app.py

import gradio as gr
from transformers import pipeline
import difflib

# --- Model Loading ---
# We use the 'text2text-generation' pipeline. 
# device=-1 forces CPU usage, which is required for the free tier.
print("Initializing model...")

try:
    corrector = pipeline(
        "text2text-generation",
        model="HamadML/grammer_correction",
        device=-1
    )
    print("Model loaded successfully.")
except Exception as e:
    print(f"Error loading model: {e}")
    corrector = None

# --- Helper Functions for Scoring & Visuals ---

def diff_texts(text1, text2):
    """
    Compares two strings and returns HTML highlighting differences.
    Red strikethrough for deletions, Green bold for insertions.
    """
    d = difflib.SequenceMatcher(None, text1, text2)
    html = []
    for tag, i1, i2, j1, j2 in d.get_opcodes():
        if tag == 'delete':
            # Mistake: Red strikethrough
            html.append(f'<span style="color: #ef4444; text-decoration: line-through; background-color: #fee2e2; padding: 0 2px; border-radius: 2px;">{text1[i1:i2]}</span>')
        elif tag == 'insert':
            # Correction: Green bold
            html.append(f'<span style="color: #16a34a; font-weight: bold; background-color: #dcfce7; padding: 0 2px; border-radius: 2px;">{text2[j1:j2]}</span>')
        elif tag == 'replace':
            # Mistake -> Correction
            html.append(f'<span style="color: #ef4444; text-decoration: line-through; background-color: #fee2e2; padding: 0 2px; border-radius: 2px;">{text1[i1:i2]}</span>')
            html.append(f'<span style="color: #16a34a; font-weight: bold; background-color: #dcfce7; padding: 0 2px; border-radius: 2px;">{text2[j1:j2]}</span>')
        else:
            # Unchanged text
            html.append(text1[i1:i2])
    return "".join(html)

def calculate_rubric_score(original, corrected):
    """
    Generates a simple score and feedback based on text similarity.
    """
    matcher = difflib.SequenceMatcher(None, original, corrected)
    similarity = matcher.ratio() # 0.0 to 1.0
    
    # Calculate score out of 100
    score = int(similarity * 100)
    
    if score == 100:
        feedback = "Perfect! Your grammar is flawless."
        color = "#16a34a" # Green
    elif score >= 90:
        feedback = "Excellent work! Just a few minor tweaks needed."
        color = "#16a34a"
    elif score >= 70:
        feedback = "Good effort. You have some grammar errors to fix."
        color = "#ca8a04" # Yellow/Orange
    else:
        feedback = "Needs improvement. Pay close attention to the corrections below."
        color = "#dc2626" # Red
        
    return score, feedback, color

# --- Core Logic ---
def evaluate_text(text):
    if not text or not text.strip():
        return ""
    
    if corrector is None:
        return "<p style='color:red;'>Error: The model failed to load.</p>"

    try:
        # 1. Get corrected text from AI
        results = corrector(text, max_length=128)
        corrected_text = results[0]['generated_text']
        
        # 2. Generate Visual Diff
        diff_html = diff_texts(text, corrected_text)
        
        # 3. Calculate Score
        score, feedback, color = calculate_rubric_score(text, corrected_text)
        
        # 4. Construct HTML Report
        report_html = f"""
        <div style="font-family: sans-serif; padding: 24px; border: 1px solid #e5e7eb; border-radius: 12px; background: white; box-shadow: 0 4px 6px -1px rgba(0, 0, 0, 0.1);">
            <div style="display: flex; justify-content: space-between; align-items: center; margin-bottom: 20px; border-bottom: 2px solid #f3f4f6; padding-bottom: 15px;">
                <h2 style="margin: 0; color: #1f2937; font-size: 1.5em;">Teacher's Report</h2>
                <div style="background: {color}; color: white; padding: 8px 20px; border-radius: 99px; font-weight: bold; font-size: 1.2em;">
                    {score}/100
                </div>
            </div>
            
            <div style="margin-bottom: 25px;">
                <p style="color: #6b7280; margin: 0 0 8px 0; font-size: 0.85em; text-transform: uppercase; letter-spacing: 0.1em; font-weight: bold;">Feedback</p>
                <p style="margin: 0; color: #374151; font-size: 1.1em; font-style: italic;">"{feedback}"</p>
            </div>

            <div>
                <p style="color: #6b7280; margin: 0 0 12px 0; font-size: 0.85em; text-transform: uppercase; letter-spacing: 0.1em; font-weight: bold;">Correction View</p>
                <div style="line-height: 1.8; font-size: 1.2em; color: #1f2937; background: #f9fafb; padding: 15px; border-radius: 8px; border: 1px solid #e5e7eb;">
                    {diff_html}
                </div>
            </div>
        </div>
        """
        return report_html
        
    except Exception as e:
        return f"<p style='color:red;'>Error during processing: {str(e)}</p>"

# --- User Interface ---
# CSS to hide footer and API links visually
css = """
footer {display: none !important;}
.api-link {display: none !important;}
"""

with gr.Blocks(title="Grammar Evaluator", theme=gr.themes.Soft(), css=css) as demo:
    gr.Markdown(
        """
        # 📝 AI Grammar Tool (Helper)
        Type your sentence below. The AI will grade it, cross out mistakes in <span style='color: red; text-decoration: line-through;'>red</span>, and write corrections in <span style='color: green; font-weight: bold;'>green</span>.
        """
    )
    
    # Vertical Layout
    input_box = gr.Textbox(
        label="Student Writing", 
        placeholder="Example: I has went to the store yesterday...",
        lines=5
    )
    
    submit_btn = gr.Button("Check My Text", variant="primary", size="lg")
    
    output_html = gr.HTML(label="Evaluation Report")

    submit_btn.click(fn=evaluate_text, inputs=input_box, outputs=output_html)
    input_box.submit(fn=evaluate_text, inputs=input_box, outputs=output_html)

if __name__ == "__main__":
    demo.launch()