query: query the memery. Args: query_texts: the query texts to search in the memery. collection: the name of the collection to search. n_results: the number of results to return. Returns: QueryResult class QueryResult(TypedDict):
(self, query_texts: List[str], collection: str = None, n_results: int = 5)
| 85 | return ids |
| 86 | |
| 87 | def query(self, query_texts: List[str], collection: str = None, n_results: int = 5) -> QueryResult: |
| 88 | """ |
| 89 | query: query the memery. |
| 90 | Args: |
| 91 | query_texts: the query texts to search in the memery. |
| 92 | collection: the name of the collection to search. |
| 93 | n_results: the number of results to return. |
| 94 | |
| 95 | Returns: QueryResult |
| 96 | class QueryResult(TypedDict): |
| 97 | ids: List[IDs] |
| 98 | embeddings: Optional[ |
| 99 | Union[ |
| 100 | List[Embeddings], |
| 101 | List[PyEmbeddings], |
| 102 | List[NDArray[Union[np.int32, np.float32]]], |
| 103 | ] |
| 104 | ] |
| 105 | documents: Optional[List[List[Document]]] |
| 106 | uris: Optional[List[List[URI]]] |
| 107 | data: Optional[List[Loadable]] |
| 108 | metadatas: Optional[List[List[Metadata]]] |
| 109 | distances: Optional[List[List[float]]] |
| 110 | included: Include |
| 111 | """ |
| 112 | if not collection: |
| 113 | collection = self.collection_name |
| 114 | query_embedding = self.embedder(query_texts) |
| 115 | return self.client.get_or_create_collection(collection).query(query_embeddings=query_embedding, n_results=n_results) |
| 116 | |
| 117 | def peek(self, collection: str = None, n_results: int = 20): |
| 118 | """ |
no outgoing calls
no test coverage detected