -61,14 +60,17 @@ def load_config():
         return yaml.safe_load(f)
 
 def render_modern_info():
-    config = load_config()
-    return generate_pretty_html(config)
+    try:
+        config = load_config()
+        return generate_pretty_html(config)
+    except Exception as e:
+        return f"<div style='color: red;'>Error loading config: {str(e)}</div>"
 
 def load_readme():
     with open("README.md", "r", encoding="utf-8") as f:
         return f.read()
 
-# --- Helper: Split Text Into Chunks ---
+# ================== Helper Functions ==================
 def split_text_into_chunks(text, max_chars=400):
     sentences = text.replace("...", ".").split(". ")
     chunks = []
@@ -83,7 +85,7 @@ def split_text_into_chunks(text, max_chars=400):
         chunks.append(current_chunk)
     return [f"{chunk}." for chunk in chunks if chunk.strip()]
 
-# --- Load Models Function ---
+# ================== Model Loading ==================
 @spaces.GPU
 def load_models():
     global tokenizer, llm_model, tts_processor, tts_model, tts_vocoder, speaker_embeddings, whisper_processor, whisper_model
@@ -132,7 +134,7 @@ def load_models():
         except Exception as e:
             print(f"Error loading Whisper: {e}")
 
-# --- Generate Response and Audio ---
+# ================== Chat & Audio Functions ==================
 @spaces.GPU
 def generate_response_and_audio(message, history):
     global first_load
@@ -196,7 +198,6 @@ def generate_response_and_audio(message, history):
 
     return history + [{"role": "assistant", "content": generated_text}], audio_path
 
-# --- Transcribe Audio ---
 @spaces.GPU
 def transcribe_audio(filepath):
     global first_load
@@ -216,7 +217,7 @@ def transcribe_audio(filepath):
     except Exception as e:
         return f"Transcription failed: {e}"
 
-# --- Gradio UI ---
+# ================== Gradio UI ==================
 with gr.Blocks() as demo:
     gr.Markdown("# Qwen2.5 Chatbot with Voice Input/Output")
     
@@ -233,9 +234,15 @@ with gr.Blocks() as demo:
 
     clear_btn = gr.Button("Clear All")
     clear_btn.click(lambda: ([], "", None), None, [chatbot, text_input, audio_output])
-    #gr.Markdown("---")
+    
     gr.Markdown(load_readme())
     gr.Markdown("---")
-    #html_output = gr.HTML()
 
-demo.load(fn=render_modern_info, outputs=html_output)
+    # ✅ Define html_output BEFORE using it
+    html_output = gr.HTML("<div style='text-align:center; padding: 20px;'>Loading model info...</div>")
+    
+    # ✅ Now this works!
+    demo.load(fn=render_modern_info, outputs=html_output)
+
+# ================== Launch App ==================
+demo.queue().launch()