Call out to OpenAI's embedding endpoint for embedding search docs. Args: texts: The list of texts to embed. Returns: List of embeddings, one for each text.
(
self,
texts: List[str],
)
| 212 | return embeddings |
| 213 | |
| 214 | def embed_documents( |
| 215 | self, |
| 216 | texts: List[str], |
| 217 | ) -> List[List[float]]: |
| 218 | """Call out to OpenAI's embedding endpoint for embedding search docs. |
| 219 | |
| 220 | Args: |
| 221 | texts: The list of texts to embed. |
| 222 | |
| 223 | Returns: |
| 224 | List of embeddings, one for each text. |
| 225 | """ |
| 226 | # NOTE: to keep things simple, we assume the list may contain texts longer |
| 227 | # than the maximum context and use length-safe embedding function. |
| 228 | return self._get_len_safe_embeddings(texts) |
| 229 | |
| 230 | |
| 231 | def embed_query(self, text: str) -> List[float]: |
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