API Reference

Vector Stores

Files

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Update vector store file attributes

vector_stores.files.update(strfile_id, FileUpdateParams**kwargs) -> VectorStoreFile

POST/vector_stores/{vector_store_id}/files/{file_id}

Update attributes on a vector store file.

ParametersExpand Collapse

vector_store_id: str

file_id: str

attributes: Optional[Dict[str, Union[str, float, bool]]]

Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard. Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters, booleans, or numbers.

ReturnsExpand Collapse

class VectorStoreFile: …

A list of files attached to a vector store.

id: str

The identifier, which can be referenced in API endpoints.

created_at: int

The Unix timestamp (in seconds) for when the vector store file was created.

formatunixtime

last_error: Optional[LastError]

The last error associated with this vector store file. Will be null if there are no errors.

object: Literal["vector_store.file"]

The object type, which is always vector_store.file.

status: Literal["in_progress", "completed", "cancelled", "failed"]

The status of the vector store file, which can be either in_progress, completed, cancelled, or failed. The status completed indicates that the vector store file is ready for use.

usage_bytes: int

The total vector store usage in bytes. Note that this may be different from the original file size.

vector_store_id: str

The ID of the vector store that the File is attached to.

attributes: Optional[Dict[str, Union[str, float, bool]]]

Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard. Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters, booleans, or numbers.

chunking_strategy: Optional[FileChunkingStrategy]

The strategy used to chunk the file.

Update vector store file attributes

Python

HTTP

Python

TypeScript

Go

Ruby

Java

CLI Tool

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
)
vector_store_file = client.vector_stores.files.update(
    file_id="file-abc123",
    vector_store_id="vs_abc123",
    attributes={
        "foo": "string"
    },
)
print(vector_store_file.id)

{
  "id": "file-abc123",
  "object": "vector_store.file",
  "usage_bytes": 1234,
  "created_at": 1699061776,
  "vector_store_id": "vs_abcd",
  "status": "completed",
  "last_error": null,
  "chunking_strategy": {...},
  "attributes": {"key1": "value1", "key2": 2}
}

Returns Examples

{
  "id": "file-abc123",
  "object": "vector_store.file",
  "usage_bytes": 1234,
  "created_at": 1699061776,
  "vector_store_id": "vs_abcd",
  "status": "completed",
  "last_error": null,
  "chunking_strategy": {...},
  "attributes": {"key1": "value1", "key2": 2}
}