Passages
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class Passage: …
Representation of a passage, which is stored in archival memory.
embedding: Optional[List[float]]
The embedding of the passage.
embedding_config: Optional[EmbeddingConfig]
Configuration for embedding model connection and processing parameters.
embedding_dim: int
The dimension of the embedding.
embedding_endpoint_type: Literal["openai", "anthropic", "bedrock", 16 more]
The endpoint type for the model.
embedding_model: str
The model for the embedding.
azure_deployment: Optional[str]
The Azure deployment for the model.
azure_endpoint: Optional[str]
The Azure endpoint for the model.
azure_version: Optional[str]
The Azure version for the model.
batch_size: Optional[int]
The maximum batch size for processing embeddings.
embedding_chunk_size: Optional[int]
The chunk size of the embedding.
embedding_endpoint: Optional[str]
The endpoint for the model (None if local).
handle: Optional[str]
The handle for this config, in the format provider/model-name.
text: str
The text of the passage.
id: Optional[str]
The human-friendly ID of the Passage
archive_id: Optional[str]
The unique identifier of the archive containing this passage.
created_at: Optional[datetime]
The creation date of the passage.
created_by_id: Optional[str]
The id of the user that made this object.
file_id: Optional[str]
The unique identifier of the file associated with the passage.
file_name: Optional[str]
The name of the file (only for source passages).
is_deleted: Optional[bool]
Whether this passage is deleted or not.
last_updated_by_id: Optional[str]
The id of the user that made this object.
metadata: Optional[Dict[str, object]]
The metadata of the passage.
Deprecatedsource_id: Optional[str]
Deprecated: Use folder_id field instead. The data source of the passage.
tags: Optional[List[str]]
Tags associated with this passage.
updated_at: Optional[datetime]
The timestamp when the object was last updated.