Update app.py

app.py

@@ -1,47 +1,15 @@
-import os
-import json
 import gradio as gr
-from transformers import AutoTokenizer, AutoModelForCausalLM
+from tinyllama_inference import evaluate_code
 
-def load_model():
-    # Use a public, open-source model for code evaluation.
-    model_name = "Salesforce/codegen-350M-mono"
-    tokenizer = AutoTokenizer.from_pretrained(model_name)
-    model = AutoModelForCausalLM.from_pretrained(model_name)
-    return tokenizer, model
-
-# Load the model once at startup.
-tokenizer, model = load_model()
-
-def evaluate_model(prompt):
-    inputs = tokenizer(prompt, return_tensors="pt")
-    outputs = model.generate(**inputs, max_new_tokens=150)
-    response_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
-    try:
-        result = json.loads(response_text.strip())
-    except Exception as e:
-        result = {"stars": 0, "feedback": "Evaluation failed. Unable to parse AI response."}
-    return result
-
-def evaluate_code(language, question, code):
+def evaluate_interface(language, question, code):
     if not code.strip():
         return "Error: No code provided. Please enter your solution code."
-    
-    # Build the prompt for the evaluation model.
-    prompt = f"""
-You are an expert code evaluator.
-Rate the following solution on a scale of 0-5 (0 = completely incorrect, 5 = excellent) and provide a concise feedback message.
-Language: {language}
-Problem: "{question}"
-Solution: "{code}"
-Return ONLY valid JSON: {{"stars": number, "feedback": string}}.
-Do not include any extra text.
-"""
-    result = evaluate_model(prompt)
+    # Here you might choose to use the language input to further tailor the prompt if needed.
+    result = evaluate_code(question, code)
     return f"Stars: {result.get('stars', 0)}\nFeedback: {result.get('feedback', '')}"
 
 iface = gr.Interface(
-    fn=evaluate_code,
+    fn=evaluate_interface,
     inputs=[
         gr.Dropdown(choices=["C", "Python", "Java"], label="Language"),
         gr.Textbox(lines=2, placeholder="Enter the problem question here...", label="Question"),