"""Opt-in operational fixtures using staged real Google weights, CPU only."""
import io
import math
import os
import unittest
import wave
from engine import get_model,embedding_features,inspect_content,cosine
from semantic import validate_vectors,DIMENSIONS

@unittest.skipUnless(os.environ.get('SAFETYNET_TEST_NATIVE_SEMANTIC')=='1','Opt in to verified native CPU fixtures')
class NativeCPUFixtures(unittest.TestCase):
    @classmethod
    def setUpClass(cls):cls.model=get_model()
    @classmethod
    def tearDownClass(cls):cls.model.close()
    def test_real_paraphrase_blocks_and_unrelated_text_allows(self):
        reference=embedding_features(b'Our confidential launch plan schedules the new product announcement for next October.')
        protected=b'The secret product rollout will be announced in October next year.'
        public=b'The public cafeteria menu includes tomato soup and bread.'
        related=embedding_features(protected);unrelated=embedding_features(public)
        self.assertGreater(cosine(reference['vector'],related['vector']),.8)
        self.assertLess(cosine(reference['vector'],unrelated['vector']),.8)
        policy={'dlp':{'maxBytes':1048576,'rules':[],'semantic':{**self.model.info(),'enabled':True,'categories':[{'id':'native-reference','prototype':reference['vector'],'prototypes':reference['vectors'],'threshold':.8}]}}}
        self.assertEqual(inspect_content(protected,policy)['ruleId'],'native-reference')
        self.assertEqual(inspect_content(public,policy)['decision'],'allow')
    def test_native_token_windows_cover_long_document_tail(self):
        text='Public synthetic office lunch menu and team meeting schedule. '*600+'Final unique coverage marker.'
        result=embedding_features(text.encode())
        self.assertGreater(result['coverage']['textChunks'],1)
        self.assertTrue(result['coverage']['complete']);validate_vectors(result['vectors'])
    def test_native_image_encoder_returns_real_normalized_vector(self):
        from PIL import Image,ImageDraw
        image=Image.new('RGB',(192,192),'white');draw=ImageDraw.Draw(image)
        draw.rectangle((20,20,90,170),fill='blue');draw.ellipse((110,50,175,115),fill='red')
        output=io.BytesIO();image.save(output,format='PNG')
        vectors=self.model.image_vectors(output.getvalue())
        self.assertEqual(len(vectors),1);validate_vectors(vectors)
    def test_native_audio_encoder_returns_real_normalized_vector(self):
        import numpy as np
        samples=(np.sin(np.arange(16000)*2*math.pi*440/16000)*12000).astype('<i2')
        output=io.BytesIO()
        with wave.open(output,'wb') as stream:
            stream.setnchannels(1);stream.setsampwidth(2);stream.setframerate(16000);stream.writeframes(samples.tobytes())
        vectors=self.model.audio_vectors(output.getvalue())
        self.assertEqual(len(vectors),1);validate_vectors(vectors)

if __name__=='__main__':unittest.main()