Update app.py

app.py

@@ -1,18 +1,29 @@
+# Copyright (c) 2008-2021, Hazelcast, Inc. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
 import gradio as gr
 import torch
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 
-# Lightweight model for fast inference
-model_name = "Salesforce/codet5p-220m"
+# Model configuration
+model_name = "Salesforce/codet5p-770m"
 tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForSeq2SeqLM.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)
 
-# Prompt templates
+# Prompts for different languages
 language_prompts = {
     "Python": "Fix this Python code:\n",
     "C": "Fix this C code:\n",
@@ -20,65 +31,35 @@ language_prompts = {
     "JavaScript": "Fix this JavaScript code:\n"
 }
 
-# Debugger logic
+# Debugging logic
 def eternos_debugger(code, error, language):
     if not code.strip():
         return "❌ Please provide code."
+
     prompt = f"{language_prompts[language]}{code}\nError:\n{error}\nCorrected code:\n"
     inputs = tokenizer(prompt, return_tensors="pt", truncation=True, max_length=512).to(device)
     outputs = model.generate(
         **inputs,
-        max_new_tokens=128,
-        temperature=0.1,
-        do_sample=False,
-        pad_token_id=tokenizer.pad_token_id or tokenizer.eos_token_id
+        max_new_tokens=256,
+        temperature=0.2,
+        do_sample=False
     )
     response = tokenizer.decode(outputs[0], skip_special_tokens=True)
     return response.strip()
 
-# Reinforcement learning simulation
-def rl_simulation():
-    import gym
-    import numpy as np
-
-    env = gym.make("FrozenLake-v1", is_slippery=False)
-    Q = np.zeros([env.observation_space.n, env.action_space.n])
-    episodes = 500
-    learning_rate = 0.8
-    discount_factor = 0.95
-
-    for ep in range(episodes):
-        state = env.reset()[0]
-        done = False
-        while not done:
-            action = np.argmax(Q[state, :] + np.random.randn(1, env.action_space.n) * (1.0 / (ep + 1)))
-            new_state, reward, done, _, _ = env.step(action)
-            Q[state, action] += learning_rate * (reward + discount_factor * np.max(Q[new_state, :]) - Q[state, action])
-            state = new_state
-
-    return "🧠 RL training complete! Agent learned to navigate FrozenLake."
-
-# UI Layout (no background CSS for white theme)
-with gr.Blocks(theme=gr.themes.Soft()) as demo:
-    with gr.Tab("Eternos Debugger"):
-        gr.Markdown("## ⚙️ Eternos — AI Code Debugger")
-        gr.Markdown("Supports Python, C, C++, JavaScript — powered by CodeT5p (Fast Edition)")
-
-        with gr.Row():
-            code_input = gr.Textbox(label="📝 Your Code", lines=12)
-            error_input = gr.Textbox(label="⚠️ Error Message (optional)", lines=4)
+# UI setup
+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 CodeT5p")
 
-        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.Row():
+        code_input = gr.Textbox(label="📝 Your Code", lines=12)
+        error_input = gr.Textbox(label="⚠️ Error Message (optional)", lines=4)
 
-        run_btn.click(fn=eternos_debugger, inputs=[code_input, error_input, language_input], outputs=output_code)
+    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.Tab("Reinforcement Learning Demo"):
-        gr.Markdown("## 🤖 Reinforcement Learning Example")
-        gr.Markdown("Simulates a Q-learning agent on FrozenLake.")
-        rl_output = gr.Textbox(label="🔄 Output", lines=4)
-        rl_btn = gr.Button("🏁 Run RL Simulation")
-        rl_btn.click(fn=rl_simulation, inputs=[], outputs=rl_output)
+    run_btn.click(fn=eternos_debugger, inputs=[code_input, error_input, language_input], outputs=output_code)
 
 demo.launch()