import os
import gradio as gr
import google.generativeai as genai


# Configure Gemini API
genai.configure(api_key=os.getenv("GEMINI_API_KEY"))

def upload_to_gemini(path, mime_type=None):
    """Uploads the given file to Gemini.

    See https://ai.google.dev/gemini-api/docs/prompting_with_media
    """
    file = genai.upload_file(path, mime_type=mime_type)
    print(f"Uploaded file '{file.display_name}' as: {file.uri}")
    return file

# Create the model
generation_config = {
    "temperature": 1,
    "top_p": 0.95,
    "top_k": 40,
    "max_output_tokens": 8192,
    "response_mime_type": "text/plain",
}

model = genai.GenerativeModel(
    model_name="gemini-1.5-pro-002",
    generation_config=generation_config,
)

def process_image(image):
    # Save the uploaded image to a temporary path
    temp_path = "uploaded_image.png"
    image.save(temp_path)

    # Upload the image to Gemini
    file = upload_to_gemini(temp_path, mime_type="image/png")

    # Start chat session with the uploaded image
    chat_session = model.start_chat(
        history=[
            {
                "role": "user",
                "parts": [
                    file,
                    (
                        "You are an expert in nutritionist where you need to see the food items from the image "
                        "and calculate the total calories, also provide the details of every food items with calories intake "
                        "is below format\n"
                        "1. Item 1 - no of calories\n"
                        "2. Item 2 - no of calories\n"
                        "----\n"
                        "----\n"
                        # "Finally you can also mention whether the food is healthy or not and also mention the percentage split of the ratio of \n"
                        # "Carbohydrates, fats, fibres, sugar and other important things required in our diet.\n"
                        "Never doubt your knowledge and always be confident in your responses.\n"
                        "Respond only in Ukrainian.\n\n"
                    ),
                ],
            },
        ]
    )

    # Send message to the model
    response = chat_session.send_message("Please analyze the uploaded image.")
    return response.text

# Create Gradio interface
iface = gr.Interface(
    fn=process_image,
    inputs=gr.Image(type="pil", label="Upload Food Image"),
    outputs='markdown',
    title="Nutritionist AI",
    description="Upload a   n image of your food, and the AI will calculate total calories, provide details of each food item with calorie intake, assess the healthiness, and provide percentage splits of carbohydrates, fats, fibers, sugar, and other essential nutrients. Responses are in Ukrainian."
)

if __name__ == "__main__":
    iface.launch()