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Vector Stores

Create vector store

vector_stores.create(VectorStoreCreateParams**kwargs) -> VectorStore
POST/vector_stores

Create a vector store.

ParametersExpand Collapse
chunking_strategy: Optional[FileChunkingStrategyParam]

The chunking strategy used to chunk the file(s). If not set, will use the auto strategy. Only applicable if file_ids is non-empty.

Accepts one of the following:
class AutoFileChunkingStrategyParam: …

The default strategy. This strategy currently uses a max_chunk_size_tokens of 800 and chunk_overlap_tokens of 400.

type: Literal["auto"]

Always auto.

class StaticFileChunkingStrategyObjectParam: …

Customize your own chunking strategy by setting chunk size and chunk overlap.

chunk_overlap_tokens: int

The number of tokens that overlap between chunks. The default value is 400.

Note that the overlap must not exceed half of max_chunk_size_tokens.

max_chunk_size_tokens: int

The maximum number of tokens in each chunk. The default value is 800. The minimum value is 100 and the maximum value is 4096.

minimum100
maximum4096
type: Literal["static"]

Always static.

description: Optional[str]

A description for the vector store. Can be used to describe the vector store's purpose.

expires_after: Optional[ExpiresAfter]

The expiration policy for a vector store.

anchor: Literal["last_active_at"]

Anchor timestamp after which the expiration policy applies. Supported anchors: last_active_at.

days: int

The number of days after the anchor time that the vector store will expire.

minimum1
maximum365
file_ids: Optional[SequenceNotStr[str]]

A list of File IDs that the vector store should use. Useful for tools like file_search that can access files.

metadata: Optional[Metadata]

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.

name: Optional[str]

The name of the vector store.

ReturnsExpand Collapse
class VectorStore: …

A vector store is a collection of processed files can be used by the file_search tool.

id: str

The identifier, which can be referenced in API endpoints.

created_at: int

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

file_counts: FileCounts
cancelled: int

The number of files that were cancelled.

completed: int

The number of files that have been successfully processed.

failed: int

The number of files that have failed to process.

in_progress: int

The number of files that are currently being processed.

total: int

The total number of files.

last_active_at: Optional[int]

The Unix timestamp (in seconds) for when the vector store was last active.

metadata: Optional[Metadata]

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.

name: str

The name of the vector store.

object: Literal["vector_store"]

The object type, which is always vector_store.

status: Literal["expired", "in_progress", "completed"]

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

Accepts one of the following:
"expired"
"in_progress"
"completed"
usage_bytes: int

The total number of bytes used by the files in the vector store.

expires_after: Optional[ExpiresAfter]

The expiration policy for a vector store.

anchor: Literal["last_active_at"]

Anchor timestamp after which the expiration policy applies. Supported anchors: last_active_at.

days: int

The number of days after the anchor time that the vector store will expire.

minimum1
maximum365
expires_at: Optional[int]

The Unix timestamp (in seconds) for when the vector store will expire.

Create vector store

from openai import OpenAI
client = OpenAI()

vector_store = client.vector_stores.create(
  name="Support FAQ"
)
print(vector_store)

{
  "id": "vs_abc123",
  "object": "vector_store",
  "created_at": 1699061776,
  "name": "Support FAQ",
  "description": "Contains commonly asked questions and answers, organized by topic.",
  "bytes": 139920,
  "file_counts": {
    "in_progress": 0,
    "completed": 3,
    "failed": 0,
    "cancelled": 0,
    "total": 3
  }
}
Returns Examples
{
  "id": "vs_abc123",
  "object": "vector_store",
  "created_at": 1699061776,
  "name": "Support FAQ",
  "description": "Contains commonly asked questions and answers, organized by topic.",
  "bytes": 139920,
  "file_counts": {
    "in_progress": 0,
    "completed": 3,
    "failed": 0,
    "cancelled": 0,
    "total": 3
  }
}