Storage context
StorageContext
dataclass
#
Storage context.
The storage context container is a utility container for storing nodes, indices, and vectors. It contains the following: - docstore: BaseDocumentStore - index_store: BaseIndexStore - vector_store: VectorStore - graph_store: GraphStore
Source code in llama-index-core/llama_index/core/storage/storage_context.py
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from_defaults
classmethod
#
from_defaults(docstore: Optional[BaseDocumentStore] = None, index_store: Optional[BaseIndexStore] = None, vector_store: Optional[Union[VectorStore, BasePydanticVectorStore]] = None, image_store: Optional[VectorStore] = None, vector_stores: Optional[Dict[str, Union[VectorStore, BasePydanticVectorStore]]] = None, graph_store: Optional[GraphStore] = None, persist_dir: Optional[str] = None, fs: Optional[AbstractFileSystem] = None) -> StorageContext
Create a StorageContext from defaults.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
docstore |
Optional[BaseDocumentStore]
|
document store |
None
|
index_store |
Optional[BaseIndexStore]
|
index store |
None
|
vector_store |
Optional[VectorStore]
|
vector store |
None
|
graph_store |
Optional[GraphStore]
|
graph store |
None
|
image_store |
Optional[VectorStore]
|
image store |
None
|
Source code in llama-index-core/llama_index/core/storage/storage_context.py
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persist #
persist(persist_dir: Union[str, PathLike] = DEFAULT_PERSIST_DIR, docstore_fname: str = DOCSTORE_FNAME, index_store_fname: str = INDEX_STORE_FNAME, vector_store_fname: str = VECTOR_STORE_FNAME, image_store_fname: str = IMAGE_STORE_FNAME, graph_store_fname: str = GRAPH_STORE_FNAME, fs: Optional[AbstractFileSystem] = None) -> None
Persist the storage context.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
persist_dir |
str
|
directory to persist the storage context |
DEFAULT_PERSIST_DIR
|
Source code in llama-index-core/llama_index/core/storage/storage_context.py
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from_dict
classmethod
#
from_dict(save_dict: dict) -> StorageContext
Create a StorageContext from dict.
Source code in llama-index-core/llama_index/core/storage/storage_context.py
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add_vector_store #
add_vector_store(vector_store: VectorStore, namespace: str) -> None
Add a vector store to the storage context.
Source code in llama-index-core/llama_index/core/storage/storage_context.py
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Init file of LlamaIndex.
load_index_from_storage #
load_index_from_storage(storage_context: StorageContext, index_id: Optional[str] = None, **kwargs: Any) -> BaseIndex
Load index from storage context.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
storage_context |
StorageContext
|
storage context containing docstore, index store and vector store. |
required |
index_id |
Optional[str]
|
ID of the index to load. Defaults to None, which assumes there's only a single index in the index store and load it. |
None
|
**kwargs |
Any
|
Additional keyword args to pass to the index constructors. |
{}
|
Source code in llama-index-core/llama_index/core/indices/loading.py
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load_indices_from_storage #
load_indices_from_storage(storage_context: StorageContext, index_ids: Optional[Sequence[str]] = None, **kwargs: Any) -> List[BaseIndex]
Load multiple indices from storage context.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
storage_context |
StorageContext
|
storage context containing docstore, index store and vector store. |
required |
index_id |
Optional[Sequence[str]]
|
IDs of the indices to load. Defaults to None, which loads all indices in the index store. |
required |
**kwargs |
Any
|
Additional keyword args to pass to the index constructors. |
{}
|
Source code in llama-index-core/llama_index/core/indices/loading.py
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