from fastapi import FastAPI, File, UploadFile, Form
from fastapi.responses import JSONResponse
from fastapi.middleware.cors import CORSMiddleware
from fastapi.staticfiles import StaticFiles
import tempfile, subprocess, whisper, os

# Set writable cache dir
os.environ["XDG_CACHE_HOME"] = "/tmp"

# Instantiate app first
app = FastAPI()

# CORS middleware
app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],
    allow_methods=["*"],
    allow_headers=["*"]
)

# Serve static frontend files
app.mount("/", StaticFiles(directory="static", html=True), name="static")

# Load whisper model
model = whisper.load_model("base")

@app.post("/api/analyze")
async def analyze(file: UploadFile = File(None), url: str = Form(None)):
    if not file and not url:
        return JSONResponse({"error": "No input provided"}, status_code=400)

    # Download or save uploaded file
    if url:
        tmp = tempfile.NamedTemporaryFile(delete=False, suffix='.mp4')
        subprocess.run(["yt-dlp", "-o", tmp.name, url], check=True)
        path = tmp.name
    else:
        tmp = tempfile.NamedTemporaryFile(delete=False, suffix=file.filename)
        tmp.write(await file.read())
        tmp.close()
        path = tmp.name

    # Extract audio using ffmpeg
    wav_path = path + ".wav"
    subprocess.run(["ffmpeg", "-y", "-i", path, "-ar", "16000", wav_path],
                   stderr=subprocess.DEVNULL, stdout=subprocess.DEVNULL)

    # Transcribe and detect cues
    result = model.transcribe(wav_path)
    transcript = [seg["text"].strip() for seg in result["segments"]]

    flags = []
    for seg in result["segments"]:
        if "buy" in seg["text"].lower() and seg["avg_logprob"] < -1:
            flags.append({
                "type": "keyword_lowprob",
                "timestamp": f"{seg['start']:.02f}s",
                "content": seg['text']
            })

    summary = "No obvious subliminals" if not flags else "⚠ Potential subliminal cues found"
    return {
        "summary": summary,
        "transcript": transcript,
        "subliminal_flags": flags
    }