## install PyTesseract
os.system('pip install -q pytesseract')
import openai
import gradio as gr
import pytesseract
from PIL import Image
import numpy as np

# set your OpenAI API key here
openai.api_key = "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"

def generate_questions(text):
    # set parameters for question generation
    prompts = [
                    f"Generate 5-mark questions based on the following text:\n{text}\n\nQuestions:",
                    f"What are some opinion-based questions that can be asked about the following text?\n{text}\n\nQuestions:",
                    f"What are some fact-based questions that can be asked about the following text?\n{text}\n\nQuestions:",
                    f"Generate 3 tricky questions that require creative thinking based on the following text:\n{text}\n\nQuestions:",
                    f"Generate 2 long questions (10+ words) and 3 short questions (5-7 words) based on the following text:\n{text}\n\nQuestions:"
    ]
    model = "text-davinci-003"
    temperature = 0.7
    max_tokens = 200
    
    # generate questions using the OpenAI API
    questions = []
    counter = 1  # initialize counter variable
    for prompt in prompts:
        response = openai.Completion.create(engine=model, prompt=prompt, temperature=temperature, max_tokens=max_tokens)
        prompt_questions = response.choices[0].text.strip().split("\n")
        # remove any duplicate questions
        prompt_questions = list(set(prompt_questions))
        for question in prompt_questions:
            numbered_question = f"{counter}. {question}"  # add counter to beginning of question
            questions.append(numbered_question)
            counter += 1
    
    # return the generated questions
    return "\n".join(questions)


def generate_questions_from_image(image):
    # preprocess image and convert to text
    image = Image.fromarray(np.uint8(image))
    image_text = pytesseract.image_to_string(image)
    
    # generate questions from image text
    return generate_questions(image_text)


# create the Gradio interface
iface = gr.Interface(fn=generate_questions_from_image,
                     inputs=gr.inputs.Image(label="Upload an image"),
                     outputs=gr.outputs.Textbox(label="Generated Questions"),
                     title="Question Generator By Daksh Chawla",
                     description="Generate a diverse set of questions based on the provided image input.")

# launch the interface
iface.launch(share=False)