Loads the embedding model pulled from the embedding_record of the library.
(self)
| 263 | os.chmod(query_history_path, 0o777) |
| 264 | |
| 265 | def load_embedding_model(self): |
| 266 | |
| 267 | """ Loads the embedding model pulled from the embedding_record of the library. """ |
| 268 | |
| 269 | # skip if already instantiated self.embedding_model |
| 270 | |
| 271 | if not self.embedding_model: |
| 272 | |
| 273 | if self.user_passed_model: |
| 274 | |
| 275 | if self.from_hf: |
| 276 | self.embedding_model = ModelCatalog().load_hf_embedding_model(self.user_passed_model, |
| 277 | self.user_passed_tokenizer) |
| 278 | if self.from_sentence_transformer: |
| 279 | self.embedding_model = ModelCatalog().load_sentence_transformer_model(self.user_passed_model, |
| 280 | self.embedding_model_name) |
| 281 | |
| 282 | else: |
| 283 | if ModelCatalog().lookup_model_card(self.embedding_model_name): |
| 284 | self.embedding_model = ModelCatalog().load_model(selected_model=self.embedding_model_name, |
| 285 | api_key=self.model_api_key) |
| 286 | else: |
| 287 | logger.info(f"update: Query - selected embedding model could not be found - " |
| 288 | f"{self.embedding_model_name}") |
| 289 | |
| 290 | return self |
| 291 | |
| 292 | def get_output_keys(self): |
| 293 |
no test coverage detected