Rename app.py to Scoring System.py

Scoring System.py

@@ -0,0 +1,25 @@
+# scoring.py
+BAND_CRITERIA = {
+    'vocab': {
+        9: {"threshold": 0.9, "description": "Sophisticated lexical items"},
+        8: {"threshold": 0.8, "description": "Wide resource, occasional errors"},
+        7: {"threshold": 0.7, "description": "Adequate range"},
+        6: {"threshold": 0.6, "description": "Limited range"}
+    },
+    'grammar': {
+        9: {"errors": 0, "description": "Virtually error-free"},
+        8: {"errors": 2, "description": "Rare minor errors"},
+        7: {"errors": 4, "description": "Some errors"},
+        6: {"errors": 6, "description": "Frequent errors"}
+    }
+}
+
+def convert_to_band(raw_score, category):
+    """Convert raw model output to IELTS band"""
+    bands = sorted(BAND_CRITERIA[category].items(), reverse=True)
+    for band, criteria in bands:
+        if category == 'vocab' and raw_score >= criteria['threshold']:
+            return band
+        elif category == 'grammar' and raw_score <= criteria['errors']:
+            return band
+    return 4  # Minimum band

app.py

@@ -1,93 +0,0 @@
-import gradio as gr
-import spacy
-import requests
-from transformers import pipeline
-from supabase import create_client
-from statistics import mean
-
-# Configuration
-SUPABASE_URL = "your-supabase-url"
-SUPABASE_KEY = "your-supabase-key"
-HF_TOKEN = "your-hf-token"
-nlp = spacy.load("en_core_web_lg")
-
-# Models
-MODELS = {
-    "vocab": pipeline("text-classification", 
-                    model="domenicrosati/IELTS-writing-task-2-rater"),
-    "grammar": pipeline("text2text-generation",
-                       model="vennify/t5-base-grammar-correction"),
-    "coherence": pipeline("feature-extraction",
-                        model="sentence-transformers/all-mpnet-base-v2")
-}
-
-# Supabase Client
-supabase = create_client(SUPABASE_URL, SUPABASE_KEY)
-
-def analyze_text(essay):
-    """Comprehensive text analysis using multiple NLP techniques"""
-    doc = nlp(essay)
-    
-    # Vocabulary Analysis
-    vocab_score = MODELS["vocab"](essay)[0]["score"] * 9
-    
-    # Grammar Analysis
-    grammar_errors = len(MODELS["grammar"](f"grammar: {essay}")[0]["generated_text"].split("<error>")) - 1
-    grammar_score = max(1, 9 - (grammar_errors // 1.2))
-    
-    # Coherence Analysis
-    embeddings = MODELS["coherence"](essay)
-    transition_words = ["however", "moreover", "furthermore", "consequently"]
-    transitions = sum(1 for token in doc if token.text.lower() in transition_words)
-    coherence_score = min(9, 4 + (transitions * 0.5) + (len(doc.ents) * 0.2))
-    
-    # Task Achievement (Using Mistral-7B)
-    task_response = requests.post(
-        "https://api-inference.huggingface.co/models/mistralai/Mistral-7B-Instruct-v0.3",
-        headers={"Authorization": f"Bearer {HF_TOKEN}"},
-        json={"inputs": f"Rate IELTS task achievement (1-9): {essay}"}
-    )
-    task_score = int(task_response.json()[0]["generated_text"][:1]) if task_response.ok else 6
-    
-    return {
-        "vocab": round(vocab_score, 1),
-        "grammar": grammar_score,
-        "coherence": round(coherence_score, 1),
-        "task": task_score,
-        "overall": round(mean([vocab_score, grammar_score, coherence_score, task_score]), 1)
-    }
-
-def evaluate_ielts(essay):
-    analysis = analyze_text(essay)
-    
-    # Store results
-    supabase.table("ielts_results").insert({
-        "essay": essay,
-        "scores": analysis,
-        "timestamp": "now()"
-    }).execute()
-    
-    return analysis
-
-# Professional Gradio Interface
-with gr.Blocks(theme=gr.themes.Soft(), css=".gradio-container {max-width: 800px!important}") as demo:
-    gr.Markdown("## Professional IELTS Evaluation System")
-    
-    with gr.Row():
-        essay_input = gr.Textbox(label="Enter Essay", lines=10, 
-                               placeholder="Discuss both views and give your opinion...")
-        output_json = gr.JSON(label="Evaluation Results")
-    
-    with gr.Row():
-        gr.Examples(
-            examples=[
-                ["While some argue technology improves learning, others believe it distracts students. This essay examines both perspectives before concluding that balanced use offers optimal benefits."],
-                ["Environmental protection requires global cooperation. Governments must implement stricter regulations while promoting sustainable energy alternatives to combat climate change effectively."]
-            ],
-            inputs=essay_input
-        )
-    
-    submit_btn = gr.Button("Evaluate", variant="primary")
-    submit_btn.click(fn=evaluate_ielts, inputs=essay_input, outputs=output_json)
-
-demo.launch()