import streamlit as st
import openai
import os
import json
import base64

from PIL import Image

from google_auth_oauthlib.flow import InstalledAppFlow
from googleapiclient.discovery import build
from google.oauth2.credentials import Credentials


# ---------------- CONFIG ---------------- #

openai.api_key = os.getenv("OPENAI_API_KEY")

SCOPES = [
    "https://www.googleapis.com/auth/classroom.courses",
    "https://www.googleapis.com/auth/classroom.coursework.students",
    "https://www.googleapis.com/auth/classroom.rosters"
]


# ---------------- GOOGLE AUTH ---------------- #

def authenticate_google():

    creds = None

    if os.path.exists("token.json"):
        creds = Credentials.from_authorized_user_file("token.json", SCOPES)

    if not creds or not creds.valid:

        flow = InstalledAppFlow.from_client_secrets_file(
            "credentials.json",
            SCOPES
        )

        creds = flow.run_local_server(port=0)

        with open("token.json", "w") as token:
            token.write(creds.to_json())

    service = build("classroom", "v1", credentials=creds)

    return service


# ---------------- AI FUNCTIONS ---------------- #

def analyze_image(image):

    buffered = image_to_base64(image)

    prompt = """
    Analyze this educational image and generate:

    1. Course Title
    2. Course Description
    3. Topic Name
    4. Detailed Explanation
    """

    response = openai.ChatCompletion.create(
        model="gpt-4o-mini",
        messages=[
            {"role": "user", "content": [
                {"type": "text", "text": prompt},
                {
                    "type": "image_url",
                    "image_url": {"url": f"data:image/png;base64,{buffered}"}
                }
            ]}
        ]
    )

    return response.choices[0].message.content


def generate_mcqs(text):

    prompt = f"""
    Create 5 multiple choice questions in JSON format.

    Based on:

    {text}

    Format:

    [
      {{
        "question": "",
        "options": ["A","B","C","D"],
        "answer": ""
      }}
    ]
    """

    response = openai.ChatCompletion.create(
        model="gpt-4o-mini",
        messages=[{"role": "user", "content": prompt}]
    )

    return response.choices[0].message.content


def image_to_base64(img):

    import io

    buffer = io.BytesIO()
    img.save(buffer, format="PNG")

    return base64.b64encode(buffer.getvalue()).decode()


# ---------------- CLASSROOM FUNCTIONS ---------------- #

def create_course(service, title, desc):

    course = {
        "name": title,
        "descriptionHeading": title,
        "description": desc,
        "room": "AI Classroom",
        "ownerId": "me"
    }

    return service.courses().create(body=course).execute()


def create_topic(service, course_id, name):

    topic = {
        "name": name
    }

    return service.courses().topics().create(
        courseId=course_id,
        body=topic
    ).execute()


def post_material(service, course_id, topic_id, text):

    material = {
        "title": "AI Generated Lesson",
        "description": text,
        "topicId": topic_id,
        "state": "PUBLISHED",
        "workType": "ASSIGNMENT"
    }

    return service.courses().courseWork().create(
        courseId=course_id,
        body=material
    ).execute()


# ---------------- STREAMLIT UI ---------------- #

st.set_page_config(page_title="AI E-Learning Platform")

st.title("📘 AI Powered E-Learning System")


uploaded = st.file_uploader(
    "Upload Educational Image",
    type=["png", "jpg", "jpeg"]
)


if uploaded:

    image = Image.open(uploaded)

    st.image(image, caption="Uploaded Image")

    if st.button("Generate Explanation"):

        with st.spinner("Analyzing..."):

            output = analyze_image(image)

        st.subheader("AI Output")
        st.write(output)

        st.session_state["lesson"] = output


if "lesson" in st.session_state:

    if st.button("Generate MCQs"):

        with st.spinner("Creating Questions..."):

            mcqs = generate_mcqs(st.session_state["lesson"])

        st.subheader("MCQs")
        st.code(mcqs, language="json")

        st.session_state["mcqs"] = mcqs


if "lesson" in st.session_state:

    if st.button("Publish to Google Classroom"):

        with st.spinner("Connecting to Classroom..."):

            service = authenticate_google()

        title = "AI Generated Course"
        desc = "Created using LLM"

        course = create_course(service, title, desc)

        topic = create_topic(
            service,
            course["id"],
            "AI Topic"
        )

        post_material(
            service,
            course["id"],
            topic["topicId"],
            st.session_state["lesson"]
        )

        st.success("Course Published Successfully!")