__init__ - CyborgDB Docs

Initializes a new CyborgVectorStore instance for use with LangChain.

Embedded
Python SDK
JS/TS

CyborgVectorStore(
    index_name: str,
    index_key: bytes | list[int] | tuple[int, ...] | np.ndarray,
    api_key: str,
    embedding: Embeddings,
    index_location: DBConfig,
    config_location: DBConfig,
    items_location: Optional[DBConfig] = None,
    index_type: str = "ivfsq",
    index_config_params: Optional[Dict[str, Any]] = None,
    dimension: Optional[int] = None,
    metric: str = "cosine",
    gpu_config: Optional[GPUConfig] = None
)

Parameters

Parameter	Type	Description
`index_name`	`str`	Name of the index (must be unique)
`index_key`	`bytes \| list[int] \| tuple[int, ...] \| np.ndarray`	32-byte encryption key for securing index data
`api_key`	`str`	API key for CyborgDB authentication
`embedding`	`Embeddings`	LangChain Embeddings 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"`, `"ivfpq"`, or `"ivfsq"` (default: `"ivfsq"`)
`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"`)
`gpu_config`	`Optional[GPUConfig]`	(Optional) GPU configuration for accelerated operations

Returns

CyborgVectorStore: Initialized vector store instance

Example Usage

from cyborgdb_core.integrations.langchain import CyborgVectorStore
from cyborgdb_core import DBConfig
from langchain_openai import OpenAIEmbeddings

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

# Initialize with LangChain Embeddings
store = CyborgVectorStore(
    index_name="my_documents",
    index_key=index_key,
    api_key="your-api-key",
    embedding=OpenAIEmbeddings(),
    index_location=DBConfig("redis", connection_string="redis://localhost:6379"),
    config_location=DBConfig("postgres", connection_string="host=localhost dbname=vectordb user=postgres"),
    index_type="ivfsq",
    metric="cosine"
)

CyborgVectorStore(
    index_name: str,
    index_key: bytes,
    api_key: str,
    embedding: Union[str, Embeddings, SentenceTransformer],
    base_url: str,
    verify_ssl: Optional[bool] = 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
`base_url`	`str`	Base URL of the CyborgDB microservice endpoint
`verify_ssl`	`Optional[bool]`	(Optional) SSL verification. When `None`, automatically disabled for `localhost` and `http://` URLs
`index_type`	`str`	Type of index: `"ivfflat"`, `"ivfpq"`, or `"ivfsq"` (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

The Python SDK requires a running CyborgDB service. Use base_url to point to your service endpoint instead of providing DBConfig storage locations.

Example Usage

from cyborgdb.integrations.langchain import CyborgVectorStore

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

# 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",
    base_url="http://localhost:8000",
    index_type="ivfflat",
    metric="cosine"
)

new CyborgVectorStore(embeddings: EmbeddingsInterface, config: CyborgVectorStoreConfig)

Parameters

Parameter	Type	Description
`embeddings`	`EmbeddingsInterface`	LangChain embeddings instance
`config`	`CyborgVectorStoreConfig`	Configuration object (see below)

CyborgVectorStoreConfig

Parameter	Type	Description
`baseUrl`	`string`	Base URL of the CyborgDB microservice endpoint
`apiKey`	`string`	API key for CyborgDB authentication
`indexName`	`string`	Name of the index (must be unique)
`indexKey`	`Uint8Array`	32-byte encryption key for securing index data
`indexType`	`string`	(Optional) Type of index: `"ivfflat"`, `"ivfpq"`, or `"ivfsq"` (default: `"ivfflat"`)
`indexConfigParams`	`Record<string, number>`	(Optional) Additional index configuration parameters
`dimension`	`number`	(Optional) Embedding dimension (auto-inferred if not provided)
`metric`	`string`	(Optional) Distance metric: `"cosine"`, `"euclidean"`, or `"squared_euclidean"` (default: `"cosine"`)
`verifySsl`	`boolean`	(Optional) SSL verification (default: `true`)

Returns

CyborgVectorStore: Initialized vector store instance

The JS/TS SDK requires a running CyborgDB service. Use baseUrl to point to your service endpoint instead of providing DBConfig storage locations.

Example Usage

import { CyborgVectorStore } from 'cyborgdb';
import { OpenAIEmbeddings } from '@langchain/openai';

const store = new CyborgVectorStore(
    new OpenAIEmbeddings(),
    {
        baseUrl: "http://localhost:8000",
        apiKey: "your-api-key",
        indexName: "my_documents",
        indexKey: CyborgVectorStore.generateKey(),
        indexType: "ivfflat",
        metric: "cosine"
    }
);

Exceptions

ValueError

Throws if index_type is invalid

RuntimeError

Throws if no embedding model provided and dimension not specified

Introduction

CyborgVectorStore

Types

init

Parameters

Returns

Example Usage

Parameters

Returns

Example Usage

Parameters

CyborgVectorStoreConfig

Returns

Example Usage

Exceptions

Introduction

CyborgVectorStore

Types

​Parameters

​Returns

​Example Usage

​Parameters

​Returns

​Example Usage

​Parameters

​CyborgVectorStoreConfig

​Returns

​Example Usage

​Exceptions

Parameters

Returns

Example Usage

Parameters

Returns

Example Usage

Parameters

CyborgVectorStoreConfig

Returns

Example Usage

Exceptions