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'{text1[i1:i2]}')
elif tag == 'insert':
# Correction: Green bold
html.append(f'{text2[j1:j2]}')
elif tag == 'replace':
# Mistake -> Correction
html.append(f'{text1[i1:i2]}')
html.append(f'{text2[j1:j2]}')
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 "Error: The model failed to load.
"
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"""
Teacher's Report
{score}/100
Correction View
{diff_html}
"""
return report_html
except Exception as e:
return f"Error during processing: {str(e)}
"
# --- 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 red, and write corrections in green.
"""
)
# 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()