Update app.py

app.py

@@ -3,46 +3,53 @@ import streamlit as st
 from extractor import extract_ppt_text, extract_pdf_text
 from tts_engine import generate_voice
 
+
 st.title("AI Lecture Voice Generator")
 
-st.write("Convert PPT, PDF, or Text into Indian English or Tamil speech")
+st.write("Convert PPT, PDF or text into speech")
+
 
-file = st.file_uploader(
-    "Upload PPT, PDF, or TXT file",
+uploaded_file = st.file_uploader(
+    "Upload PPT, PDF or TXT",
     type=["pptx","pdf","txt"]
 )
 
+
 language = st.selectbox(
-    "Select Voice Language",
+    "Voice Language",
     ["English","Tamil"]
 )
 
+
 text_data = ""
 
-if file:
 
-    if file.name.endswith(".pptx"):
-        text_data = extract_ppt_text(file)
+if uploaded_file:
+
+    if uploaded_file.name.endswith(".pptx"):
+
+        text_data = extract_ppt_text(uploaded_file)
 
-    elif file.name.endswith(".pdf"):
-        text_data = extract_pdf_text(file)
+    elif uploaded_file.name.endswith(".pdf"):
+
+        text_data = extract_pdf_text(uploaded_file)
 
     else:
-        text_data = file.read().decode()
 
-    st.subheader("Extracted Text")
+        text_data = uploaded_file.read().decode()
+
+
+    st.text_area("Extracted Text", text_data, height=200)
 
-    st.text_area("Preview", text_data, height=200)
 
-if st.button("Generate Lecture Voice"):
+if st.button("Generate Speech"):
 
     if text_data == "":
-        st.warning("Upload file first")
-        st.stop()
 
-    audio = generate_voice(text_data, language)
+        st.warning("Upload a file first")
+
+    else:
+
+        audio = generate_voice(text_data, language)
 
-    st.audio(audio)
-    @st.cache_resource
-def init_models():
-    load_models()
+        st.audio(audio)