import base64
import os
import uuid
import time
import cv2
import gradio as gr
import numpy as np
import requests

MARKDOWN = """
# ♠ Alyxsissy GPT-Vision Testing 👁‍🗨

Skeleton API structure for GPT-4-Vision. Implimentation into SissyGPT WiP.
"""
AVATARS = (
    "https://raw.githubusercontent.com/Nymbo/Web-Hosted-Images/main/Alyxsissy%20Favicon.png?token=GHSAT0AAAAAACJF7K6DI4PXYMGQU3TPEZ2GZL2LFXA",
    "https://media.roboflow.com/spaces/openai-white-logomark.png"
)
IMAGE_CACHE_DIRECTORY = "data"
API_URL = "https://api.openai.com/v1/chat/completions"


def preprocess_image(image: np.ndarray) -> np.ndarray:
    image = np.fliplr(image)
    return cv2.cvtColor(image, cv2.COLOR_RGB2BGR)


def encode_image_to_base64(image: np.ndarray) -> str:
    success, buffer = cv2.imencode('.jpg', image)
    if not success:
        raise ValueError("Could not encode image to JPEG format.")

    encoded_image = base64.b64encode(buffer).decode('utf-8')
    return encoded_image


def compose_payload(image: np.ndarray, prompt: str) -> dict:
    base64_image = encode_image_to_base64(image)
    return {
        "model": "gpt-4-vision-preview",
        "messages": [
            {
                "role": "user",
                "content": [
                    {
                        "type": "text",
                        "text": prompt
                    },
                    {
                        "type": "image_url",
                        "image_url": {
                            "url": f"data:image/jpeg;base64,{base64_image}"
                        }
                    }
                ]
            }
        ],
        "max_tokens": 300
    }


def compose_headers(api_key: str) -> dict:
    return {
        "Content-Type": "application/json",
        "Authorization": f"Bearer {api_key}"
    }


def prompt_image(api_key: str, image: np.ndarray, prompt: str) -> str:
    headers = compose_headers(api_key=api_key)
    payload = compose_payload(image=image, prompt=prompt)
    response = requests.post(url=API_URL, headers=headers, json=payload).json()

    if 'error' in response:
        raise ValueError(response['error']['message'])
    return response['choices'][0]['message']['content']


def cache_image(image: np.ndarray) -> str:
    image_filename = f"{uuid.uuid4()}.jpeg"
    os.makedirs(IMAGE_CACHE_DIRECTORY, exist_ok=True)
    image_path = os.path.join(IMAGE_CACHE_DIRECTORY, image_filename)
    cv2.imwrite(image_path, image)
    return image_path


def respond(api_key: str, image: np.ndarray, prompt: str, chat_history):
    if not api_key:
        raise ValueError(
            "API_KEY is not set. "
            "Please follow the instructions in the README to set it up.")

    image = preprocess_image(image=image)
    cached_image_path = cache_image(image)
    response = prompt_image(api_key=api_key, image=image, prompt=prompt)
    chat_history.append(((cached_image_path,), None))
    chat_history.append((prompt, response))
    return "", chat_history


with gr.Blocks(theme=gr.themes.Default(primary_hue="pink", secondary_hue="pink")) as demo:
    gr.Markdown(MARKDOWN)
    with gr.Row():
        webcam = gr.Webcam(label="Webcam", source="webcam", streaming=True)
        with gr.Column():
            api_key_textbox = gr.Textbox(
                label="OpenAI API KEY", type="password")
            chatbot = gr.Chatbot(
                height=500, bubble_full_width=False, avatar_images=AVATARS)
            message_textbox = gr.Textbox()
            clear_button = gr.ClearButton(message_textbox, chatbot, variant="primary")

    message_textbox.submit(
        fn=respond,
        inputs=[api_key_textbox, webcam, message_textbox, chatbot],
        outputs=[message_textbox, chatbot]
    )

demo.launch(debug=False, show_error=True)