import gradio as gr
import os
from tempfile import NamedTemporaryFile
def file_dashboard():
with gr.Column() as file_panel:
gr.Markdown("""
📄 File-Based Learning with Chatter the Owl
Upload your notes, textbooks, or slides, and let me turn them into summaries, quizzes, and flashcards!
""")
file_upload = gr.File(label="📁 Upload Your Study Material", file_types=[".pdf", ".txt", ".md", ".pptx"])
question_box = gr.Textbox(label="💬 Ask a question about the uploaded file")
with gr.Tabs():
with gr.Tab("📚 Summary"):
summary_output = gr.Textbox(label="Generated Summary", lines=8, interactive=False)
with gr.Tab("🧠 Flashcards"):
flashcard_output = gr.Textbox(label="Generated Flashcards", lines=8, interactive=False)
with gr.Tab("❓ Quiz"):
quiz_output = gr.Textbox(label="Generated Quiz Questions", lines=8, interactive=False)
with gr.Tab("💬 Answer to Your Question"):
answer_output = gr.Textbox(label="Answer", lines=4, interactive=False)
def placeholder_logic(file, question):
# Placeholder logic until GPT + parsing is added
summary = "This is a summary of your uploaded content."
flashcards = "Flashcard 1: Question? | Answer.\nFlashcard 2: Question? | Answer."
quiz = "1. What is...?\n2. Explain..."
answer = f"You asked: {question}\nHere's a helpful answer from your content."
return summary, flashcards, quiz, answer
file_upload.change(
fn=lambda file: placeholder_logic(file, ""),
inputs=[file_upload],
outputs=[summary_output, flashcard_output, quiz_output, answer_output]
)
question_box.change(
fn=lambda question: placeholder_logic(None, question),
inputs=[question_box],
outputs=[summary_output, flashcard_output, quiz_output, answer_output]
)
return file_panel