Update app.py

app.py

@@ -630,11 +630,11 @@ from langchain.chains import RetrievalQA
 from langchain.chains.conversation.memory import ConversationBufferWindowMemory
 from langchain.agents import Tool, initialize_agent
 from huggingface_hub import login
-from parler_tts import ParlerTTSForConditionalGeneration
-from transformers import AutoTokenizer, AutoFeatureExtractor, set_seed
 
 from transformers.models.speecht5.number_normalizer import EnglishNumberNormalizer
 from string import punctuation
+from parler_tts import ParlerTTSForConditionalGeneration
+from transformers import AutoTokenizer, AutoFeatureExtractor, set_seed
 
 device = "cuda:0" if torch.cuda.is_available() else "cpu"
 
@@ -672,7 +672,9 @@ def generate_audio(text, description="Thomas speaks with emphasis and excitement
     prompt = tokenizer(preprocess(text), return_tensors="pt").to(device)
 
     set_seed(SEED)
-    generation = model.generate(input_ids=inputs.input_ids, prompt_input_ids=prompt.input_ids)
+    input_features = model.get_input_features(prompt.input_ids)  # Ensure we have input_features
+
+    generation = model.generate(input_features=input_features, input_ids=inputs.input_ids)
     audio_arr = generation.cpu().numpy().squeeze()
 
     with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as f:
@@ -682,6 +684,11 @@ def generate_audio(text, description="Thomas speaks with emphasis and excitement
     logging.debug(f"Audio saved to {temp_audio_path}")
     return temp_audio_path
 
+def install_parler_tts():
+    subprocess.check_call([sys.executable, "-m", "pip", "install", "git+https://github.com/huggingface/parler-tts.git"])
+
+# Call the function to install parler-tts
+install_parler_tts()
 
 # Check if the token is already set in the environment variables
 hf_token = os.getenv("HF_TOKEN")
@@ -1223,9 +1230,3 @@ with gr.Blocks(theme='Pijush2023/scikit-learn-pijush') as demo:
      
 demo.queue()
 demo.launch(share=True)
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