# Code Debugger Agent - Web Version with Memory and Fix Options
# - Built with Gradio UI
# - Accepts user code input
# - Uses OpenAI GPT-4 to identify and fix bugs
# - Suggests multiple fix options
# - Remembers previous inputs during session

import openai
import gradio as gr
import tempfile
import subprocess
import os

import os
openai.api_key = os.getenv("OPENAI_API_KEY")
 # Replace with your OpenAI API key
if not openai.api_key:
    raise EnvironmentError("OPENAI_API_KEY is not set in environment variables.")

# Simple in-session memory
code_history = []

# Ask GPT-4 to fix code and return multiple versions
def ask_gpt_for_fixes(code):
    prompt = f"""
You are an expert Python debugger. Analyze the code below and suggest 3 different corrected versions if bugs are found. Each version should be well-formatted and wrapped in triple backticks.

```python
{code}
```
"""
    response = openai.ChatCompletion.create(
        model="gpt-4",
        messages=[
            {"role": "system", "content": "You are a helpful Python debugging assistant."},
            {"role": "user", "content": prompt}
        ],
        temperature=0.4,
        max_tokens=1500
    )
    return response.choices[0].message.content.strip()

# Run code in a temporary file
def run_code(code):
    with tempfile.NamedTemporaryFile(delete=False, suffix=".py", mode="w") as f:
        f.write(code)
        path = f.name

    try:
        result = subprocess.run(
            ["python", path],
            stdout=subprocess.PIPE,
            stderr=subprocess.PIPE,
            text=True,
            timeout=10
        )
        return result.stdout or "", result.stderr or ""
    finally:
        os.remove(path)

# Gradio interface logic
def debug_code_interface(user_code):
    code_history.append(user_code)
    suggestions = ask_gpt_for_fixes(user_code)

    # Extract the first fixed code block for execution (basic example)
    fixed_code = suggestions.split("```python")
    if len(fixed_code) > 1:
        first_fix = fixed_code[1].split("```")[0]
    else:
        first_fix = user_code  # fallback

    output, error = run_code(first_fix)

    return suggestions, output, error, "\n--- Session History ---\n" + "\n\n".join(code_history)

# Gradio app
demo = gr.Interface(
    fn=debug_code_interface,
    inputs=gr.Textbox(lines=20, placeholder="Paste your Python code here...", label="Your Code"),
    outputs=[
        gr.Textbox(label="Fix Suggestions (Multiple Options)"),
        gr.Textbox(label="Output from First Fix"),
        gr.Textbox(label="Errors from First Fix"),
        gr.Textbox(label="Session Memory")
    ],
    title="AI Code Debugger Agent",
    description="Paste Python code. The agent will fix bugs, show multiple versions, run the first one, and maintain memory for the session."
)

demo.launch()