app.py

import gradio as gr

# ✅ Placeholder AI logic (will upgrade to real LLM next)
def generate_code(task, language="Python"):
    boilerplate = {
        "Python": "# Python example\n\ndef main():\n    print('Hello World')\n\nmain()",
        "JavaScript": "// JavaScript example\n\nconsole.log('Hello World');",
        "Java": "public class Main {\n    public static void main(String[] args) {\n        System.out.println('Hello World');\n    }\n}",
        "Windows Batch": "@echo off\necho Hello World\npause"
    }
    return f"// Generated Task: {task}\n\n{boilerplate.get(language, '// Language not supported yet')}"

def explain_code(code):
    return "🧠 This code prints a greeting message.\nI will provide deeper analysis in the upgraded AI version."

def fix_code(code):
    return "✅ Fixed Code:\n" + code.replace(";;", ";").replace("pass", "# TODO: add logic")

def chat(message, history):
    history = history or []
    reply = f"🤖 AI Programmer: I understand your message:\n{message}\n\nTell me what you want to build!"
    history.append((message, reply))
    return history

def chat_handler(message, history):
    """
    message: str from textbox
    history: existing chat history list (list of tuples/lists)
    Must return: updated history (list of tuples/lists)
    """
    history = history or []

    # sanitize input
    msg = (message or "").strip()
    if not msg:
        history.append(("", "Please type a question or command."))
        return history

    # simple keyword-driven assistant (expand to real LLM later)
    low = msg.lower()
    if "hello" in low or "hi" in low:
        reply = "Hello! 👋 What would you like to build or debug today?"
    elif "generate" in low or "build" in low:
        reply = "Tell me the language and a short description (e.g., 'python: web scraper that saves to csv')."
    elif "fix" in low or "bug" in low:
        reply = "Paste the code (or error message) and I'll suggest fixes and diagnostics."
    elif "explain" in low or "what does" in low:
        reply = "Paste the code you want explained and I'll walk through it step-by-step."
    else:
        # fallback behavior — useful when switching to a real model later
        reply = "I can generate, explain, and fix code. Try commands like: `generate`, `fix`, or `explain`."

    # Append user message and bot reply as a tuple (user, bot)
    history.append((message, reply))
    return history

# UI wiring for the Chat tab
with gr.Blocks() as app:

   with gr.Tab("Chat"):  # line 60
    # everything inside the tab must be indented
    chatbot = gr.Chatbot(label="Programming Assistant", type="messages")
    chat_input = gr.Textbox(label="Ask anything...", placeholder="Type a question here...")
    send_btn = gr.Button("Send")
    clear_btn = gr.Button("Clear")

    def chat_handler(message, history):
        history = history or []
        msg = message.strip()
        if not msg:
            history.append({"role": "assistant", "content": "Please type a message."})
            return history
        history.append({"role": "user", "content": msg})
        reply = f"I heard you: {msg}"
        history.append({"role": "assistant", "content": reply})
        return history

    send_btn.click(chat_handler, [chat_input, chatbot], chatbot)
    chat_input.submit(chat_handler, [chat_input, chatbot], chatbot)
    clear_btn.click(lambda: [], None, chatbot)




    # Callback for chat
    def chat_handler(message, history):
        history = history or []
        msg = (message or "").strip()
        if not msg:
            history.append({"role": "assistant", "content": "Please type a question!"})
            return history

        # Simple AI placeholder logic
        low = msg.lower()
        if "generate" in low:
            reply = "Tell me the language and a short description, e.g. 'python: web scraper'"
        elif "fix" in low:
            reply = "Paste your code and error message; I can suggest fixes."
        else:
            reply = "I can generate, explain, and fix code. Try: generate, fix, explain."

        # Use 'messages' format
        history.append({"role": "user", "content": message})
        history.append({"role": "assistant", "content": reply})
        return history

    # Wire buttons and submit inside Blocks context
    send_btn.click(chat_handler, inputs=[chat_input, chatbot], outputs=chatbot)
    chat_input.submit(chat_handler, inputs=[chat_input, chatbot], outputs=chatbot)
    clear_btn.click(lambda: [], None, chatbot, queue=False)


# ✅ UI Layout
with gr.Blocks(title="Synthetic AI Coder") as app:

    gr.Markdown(
        """
        # 🤖 Synthetic AI Coder
        Build real software — Windows, Python, JavaScript, Java.
        """
    )

    with gr.Tab("✨ Generate Code"):
        task = gr.Textbox(label="Describe the program you want")
        lang = gr.Dropdown(
            ["Python", "JavaScript", "Java", "Windows Batch"],
            label="Language",
            value="Python"
        )
        output = gr.Code(label="Generated Code", language="python")
        generate_btn = gr.Button("Generate Software Code")
        generate_btn.click(generate_code, [task, lang], output)

    with gr.Tab("📘 Explain Code"):
        code_input = gr.Textbox(label="Paste code here", lines=10)
        explanation = gr.Textbox(label="Explanation", lines=10)
        explain_btn = gr.Button("Explain Code")
        explain_btn.click(explain_code, code_input, explanation)

    with gr.Tab("🛠 Fix/Improve Code"):
        broken = gr.Textbox(label="Paste broken code", lines=10)
        fixed = gr.Code(label="Fixed Code")
        fix_btn = gr.Button("Fix Code")
        fix_btn.click(fix_code, broken, fixed)

    with gr.Tab("💬 AI Programming Chat"):
        chatbot = gr.Chatbot()
        chat_input = gr.Textbox(label="Ask about software development")
        chat_input.submit(chat, [chat_input, chatbot], chatbot)
        gr.Button("Clear").click(lambda: [], None, chatbot)


# ✅ Required for Hugging Face Spaces
if __name__ == "__main__":
    app.launch()