| import gradio as gr |
| from transformers import pipeline |
| import re |
|
|
| |
| generator = pipeline("text2text-generation", model="declare-lab/flan-alpaca-base", device=-1) |
|
|
| |
| 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}\"\"\" |
| """ |
|
|
| |
| def extract_text(file): |
| if file.name.endswith(".txt"): |
| return file.read().decode("utf-8") |
| return "Unsupported file type. Please upload a .txt file." |
|
|
| |
| 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"] |
|
|
| |
| 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 |
|
|
| |
| 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() |
|
|
