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File size: 1,575 Bytes
6903fe1 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 | from fastapi import FastAPI, File, Form, UploadFile
from src.engines.visual_engine import VisualSecurityEngine
app = FastAPI(title="Visual Security Engine API")
_ENGINE: VisualSecurityEngine | None = None
@app.on_event("startup")
def load_engine() -> None:
global _ENGINE
if _ENGINE is None:
_ENGINE = VisualSecurityEngine()
@app.get("/")
def health_check() -> dict:
return {"status": "ok"}
@app.post("/analyze")
async def analyze_image(
image: UploadFile = File(...),
audio_transcript: str = Form(""),
run_ocr: bool = Form(True),
run_injection: bool = Form(True),
run_cross_modal: bool = Form(True),
) -> dict:
if _ENGINE is None:
load_engine()
engine = _ENGINE
image_bytes = await image.read()
if run_injection:
run_ocr = True
text_payload = None
if run_ocr:
text_payload = engine.extract_text(image_bytes)
if run_injection:
injection_result = engine.detect_injection_from_text(
text_payload["normalized_text"] if text_payload else ""
)
else:
injection_result = {"skipped": True}
if run_cross_modal and audio_transcript.strip():
cross_modal_result = engine.check_cross_modal(image_bytes, audio_transcript)
elif run_cross_modal:
cross_modal_result = {"is_mismatch": True, "consistency_score": 0.0}
else:
cross_modal_result = {"skipped": True}
return {
"ocr": text_payload or {"skipped": True},
"injection": injection_result,
"cross_modal": cross_modal_result,
}
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