# Configuration File Reference

The `assets/config.yml` file is the central place to configure the ConversionFlow pipeline. This document provides a reference for all the parameters in this file.

## `project_name`

-   **Type**: `string`
-   **Description**: The name of your project. Used for titling outputs and reports.

## `preprocess`

This section controls the preprocessing of the data.

-   `scaling`:
    -   `enabled`: `boolean` - Whether to enable scaling of numerical features.
    -   `method`: `string` - The scaling method to use (e.g., `standard`).
-   `missing_values`:
    -   `strategy`: `string` - The strategy for handling missing values (e.g., `fill`).
    -   `fill_value`: `any` - The value to use when filling missing values.
-   `exclude_from_scaling`: `list` - A list of column names to exclude from scaling.

## `api`

-   `gemini_key`: `string` - Your API key for the Google Gemini API, used for automated analysis.

## `model`

This section defines the structure of the Bayesian Network.

-   `name`: `string` - A unique name for your model.
-   `description`: `string` - A brief description of the model.
-   `nodes`: `dict` - A dictionary where keys are stage names and values are lists of node names.
-   `edges`: `list` - A list of lists, where each inner list represents a directed edge from a parent to a child node.

## `priors`

This section defines the prior distributions for the model parameters.

-   `beta_distributions`: `dict` - A nested dictionary defining the priors for the `beta` coefficients.
    -   The top-level key is the parent node.
    -   The nested key is the child node.
    -   The value is a dictionary specifying the `distribution` (e.g., `Normal`, `HalfCauchy`) and its parameters (e.g., `mu`, `sigma`).

## `inference`

This section controls the MCMC inference process.

-   `draws`: `int` - The number of samples to draw from the posterior distribution.
-   `tune`: `int` - The number of tuning (burn-in) steps to discard.
-   `chains`: `int` - The number of independent Markov chains to run.
-   `random_seed`: `int` - A random seed for reproducibility.
-   `target_accept`: `float` - The target acceptance rate for the NUTS sampler.
-   `max_treedepth`: `int` - The maximum tree depth for the NUTS sampler.

## `output`

This section controls the output of the pipeline.

-   `directory`: `string` - The directory where the output files will be saved.
-   `figures`:
    -   `extension`: `string` - The file extension for the output plots (e.g., `.png`).
    -   `dpi`: `int` - The resolution of the output plots.

## `logging`

This section controls the logging configuration.

-   `level`: `string` - The logging level (e.g., `INFO`, `DEBUG`).
-   `file`: `string` - The path to the log file.