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| ## 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) | |