Spaces:
Sleeping
Sleeping
| import gradio as gr | |
| from groq import Groq | |
| import os | |
| # Initialize Groq client | |
| client = Groq(api_key=os.environ["GROQ_API_KEY"]) | |
| def generate_tutor_output(chapter, difficulty, student_input): | |
| prompt = f""" | |
| You are an expert 10th-grade physics tutor at the {difficulty} level. | |
| The student has selected the following chapter: "{chapter}" and provided this input: "{student_input}" | |
| Please generate an unsolved test with: | |
| 1. Multiple Choice Questions (MCQs) | |
| 2. Short Answer Questions | |
| 3. Long Answer Questions | |
| Format your response as a JSON object with keys: "mcqs", "short_questions", "long_questions" | |
| """ | |
| completion = client.chat.completions.create( | |
| messages=[ | |
| { | |
| "role": "system", | |
| "content": "You are the world's best AI tutor specializing in 10th-grade physics, adept at creating customized tests. Generate MCQs, short questions, and long questions based on the provided chapter." | |
| }, | |
| { | |
| "role": "user", | |
| "content": prompt, | |
| } | |
| ], | |
| model="llama3-groq-70b-8192-tool-use-preview", | |
| max_tokens=1000, | |
| ) | |
| print("Raw Model Output:", completion.choices[0].message.content) # Debugging output | |
| return completion.choices[0].message.content | |
| with gr.Blocks() as demo: | |
| gr.Markdown("# 🎓 10th Grade Physics Tutor - Test Generator") | |
| with gr.Row(): | |
| with gr.Column(scale=2): | |
| chapter = gr.Dropdown( | |
| ["Chapter 1: Kinematics", "Chapter 2: Dynamics", "Chapter 3: Energy", "Chapter 4: Waves"], | |
| label="Select Chapter", | |
| info="Choose the chapter for the test" | |
| ) | |
| difficulty = gr.Radio( | |
| ["Beginner", "Intermediate", "Advanced"], | |
| label="Difficulty Level", | |
| info="Select your proficiency level" | |
| ) | |
| student_input = gr.Textbox( | |
| placeholder="Enter additional details...", | |
| label="Your Input", | |
| info="Specify 'MCQs', 'short questions', or 'long questions' if needed" | |
| ) | |
| submit_button = gr.Button("Generate Test", variant="primary") | |
| with gr.Column(scale=3): | |
| mcq_output = gr.Markdown(label="MCQs") | |
| short_question_output = gr.Markdown(label="Short Questions") | |
| long_question_output = gr.Markdown(label="Long Questions") | |
| gr.Markdown(""" | |
| ### Instructions | |
| 1. Select a chapter to generate questions from. | |
| 2. Choose your difficulty level. | |
| 3. Provide any additional details if needed. | |
| 4. Specify 'MCQs', 'short questions', or 'long questions' to filter the output, or leave blank for all types. | |
| 5. Click 'Generate Test' to receive questions based on the chapter. | |
| """) | |
| def process_output(output, user_input): | |
| try: | |
| # Parse the JSON output | |
| parsed = eval(output) | |
| # Filter based on the user input | |
| mcqs, short_questions, long_questions = "", "", "" | |
| if "mcq" in user_input.lower(): | |
| mcqs = "\n".join([f"**Q:** {mcq['question']} - Options: {', '.join(mcq['options'])}" for mcq in parsed.get("mcqs", [])]) | |
| if "short" in user_input.lower(): | |
| short_questions = "\n".join([sq["question"] for sq in parsed.get("short_questions", [])]) | |
| if "long" in user_input.lower(): | |
| long_questions = "\n".join([lq["question"] for lq in parsed.get("long_questions", [])]) | |
| # Default to all types if no specific type is mentioned | |
| if not any(keyword in user_input.lower() for keyword in ["mcq", "short", "long"]): | |
| mcqs = "\n".join([f"**Q:** {mcq['question']} - Options: {', '.join(mcq['options'])}" for mcq in parsed.get("mcqs", [])]) | |
| short_questions = "\n".join([sq["question"] for sq in parsed.get("short_questions", [])]) | |
| long_questions = "\n".join([lq["question"] for lq in parsed.get("long_questions", [])]) | |
| return mcqs or "No MCQs available", short_questions or "No short questions available", long_questions or "No long questions available" | |
| except Exception as e: | |
| print("Error processing output:", e) # Additional error message for debugging | |
| return "Error parsing output", "No short questions available", "No long questions available" | |
| submit_button.click( | |
| fn=lambda c, d, i: process_output(generate_tutor_output(c, d, i), i), | |
| inputs=[chapter, difficulty, student_input], | |
| outputs=[mcq_output, short_question_output, long_question_output] | |
| ) | |
| if __name__ == "__main__": |