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

# mellea.formatters.granite.intrinsics.util

> Common utility functions for this package.

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Common utility functions for this package.

## Functions

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### <span className="ml-2 inline-flex items-center rounded-full px-2 py-1 text-[0.7rem] font-bold tracking-wide bg-[#3064E3]/20 text-[#1D4ED8]">FUNC</span> `make_config_dict` <sup><a href="https://github.com/generative-computing/mellea/blob/v0.6.0/mellea/formatters/granite/intrinsics/util.py#L24" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>

```python theme={null}
make_config_dict(config_file: str | pathlib.Path | None = None, config_dict: dict | None = None) -> dict | None
```

Create a configuration dictionary from YAML file or dict.

This function is not a public API and is not intended for use outside this library.

Common initialization code for reading YAML config files in factory classes.
Also parses JSON fields.

**Args:**

* `config_file`: Path to a YAML configuration file. Exactly one of `config_file`
  and `config_dict` must be provided.
* `config_dict`: Pre-parsed configuration dict (from `yaml.safe_load()`). Exactly
  one of `config_file` and `config_dict` must be provided.

**Returns:**

* Validated configuration dict with optional fields set to `None` and JSON
* string fields parsed to Python objects.

**Raises:**

* `ValueError`: If both or neither of `config_file` and `config_dict` are
  provided, if a required field is missing, if an unexpected top-level
  field is encountered, or if a JSON field cannot be parsed.

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### <span className="ml-2 inline-flex items-center rounded-full px-2 py-1 text-[0.7rem] font-bold tracking-wide bg-[#3064E3]/20 text-[#1D4ED8]">FUNC</span> `obtain_lora` <sup><a href="https://github.com/generative-computing/mellea/blob/v0.6.0/mellea/formatters/granite/intrinsics/util.py#L100" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>

```python theme={null}
obtain_lora(revision: str = 'main', alora: bool = False, cache_dir: str | None = None, file_glob: str = '*') -> pathlib.Path
```

Download and cache an adapter that implements and intrinsic.

Downloads a LoRA or aLoRA adapter from a collection of adapters that follow the
same layout as the [Granite Intrinsics Library](https://huggingface.co/ibm-granite/granitelib-rag-r1.0). Caches the downloaded
adapter files on local disk.

**Args:**

* `intrinsic_name`: Short name of the intrinsic model, such as `"certainty"`.
* `target_model_name`: Name of the base model for the LoRA or aLoRA adapter.
* `repo_id`: Hugging Face Hub repository containing a collection of LoRA and/or
  aLoRA adapters for intrinsics.
* `revision`: Git revision of the repository to download from.
* `alora`: If `True`, load the aLoRA version of the intrinsic; otherwise use LoRA.
* `cache_dir`: Local directory to use as a cache (Hugging Face Hub format), or
  `None` to use the default location.
* `file_glob`: Only files matching this glob will be downloaded to the cache.

**Returns:**

* Full path to the local copy of the specified (a)LoRA adapter, suitable for
* passing to commands that serve the adapter.

**Raises:**

* `ValueError`: If the specified intrinsic adapter cannot be found in the
  Hugging Face Hub repository at the expected path.

<div className="w-full h-px bg-gray-200 dark:bg-gray-700 my-4" />

### <span className="ml-2 inline-flex items-center rounded-full px-2 py-1 text-[0.7rem] font-bold tracking-wide bg-[#3064E3]/20 text-[#1D4ED8]">FUNC</span> `obtain_io_yaml` <sup><a href="https://github.com/generative-computing/mellea/blob/v0.6.0/mellea/formatters/granite/intrinsics/util.py#L175" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>

```python theme={null}
obtain_io_yaml(revision: str = 'main', alora: bool = False, cache_dir: str | None = None) -> pathlib.Path
```

Download cached `io.yaml` configuration file for an intrinsic.

Downloads an `io.yaml` configuration file for an intrinsic
with a model repository that follows the format of the
[Granite Intrinsics Library](https://huggingface.co/ibm-granite/granitelib-rag-r1.0) if one is not
already in the local cache.

**Args:**

* `intrinsic_name`: Short name of the intrinsic model, such as `"certainty"`.
* `target_model_name`: Name of the base model for the LoRA or aLoRA adapter.
* `repo_id`: Hugging Face Hub repository containing a collection of LoRA and/or
  aLoRA adapters for intrinsics.
* `revision`: Git revision of the repository to download from.
* `alora`: If `True`, load the aLoRA version of the intrinsic; otherwise use LoRA.
* `cache_dir`: Local directory to use as a cache (Hugging Face Hub format), or
  `None` to use the default location.

**Returns:**

* Full path to the local copy of the `io.yaml` file, suitable for passing to
* `IntrinsicsRewriter`.

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