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

# Camel.storages.vectordb storages.base

<a id="camel.storages.vectordb_storages.base" />

<a id="camel.storages.vectordb_storages.base.VectorRecord" />

## VectorRecord

```python theme={"system"}
class VectorRecord(BaseModel):
```

Encapsulates information about a vector's unique identifier and its
payload, which is primarily used as a data transfer object when saving
to vector storage.

**Parameters:**

* **vector** (List\[float]): The numerical representation of the vector.
* **id** (str, optional): A unique identifier for the vector. If not provided, an random uuid will be assigned.
* **payload** (Optional\[Dict\[str, Any]], optional): Any additional metadata or information related to the vector. (default: :obj:`None`)

<a id="camel.storages.vectordb_storages.base.VectorDBQuery" />

## VectorDBQuery

```python theme={"system"}
class VectorDBQuery(BaseModel):
```

Represents a query to a vector database.

**Parameters:**

* **query\_vector** (List\[float]): The numerical representation of the query vector.
* **top\_k** (int, optional): The number of top similar vectors to retrieve from the database. (default: :obj:`1`)

<a id="camel.storages.vectordb_storages.base.VectorDBQuery.__init__" />

### **init**

```python theme={"system"}
def __init__(
    self,
    query_vector: List[float],
    top_k: int,
    **kwargs: Any
):
```

Pass in query\_vector and tok\_k as positional arg.

**Parameters:**

* **query\_vector** (List\[float]): The numerical representation of the query vector.
* **top\_k** (int, optional): The number of top similar vectors to retrieve from the database. (default: :obj:`1`)

<a id="camel.storages.vectordb_storages.base.VectorDBQueryResult" />

## VectorDBQueryResult

```python theme={"system"}
class VectorDBQueryResult(BaseModel):
```

Encapsulates the result of a query against a vector database.

**Parameters:**

* **record** (VectorRecord): The target vector record.
* **similarity** (float): The similarity score between the query vector and the record.

<a id="camel.storages.vectordb_storages.base.VectorDBQueryResult.create" />

### create

```python theme={"system"}
def create(
    cls,
    similarity: float,
    vector: List[float],
    id: str,
    payload: Optional[Dict[str, Any]] = None
):
```

A class method to construct a `VectorDBQueryResult` instance.

<a id="camel.storages.vectordb_storages.base.VectorDBStatus" />

## VectorDBStatus

```python theme={"system"}
class VectorDBStatus(BaseModel):
```

Vector database status.

**Parameters:**

* **vector\_dim** (int): The dimension of stored vectors.
* **vector\_count** (int): The number of stored vectors.

<a id="camel.storages.vectordb_storages.base.BaseVectorStorage" />

## BaseVectorStorage

```python theme={"system"}
class BaseVectorStorage(ABC):
```

An abstract base class for vector storage systems.

<a id="camel.storages.vectordb_storages.base.BaseVectorStorage.add" />

### add

```python theme={"system"}
def add(self, records: List[VectorRecord], **kwargs: Any):
```

Saves a list of vector records to the storage.

**Parameters:**

* **records** (List\[VectorRecord]): List of vector records to be saved. \*\*kwargs (Any): Additional keyword arguments.

<a id="camel.storages.vectordb_storages.base.BaseVectorStorage.delete" />

### delete

```python theme={"system"}
def delete(self, ids: List[str], **kwargs: Any):
```

Deletes a list of vectors identified by their IDs from the storage.

**Parameters:**

* **ids** (List\[str]): List of unique identifiers for the vectors to be deleted. \*\*kwargs (Any): Additional keyword arguments.

<a id="camel.storages.vectordb_storages.base.BaseVectorStorage.status" />

### status

```python theme={"system"}
def status(self):
```

**Returns:**

VectorDBStatus: The vector database status.

<a id="camel.storages.vectordb_storages.base.BaseVectorStorage.query" />

### query

```python theme={"system"}
def query(self, query: VectorDBQuery, **kwargs: Any):
```

Searches for similar vectors in the storage based on the provided
query.

**Parameters:**

* **query** (VectorDBQuery): The query object containing the search vector and the number of top similar vectors to retrieve. \*\*kwargs (Any): Additional keyword arguments.

**Returns:**

List\[VectorDBQueryResult]: A list of vectors retrieved from the
storage based on similarity to the query vector.

<a id="camel.storages.vectordb_storages.base.BaseVectorStorage.clear" />

### clear

```python theme={"system"}
def clear(self):
```

Remove all vectors from the storage.

<a id="camel.storages.vectordb_storages.base.BaseVectorStorage.load" />

### load

```python theme={"system"}
def load(self):
```

Load the collection hosted on cloud service.

<a id="camel.storages.vectordb_storages.base.BaseVectorStorage.client" />

### client

```python theme={"system"}
def client(self):
```

Provides access to the underlying vector database client.

<a id="camel.storages.vectordb_storages.base.BaseVectorStorage.get_payloads_by_vector" />

### get\_payloads\_by\_vector

```python theme={"system"}
def get_payloads_by_vector(self, vector: List[float], top_k: int):
```

Returns payloads of top k vector records that closest to the given
vector.

This function is a wrapper of `BaseVectorStorage.query`.

**Parameters:**

* **vector** (List\[float]): The search vector.
* **top\_k** (int): The number of top similar vectors.

**Returns:**

List\[List\[Dict\[str, Any]]]: A list of vector payloads retrieved
from the storage based on similarity to the query vector.