# store.OpenAIStore


A vector store backed by OpenAI's Vector Store API.


Usage

``` python
store.OpenAIStore(
    client,
    store_id,
    *,
    attributes_spec=None,
    attributes=None,
)
```


OpenAIStore uses OpenAI's hosted vector storage service for document storage and retrieval. Documents are uploaded as files and automatically chunked and embedded by OpenAI.


## Examples


``` python
from raghilda.store import OpenAIStore

# Create a new store
store = OpenAIStore.create(name="my-store")

# Or connect to an existing store
store = OpenAIStore.connect(store_id="vs_abc123")

# Insert documents
from raghilda.document import MarkdownDocument
doc = MarkdownDocument(content="# Hello\nWorld", origin="example.md")
store.upsert(doc)

# Retrieve similar chunks
chunks = store.retrieve("greeting", top_k=5)
```


## Methods

| Name | Description |
|----|----|
| [connect()](#connect) | Connect to an existing OpenAI vector store. |
| [create()](#create) | Create a new OpenAI vector store. |
| [retrieve()](#retrieve) | Retrieve the most similar chunks to the given text. |

------------------------------------------------------------------------


### connect()


Connect to an existing OpenAI vector store.


Usage

``` python
connect(store_id, base_url="https://api.openai.com/v1", api_key=None)
```


#### Parameters


`store_id: str`  
The ID of the vector store to connect to (e.g., "vs_abc123").

`base_url: str = ``"https://api.openai.com/v1"`  
Base URL for the OpenAI API.

`api_key: str | None = None`  
OpenAI API key. If None, uses the OPENAI_API_KEY environment variable.


#### Returns


`OpenAIStore`  
A connected store instance.


------------------------------------------------------------------------


### create()


Create a new OpenAI vector store.


Usage

``` python
create(
    base_url="https://api.openai.com/v1",
    api_key=None,
    *,
    attributes=None,
    metadata=None,
    **kwargs
)
```


#### Parameters


`base_url: str = ``"https://api.openai.com/v1"`  
Base URL for the OpenAI API.

`api_key: str | None = None`  
OpenAI API key. If None, uses the OPENAI_API_KEY environment variable.

`attributes: AttributesSchemaSpec | None = None`  
Optional schema for user-defined attribute columns. Attribute names use identifier-style syntax. OpenAIStore filters only support declared attributes.

`metadata: Mapping[str, str] | None = None`  
Additional metadata to attach to the OpenAI vector store resource.

`**kwargs`  
Additional arguments passed to the vector store creation (e.g., name, expires_after).


#### Returns


`OpenAIStore`  
A newly created store instance.


------------------------------------------------------------------------


### retrieve()


Retrieve the most similar chunks to the given text.


Usage

``` python
retrieve(text, top_k, *, attributes_filter=None, **kwargs)
```


#### Parameters


`text: str`  
The query text to search for.

`top_k: int`  
The maximum number of chunks to return.

`attributes_filter: AttributeFilter | None = None`  
Optional attribute filter as SQL-like string or dict AST. Supports declared attributes only. Built-in columns such as `origin` are not available in OpenAI filters.

`**kwargs`  
Additional arguments passed to OpenAI's `vector_stores.search()`.


#### Returns


`Sequence[RetrievedOpenAIMarkdownChunk]`  
The retrieved chunks with their relevance metrics.