import base64
import mimetypes

from langchain_core.messages import HumanMessage

_PROMPT = (
    "Analyze this image thoroughly and produce a detailed markdown description.\n\n"
    "Include:\n"
    "- All visible text, transcribed verbatim\n"
    "- Description of diagrams, charts, tables, or visual structures\n"
    "- Key subjects, objects, or scenes depicted\n\n"
    "Output only the markdown content, no preamble."
)


def _image_to_data_url(file_path: str) -> str:
    mime_type, _ = mimetypes.guess_type(file_path)
    if not mime_type or not mime_type.startswith("image/"):
        mime_type = "image/png"
    with open(file_path, "rb") as f:
        encoded = base64.b64encode(f.read()).decode("ascii")
    return f"data:{mime_type};base64,{encoded}"


async def parse_with_vision_llm(file_path: str, filename: str, llm) -> str:
    data_url = _image_to_data_url(file_path)
    message = HumanMessage(
        content=[
            {"type": "text", "text": _PROMPT},
            {"type": "image_url", "image_url": {"url": data_url}},
        ]
    )
    response = await llm.ainvoke([message])
    text = response.content if hasattr(response, "content") else str(response)
    if not text or not text.strip():
        raise ValueError(f"Vision LLM returned empty content for {filename}")
    return text.strip()