Update app.py

app.py

@@ -2,6 +2,7 @@ import streamlit as st
 from PyPDF2 import PdfReader
 import pandas as pd
 from transformers import pipeline
+import random
 
 # Load the Hugging Face model for text generation (Bloom or any other open-source model)
 @st.cache_resource
@@ -29,12 +30,13 @@ def read_csv_file(file):
 
 # Function to search for a topic in the extracted content
 def search_topic_in_content(content, topic):
-    topic_content = [line for line in content.split("\n") if topic.lower() in line.lower()]
-    return "\n".join(topic_content)
+    sentences = content.split(".")  # Break content into sentences
+    topic_sentences = [s for s in sentences if topic.lower() in s.lower()]  # Filter sentences containing the topic
+    return ". ".join(topic_sentences) if topic_sentences else None
 
-# Function to generate study material using Hugging Face model
-def generate_content(topic):
-    prompt = f"Explain the topic '{topic}' in simple terms for electrical engineering students."
+# Function to generate content using Hugging Face model
+def generate_ai_content(topic):
+    prompt = f"Explain '{topic}' in simple terms for engineering students. Provide examples and applications."
     response = text_generator(prompt, max_length=300, num_return_sequences=1)
     return response[0]['generated_text']
 
@@ -55,7 +57,7 @@ st.sidebar.header("AI-Based Tutor")
 
 # File upload section
 uploaded_file = st.sidebar.file_uploader("Upload Study Material (PDF/TXT/CSV)", type=["pdf", "txt", "csv"])
-topic = st.sidebar.text_input("Enter a topic (e.g., DC Motors, Transformers)")
+topic = st.sidebar.text_input("Enter a topic (e.g., Newton's Third Law, DC Motors)")
 
 # Process uploaded file
 content = ""
@@ -77,14 +79,16 @@ if uploaded_file:
 if st.button("Generate Study Material"):
     if topic:
         st.header(f"Study Material: {topic}")
+        # Extract relevant content from the uploaded material
         filtered_content = search_topic_in_content(content, topic) if content else ""
         if filtered_content:
-            st.write("**Relevant Extracted Content:**")
+            st.write("**Relevant Extracted Content from Uploaded Material:**")
             st.write(filtered_content)
-
-        ai_content = generate_content(topic)
-        st.write("**AI-Generated Content:**")
-        st.write(ai_content)
+        else:
+            st.warning("No relevant content found in the uploaded material. Generating AI-based content instead.")
+            ai_content = generate_ai_content(topic)
+            st.write("**AI-Generated Content:**")
+            st.write(ai_content)
     else:
         st.warning("Please enter a topic!")