create_cache.mdx

title	create_cache
description	Create a new cache with specified configuration

```python def create_cache( name: str, model: str, gguf_file: str, filters: Optional[Dict[str, Any]] = None, docs: Optional[List[str]] = None, ) -> Dict[str, Any] ``` ```python async def create_cache( name: str, model: str, gguf_file: str, filters: Optional[Dict[str, Any]] = None, docs: Optional[List[str]] = None, ) -> Dict[str, Any] ```

Parameters

• name (str): Name of the cache to create
• model (str): Name of the model to use (e.g. "llama2")
• gguf_file (str): Name of the GGUF file to use for the model
• filters (Dict[str, Any], optional): Optional metadata filters to determine which documents to include. These filters will be applied in addition to any specific docs provided.
• docs (List[str], optional): Optional list of specific document IDs to include. These docs will be included in addition to any documents matching the filters.

Returns

• Dict[str, Any]: Created cache configuration

Examples

```python from morphik import Morphik

db = Morphik()

# This will include both:
# 1. Any documents with category="programming"
# 2. The specific documents "doc1" and "doc2" (regardless of their category)
cache = db.create_cache(
    name="programming_cache",
    model="llama2",
    gguf_file="llama-2-7b-chat.Q4_K_M.gguf",
    filters={"category": "programming"},
    docs=["doc1", "doc2"]
)
```

```python from morphik import AsyncMorphik

async with AsyncMorphik() as db:
    # This will include both:
    # 1. Any documents with category="programming"
    # 2. The specific documents "doc1" and "doc2" (regardless of their category)
    cache = await db.create_cache(
        name="programming_cache",
        model="llama2",
        gguf_file="llama-2-7b-chat.Q4_K_M.gguf",
        filters={"category": "programming"},
        docs=["doc1", "doc2"]
    )
```

Cache Usage

After creating a cache, you can interact with it using the get_cache method, which returns a Cache object that provides methods for querying and updating the cache.

```python cache = db.get_cache("programming_cache") response = cache.query("Explain recursion in programming") ``` ```python cache = await db.get_cache("programming_cache") response = await cache.query("Explain recursion in programming") ```