> ## Documentation Index
> Fetch the complete documentation index at: https://docs.cyborg.co/llms.txt
> Use this file to discover all available pages before exploring further.

# __init__

Initializes a new CyborgVectorStore instance for use with LangChain.

```python theme={null}
CyborgVectorStore(
    index_name: str,
    index_key: bytes,
    api_key: str,
    embedding: Union[str, Embeddings, SentenceTransformer],
    index_location: DBConfig,
    config_location: DBConfig,
    items_location: Optional[DBConfig] = None,
    index_type: str = "ivfflat",
    index_config_params: Optional[Dict[str, Any]] = None,
    dimension: Optional[int] = None,
    metric: str = "cosine"
)
```

### Parameters

| Parameter             | Type                                          | Description                                                                         |
| --------------------- | --------------------------------------------- | ----------------------------------------------------------------------------------- |
| `index_name`          | `str`                                         | Name of the index (must be unique)                                                  |
| `index_key`           | `bytes`                                       | 32-byte encryption key for securing index data                                      |
| `api_key`             | `str`                                         | API key for CyborgDB authentication                                                 |
| `embedding`           | `Union[str, Embeddings, SentenceTransformer]` | Embedding model name or instance                                                    |
| `index_location`      | `DBConfig`                                    | Configuration for index data storage location                                       |
| `config_location`     | `DBConfig`                                    | Configuration for index config storage location                                     |
| `items_location`      | `Optional[DBConfig]`                          | *(Optional)* Location for item data storage (default: memory)                       |
| `index_type`          | `str`                                         | Type of index: "ivfflat", "ivf", or "ivfpq" (default: "ivfflat")                    |
| `index_config_params` | `Optional[Dict[str, Any]]`                    | *(Optional)* Additional index configuration parameters                              |
| `dimension`           | `Optional[int]`                               | *(Optional)* Embedding dimension (auto-inferred if not provided)                    |
| `metric`              | `str`                                         | Distance metric: "cosine", "euclidean", or "squared\_euclidean" (default: "cosine") |

### Returns

`CyborgVectorStore`: Initialized vector store instance

### Exceptions

<AccordionGroup>
  <Accordion title="ValueError">
    * Throws if index\_type is invalid
  </Accordion>

  <Accordion title="RuntimeError">
    * Throws if no embedding model provided and dimension not specified
  </Accordion>
</AccordionGroup>

### Example Usage

```python theme={null}
from cyborgdb_core.langchain import CyborgVectorStore
from cyborgdb_core import DBConfig

# Generate a secure key
index_key = CyborgVectorStore.generate_key()

# Initialize with string embedding model name
store = CyborgVectorStore(
    index_name="my_documents",
    index_key=index_key,
    api_key="your-api-key",
    embedding="sentence-transformers/all-MiniLM-L6-v2",
    index_location=DBConfig("s3", bucket="my-bucket"),
    config_location=DBConfig("s3", bucket="my-bucket"),
    index_type="ivfflat",
    metric="cosine"
)
```