Implementation:Openai Openai python Vector Store Search Response

Knowledge Sources	Openai_Openai_python OpenAI API Reference
Domains	API_Types, Python
Last Updated	2026-02-15 00:00 GMT

Overview

Concrete tool for representing a single search result from a VectorStore search operation, provided by the openai-python SDK.

Description

VectorStoreSearchResponse is a Pydantic BaseModel subclass that represents an individual search result returned by the vector store search endpoint. Each result includes the matched content chunks (a list of Content objects), the file_id and filename of the source file, a similarity score, and optional attributes (key-value metadata). The nested Content model contains the text content and its type (always "text").

Usage

Import this type when you need to type-annotate or inspect individual search results returned by client.vector_stores.search(). The response from the search endpoint contains a list of these objects.

Code Reference

Source Location

• Repository: openai-python
• File: src/openai/types/vector_store_search_response.py

Signature

class Content(BaseModel):
    text: str
    type: Literal["text"]


class VectorStoreSearchResponse(BaseModel):
    attributes: Optional[Dict[str, Union[str, float, bool]]] = None
    content: List[Content]
    file_id: str
    filename: str
    score: float

Import

from openai.types import VectorStoreSearchResponse

I/O Contract

Fields (VectorStoreSearchResponse)

Name	Type	Required	Description
attributes	Optional[Dict[str, Union[str, float, bool]]]	No	Key-value pairs attached to the object for filtering and metadata.
content	List[Content]	Yes	Content chunks from the matched file.
file_id	str	Yes	The ID of the vector store file.
filename	str	Yes	The name of the vector store file.
score	float	Yes	The similarity score for the result.

Fields (Content)

Name	Type	Required	Description
text	str	Yes	The text content returned from search.
type	Literal["text"]	Yes	The type of content, always "text".

Usage Examples

from openai import OpenAI
from openai.types import VectorStoreSearchResponse

client = OpenAI()

results = client.vector_stores.search("vs_abc123", query="setup guide")

for result in results.data:
    result: VectorStoreSearchResponse
    print(f"File: {result.filename} (score: {result.score})")
    for chunk in result.content:
        print(f"  {chunk.text[:100]}...")

Related Pages

• Environment:Openai_Openai_python_Python_3_9_Plus