app.py

from fastapi import FastAPI, UploadFile, File
from pywhispercpp.model import Model
import uvicorn
import tempfile
import os
from time import time

app = FastAPI(title="pyWhisperCPP API")

# Load model ONCE at startup
#MODEL_PATH = "ggml-tiny.en.bin"
#model = Model(MODEL_PATH)
#model = Model('base.en')
model = Model("base.en-q5_1")
@app.get("/")
def root():
    return {"status": "Whisper.cpp API is running!"}

@app.post("/transcribe")
async def transcribe(file: UploadFile = File(...)):
    # Save uploaded audio
    with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as temp:
        temp.write(await file.read())
        temp.flush()
        audio_path = temp.name

    start = time()
    segments = model.transcribe(audio_path)
    text = " ".join([seg.text for seg in segments])
    elapsed = round(time() - start, 3)

    os.remove(audio_path)

    return {
        "text": text,
        "processing_time_seconds": elapsed
    }

if __name__ == "__main__":
    uvicorn.run(app, host="0.0.0.0", port=7860)