Update app.py

app.py

@@ -17,6 +17,11 @@ from huggingface_hub import login, hf_hub_download, scan_cache_dir
 import speech_recognition as sr
 import openai
 
+import torch
+print("CUDA available:", torch.cuda.is_available())
+print("CUDA device:", torch.cuda.current_device() if torch.cuda.is_available() else "None")
+
+
 # Set up environment variables and timeouts
 os.environ["HF_HUB_DOWNLOAD_TIMEOUT"] = "300"  # 5-minute timeout
 
@@ -37,9 +42,9 @@ if HF_TOKEN:
 else:
     print("⚠️ HF_TOKEN not found. Proceeding without login...")
 
-# Set up device (GPU if available, otherwise CPU)
-device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-print(f"🔧 Using device: {device}")
+# # Set up device (GPU if available, otherwise CPU)
+# device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+# print(f"🔧 Using device: {device}")
 
 # Initialize model variables
 tts_model = None
@@ -83,7 +88,8 @@ def load_tts_model_with_retry(max_retries=3, retry_delay=5):
                 tts_repo_id,
                 trust_remote_code=True,
                 local_files_only=True,
-                device_map="auto"  # <-- Use device_map instead of .to(device)
+                device_map="auto"  
+                torch_dtype=torch.float16
             )
             tts_model_wrapper = TTSModelWrapper(tts_model)
             print("TTS model loaded from cache successfully!")
@@ -101,6 +107,7 @@ def load_tts_model_with_retry(max_retries=3, retry_delay=5):
                 use_auth_token=HF_TOKEN,
                 low_cpu_mem_usage=True,
                 device_map="auto"  # <-- Use device_map here as well
+                
             )
             tts_model_wrapper = TTSModelWrapper(tts_model)
             print(f"TTS model loaded successfully! Type: {type(tts_model)}")
@@ -398,7 +405,7 @@ def enhance_audio(audio_data):
 
     return audio_data
 
-def split_into_chunks(text, max_length=20):
+def split_into_chunks(text, max_length=8):
     """Split text into smaller chunks based on punctuation and length"""
     # First split by sentences
     sentence_markers = ['.', '?', '!', ';', ':', '।', '॥']