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| import gradio as gr | |
| from groq import Groq | |
| import os | |
| import json | |
| # Initialize Groq client | |
| client = Groq(api_key=os.environ["GROQ_API_KEY"]) | |
| print("API Key:", os.environ.get("GROQ_API_KEY")) # Debug print | |
| def generate_tutor_output(subject, grade, student_input, model): | |
| prompt = f""" | |
| You are an expert tutor in {subject} for a {grade} grade student. | |
| The student has provided the following input: "{student_input}" | |
| Please generate: | |
| 1. A fun, engaging lesson (2-3 paragraphs) tailored to a {grade} grader's understanding. | |
| 2. A thought-provoking multiple-choice question (with 4 options: a, b, c, d) to test understanding. | |
| 3. Constructive feedback on the student's input. | |
| Format your response as a JSON object with keys: "lesson", "question", "options", "correct_answer", "feedback" | |
| """ | |
| try: | |
| completion = client.chat.completions.create( | |
| messages=[ | |
| { | |
| "role": "system", | |
| "content": f"You are a fun, creative AI tutor for {grade} graders, expert in {subject}. You explain concepts in a simple, exciting way with relatable examples (like math problems for their age). Your goal is to spark curiosity and help students practice what they learn!", | |
| }, | |
| { | |
| "role": "user", | |
| "content": prompt, | |
| } | |
| ], | |
| model=model, | |
| max_tokens=1200, | |
| ) | |
| return completion.choices[0].message.content | |
| except Exception as e: | |
| print(f"Groq API Error: {str(e)}") # Debug print | |
| return json.dumps({ | |
| "lesson": f"Error: Could not generate lesson. API error: {str(e)}", | |
| "question": "No question available", | |
| "options": [], | |
| "correct_answer": "", | |
| "feedback": "No feedback available due to API error" | |
| }) | |
| def check_answer(selected_answer, correct_answer): | |
| if selected_answer == correct_answer: | |
| return "🎉 Awesome job! You got it right! Keep rocking it!", 10 | |
| else: | |
| return f"😅 Not quite! The correct answer was '{correct_answer}'. Try again next time!", 0 | |
| with gr.Blocks(title="Learn & Practice 🚀") as demo: | |
| gr.Markdown("# 🚀 Learn & Practice Zone (Grades 5-10)") | |
| # Input Section | |
| with gr.Row(): | |
| with gr.Column(scale=2): | |
| subject = gr.Dropdown( | |
| ["Math", "Science", "History", "Geography", "Economics"], | |
| label="Subject", | |
| info="Pick your favorite subject!" | |
| ) | |
| grade = gr.Dropdown( | |
| ["5th Grade", "6th Grade", "7th Grade", "8th Grade", "9th Grade", "10th Grade"], | |
| label="Your Grade", | |
| info="Select your grade level" | |
| ) | |
| model_select = gr.Dropdown( | |
| [ | |
| "mixtral-8x7b-32768", | |
| "llama3-8b-8192", # Fallback model | |
| "qwen-2.5-32b" | |
| ], | |
| label="AI Tutor Model", | |
| value="mixtral-8x7b-32768", | |
| info="Choose your AI tutor" | |
| ) | |
| student_input = gr.Textbox( | |
| placeholder="What do you want to learn today?", | |
| label="Your Question", | |
| info="Ask anything about the subject!" | |
| ) | |
| submit_button = gr.Button("Get Lesson & Practice", variant="primary") | |
| # Output Section | |
| with gr.Column(scale=3): | |
| lesson_output = gr.Markdown(label="Your Lesson") | |
| question_output = gr.Markdown(label="Test Your Skills") | |
| options_output = gr.Radio(label="Choose an Answer", choices=[], visible=False) | |
| feedback_output = gr.Markdown(label="Feedback on Your Question") | |
| answer_feedback = gr.Markdown(label="Answer Feedback") | |
| points = gr.Number(label="Your Points", value=0) | |
| # Instructions | |
| gr.Markdown(""" | |
| ### How to Play & Learn | |
| 1. Pick a subject and your grade. | |
| 2. Choose an AI tutor model. | |
| 3. Ask a question or topic you’re curious about. | |
| 4. Read the fun lesson, then answer the question to test yourself. | |
| 5. Earn points for correct answers and keep learning! | |
| """) | |
| def process_output(output): | |
| print(f"Raw API Output: {output}") # Debug print | |
| try: | |
| parsed = json.loads(output) | |
| options = [f"{k}. {v}" for k, v in zip(["a", "b", "c", "d"], parsed["options"])] | |
| return ( | |
| parsed["lesson"], | |
| parsed["question"], | |
| options, | |
| parsed["correct_answer"], | |
| parsed["feedback"] | |
| ) | |
| except Exception as e: | |
| print(f"JSON Parsing Error: {str(e)}") # Debug print | |
| return ( | |
| f"Error parsing response: {str(e)}", | |
| "No question available", | |
| [], | |
| "", | |
| "No feedback available" | |
| ) | |
| def update_interface(subject, grade, student_input, model): | |
| print(f"Selected Model: {model}") # Debug print | |
| output = generate_tutor_output(subject, grade, student_input, model) | |
| lesson, question, options, correct_answer, feedback = process_output(output) | |
| return ( | |
| lesson, | |
| question, | |
| gr.update(choices=options, visible=True), | |
| feedback, | |
| "", # Clear answer feedback | |
| gr.update(value=0) # Reset points | |
| ), correct_answer | |
| # State to store correct answer | |
| correct_answer_state = gr.State() | |
| submit_button.click( | |
| fn=update_interface, | |
| inputs=[subject, grade, student_input, model_select], | |
| outputs=[lesson_output, question_output, options_output, feedback_output, answer_feedback, points] | |
| ).then( | |
| fn=lambda x: x, | |
| inputs=[gr.State()], | |
| outputs=[correct_answer_state] | |
| ) | |
| options_output.change( | |
| fn=check_answer, | |
| inputs=[options_output, correct_answer_state], | |
| outputs=[answer_feedback, points] | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch(server_name="0.0.0.0", server_port=7860) |