# MongoDBAtlasSemanticCache

> **Class** in `langchain_mongodb`

📖 [View in docs](https://reference.langchain.com/python/langchain-mongodb/cache/MongoDBAtlasSemanticCache)

MongoDB Atlas Semantic cache.

A Cache backed by a MongoDB Atlas server with vector-store support

## Signature

```python
MongoDBAtlasSemanticCache(
    self,
    connection_string: str,
    embedding: Embeddings,
    collection_name: str = 'default',
    database_name: str = 'default',
    index_name: str = 'default',
    wait_until_ready: Optional[float] = None,
    score_threshold: Optional[float] = None,
    **kwargs: Dict[str, Any] = {},
)
```

## Parameters

| Name | Type | Required | Description |
|------|------|----------|-------------|
| `connection_string` | `str` | Yes | MongoDB URI to connect to MongoDB Atlas cluster. |
| `embedding` | `Embeddings` | Yes | Text embedding model to use. |
| `collection_name` | `str` | No | MongoDB Collection to add the texts to. Defaults to "default". (default: `'default'`) |
| `database_name` | `str` | No | MongoDB Database where to store texts. Defaults to "default". (default: `'default'`) |
| `index_name` | `str` | No | Name of the Atlas Search index. defaults to 'default' (default: `'default'`) |
| `wait_until_ready` | `float` | No | Wait this time for Atlas to finish indexing the stored text. Defaults to None. (default: `None`) |

## Extends

- `BaseCache`
- `MongoDBAtlasVectorSearch`

## Constructors

```python
__init__(
    self,
    connection_string: str,
    embedding: Embeddings,
    collection_name: str = 'default',
    database_name: str = 'default',
    index_name: str = 'default',
    wait_until_ready: Optional[float] = None,
    score_threshold: Optional[float] = None,
    **kwargs: Dict[str, Any] = {},
)
```

| Name | Type |
|------|------|
| `connection_string` | `str` |
| `embedding` | `Embeddings` |
| `collection_name` | `str` |
| `database_name` | `str` |
| `index_name` | `str` |
| `wait_until_ready` | `Optional[float]` |
| `score_threshold` | `Optional[float]` |


## Properties

- `LLM`
- `RETURN_VAL`
- `collection`
- `score_threshold`

## Methods

- [`lookup()`](https://reference.langchain.com/python/langchain-mongodb/cache/MongoDBAtlasSemanticCache/lookup)
- [`update()`](https://reference.langchain.com/python/langchain-mongodb/cache/MongoDBAtlasSemanticCache/update)
- [`clear()`](https://reference.langchain.com/python/langchain-mongodb/cache/MongoDBAtlasSemanticCache/clear)

---

[View source on GitHub](https://github.com/langchain-ai/langchain-mongodb/blob/ad9050c28e092b335dcb846f77c0ec2245553f79/libs/langchain-mongodb/langchain_mongodb/cache.py#L108)