from __future__ import annotations
import asyncio
import json
from pathlib import Path

from fastapi import FastAPI, HTTPException
from fastapi.responses import FileResponse, JSONResponse, StreamingResponse
from fastapi.staticfiles import StaticFiles
from pydantic import BaseModel

from .config import Settings
from .health import check_magpie, check_parakeet, check_vllm
from .models import load_catalog
from .ssh import ssh_run
from .swap import SwapManager


settings = Settings.from_env()
catalog = load_catalog(settings.models_yaml)
swap_manager = SwapManager(settings, catalog)

app = FastAPI(title="spark-control", version="0.1.0")

_STATIC_DIR = Path(__file__).resolve().parent / "static"
app.mount("/static", StaticFiles(directory=_STATIC_DIR), name="static")


@app.get("/", include_in_schema=False)
async def index() -> FileResponse:
    return FileResponse(_STATIC_DIR / "index.html")


@app.get("/api/config")
async def get_config() -> dict:
    return {
        "configured": settings.configured,
        "spark1_host": settings.spark1_host,
        "spark2_host": settings.spark2_host,
        "vllm_port": settings.vllm_port,
    }


@app.get("/api/models")
async def get_models() -> dict:
    return {
        "defaults": catalog.defaults.model_dump(),
        "models": {k: v.model_dump() for k, v in catalog.models.items()},
    }


@app.get("/api/endpoints")
async def get_endpoints() -> dict:
    """Service-discovery summary. Stable shape; other apps on the LAN can poll this
    to learn the OpenAI-compatible vLLM endpoint, the Parakeet STT endpoint, and the
    Magpie TTS endpoint without needing to know the individual Spark IPs."""
    vllm, parakeet, magpie = await asyncio.gather(
        check_vllm(settings),
        check_parakeet(settings),
        check_magpie(settings),
    )
    return {
        "vllm": {
            "ready": bool(vllm.get("ok")),
            "base_url": vllm.get("base_url"),
            "model": vllm.get("current_model"),
            "openai_compat": True,
        },
        "parakeet": {
            "ready": bool(parakeet.get("ok")),
            "base_url": parakeet.get("base_url"),
            "kind": "stt",
            "model": (parakeet.get("detail") or {}).get("model") if isinstance(parakeet.get("detail"), dict) else None,
        },
        "magpie": {
            "ready": bool(magpie.get("ok")),
            "base_url": magpie.get("base_url"),
            "kind": "tts",
        },
    }


@app.get("/api/status")
async def get_status() -> dict:
    vllm, parakeet, magpie = await asyncio.gather(
        check_vllm(settings),
        check_parakeet(settings),
        check_magpie(settings),
    )
    current_key = _identify_current_model(vllm.get("current_model"))
    return {
        "configured": settings.configured,
        "vllm": vllm,
        "parakeet": parakeet,
        "magpie": magpie,
        "current_model_key": current_key,
        "current_swap_job": swap_manager.current_job_id,
    }


def _identify_current_model(repo: str | None) -> str | None:
    if not repo:
        return None
    for key, m in catalog.models.items():
        if m.repo == repo:
            return key
    return None


class SwapRequest(BaseModel):
    model_key: str
    dry_run: bool = False


@app.post("/api/swap")
async def post_swap(req: SwapRequest) -> dict:
    if not settings.configured and not req.dry_run:
        raise HTTPException(503, "spark1 not configured")
    try:
        job = await swap_manager.trigger(req.model_key, dry_run=req.dry_run)
    except KeyError:
        raise HTTPException(404, f"unknown model: {req.model_key}")
    except RuntimeError as e:
        raise HTTPException(409, str(e))
    return {"job_id": job.id, "model_key": job.model_key, "state": job.state}


@app.get("/api/swap/{job_id}")
async def get_swap(job_id: str) -> dict:
    job = swap_manager.get(job_id)
    if job is None:
        raise HTTPException(404, "no such job")
    return {
        "id": job.id,
        "model_key": job.model_key,
        "state": job.state,
        "started_at": job.started_at,
        "finished_at": job.finished_at,
        "returncode": job.returncode,
        "dry_run": job.dry_run,
        "lines": job.lines,
    }


@app.get("/api/swap/{job_id}/stream")
async def stream_swap(job_id: str):
    job = swap_manager.get(job_id)
    if job is None:
        raise HTTPException(404, "no such job")

    async def gen():
        sent = 0
        while True:
            n = len(job.lines)
            if n > sent:
                for line in job.lines[sent:n]:
                    payload = json.dumps({"line": line, "state": job.state})
                    yield f"data: {payload}\n\n"
                sent = n
            if job.returncode is not None and sent >= len(job.lines):
                payload = json.dumps({
                    "state": job.state,
                    "returncode": job.returncode,
                    "finished_at": job.finished_at,
                })
                yield f"event: done\ndata: {payload}\n\n"
                return
            await asyncio.sleep(0.4)

    return StreamingResponse(gen(), media_type="text/event-stream")


@app.post("/api/test-connection")
async def test_connection() -> dict:
    """Probe both Sparks with a `hostname` command. Useful for the StartOS setup flow."""
    results: dict[str, dict] = {}
    if settings.spark1_host:
        rc, out, err = await ssh_run(settings.spark1_host, settings.spark1_user, "hostname && docker ps --format '{{.Names}}'", settings, timeout=10)
        results["spark1"] = {"ok": rc == 0, "rc": rc, "stdout": out.strip(), "stderr": err.strip()}
    else:
        results["spark1"] = {"ok": False, "error": "not configured"}
    if settings.spark2_host:
        rc, out, err = await ssh_run(settings.spark2_host, settings.spark2_user, "hostname && docker ps --format '{{.Names}}'", settings, timeout=10)
        results["spark2"] = {"ok": rc == 0, "rc": rc, "stdout": out.strip(), "stderr": err.strip()}
    else:
        results["spark2"] = {"ok": False, "error": "not configured"}
    return results