transmutation 0.3.2

High-performance document conversion engine for AI/LLM embeddings - 27 formats supported
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//! Machine Learning module for document layout analysis
//!
//! This module provides ONNX-based ML models for:
//! - Layout detection (LayoutModel)
//! - Table structure recognition (TableStructureModel)
//!
//! All models are optional and only compiled when `docling-ffi` feature is enabled.

#![allow(missing_docs)]

#[cfg(feature = "docling-ffi")]
pub mod preprocessing;

#[cfg(feature = "docling-ffi")]
pub mod layout_model;

#[cfg(feature = "docling-ffi")]
pub mod table_structure_model;

#[cfg(feature = "docling-ffi")]
pub mod model_manager;

#[cfg(feature = "docling-ffi")]
pub mod model_cache;

#[cfg(feature = "docling-ffi")]
pub mod cell_matching;

#[cfg(feature = "docling-ffi")]
pub use cell_matching::{CellMatcher, MatchedCell};
#[cfg(feature = "docling-ffi")]
pub use layout_model::LayoutModel;
#[cfg(feature = "docling-ffi")]
pub use model_cache::{clear_model_cache, get_layout_model, get_table_model};
#[cfg(feature = "docling-ffi")]
pub use model_manager::ModelManager;
#[cfg(feature = "docling-ffi")]
pub use table_structure_model::TableStructureModel;

use crate::error::Result;

/// Trait for ML models that process document pages
#[cfg(feature = "docling-ffi")]
pub trait DocumentModel {
    /// Model input type
    type Input;
    /// Model output type
    type Output;

    /// Run inference on input (ort v2 requires mutable session)
    fn predict(&mut self, input: &Self::Input) -> Result<Self::Output>;

    /// Get model name for logging
    fn name(&self) -> &str;
}