import gradio as gr
import os
import sys
import json
import requests
import random

# =====================================================
# Environment variables (Hugging Face Spaces SAFE)
# =====================================================

MODEL = "gpt-4.1-mini"  # Updated to a valid model for Responses API

API_URL = os.getenv("API_URL")
if not API_URL:
    raise RuntimeError("API_URL not set in Hugging Face Secrets")

DISABLED = os.getenv("DISABLED", "False") == "True"

keys = os.getenv("OPENAI_API_KEYS")
if not keys:
    raise RuntimeError("OPENAI_API_KEYS not set in Hugging Face Secrets")

OPENAI_API_KEYS = [k.strip() for k in keys.split(",") if k.strip()]
if not OPENAI_API_KEYS:
    raise RuntimeError("OPENAI_API_KEYS is empty")

NUM_THREADS = int(os.getenv("NUM_THREADS", "2"))

print("HF Space started")
print("API_URL loaded")
print("OPENAI_API_KEYS count:", len(OPENAI_API_KEYS))
print("NUM_THREADS:", NUM_THREADS)

# =====================================================
# Exception handling
# =====================================================

def exception_handler(exception_type, exception, traceback):
    print(f"{exception_type.__name__}: {exception}")

sys.excepthook = exception_handler
sys.tracebacklimit = 0

# =====================================================
# Prediction function (Responses API compatible)
# =====================================================

def predict(inputs, top_p, temperature, chat_counter, chatbot, history, request: gr.Request):
    if not OPENAI_API_KEYS:
        raise RuntimeError("No OpenAI API keys available")

    OPENAI_API_KEY = random.choice(OPENAI_API_KEYS)

    headers = {
        "Content-Type": "application/json",
        "Authorization": f"Bearer {OPENAI_API_KEY}"
    }

    # Build payload for Responses API
    payload = {
        "model": MODEL,
        "input": inputs,
        "temperature": temperature,
        "top_p": top_p
    }

    chat_counter += 1
    history.append({"role": "user", "content": inputs})

    try:
        response = requests.post(API_URL, headers=headers, json=payload, timeout=60)
        print("Status code:", response.status_code)

        if response.status_code != 200:
            print("Response text:", response.text)
            output_text = f"Error: {response.status_code}"
        else:
            data = response.json()
            # Extract text output from Responses API
            output_text = data["output"][0]["content"][0]["text"]
            history.append({"role": "assistant", "content": output_text})

        # Convert history to Gradio 'messages' format
        messages = [{"role": msg["role"], "content": msg["content"]} for msg in history]

        yield messages, history, chat_counter, response, gr.update(interactive=True), gr.update(interactive=True)

    except Exception as e:
        print(f"API request error: {e}")
        messages = [{"role": msg["role"], "content": msg["content"]} for msg in history]
        yield messages, history, chat_counter, None, gr.update(interactive=True), gr.update(interactive=True)

# =====================================================
# UI helpers
# =====================================================

def reset_textbox():
    return gr.update(value="", interactive=False), gr.update(interactive=False)

# =====================================================
# Gradio UI
# =====================================================

title = "<h1 align='center'>Hello welcome</h1>"
if DISABLED:
    title = """<h1 align="center" style="color:red">
    This app has reached its usage limit. Please check back later.
    </h1>"""

description = "kutti."

theme = gr.themes.Default(primary_hue="green")

with gr.Blocks(
    css="""
    #col_container { margin-left: auto; margin-right: auto; }
    #chatbot { height: 520px; overflow: auto; }
    """,
    theme=theme,
) as demo:

    gr.HTML(title)
    gr.HTML("<h3 align='center'>I'm Kutti</h3>")

    with gr.Column(elem_id="col_container", visible=False) as main_block:
        chatbot = gr.Chatbot(elem_id="chatbot", type="messages")  # Fixed warning
        inputs = gr.Textbox(placeholder="Hi there!", label="Type an input and press Enter")
        state = gr.State([])

        with gr.Row():
            with gr.Column(scale=7):
                b1 = gr.Button(visible=not DISABLED)
            with gr.Column(scale=3):
                server_status_code = gr.Textbox(label="Status code")

        with gr.Accordion("Parameters", open=False):
            top_p = gr.Slider(0, 1.0, value=1.0, step=0.05, label="Top-p")
            temperature = gr.Slider(0, 5.0, value=1.0, step=0.1, label="Temperature")
            chat_counter = gr.Number(value=0, visible=False, precision=0)

    with gr.Column(elem_id="user_consent_container") as user_consent_block:
        accept_checkbox = gr.Checkbox(visible=False)
        js = "(x) => confirm('By clicking OK, you agree to data usage terms.')"

        with gr.Accordion("User Consent", open=True):
            gr.Markdown(
                "By using this app, you consent to data collection for research and security purposes."
            )
            accept_button = gr.Button("I Agree")

        def enable_inputs():
            return gr.update(visible=False), gr.update(visible=True)

    accept_button.click(None, None, accept_checkbox, js=js, queue=False)
    accept_checkbox.change(
        fn=enable_inputs,
        inputs=[],
        outputs=[user_consent_block, main_block],
        queue=False,
    )

    inputs.submit(reset_textbox, [], [inputs, b1], queue=False)
    inputs.submit(
        predict,
        [inputs, top_p, temperature, chat_counter, chatbot, state],
        [chatbot, state, chat_counter, server_status_code, inputs, b1],
    )

    b1.click(reset_textbox, [], [inputs, b1], queue=False)
    b1.click(
        predict,
        [inputs, top_p, temperature, chat_counter, chatbot, state],
        [chatbot, state, chat_counter, server_status_code, inputs, b1],
    )

    demo.queue(
        max_size=10,
        default_concurrency_limit=NUM_THREADS,
        api_open=False,
    ).launch(share=False)