from base64 import b64encode
from typing import List, Dict

from fastapi.datastructures import UploadFile


async def get_writing_args_academic(task: int, attachment: UploadFile, difficulty: str) -> List[Dict]:
    writing_args = {
        "1": {
            "prompt": (
                'Analyze the uploaded image and create a detailed IELTS Writing Task 1 Academic prompt.\n'
                'Based on the visual data presented, craft a prompt that accurately reflects the image\'s '
                'content, complexity, and academic nature.\n'
            ),
            "instructions": (
                'The generated prompt must:\n'
                '1. Clearly describe the type of visual representation in the image\n'
                '2. Provide a concise context for the data shown\n'
                f'3. Be adequate for {difficulty} CEFR level users\n'
                '4. End with the standard IELTS Task 1 Academic instruction:\n'
                '"Summarise the information by selecting and reporting the main features, and make comparisons where relevant."'
            )
        },
    }

    if task == 2:
        raise NotImplemented("Task 2 academic isn't implemented yet, current implementation still uses General Task 2 prompts.")

    attachment_bytes = await attachment.read()


    messages = [
        {
            "role": "user",
            "content": writing_args[str(task)]["prompt"]
        },
        {
            "role": "user",
            "content": [
                {
                    "type": "text",
                    "text": writing_args[str(task)]["instructions"],
                },
                {
                    "type": "image_url",
                    "image_url": {
                        "url": f"data:image/{attachment.filename.split('.')[-1]};base64,{b64encode(attachment_bytes).decode('utf-8')}"
                    }
                }
            ]
        }
    ]

    return messages