"""HTTP service for roomtsc 0.1.

  POST /api/predict   body: {"structure": "<CIF or POSCAR text>"}   returns the estimate as JSON
  GET  /api/health    returns the model version and what it was trained on

Run:  uvicorn serve:app --app-dir model --host 0.0.0.0 --port 8000
"""
import pathlib
import sys

from fastapi import FastAPI, HTTPException
from pydantic import BaseModel, Field
from pymatgen.core import Structure

sys.path.insert(0, str(pathlib.Path(__file__).resolve().parent))
import predict as P

app = FastAPI(title='roomtsc', docs_url=None, redoc_url=None, openapi_url=None)


class Query(BaseModel):
    structure: str = Field(max_length=200_000)


def parse(text):
    """A CIF if it looks like one, otherwise a POSCAR."""
    fmt = 'cif' if ('_cell_length_a' in text or text.lstrip().startswith('data_')) else 'poscar'
    try:
        return Structure.from_str(text, fmt=fmt)
    except Exception as err:
        raise HTTPException(422, f'could not read the structure as {fmt.upper()}: {str(err)[:200]}')


@app.get('/api/health')
def health():
    meta = P.models()['meta']
    return dict(model=meta['name'], version=meta['version'], trained_on=meta['trained_on'], graph_members=len(meta['graph_seeds']))


@app.post('/api/predict')
def predict(q: Query):
    st = parse(q.structure)
    try:
        return P.predict(st)
    except ValueError as err:
        raise HTTPException(422, str(err))