App.py

# app.py
import os
import time
import traceback
import openai
import gradio as gr

# ---- Config / Defaults ----
MODEL_NAME = "gpt-3.5-turbo"  # change to "gpt-4" if you have access
DEFAULT_SYSTEM_PROMPT = (
    "You are a kind, empathetic bilingual assistant (Urdu & English). "
    "Answer concisely and helpfully. If user writes in Urdu, reply in Urdu; "
    "if in English, reply in English. Preserve politeness and clarity."
)

# Load API key from env (Hugging Face secret should set OPENAI_API_KEY)
openai.api_key = os.getenv("OPENAI_API_KEY")

# ---- Helpers ----
def detect_language(text: str) -> str:
    # Very simple heuristic: presence of Arabic/Persian/Urdu characters
    for ch in text:
        if '\u0600' <= ch <= '\u06FF':
            return "ur"
    return "en"

def fallback_reply(user_message: str):
    """If no API key or API fails, return a helpful local reply."""
    lang = detect_language(user_message)
    if lang == "ur":
        # Some friendly fallback phrases in Urdu
        responses = [
            "معذرت — ابھی سرور سے رابطہ ممکن نہیں۔ میں آپ کا پیغام نوٹ کر رہا ہوں: " + user_message,
            "میں فی الحال API سے جڑ نہیں پارہا، مگر بتائیں میں ابھی بھی سن رہا ہوں۔",
            "آپ نے کہا: " + user_message + " — جب سروس واپس آئے گی تو مفصل جواب دوں گا۔"
        ]
    else:
        responses = [
            "Sorry — I'm temporarily offline. Noting your message: " + user_message,
            "I can't reach the API right now, but I'm listening. Please try again shortly.",
            "You said: " + user_message + " — I'll respond fully once service is available."
        ]
    # rotate based on time to vary replies
    return responses[int(time.time()) % len(responses)]

def call_openai_chat(system_prompt, user_message, max_tokens=512, temperature=0.7, top_p=0.95):
    """
    Call OpenAI ChatCompletion and return assistant text.
    Raises Exception on failure.
    """
    # messages: system + user
    messages = [{"role": "system", "content": system_prompt},
                {"role": "user", "content": user_message}]
    resp = openai.ChatCompletion.create(
        model=MODEL_NAME,
        messages=messages,
        max_tokens=max_tokens,
        temperature=temperature,
        top_p=top_p,
    )
    # defensive extraction
    try:
        text = resp.choices[0].message.content
    except Exception:
        text = resp.choices[0].text if hasattr(resp.choices[0], "text") else ""
    return text.strip()

# ---- Main chat handler ----
def respond(message, chat_history, system_message, max_tokens, temperature, top_p):
    """
    message: user input string
    chat_history: list of tuples [(user, bot), ...]
    system_message: custom system prompt (string)
    max_tokens, temperature, top_p: numeric controls
    """
    if chat_history is None:
        chat_history = []

    system_prompt = system_message.strip() or DEFAULT_SYSTEM_PROMPT

    # if empty message
    if not message or not message.strip():
        return chat_history + [("","Please type something or ask a question.")]

    # try OpenAI if key present
    if openai.api_key:
        try:
            reply = call_openai_chat(system_prompt, message,
                                     max_tokens=int(max_tokens),
                                     temperature=float(temperature),
                                     top_p=float(top_p))
        except Exception as e:
            # log traceback to help debugging (visible in Space logs)
            print("OpenAI call failed:", str(e))
            traceback.print_exc()
            reply = (
                "معذرت! سروس سے رابطے میں مسئلہ آیا۔ براہِ کرم بعد میں دوبارہ کوشش کریں۔"
                if detect_language(message) == "ur"
                else "Sorry! There was an issue contacting the service. Please try again later."
            )
    else:
        # No API key — graceful fallback
        reply = fallback_reply(message)

    chat_history = chat_history + [(message, reply)]
    return chat_history

# ---- Gradio UI ----
with gr.Blocks(theme=gr.themes.Default()) as demo:
    gr.Markdown("<h2>🤝 What In Mind AI — Urdu & English Chatbot</h2>")
    gr.Markdown("A warm, bilingual assistant. If OpenAI key is not set, the bot uses a safe local fallback.")

    with gr.Row():
        with gr.Column(scale=3):
            chatbot = gr.Chatbot(label="Chat")
            message = gr.Textbox(placeholder="Type in Urdu or English...", show_label=False)
            with gr.Row():
                send = gr.Button("Send")
                clear = gr.Button("Clear")

        with gr.Column(scale=1):
            gr.Markdown("### Settings")
            system_message = gr.Textbox(value=DEFAULT_SYSTEM_PROMPT, label="System prompt (optional)")
            max_tokens = gr.Slider(minimum=64, maximum=1024, value=512, step=64, label="Max new tokens")
            temperature = gr.Slider(minimum=0.1, maximum=1.0, value=0.7, step=0.05, label="Temperature")
            top_p = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus)")

    # state for history
    history_state = gr.State([])

    def submit_click(msg, history, sysmsg, max_tokens, temperature, top_p):
        new_hist = respond(msg, history, sysmsg, max_tokens, temperature, top_p)
        # gr.Chatbot expects list of tuples
        return "", new_hist

    send.click(fn=submit_click, inputs=[message, history_state, system_message, max_tokens, temperature, top_p], outputs=[message, chatbot,])
    message.submit(fn=submit_click, inputs=[message, history_state, system_message, max_tokens, temperature, top_p], outputs=[message, chatbot,])
    clear.click(lambda: ([], ""), [], [chatbot, message])

    # sync state: after each update set history_state
    def sync_state(history):
        return history
    chatbot.change(fn=lambda history: None, inputs=[chatbot], outputs=[])

    gr.Markdown("---")
    gr.Markdown("**Note:** To enable OpenAI responses, add your OpenAI API key as a secret named `OPENAI_API_KEY` in your Hugging Face Space settings. Do not share your key publicly.")

# Launch
if __name__ == "__main__":
    demo.launch()