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Class: MossClient
Semantic search client for vector similarity operations.
Methods
create_index(index_name, docs, model_id)
Create a new index populated with documents.
Parameters
- index_name (
str): Name of the index to create.
- docs (List[
DocumentInfo]): Documents to ingest into the index.
- model_id (
str): Identifier for the embedding model.
Returns
bool
True if the creation request succeeded.
get_index(index_name)
Retrieve metadata for a single index.
Parameters
- index_name (
str): Name of the index to inspect.
Returns
IndexInfo
Metadata describing the requested index.
list_indexes()
List all indexes in the current project.
Returns
List[IndexInfo]
List[IndexInfo]: Collection of index metadata objects.
delete_index(index_name)
Delete an index and all associated documents.
Parameters
- index_name (
str): Name of the index to delete.
Returns
bool
True if the deletion request succeeded.
add_docs(index_name, docs, options)
Insert or update documents in an index.
Parameters
- index_name (
str): Target index name.
- docs (List[
DocumentInfo]): Documents to add or upsert.
- options (Optional[
AddDocumentsOptions]): Upsert behavior overrides.
Returns
Dict[str, int]
Dict[str, int]: Mutation counts such as inserted or updated totals.
delete_docs(index_name, doc_ids)
Remove documents by identifier.
Parameters
- index_name (
str): Target index name.
- doc_ids (
List[str]): Identifiers of documents to delete.
Returns
Dict[str, int]
Dict[str, int]: Summary counts for deleted documents.
get_docs(index_name, options)
Fetch documents stored in an index.
Parameters
- index_name (
str): Target index name.
- options (Optional[
GetDocumentsOptions]): Retrieval filters.
Returns
List[DocumentInfo]
List[DocumentInfo]: Documents that satisfy the filters.
load_index(index_name)
Load an index from persistent storage.
Parameters
- index_name (
str): Name of the index to load.
Returns
str
Identifier or status describing the loaded index.
query(index_name, query, top_k, alpha)
Execute a semantic similarity search.
Parameters
- index_name (
str): Target index name.
- query (
str): Natural language query string.
- top_k (
int): Maximum number of documents to return.
- alpha (
Optional[float]): Hybrid weighting value.
Returns
SearchResult
Ranked documents and metadata for the query. 
