app.py

import gradio as gr
import requests
import os

# ------------------ GROQ SETTINGS ------------------
GROQ_API_KEY = os.getenv("GROQ_API_KEY") or "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"
GROQ_MODEL = "llama3-70b-8192"

def query_gpt(prompt):
    headers = {
        "Authorization": f"Bearer {GROQ_API_KEY}",
        "Content-Type": "application/json"
    }
    data = {
        "model": GROQ_MODEL,
        "messages": [{"role": "user", "content": prompt}]
    }
    response = requests.post("https://api.groq.com/openai/v1/chat/completions", json=data, headers=headers)
    return response.json()['choices'][0]['message']['content']

# ------------------ SYLLABUS DATA ------------------
class_subject_chapters = {
    "9": {
        "Physics": ["Introduction to Physics", "Kinematics", "Dynamics", "Turning Effect of Forces", "Gravitation", "Work and Energy", "Properties of Matter", "Thermal Properties of Matter", "Transfer of Heat"],
        "Biology": ["Introduction to Biology", "Solving a Biological Problem", "Biodiversity", "Cells and Tissues", "Cell Cycle", "Enzymes", "Bioenergetics", "Nutrition", "Transport"],
        "Chemistry": ["Fundamentals of Chemistry", "Structure of Atoms", "Periodic Table", "Structure of Molecules", "Physical States of Matter", "Solutions", "Electrochemistry", "Chemical Reactivity"]
    },
    "10": {
        "Physics": ["Simple Harmonic Motion and Waves", "Sound", "Geometrical Optics", "Electrostatics", "Current Electricity", "Electromagnetism", "Basic Electronics", "Information and Communication Technology", "Atomic and Nuclear Physics"],
        "Biology": ["Gaseous Exchange", "Homeostasis", "Coordination and Control", "Support and Movement", "Reproduction", "Inheritance", "Man and His Environment", "Biotechnology", "Pharmacology"],
        "Chemistry": ["Chemical Equilibrium", "Acids, Bases and Salts", "Organic Chemistry", "Hydrocarbons", "Biochemistry", "Environmental Chemistry", "Chemical Industries"]
    },
    "11": {
        "Physics": ["Measurements", "Vectors and Equilibrium", "Motion and Force", "Work and Energy", "Circular Motion", "Fluid Dynamics", "Oscillations", "Waves", "Physical Optics", "Thermodynamics"],
        "Biology": ["Introduction to Biology", "Biological Molecules", "Enzymes", "The Cell", "Cell Cycle", "Variety of Life", "Kingdom Prokaryotae", "Kingdom Protista", "Kingdom Fungi", "Kingdom Plantae", "Kingdom Animalia"],
        "Chemistry": ["Basic Concepts", "Experimental Techniques", "Gases", "Liquids and Solids", "Atomic Structure", "Chemical Bonding", "Thermochemistry", "Chemical Equilibrium", "Ionic Equilibrium", "Redox Reactions"]
    },
    "12": {
        "Physics": ["Electrostatics", "Current Electricity", "Electromagnetism", "Electromagnetic Induction", "Alternating Current", "Physics of Solids", "Electronics", "Dawn of Modern Physics", "Atomic Spectra", "Nuclear Physics"],
        "Biology": ["Homeostasis", "Support and Movement", "Coordination and Control", "Reproduction", "Growth and Development", "Chromosomes and DNA", "Biotechnology", "Evolution", "Ecosystem", "Some Major Ecosystems"],
        "Chemistry": ["Periodic Classification", "Transition Elements", "Chemical Reactivity", "Alcohols and Phenols", "Aldehydes and Ketones", "Carboxylic Acids", "Amines", "Polymers", "Biochemistry", "Environmental Chemistry"]
    }
}

# ------------------ FILE READER ------------------
def read_uploaded_file(file):
    if file is None:
        return ""
    if file.name.endswith(".txt"):
        return file.read().decode("utf-8")
    elif file.name.endswith(".pdf"):
        from PyPDF2 import PdfReader
        reader = PdfReader(file)
        return "\n".join(page.extract_text() for page in reader.pages if page.extract_text())
    elif file.name.endswith(".docx"):
        import docx
        doc = docx.Document(file)
        return "\n".join(p.text for p in doc.paragraphs)
    else:
        return "Unsupported file format. Please upload a PDF, DOCX, or TXT file."

# ------------------ MAIN BOT FUNCTION ------------------
def tutor_bot(mode, selected_class, selected_subject, selected_chapter, action_type, uploaded_file):
    if mode == "File Upload Mode" and uploaded_file is not None:
        file_text = read_uploaded_file(uploaded_file)
        if not file_text.strip():
            return "Could not read text from the uploaded file."
        prompt = f"Based on the following content, {action_type.lower()}: \n\n{file_text[:4000]}"  # keep it under token limits
        gpt_response = query_gpt(prompt)
        return gpt_response

    elif mode == "Syllabus Mode":
        if not selected_class or not selected_subject or not selected_chapter:
            return "Please select class, subject, and chapter."
        prompt = f"The user is studying in Class {selected_class}. Give a detailed response for the chapter '{selected_chapter}' in the subject '{selected_subject}'."
        if action_type == "Summarize Important Points":
            prompt = f"Summarize the key points of the chapter '{selected_chapter}' from Class {selected_class} {selected_subject}."
        elif action_type == "Generate MCQs":
            prompt = f"Create 5 multiple choice questions (MCQs) with 4 options each for the chapter '{selected_chapter}' from Class {selected_class} {selected_subject}."
        elif action_type == "Simplify Concepts":
            prompt = f"Explain in very simple terms the important concepts from the chapter '{selected_chapter}' from Class {selected_class} {selected_subject} for a 14-year-old student."

        gpt_response = query_gpt(prompt)
        search_query = f"{selected_class} {selected_subject} {selected_chapter} in Urdu"
        youtube_link = f"https://www.youtube.com/results?search_query={search_query.replace(' ', '+')}"
        gpt_response += f"\n\n🎥 **Watch this topic on YouTube:** [Click here]({youtube_link})"
        return gpt_response

    return "Invalid mode or missing input."

# ------------------ GRADIO UI ------------------
with gr.Blocks(title="AI Textbook Tutor") as app:
    gr.Markdown("## 📘 AI Textbook Tutor\nChoose a mode to either upload your file or select chapter-wise content to get summaries, MCQs, or simplified explanations.")

    mode = gr.Radio(["Syllabus Mode", "File Upload Mode"], label="Select Mode", value="Syllabus Mode")

    with gr.Row():
        class_dropdown = gr.Dropdown(label="Class", choices=list(class_subject_chapters.keys()))
        subject_dropdown = gr.Dropdown(label="Subject")
        chapter_dropdown = gr.Dropdown(label="Chapter")

    file_input = gr.File(label="Upload File (PDF, DOCX, TXT)", file_types=[".pdf", ".docx", ".txt"])
    action_dropdown = gr.Radio(["Summarize Important Points", "Generate MCQs", "Simplify Concepts"], label="Task", value="Summarize Important Points")

    run_button = gr.Button("Run Tutor 🧠")
    output_box = gr.Markdown()

    def update_subjects(selected_class):
        return gr.update(choices=list(class_subject_chapters[selected_class].keys()), value=None)

    def update_chapters(selected_class, selected_subject):
        return gr.update(choices=class_subject_chapters[selected_class][selected_subject], value=None)

    def toggle_ui(selected_mode):
        if selected_mode == "File Upload Mode":
            return (
                gr.update(visible=False),  # Class
                gr.update(visible=False),  # Subject
                gr.update(visible=False),  # Chapter
                gr.update(visible=True)    # File input
            )
        else:
            return (
                gr.update(visible=True),
                gr.update(visible=True),
                gr.update(visible=True),
                gr.update(visible=False)
            )

    class_dropdown.change(update_subjects, inputs=class_dropdown, outputs=subject_dropdown)
    subject_dropdown.change(update_chapters, inputs=[class_dropdown, subject_dropdown], outputs=chapter_dropdown)
    mode.change(toggle_ui, inputs=mode, outputs=[class_dropdown, subject_dropdown, chapter_dropdown, file_input])

    run_button.click(
        tutor_bot,
        inputs=[mode, class_dropdown, subject_dropdown, chapter_dropdown, action_dropdown, file_input],
        outputs=output_box
    )

app.launch()