Update app.py

app.py

@@ -1,36 +1,24 @@
 import streamlit as st
-from transformers import AutoTokenizer, AutoModelForCausalLM
-import requests
+from transformers import pipeline
 
-# Initialize the tokenizer and model
-tokenizer = AutoTokenizer.from_pretrained("PawanKrd/CosmosRP-8k")
-model = AutoModelForCausalLM.from_pretrained("PawanKrd/CosmosRP-8k")
+# Set up the text-to-speech pipeline
+pipe = pipeline('text-to-speech', model='Xenova/speecht5_tts')
 
-st.title("CosmosRP-8k Roleplay Chatbot")
+def text_to_speech(text):
+    result = pipe(text)
+    audio_path = 'output.wav'
+    with open(audio_path, 'wb') as f:
+        f.write(result['audio'])
+    return audio_path
 
-user_input = st.text_input("You:", "")
+st.title("Text to Speech with Hugging Face Model")
 
-if st.button("Generate Response"):
-    if user_input:
-        # Define the endpoint and payload
-        endpoint_url = "https://api.pawan.krd/cosmosrp/v1/chat/completions"
-        headers = {
-            "Content-Type": "application/json"
-        }
-        data = {
-            "model": "cosmosrp",
-            "messages": [
-                {"role": "system", "content": "You are a roleplay assistant."},
-                {"role": "user", "content": user_input}
-            ]
-        }
-        
-        # Make the request to the API
-        response = requests.post(endpoint_url, headers=headers, json=data)
-        result = response.json()
-        
-        # Extract and display the response
-        generated_response = result['choices'][0]['message']['content']
-        st.text_area("CosmosRP-8k:", generated_response)
+text = st.text_area("Enter text to convert to speech:")
+
+if st.button("Convert"):
+    if text:
+        audio_file = text_to_speech(text)
+        audio_bytes = open(audio_file, 'rb').read()
+        st.audio(audio_bytes, format='audio/wav')
     else:
         st.warning("Please enter some text.")