trial3cata app.py

app.py

@@ -1,16 +1,16 @@
 import gradio as gr
 from transformers import pipeline
+import re
 
-# ✅ Updated to better CPU-compatible instruction-following model
+# ✅ Use a small, instruction-following model that works on CPU
 generator = pipeline("text2text-generation", model="declare-lab/flan-alpaca-base", device=-1)
 
-# 🧠 Strong prompt with JSON enforcement
+# 🧠 Structured prompt
 def build_prompt(essay_text):
     return f"""
 You are an English teacher.
 
-Please evaluate the following student essay across these 6 categories.
-Each should receive a score from 0 to 100:
+Evaluate the essay below in 6 categories. For each category, give a score from 0 to 100:
 
 1. Grammar & Mechanics  
 2. Coherence & Flow  
@@ -19,30 +19,28 @@ Each should receive a score from 0 to 100:
 5. Structure & Organization  
 6. Teacher-Specific Style  
 
-Then, calculate the average of all 6 and return it as "Total Grade".
+Then, calculate the average of these 6 scores and return it as "Total Grade".
 
-Respond ONLY in this exact JSON format:
-{{
-  "Grammar & Mechanics": 87,
-  "Coherence & Flow": 92,
-  "Clarity & Style": 85,
-  "Argument Strength & Evidence": 90,
-  "Structure & Organization": 88,
-  "Teacher-Specific Style": 91,
-  "Total Grade": 88.83
-}}
+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}\"\"\"
 """
 
-# 📄 Optional file input (.txt only)
+# 📄 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."
 
-# 🧪 Essay grading logic
+# 🧪 Main logic
 def grade_essay(essay, file):
     if not essay and not file:
         return "Please provide either text or a file."
@@ -55,13 +53,26 @@ def grade_essay(essay, file):
     prompt = build_prompt(essay)
     result = generator(prompt, max_new_tokens=128)[0]["generated_text"]
 
-    # Extract only JSON part if present
-    start = result.find("{")
-    end = result.rfind("}") + 1
-    if start != -1 and end != -1:
-        return result[start:end]
-
-    return "Model response could not be parsed. Try rephrasing your essay or shortening the input."
+    # 🔍 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:
@@ -72,7 +83,7 @@ with gr.Blocks() as demo:
         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.Textbox(label="AI Evaluation Output", lines=15)
+    output = gr.JSON(label="Evaluation Results")
 
     submit = gr.Button("Evaluate Essay")
     submit.click(fn=grade_essay, inputs=[essay_input, file_input], outputs=output)