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import gradio as gr
from transformers import pipeline
import re
# ✅ Use a small, instruction-following model that works on CPU
generator = pipeline("text2text-generation", model="declare-lab/flan-alpaca-base", device=-1)
# 🧠 Structured prompt
def build_prompt(essay_text):
return f"""
You are an English teacher.
Evaluate the essay below in 6 categories. For each category, give a score from 0 to 100:
1. Grammar & Mechanics
2. Coherence & Flow
3. Clarity & Style
4. Argument Strength & Evidence
5. Structure & Organization
6. Teacher-Specific Style
Then, calculate the average of these 6 scores and return it as "Total Grade".
Respond ONLY with this exact format:
Grammar & Mechanics: [score]
Coherence & Flow: [score]
Clarity & Style: [score]
Argument Strength & Evidence: [score]
Structure & Organization: [score]
Teacher-Specific Style: [score]
Total Grade: [average]
Essay:
\"\"\"{essay_text}\"\"\"
"""
# 📄 Read .txt file input
def extract_text(file):
if file.name.endswith(".txt"):
return file.read().decode("utf-8")
return "Unsupported file type. Please upload a .txt file."
# 🧪 Main logic
def grade_essay(essay, file):
if not essay and not file:
return "Please provide either text or a file."
if file:
essay = extract_text(file)
if "Unsupported" in essay:
return essay
prompt = build_prompt(essay)
result = generator(prompt, max_new_tokens=128)[0]["generated_text"]
# 🔍 Extract scores using regex even if not formatted as JSON
categories = [
"Grammar & Mechanics",
"Coherence & Flow",
"Clarity & Style",
"Argument Strength & Evidence",
"Structure & Organization",
"Teacher-Specific Style",
"Total Grade"
]
output = {}
for cat in categories:
pattern = f"{cat}\\s*[:=]\\s*(\\d+(\\.\\d+)?)"
match = re.search(pattern, result, re.IGNORECASE)
if match:
output[cat] = float(match.group(1))
else:
output[cat] = "Not found"
return output
# 🎨 Gradio UI
with gr.Blocks() as demo:
gr.Markdown("# ✏️ MimicMark – AI Essay Evaluator")
gr.Markdown("Paste your essay or upload a `.txt` file. The AI will score it in 6 categories and return a total grade.")
with gr.Row():
essay_input = gr.Textbox(label="Paste Your Essay", lines=12)
file_input = gr.File(label="Or Upload a .txt File", file_types=[".txt"])
output = gr.JSON(label="Evaluation Results")
submit = gr.Button("Evaluate Essay")
submit.click(fn=grade_essay, inputs=[essay_input, file_input], outputs=output)
demo.launch()
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