Update app.py

app.py

@@ -1,56 +1,44 @@
 import gradio as gr
 import torch
-from transformers import AutoTokenizer, AutoModelForCausalLM
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+from threading import Thread
+import time
 
-# Model configuration: CodeGemma 1.1B
-MODEL_NAME = "google/codegemma-1.1b"
+# Load small and fast model for Python code debugging
+MODEL_NAME = "Salesforce/codet5-small"
 tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
-model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32)
+model = AutoModelForSeq2SeqLM.from_pretrained(MODEL_NAME)
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 model.to(device)
 
-# Supported languages and their prompt templates
-LANGUAGE_PROMPTS = {
-    "Python": "Fix this Python code:",
-    "C": "Fix this C code:",
-    "C++": "Fix this C++ code:",
-    "JavaScript": "Fix this JavaScript code:"
-}
-
-def eternos_debugger(code, error, language):
+def debug_python(code, progress=gr.State(0)):
     if not code.strip():
-        return "❌ Please provide code."
-    prompt = f"{LANGUAGE_PROMPTS[language]}\n{code}\nError:\n{error}\nCorrected code:\n"
+        return "❌ Please enter Python code.", 0
+
+    prompt = f"Fix this Python code:\n{code}\nCorrected code:\n"
     inputs = tokenizer(prompt, return_tensors="pt", truncation=True, max_length=512).to(device)
-    outputs = model.generate(
-        **inputs,
-        max_new_tokens=256,
-        temperature=0.1,
-        top_p=0.9,
-        do_sample=False,
-        pad_token_id=tokenizer.eos_token_id
-    )
-    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
-    return response.strip()
 
-# Gradio user interface
-def create_interface():
-    with gr.Blocks(theme=gr.themes.Soft(), css=".gradio-container {background-color: #cbedec;}") as demo:
-        gr.Markdown("## ⚙️ Eternos — AI Code Debugger")
-        gr.Markdown("Supports Python, C, C++, JavaScript — powered by CodeGemma 1.1B")
+    def update_progress():
+        for i in range(1, 101):
+            time.sleep(0.005)  # Faster loading feel
+            progress.value = i
 
-        with gr.Row():
-            code_input = gr.Textbox(label="📝 Your Code", lines=12)
-            error_input = gr.Textbox(label="⚠️ Error Message (optional)", lines=4)
+    Thread(target=update_progress).start()
+
+    outputs = model.generate(**inputs, max_new_tokens=256, temperature=0.2, do_sample=False)
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    progress.value = 100
+    return response.strip(), 100
 
-        language_input = gr.Dropdown(["Python", "C", "C++", "JavaScript"], label="🌐 Language", value="Python")
-        output_code = gr.Code(label="✅ Suggested Fix")
-        run_btn = gr.Button("🛠️ Fix Code")
+with gr.Blocks(css=".gradio-container {background-color: #cbedec;}") as app:
+    gr.Markdown("## 🐍 Python Code Debugger (Fast Mode)")
+    gr.Markdown("Just paste your Python code. The AI will fix any issues it detects.")
 
-        run_btn.click(fn=eternos_debugger, inputs=[code_input, error_input, language_input], outputs=output_code)
+    code_box = gr.Textbox(label="📝 Your Python Code", lines=12)
+    progress_bar = gr.Slider(minimum=0, maximum=100, value=0, interactive=False, label="⏳ Progress (%)")
+    output = gr.Code(label="✅ Suggested Fix")
+    fix_btn = gr.Button("🛠️ Debug Code")
 
-    return demo
+    fix_btn.click(fn=debug_python, inputs=[code_box], outputs=[output, progress_bar])
 
-if __name__ == "__main__":
-    demo = create_interface()
-    demo.launch()
+app.launch()