Update app.py

app.py

@@ -1,42 +1,111 @@
 import gradio as gr
-import torch
-from transformers import CodeT5ForConditionalGeneration, CodeT5Tokenizer
-
-# Load pre-trained CodeT5 model and tokenizer
-model = CodeT5ForConditionalGeneration.from_pretrained("Salesforce/code-t5-small")
-tokenizer = CodeT5Tokenizer.from_pretrained("Salesforce/code-t5-small")
-
-def generate_code(prompt, code_file):
-    # Read uploaded code file
-    if code_file:
-        code_text = code_file.read().decode("utf-8")
-    else:
-        code_text = ""
-
-    # Tokenize input prompt
-    input_ids = tokenizer.encode(prompt, return_tensors="pt")
-
-    # Generate code using CodeT5 model
-    output = model.generate(input_ids=input_ids, max_length=256)
-    generated_code = tokenizer.decode(output[0], skip_special_tokens=True)
-
-    # Return generated code and code preview
-    return generated_code, f"```python\n{generated_code}\n```"
-
-# Create Gradio interface
-iface = gr.Interface(
-    fn=generate_code,
-    inputs=[
-________gr.Textbox(label="Input_Prompt",_placeholder="Enter_a_prompt"),
-________gr.Upload(label="Upload_Code_File",_file_types=["py"])
-    ],
-    outputs=[
-________gr.Textbox(label="Generated_Code"),
-________gr.Code(label="Code_Preview",_language="python")
-____],
-    title="Code Generation with CodeT5",
-    description="Generate Python code based on input prompt and uploaded code file."
-)
-
-# Launch Gradio interface
-iface.launch()
+
+def fix_code(code_input, language, fix_mode):
+    """
+    Placeholder function to 'fix' the code.
+    In a real scenario, you'd integrate your LLM or custom logic here.
+    """
+    # For demonstration, just returning a mock "fixed" version
+    fixed_code = f"# Fixed [{language} - {fix_mode}]\n" + code_input
+    explanation = (
+        "Here's a mock explanation of what was fixed:\n"
+        "1. Analyzed the code.\n"
+        "2. Applied debugging/optimization.\n"
+        "3. Returned updated code."
+    )
+    return explanation, fixed_code
+
+def run_code(code_input, language):
+    """
+    Run the corrected code in a sandbox or a safe environment.
+    Here, we just pretend to run it and return a mock output.
+    
+    IMPORTANT: Executing arbitrary code can be dangerous. 
+    In real-world apps, you need a secure sandbox environment.
+    """
+    # Mock execution output
+    return f"Running [{language}] code...\nOutput:\nHello from the mock run!\n\nCode:\n{code_input}"
+
+def chat_mode_interaction(user_input):
+    """
+    Example 'Chat Mode' function.
+    """
+    # Return a mock chat response
+    return f"You said: {user_input}\n\nAI says: This is a placeholder chat response."
+
+# Build the UI
+with gr.Blocks(title="AI Code Doctor - Fix, Optimize & Run") as demo:
+    gr.Markdown(
+        """
+        # AI Code Doctor - Fix, Optimize & Run
+        **The Ultimate Debugging Machine**  
+        """
+    )
+
+    # Tabs for Code Debug vs. Chat Mode
+    with gr.Tab("Code Debug"):
+        with gr.Row():
+            with gr.Column():
+                language = gr.Dropdown(
+                    label="Select Language",
+                    choices=["Python", "JavaScript", "C++", "Mistral", "Any"],
+                    value="Python"
+                )
+                fix_mode = gr.Dropdown(
+                    label="Select Fix Mode",
+                    choices=["Fix Errors Only", "Fix + Optimize", "Fix + Explain"],
+                    value="Fix + Explain"
+                )
+                code_input = gr.Textbox(
+                    label="Paste Your Code",
+                    lines=10,
+                    placeholder="Enter code here..."
+                )
+                
+                # Buttons
+                fix_button = gr.Button("⚙️ Fix Code")
+                
+                # AI Output
+                ai_explanation = gr.Textbox(
+                    label="AI Explanation",
+                    lines=5,
+                    interactive=False
+                )
+                corrected_code = gr.Textbox(
+                    label="Corrected Code",
+                    lines=10,
+                    interactive=False
+                )
+
+            with gr.Column():
+                execution_output = gr.Textbox(
+                    label="Execution Output",
+                    lines=15,
+                    interactive=False
+                )
+                run_button = gr.Button("▶️ Run My Code")
+        
+        # Define button actions
+        fix_button.click(
+            fix_code, 
+            inputs=[code_input, language, fix_mode], 
+            outputs=[ai_explanation, corrected_code]
+        )
+        run_button.click(
+            run_code,
+            inputs=[corrected_code, language],
+            outputs=execution_output
+        )
+
+    with gr.Tab("Chat Mode"):
+        chat_input = gr.Textbox(label="Enter your message", lines=2)
+        chat_output = gr.Textbox(label="Chat Output", lines=5, interactive=False)
+        chat_button = gr.Button("Send")
+        
+        chat_button.click(
+            chat_mode_interaction,
+            inputs=chat_input,
+            outputs=chat_output
+        )
+
+demo.launch()