app/main.py

from __future__ import annotations

import hashlib
import os
from pathlib import Path

from fastapi import FastAPI, File, HTTPException, UploadFile
from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import JSONResponse

from app.config import settings
from app.jobs import JobStatus, create_job, get_job, job_to_dict
from app.pipeline.orchestrator import run_pipeline

app = FastAPI(
    title=settings.app_name,
    version=settings.app_version,
    description="Detect-X forensic media analysis API (Alpha)",
)

origins = [o.strip() for o in settings.cors_origins.split(",") if o.strip()]
app.add_middleware(
    CORSMiddleware,
    allow_origins=origins if origins != ["*"] else ["*"],
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)


def models_ready() -> dict[str, bool]:
    models_path = Path(settings.models_dir)
    visual = models_path / settings.visual_model_file
    audio = models_path / settings.audio_model_file
    return {
        "visual_model": visual.exists(),
        "audio_model": audio.exists(),
        "models_dir": str(models_path),
    }


@app.get("/")
def root():
    return {
        "service": settings.app_name,
        "version": settings.app_version,
        "status": "online",
        "docs": "/docs",
    }


@app.get("/health")
def health():
    ready = models_ready()
    return {
        "status": "healthy" if all(ready.values()) else "degraded",
        "models": ready,
        "limits": {
            "max_upload_mb": settings.max_upload_mb,
            "max_video_seconds": settings.max_video_seconds,
        },
    }


@app.post("/analyze")
async def analyze(file: UploadFile = File(...)):
    if not file.filename:
        raise HTTPException(status_code=400, detail="Filename is required")

    content = await file.read()
    size_mb = len(content) / (1024 * 1024)
    if size_mb > settings.max_upload_mb:
        raise HTTPException(
            status_code=413,
            detail=f"File exceeds {settings.max_upload_mb} MB limit",
        )

    file_hash = hashlib.sha256(content).hexdigest()
    job = create_job(file.filename)
    job.status = JobStatus.RUNNING
    job.progress = 5
    job.result = {"sha256": file_hash, "size_bytes": len(content)}

    def on_progress(stage: str, progress: int) -> None:
        job.current_stage = stage
        job.progress = progress

    try:
        job.result = run_pipeline(
            job=job,
            content=content,
            filename=file.filename,
            on_progress=on_progress,
        )
        job.result["sha256"] = file_hash
        job.result["size_bytes"] = len(content)
        job.status = JobStatus.COMPLETED
        job.progress = 100
        job.current_stage = "report"
    except ValueError as exc:
        job.status = JobStatus.FAILED
        job.error = str(exc)
        raise HTTPException(status_code=400, detail=str(exc)) from exc
    except Exception as exc:
        job.status = JobStatus.FAILED
        job.error = str(exc)
        raise HTTPException(status_code=500, detail=f"Analysis failed: {exc}") from exc

    return JSONResponse(job_to_dict(job))


@app.get("/jobs/{job_id}")
def job_status(job_id: str):
    job = get_job(job_id)
    if not job:
        raise HTTPException(status_code=404, detail="Job not found")
    return job_to_dict(job)


if os.getenv("SPACE_ID"):
    @app.get("/spaces-config")
    def spaces_config():
        return {"ready": True}