(self, texts, top_k=3)
| 418 | return None |
| 419 | |
| 420 | def batchQuery_preprocessing(self, texts, top_k=3): |
| 421 | if self.need_redis: |
| 422 | if isinstance(texts, list): |
| 423 | res = [] |
| 424 | for text in texts: |
| 425 | vec = self.embedding_model([text])[0] |
| 426 | ans = self.redisCaching.query_cache(query=text, query_vec=np.array(vec), k=top_k) |
| 427 | if ans is not None: |
| 428 | ans = str(ans).split('___') |
| 429 | res.append(ans) |
| 430 | if len(res) == len(texts): |
| 431 | return res |
| 432 | return None |
| 433 | |
| 434 | def query_embedding_preprocessing(self, text, thresholds=.9): |
| 435 | if self.need_redis: |
no test coverage detected