Update app.py

app.py

@@ -1,20 +1,43 @@
-# Function to generate discussion points with a prompt
-def generate_discussion_points(text, user_prompt=""):
+import streamlit as st
+import pdfplumber
+from transformers import pipeline
+from gtts import gTTS
+import os
+
+# Function to extract text from PDF
+def extract_text_from_pdf(pdf_file):
+    text = ""
+    try:
+        with pdfplumber.open(pdf_file) as pdf:
+            for page in pdf.pages:
+                text += page.extract_text() or ""
+    except Exception as e:
+        st.error(f"Error reading the PDF: {e}")
+    return text
+
+# Function to generate discussion points
+def generate_discussion_points(text, user_prompt=None):
     summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
-    # Prepend the user prompt to the text for guided summarization
-    input_text = f"{user_prompt}\n\n{text}"
-    summary = summarizer(input_text, max_length=130, min_length=30, do_sample=False)
+    if user_prompt:
+        text = user_prompt + " " + text  # Include the user's prompt in the summary input
+    summary = summarizer(text, max_length=130, min_length=30, do_sample=False)
     return summary[0]['summary_text']
 
-# Streamlit app
+# Function to convert text to speech
+def text_to_speech(text, output_file="output.mp3"):
+    tts = gTTS(text)
+    tts.save(output_file)
+    return output_file
+
+# Streamlit app starts here
 st.title("📄 PDF Discussion Points Generator with User Prompts")
-st.write("Upload a PDF file, provide a prompt for the summary, and listen to the generated discussion points.")
+st.write("Upload a small PDF file to generate discussion points and listen to them.")
 
 # File uploader
 uploaded_file = st.file_uploader("Upload a PDF", type=["pdf"])
 
-# Prompt input
-user_prompt = st.text_input("Enter a specific prompt for the summary (optional):", "")
+# User prompt input
+user_prompt = st.text_input("Enter a prompt for the summary (optional)")
 
 if uploaded_file:
     # Extract text from uploaded PDF