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| from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM | |
| import gradio as gr | |
| # Load the Hugging Face model | |
| model_name = "fbellame/llama2-pdf-to-quizz-13b" | |
| tokenizer = AutoTokenizer.from_pretrained(model_name) | |
| model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto") | |
| quiz_pipeline = pipeline("text2text-generation", model=model, tokenizer=tokenizer) | |
| # Example quiz data (replace with dynamic generation logic) | |
| quiz_data = [ | |
| { | |
| "question": "What is the purpose of transformers in power systems?", | |
| "options": [ | |
| "Increase voltage", | |
| "Decrease voltage", | |
| "Both increase and decrease voltage", | |
| "None of the above", | |
| ], | |
| "answer": "Both increase and decrease voltage", | |
| } | |
| ] | |
| # Feedback collection | |
| feedback_list = [] | |
| current_index = [0] | |
| def get_next_question(): | |
| if current_index[0] >= len(quiz_data): | |
| return "No more questions to review.", [] | |
| question = quiz_data[current_index[0]] | |
| return f"Question: {question['question']}", question["options"] | |
| def evaluate_question(rating, feedback, email, discipline, experience): | |
| if rating not in ["Exactly Accurate and Relevant", "I Have No Idea (Not in My Area of Expertise)"] and not feedback.strip(): | |
| return "Feedback required for this rating. Please provide corrections." | |
| question_data = quiz_data[current_index[0]] | |
| feedback_list.append({ | |
| "question": question_data["question"], | |
| "options": question_data["options"], | |
| "rating": rating, | |
| "feedback": feedback, | |
| "email": email, | |
| "discipline": discipline, | |
| "experience": experience, | |
| }) | |
| current_index[0] += 1 | |
| if current_index[0] >= len(quiz_data): | |
| return "Feedback submitted. No more questions to review." | |
| return "Feedback submitted. Next question ready." | |
| def generate_mailto_link(): | |
| if not feedback_list: | |
| return "No feedback to send." | |
| subject = "Feedback for Train the Trainer App" | |
| body_lines = ["Feedback for Train the Trainer App:\n"] | |
| for entry in feedback_list: | |
| body_lines.append(f"Question: {entry['question']}\n") | |
| body_lines.append(f"Options: {', '.join(entry['options'])}\n") | |
| body_lines.append(f"Rating: {entry['rating']}\n") | |
| body_lines.append(f"Feedback: {entry['feedback']}\n") | |
| body_lines.append(f"Email: {entry['email']}\n") | |
| body_lines.append(f"Discipline: {', '.join(entry['discipline'])}\n") | |
| body_lines.append(f"Experience: {entry['experience']} years\n") | |
| body_lines.append("\n---\n") | |
| body = "\n".join(body_lines) | |
| body_encoded = body.replace(" ", "%20").replace("\n", "%0A") | |
| mailto_link = f"mailto:[email protected]?subject={subject}&body={body_encoded}" | |
| return mailto_link | |
| # Gradio Interface | |
| with gr.Blocks() as trainer_app: | |
| gr.Markdown("# Train the Trainer: Refine AI-Generated Questions") | |
| question_box = gr.Textbox(lines=5, label="Generated Question", interactive=False) | |
| options_box = gr.CheckboxGroup([], label="Options (for reference)") | |
| rating = gr.Radio( | |
| [ | |
| "Exactly Accurate and Relevant", | |
| "Somewhat", | |
| "Kinda Sorta", | |
| "Not Even Close", | |
| "I Have No Idea (But I Should)!", | |
| "I Have No Idea (Not in My Area of Expertise)" | |
| ], | |
| label="Rate the Question", | |
| required=True | |
| ) | |
| feedback = gr.Textbox(label="Explain corrections or feedback (optional)", lines=3) | |
| email = gr.Textbox(label="Email Address (optional)") | |
| discipline = gr.CheckboxGroup( | |
| ["Electrical Power Systems", "Lighting Design", "Controls", "Other"], | |
| label="Select your discipline(s)" | |
| ) | |
| experience = gr.Number(label="Years of Experience", value=0) | |
| submit_btn = gr.Button("Submit Feedback") | |
| next_btn = gr.Button("Next Question") | |
| mailto_btn = gr.Button("Generate Mailto Link") | |
| feedback_output = gr.Textbox(label="Feedback Status", interactive=False) | |
| mailto_output = gr.Textbox(label="Mailto Link", interactive=False) | |
| next_btn.click(get_next_question, inputs=None, outputs=[question_box, options_box]) | |
| submit_btn.click( | |
| evaluate_question, | |
| inputs=[rating, feedback, email, discipline, experience], | |
| outputs=feedback_output, | |
| ) | |
| mailto_btn.click(generate_mailto_link, inputs=None, outputs=mailto_output) | |
| trainer_app.launch() |