codingSarvesh/study-ai-tool

1import os2import gradio as gr3import fitz  # PyMuPDF4import pytesseract5from PIL import Image6from transformers import pipeline7from moviepy.editor import VideoFileClip8import yt_dlp9import tempfile10 11# Load chatbot pipeline12chatbot = pipeline("text-generation", model="gpt2")13 14# Function to process various file types15def process_file(file, subject):16    if file is None:17        return "No file uploaded."18    file_path = file.name19    ext = os.path.splitext(file_path)[1].lower()20 21    text = ""22 23    if ext == ".pdf":24        with fitz.open(file_path) as doc:25            for page in doc:26                text += page.get_text()27 28    elif ext in [".png", ".jpg", ".jpeg"]:29        image = Image.open(file_path)30        text = pytesseract.image_to_string(image)31 32    elif ext == ".mp3":33        # Placeholder for audio transcription logic34        text = "Transcribed text from audio."35 36    elif ext == ".mp4":37        # Placeholder for video transcription logic38        text = "Transcribed text from video."39 40    else:41        return "Unsupported file type."42 43    # Save the extracted text under the specified subject44    subject_folder = os.path.join("subjects", subject)45    os.makedirs(subject_folder, exist_ok=True)46    with open(os.path.join(subject_folder, os.path.basename(file_path) + ".txt"), "w") as f:47        f.write(text)48 49    return text50 51# Function to process YouTube links52def process_youtube_link(link, subject):53    ydl_opts = {54        'format': 'bestaudio/best',55        'outtmpl': 'downloaded_audio.%(ext)s',56        'quiet': True,57    }58    with yt_dlp.YoutubeDL(ydl_opts) as ydl:59        ydl.download([link])60 61    # Placeholder for audio transcription logic62    text = "Transcribed text from YouTube video."63 64    # Save the extracted text under the specified subject65    subject_folder = os.path.join("subjects", subject)66    os.makedirs(subject_folder, exist_ok=True)67    with open(os.path.join(subject_folder, "youtube_video.txt"), "w") as f:68        f.write(text)69 70    return text71 72# Function to generate notes73def generate_notes(text):74    if not text.strip():75        return "No content to generate notes from."76    return f"### Notes\n\n{text}"77 78# Function to generate practice tests79def generate_practice_test(text):80    if not text.strip():81        return "No material to generate test from."82    return (83        "### Practice Test\n\n"84        "1. What is the main idea of the text?\n"85        "2. List and explain key concepts or terms.\n"86        "3. Summarize the most important point.\n"87        "4. Create a diagram or outline to explain the topic.\n"88    )89 90# Function for chatbot Q&A91def chat_with_ai(prompt):92    if not prompt.strip():93        return "Please ask a question."94    result = chatbot(prompt, max_length=100, do_sample=True)95    return result[0]['generated_text']96 97# Gradio Interface98with gr.Blocks() as app:99    gr.Markdown("# 📚 Study AI Assistant")100 101    with gr.Tab("📁 Upload Materials"):102        subject_input = gr.Textbox(label="Subject Name")103        file_input = gr.File(file_types=[".pdf", ".png", ".jpg", ".jpeg", ".mp3", ".mp4"], label="Upload File")104        upload_button = gr.Button("Extract Text")105        extracted_text = gr.Textbox(label="Extracted Text", lines=10)106        upload_button.click(process_file, inputs=[file_input, subject_input], outputs=extracted_text)107 108    with gr.Tab("🔗 YouTube Link"):109        subject_input_yt = gr.Textbox(label="Subject Name")110        link_input = gr.Textbox(label="YouTube Link")111        link_button = gr.Button("Process Link")112        link_text = gr.Textbox(label="Extracted Text", lines=10)113        link_button.click(process_youtube_link, inputs=[link_input, subject_input_yt], outputs=link_text)114 115    with gr.Tab("🧠 Notes"):116        generate_notes_button = gr.Button("Generate Notes")117        notes_output = gr.Textbox(label="Notes", lines=10)118        generate_notes_button.click(generate_notes, inputs=extracted_text, outputs=notes_output)119 120    with gr.Tab("📝 Practice Test"):121        generate_test_button = gr.Button("Generate Practice Test")122        test_output = gr.Textbox(label="Practice Test", lines=10)123        generate_test_button.click(generate_practice_test, inputs=extracted_text, outputs=test_output)124 125    with gr.Tab("💬 Chat"):126        chat_input = gr.Textbox(label="Ask a question about your material")127        chat_button = gr.Button("Ask AI")128        chat_output = gr.Textbox(label="AI Answer")129        chat_button.click(chat_with_ai, inputs=chat_input, outputs=chat_output)130 131app.launch()132