import gradio as gr
import ast


def grade(student_code):
    feedback = []
    grade = 10  # Start with full points

    try:
        tree = ast.parse(student_code)

        ema_detected = False
        i2s_used = False
        rms_calculation = False
        db_conversion = False

        for node in ast.walk(tree):
            # Check for I2S microphone usage
            if isinstance(node, ast.Assign) and isinstance(node.value, ast.Call):
                if isinstance(node.value.func, ast.Name) and node.value.func.id == "I2S":
                    i2s_used = True
            
            # Check for RMS calculation
            if isinstance(node, ast.FunctionDef) and node.name == "calculate_rms":
                rms_calculation = True
            
            # Check for dB conversion
            if isinstance(node, ast.FunctionDef) and node.name == "rms_to_db":
                db_conversion = True
            
            # Check for EMA implementation
            if isinstance(node, ast.Assign) and isinstance(node.value, ast.BinOp):
                if isinstance(node.value.op, ast.Add) and isinstance(node.value.left, ast.BinOp):
                    if isinstance(node.value.left.op, ast.Mult):
                        ema_detected = True

        if not i2s_used:
            feedback.append("⛔️ No I2S microphone setup detected (-3 pts).")
            grade -= 3
        else:
            feedback.append("✅ I2S microphone setup detected (+3 pts).")

        if not rms_calculation:
            feedback.append("⛔️ No RMS calculation function detected (-2 pts).")
            grade -= 2
        else:
            feedback.append("✅ RMS calculation function detected (+2 pts).")

        if not db_conversion:
            feedback.append("⛔️ No RMS to dB conversion function detected (-2 pts).")
            grade -= 2
        else:
            feedback.append("✅ RMS to dB conversion function detected (+2 pts).")

        if not ema_detected:
            feedback.append("⛔️ No exponential moving average (EMA) detected (-3 pts).")
            grade -= 3
        else:
            feedback.append("✅ Exponential moving average (EMA) detected (+3 pts).")

    except Exception as e:
        feedback = [f"⛔️ Error parsing code: {e}"]
        grade = 0

    grade = max(0, grade)
    grade = f"{grade}/10"
    feedback = "\n".join(feedback)
    return grade, feedback

# Interface Gradio seulement si le script est exécuté directement
if __name__ == "__main__":
    with gr.Blocks(gr.themes.Default(primary_hue="cyan")) as demo:
        with gr.Row():
            instructions = gr.Markdown("""
                ## Instructions
                1. Based on the examples you've seen so far, write a MicroPython code that follows the instructions above.                
                2. You can use the [Vittascience simulator](https://fr.vittascience.com/esp32/?mode=code&console=bottom&toolbox=scratch&simu=1&board=basic-esp32) to test your code.
                2. Click the "Grade" button to get a grade and feedback.
                3. Make sure your code is well-structured and efficient.
                4. When you're happy with your code, please upload your solution below to get graded.
                6. Good luck!
            """, container=False)
            code = gr.Code(label="MicroPython code", language="python", value='import machine\nimport time\nimport math\nfrom machine import I2S, Pin\n\n# Define your I2S pins\nCK_PIN = 32  # Clock pin\nWS_PIN = 31  # Word Select (LRCLK)\nSD_PIN = 26  # Serial Data\n\n# Your code here', lines=24)
        with gr.Row():
            feedback_output = gr.Textbox(label="Feedback", value="Click on the 'Grade' button to get feedback", interactive=False, scale=4)
            grade_output = gr.Textbox(label="Grade", interactive=False, value="0/10", scale=1)
        grade_btn = gr.Button("Grade", variant="primary")
        grade_btn.click(fn=grade, inputs=code, outputs=[grade_output, feedback_output], api_name="grade")

    demo.launch(show_error=False, allowed_paths=["/assets", "assets"], show_api=False)