Update app.py

app.py

@@ -1,67 +1,89 @@
-from ai71 import AI71
+import streamlit as st
 from transformers import pipeline
 import os
 
-# Set your API key here
-AI71_API_KEY = "your_api_key_here"  # Replace with your actual AI71 API key
-client = AI71(AI71_API_KEY)
+# Set the page configuration to wide layout
+st.set_page_config(layout="wide")
 
-# Initialize summarization pipeline using a pre-trained model
+# Initialize the summarization pipeline
 summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
 
-# Initial system message
-messages = [{"role": "system", "content": "You are a helpful assistant."}]
-
+# Define functions for summarizing, extracting key points, and generating flashcards
 def summarize_text(text):
-    """Summarize the provided text."""
     summary = summarizer(text, max_length=150, min_length=50, do_sample=False)
     return summary[0]['summary_text']
 
+def extract_key_points(text):
+    summary = summarizer(text, max_length=60, min_length=20, do_sample=False)
+    return [point['summary_text'] for point in summary]
+
 def generate_flashcards(text):
-    """Generate key points or flashcards from the provided text."""
-    flashcards = summarizer(text, max_length=60, min_length=20, do_sample=False)
-    return [card['summary_text'] for card in flashcards]
+    # Assume flashcards are similar to key points in this case
+    return extract_key_points(text)
 
 def process_file(file_path):
-    """Process the uploaded text file."""
     with open(file_path, 'r', encoding='utf-8') as file:
         text = file.read()
     summary = summarize_text(text)
+    key_points = extract_key_points(text)
     flashcards = generate_flashcards(text)
-    return summary, flashcards
-
-while True:
-    user_input = input("User (type 'upload' to upload a file, or ask a question): ")
-
-    if user_input.lower() in ["exit", "quit"]:
-        print("Exiting the chat. Goodbye!")
-        break
-    elif user_input.lower() == "upload":
-        file_path = input("Enter the file path to upload: ")
-        if os.path.exists(file_path):
-            summary, flashcards = process_file(file_path)
-            print("\nSummary:\n", summary)
-            print("\nFlashcards:\n")
-            for i, card in enumerate(flashcards, 1):
-                print(f"Flashcard {i}: {card}")
-            print("\n")
+    return summary, key_points, flashcards
+
+# Define tabs for the application
+tab1, tab2 = st.tabs(["Text Summarization", "File Upload & Process"])
+
+# Text Summarization Tab
+with tab1:
+    st.title("Text Summarization")
+
+    st.subheader("Enter Your Text")
+    user_text = st.text_area("Input Text", height=300)
+
+    if st.button("Generate Summary"):
+        if user_text:
+            summary = summarize_text(user_text)
+            key_points = extract_key_points(user_text)
+            flashcards = generate_flashcards(user_text)
+
+            st.write("### Summary")
+            st.write(summary)
+
+            st.write("### Key Points")
+            for idx, point in enumerate(key_points, start=1):
+                st.write(f"**Point {idx}:** {point}")
+
+            st.write("### Flashcards")
+            for idx, card in enumerate(flashcards, start=1):
+                st.write(f"**Flashcard {idx}:** {card}")
         else:
-            print("File not found. Please try again.")
-        continue
-
-    messages.append({"role": "user", "content": user_input})
-    print("Falcon: ", end="", flush=True)
-    response_content = ""
-
-    for chunk in client.chat.completions.create(
-        messages=messages,
-        model="tiiuae/falcon-180B-chat",
-        stream=True,
-    ):
-        delta_content = chunk.choices[0].delta.content
-        if delta_content:
-            print(delta_content, end="", flush=True)
-            response_content += delta_content
-
-    messages.append({"role": "assistant", "content": response_content})
-    print("\n")
+            st.warning("Please enter text to generate a summary.")
+
+# File Upload & Process Tab
+with tab2:
+    st.title("Upload and Process File")
+
+    uploaded_file = st.file_uploader("Choose a text file", type=["txt"])
+
+    if uploaded_file is not None:
+        # Save uploaded file temporarily
+        file_path = os.path.join("uploads", uploaded_file.name)
+        with open(file_path, "wb") as f:
+            f.write(uploaded_file.getbuffer())
+
+        # Process the file
+        summary, key_points, flashcards = process_file(file_path)
+
+        # Display the summary, key points, and flashcards
+        st.write("### Summary")
+        st.write(summary)
+
+        st.write("### Key Points")
+        for idx, point in enumerate(key_points, start=1):
+            st.write(f"**Point {idx}:** {point}")
+
+        st.write("### Flashcards")
+        for idx, card in enumerate(flashcards, start=1):
+            st.write(f"**Flashcard {idx}:** {card}")
+
+        # Clean up the temporary file
+        os.remove(file_path)