Try1 app.py

Mimicapp.py

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+import gradio as gr
+from transformers import pipeline
+import os
+
+# Load model (replace with any instruct-style model hosted on Hugging Face Hub)
+model_name = "mistralai/Mixtral-8x7B-Instruct-v0.1"  # You can change this
+generator = pipeline("text-generation", model=model_name, device=-1)  # CPU only
+
+# Prompt template
+def build_prompt(essay_text):
+    return f"""You are an experienced English teacher.
+
+Your task is to evaluate the following student essay in 6 categories, each scored from 0 to 100.
+
+Categories:
+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 the 6 scores as the Total Grade.
+
+Output format:
+Return only a JSON object like this:
+{{
+  "Grammar & Mechanics": score,
+  "Coherence & Flow": score,
+  "Clarity & Style": score,
+  "Argument Strength & Evidence": score,
+  "Structure & Organization": score,
+  "Teacher-Specific Style": score,
+  "Total Grade": average
+}}
+
+Here is the essay:
+{essay_text}
+"""
+
+# Text extractor for uploaded files
+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 function
+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=400, temperature=0.5)[0]["generated_text"]
+    
+    # Extract JSON from result
+    start = result.find("{")
+    end = result.rfind("}") + 1
+    try:
+        return result[start:end]
+    except:
+        return "Model response couldn't be parsed."
+
+# UI
+with gr.Blocks() as demo:
+    gr.Markdown("# ✏️ MimicMark - Essay Evaluator")
+    gr.Markdown("Upload or paste your essay. The AI will rate it in 6 categories and return a final score.")
+
+    with gr.Row():
+        essay_input = gr.Textbox(label="Paste Your Essay Here", lines=12)
+        file_input = gr.File(label="Or Upload a .txt File", file_types=[".txt"])
+    
+    output = gr.Textbox(label="Evaluation Output", lines=15)
+
+    btn = gr.Button("Evaluate Essay")
+    btn.click(fn=grade_essay, inputs=[essay_input, file_input], outputs=output)
+
+demo.launch()