import gradio as gr
import os
import sys
import json
import copy
import random
from gradio_client import Client

API_URL = "https://yuntian-deng-o1.hf.space"  # Базовый URL для Gradio-приложения
DISABLED = os.getenv("DISABLED") == 'True'
NUM_THREADS = int(os.getenv("NUM_THREADS", "10"))  # По умолчанию 2 потока, если не установлено

def exception_handler(exception_type, exception, traceback):
    print("%s: %s" % (exception_type.__name__, exception))
sys.excepthook = exception_handler
sys.tracebacklimit = 0

def predict(inputs, top_p, temperature, chat_counter, chatbot, state):
    client = Client(API_URL)
    
    # Initialize the conversation history if it's empty
    if state is None or state == []:
        state = []
    if chatbot is None or chatbot == []:
        chatbot = []
    
    # Append the user's message to the state as a dictionary
    state.append({"role": "user", "content": inputs})
    
    # Update the chatbot UI with the user's message (assistant's reply will be added later)
    chatbot.append((inputs, None))
    
    try:
        # Call the API endpoint /predict
        result = client.predict(
            inputs=inputs,
            top_p=top_p,
            temperature=temperature,
            chat_counter=chat_counter,
            chatbot=chatbot,  # Passing the current state of the chatbot
            api_name="/predict"
        )

        # Unpack the results
        bot_response = result[0]  # This should be the updated chatbot conversation
        chat_counter = result[1]
        server_status = result[2]
        new_input = result[3]
        
        # Retrieve the assistant's reply from the bot_response
        assistant_reply = bot_response[-1][1]
        
        # Append the assistant's reply to the state
        state.append({"role": "assistant", "content": assistant_reply})
        
        # Update the last message in chatbot with the assistant's reply
        chatbot[-1] = (chatbot[-1][0], assistant_reply)
        
        # Increment the chat counter
        chat_counter += 1
        
        # Return updated values
        return chatbot, state, chat_counter, server_status, "", gr.update(interactive=True)
    
    except Exception as e:
        print(f'Error: {e}')
        # Return the current state in case of error
        return chatbot, state, chat_counter, 'Error! Please try again', "", gr.update(interactive=True)

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

title = """<h1 align="center">OpenAI-O1-Preview: Research Preview (Short-Term Availability)</h1>"""
if DISABLED:
    title = """<h1 align="center" style="color:red">This app has reached OpenAI's usage limit. Please check back tomorrow.</h1>"""
description = """Language models can be conditioned to act like dialogue agents through a conversational prompt that typically takes the form:
```
User: <utterance>
Assistant: <utterance>
User: <utterance>
Assistant: <utterance>
...
```
In this app, you can explore the outputs of a GPT-4 turbo LLM.
"""

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" style="color: red;">If this app doesn't respond, consider trying our O1-mini app:<br/><a href="https://huggingface.co/spaces/yuntian-deng/o1mini">https://huggingface.co/spaces/yuntian-deng/o1mini</a></h3>""")

    with gr.Column(elem_id="col_container", visible=False) as main_block:
        chatbot = gr.Chatbot(elem_id='chatbot')
        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 from OpenAI server")

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

    with gr.Column(elem_id="user_consent_container") as user_consent_block:
        # Получение согласия пользователя
        accept_checkbox = gr.Checkbox(visible=False)
        js = "(x) => confirm('By clicking \"OK\", I agree that my data may be published or shared.')"
        with gr.Accordion("User Consent for Data Collection, Use, and Sharing", open=True):
            gr.HTML("""
            <div>
                <p>By using our app, which is powered by OpenAI's API, you acknowledge and agree to the following terms regarding the data you provide:</p>
                <ol>
                    <li><strong>Collection:</strong> We may collect information, including the inputs you type into our app, the outputs generated by OpenAI's API, and certain technical details about your device and connection (such as browser type, operating system, and IP address) provided by your device's request headers.</li>
                    <li><strong>Use:</strong> We may use the collected data for research purposes, to improve our services, and to develop new products or services, including commercial applications, and for security purposes, such as protecting against unauthorized access and attacks.</li>
                    <li><strong>Sharing and Publication:</strong> Your data, including the technical details collected from your device's request headers, may be published, shared with third parties, or used for analysis and reporting purposes.</li>
                    <li><strong>Data Retention:</strong> We may retain your data, including the technical details collected from your device's request headers, for as long as necessary.</li>
                </ol>
                <p>By continuing to use our app, you provide your explicit consent to the collection, use, and potential sharing of your data as described above. If you do not agree with our data collection, use, and sharing practices, please do not use our app.</p>
            </div>
            """)
            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=20, default_concurrency_limit=NUM_THREADS, api_open=False).launch(share=False)