Get embedding vector for a text string. Args: text: Text to embed Returns: Embedding vector
(self, text: str)
| 227 | ) |
| 228 | |
| 229 | def get_embedding(self, text: str) -> List[float]: |
| 230 | """ |
| 231 | Get embedding vector for a text string. |
| 232 | |
| 233 | Args: |
| 234 | text: Text to embed |
| 235 | |
| 236 | Returns: |
| 237 | Embedding vector |
| 238 | """ |
| 239 | for attempt in range(self.max_retries): |
| 240 | try: |
| 241 | return self.embedding_model_fn(text) |
| 242 | except Exception as e: |
| 243 | if attempt < self.max_retries - 1: |
| 244 | time.sleep(self.retry_delay * (attempt + 1)) |
| 245 | else: |
| 246 | raise Exception(f"Failed to get embedding after {self.max_retries} attempts: {str(e)}") |
| 247 | |
| 248 | def batch_get_embeddings(self, texts: List[str]) -> List[List[float]]: |
| 249 | """ |
no outgoing calls
no test coverage detected