"""FastAPI web demo for the Adaptive Barrier Monitor."""

from __future__ import annotations

import re
import sys
from pathlib import Path
from typing import Any, Literal

import numpy as np
from fastapi import FastAPI
from fastapi.responses import HTMLResponse
from fastapi.staticfiles import StaticFiles
from pydantic import BaseModel, Field

# Support both an installed package (`pip install -e .`) and direct launches
# from a source checkout (`uvicorn webapp.app:app`).
REPO_ROOT = Path(__file__).resolve().parents[1]
SRC_DIR = REPO_ROOT / "src"
if str(SRC_DIR) not in sys.path:
    sys.path.insert(0, str(SRC_DIR))

from adaptive_barrier import __version__
from adaptive_barrier.engine import (
    DROP_FRACTION,
    LOG_BARRIER,
    RISE_FRACTION,
    TYPICAL_ANNUAL_VOL,
    WINDOW_MINUTES,
    run_monte_carlo_simulation,
)

STATIC_DIR = REPO_ROOT / "webapp" / "static"


class SimulateRequest(BaseModel):
    """Validated Monte Carlo and detector-comparison parameters."""

    S0: float = Field(100.0, gt=0.0, le=10000.0)
    sigma_annual: float = Field(TYPICAL_ANNUAL_VOL, gt=0.0, le=2.0)
    mu_annual: float = Field(0.0, ge=-0.5, le=0.5)
    window_minutes: float = Field(1950.0, gt=0.0, le=39000.0)
    n_paths: int = Field(20, ge=1, le=100)
    n_steps: int = Field(500, ge=50, le=2000)
    use_jumps: bool = Field(
        False,
        description="Use Merton jump diffusion. The Brownian miss proxy does not control jumps.",
    )
    jump_intensity: float = Field(25.0, ge=0.0, le=500.0)
    jump_mean: float = Field(-0.02, ge=-0.5, le=0.5)
    jump_sigma: float = Field(0.05, ge=0.0, le=0.5)
    eps: float = Field(1e-3, gt=0.0, lt=1.0)
    dt_cap_minutes: float | None = Field(None, gt=0.0, le=1440.0)
    rng_seed: int | None = Field(None, ge=0, le=2_147_483_647)
    drop_fraction: float = Field(DROP_FRACTION, gt=0.0, lt=1.0)
    rise_fraction: float = Field(RISE_FRACTION, gt=0.0, le=1.0)
    max_detection_lag_steps: int | None = Field(3, ge=0, le=100)
    comparison_mode: Literal["equal_budget", "fixed_cadence"] = "equal_budget"
    fixed_cadence_minutes: float = Field(60.0, gt=0.0, le=39000.0)


def _file_version(path: Path) -> str:
    try:
        stat = path.stat()
        return f"{int(stat.st_mtime)}-{stat.st_size}"
    except FileNotFoundError:
        return "missing"


def _json_safe(obj: Any) -> Any:
    if isinstance(obj, dict):
        return {str(key): _json_safe(value) for key, value in obj.items()}
    if isinstance(obj, (list, tuple)):
        return [_json_safe(value) for value in obj]
    if isinstance(obj, np.integer):
        return int(obj)
    if isinstance(obj, np.floating):
        value = float(obj)
        return value if np.isfinite(value) else None
    if isinstance(obj, np.ndarray):
        return _json_safe(obj.tolist())
    if isinstance(obj, np.bool_):
        return bool(obj)
    return obj


app = FastAPI(title="Adaptive Barrier Monitor", version=__version__)
app.mount("/static", StaticFiles(directory=STATIC_DIR), name="static")


@app.get("/")
def index() -> HTMLResponse:
    html = (STATIC_DIR / "index.html").read_text(encoding="utf-8")
    html = re.sub(
        r'app\.css\?v=[^\s"\']+',
        f"app.css?v={_file_version(STATIC_DIR / 'app.css')}",
        html,
    )
    html = re.sub(
        r'app\.js\?v=[^\s"\']+',
        f"app.js?v={_file_version(STATIC_DIR / 'app.js')}",
        html,
    )
    return HTMLResponse(content=html)


@app.get("/api/health")
def health() -> dict:
    return {
        "ok": True,
        "version": __version__,
        "default_sigma_annual": TYPICAL_ANNUAL_VOL,
        "default_window_minutes": WINDOW_MINUTES,
        "drop_fraction": DROP_FRACTION,
        "rise_fraction": RISE_FRACTION,
        "log_barrier": LOG_BARRIER,
    }


@app.post("/api/simulate")
def simulate(req: SimulateRequest) -> dict:
    result = run_monte_carlo_simulation(**req.model_dump())
    return _json_safe(result)