import base64
import os
import gradio as gr
import openai

# OpenAI API Key
api_key = os.getenv("OPENAI_API_KEY")
client = openai.Client(api_key=api_key)

# Function to encode the image
def encode_image(image_path):
    with open(image_path, "rb") as image_file:
        return base64.b64encode(image_file.read()).decode("utf-8")


def ask_openai_about_image(image_path, user_question):
    base64_image = encode_image(image_path)
    messages = [
        {
            "role": "system",
            "content": "You are an automotive expert. Your job is to identify details in a given photo of a car.",
        },
        {
            "role": "user",
            "content": [
                {"type": "text", "text": user_question},
                {
                    "type": "image_url",
                    "image_url": {"url": f"data:image/jpeg;base64,{base64_image}"},
                },
            ],
        },
    ]

    response = client.chat.completions.create(model="gpt-4o", messages=messages)
    return response.choices[0].message.content


# Gradio interface
iface = gr.Interface(
    fn=ask_openai_about_image,
    inputs=[
        gr.Image(label="Upload Image of Car", type="filepath"),
        gr.Textbox(label="Ask if a specific badge is present"),
    ],
    examples=[
        ["data/peugeot_206_rear.jpg", "Does this car have the badge 206?"],
        ["data/peugeot_306_rear.jpg", "Does this car have the badge 106?"],
    ],
    outputs="text",
    title="Badge Detector",
    description="Upload an image of a car and type your question about the car's badge. You can also select an example image from our dataset.",
)

iface.launch()