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//! LoRA (Low-Rank Adaptation) support for Mullama
//!
//! This module provides comprehensive support for LoRA adapters, allowing fine-tuned
//! model behavior with minimal computational overhead.
use crate::error::MullamaError;
use crate::sys;
use crate::Context;
use crate::Model;
use std::ffi::CString;
use std::path::Path;
/// LoRA adapter for fine-tuning model behavior
#[derive(Debug)]
pub struct LoRAAdapter {
adapter_ptr: *mut sys::llama_adapter_lora,
path: String,
scale: f32,
}
impl LoRAAdapter {
/// Load a LoRA adapter from file
///
/// # Arguments
/// * `model` - The model to load the adapter for
/// * `path` - Path to the LoRA adapter file (.gguf format)
/// * `scale` - Scale factor for the adapter (typically 0.1 to 1.0)
///
/// # Example
/// ```rust,no_run
/// use mullama::{Model, lora::LoRAAdapter};
///
/// let model = Model::load("model.gguf")?;
/// let adapter = LoRAAdapter::load(&model, "adapter.gguf", 0.8)?;
/// # Ok::<(), mullama::MullamaError>(())
/// ```
pub fn load<P: AsRef<Path>>(model: &Model, path: P, scale: f32) -> Result<Self, MullamaError> {
let path_ref = path.as_ref();
let path_str = path_ref.to_string_lossy().to_string();
if !path_ref.exists() {
return Err(MullamaError::LoRAError(format!(
"LoRA adapter file not found: {}",
path_str
)));
}
let c_path = CString::new(path_str.clone())
.map_err(|_| MullamaError::InvalidInput("Invalid path".to_string()))?;
let adapter_ptr = unsafe { sys::llama_adapter_lora_init(model.as_ptr(), c_path.as_ptr()) };
if adapter_ptr.is_null() {
return Err(MullamaError::LoRAError(format!(
"Failed to load LoRA adapter from: {}",
path_str
)));
}
Ok(Self {
adapter_ptr,
path: path_str,
scale,
})
}
/// Apply this adapter to a context
///
/// # Arguments
/// * `ctx` - The context to apply the adapter to
///
/// # Returns
/// Result indicating success or failure
pub fn apply(&self, ctx: &mut Context) -> Result<(), MullamaError> {
let result =
unsafe { sys::llama_set_adapter_lora(ctx.as_ptr(), self.adapter_ptr, self.scale) };
if result != 0 {
return Err(MullamaError::LoRAError(
"Failed to apply LoRA adapter to context".to_string(),
));
}
Ok(())
}
/// Remove this adapter from a context
///
/// # Arguments
/// * `ctx` - The context to remove the adapter from
pub fn remove(&self, ctx: &mut Context) -> Result<(), MullamaError> {
let result = unsafe { sys::llama_rm_adapter_lora(ctx.as_ptr(), self.adapter_ptr) };
if result != 0 {
return Err(MullamaError::LoRAError(
"Failed to remove LoRA adapter from context".to_string(),
));
}
Ok(())
}
/// Get the adapter's file path
pub fn path(&self) -> &str {
&self.path
}
/// Get the adapter's scale factor
pub fn scale(&self) -> f32 {
self.scale
}
/// Set a new scale factor for this adapter
pub fn set_scale(&mut self, scale: f32) {
self.scale = scale;
}
/// Get the raw pointer (for internal use)
#[allow(dead_code)]
pub(crate) fn as_ptr(&self) -> *mut sys::llama_adapter_lora {
self.adapter_ptr
}
}
impl Drop for LoRAAdapter {
fn drop(&mut self) {
if !self.adapter_ptr.is_null() {
unsafe {
sys::llama_adapter_lora_free(self.adapter_ptr);
}
}
}
}
unsafe impl Send for LoRAAdapter {}
unsafe impl Sync for LoRAAdapter {}
/// Clear all LoRA adapters from a context
pub fn clear_adapters(ctx: &mut Context) {
unsafe {
sys::llama_clear_adapter_lora(ctx.as_ptr());
}
}
/// LoRA adapter manager for handling multiple adapters
#[derive(Debug)]
pub struct LoRAManager {
adapters: Vec<LoRAAdapter>,
active_adapters: Vec<(usize, f32)>, // (adapter_index, scale)
}
impl LoRAManager {
/// Create a new LoRA manager
pub fn new() -> Self {
Self {
adapters: Vec::new(),
active_adapters: Vec::new(),
}
}
/// Add a LoRA adapter to the manager
///
/// # Returns
/// The index of the added adapter
pub fn add_adapter(&mut self, adapter: LoRAAdapter) -> usize {
self.adapters.push(adapter);
self.adapters.len() - 1
}
/// Load and add a LoRA adapter from file
///
/// # Arguments
/// * `model` - The model to load the adapter for
/// * `path` - Path to the LoRA adapter file
/// * `scale` - Scale factor for the adapter
///
/// # Returns
/// The index of the loaded adapter
pub fn load_adapter<P: AsRef<Path>>(
&mut self,
model: &Model,
path: P,
scale: f32,
) -> Result<usize, MullamaError> {
let adapter = LoRAAdapter::load(model, path, scale)?;
Ok(self.add_adapter(adapter))
}
/// Apply all active adapters to a context
pub fn apply_to_context(&self, ctx: &mut Context) -> Result<(), MullamaError> {
for (idx, scale) in &self.active_adapters {
if let Some(adapter) = self.adapters.get(*idx) {
// Note: We need to be careful here - we're creating a temporary
// that shares the pointer but we don't want it to be freed
let result = unsafe {
sys::llama_set_adapter_lora(ctx.as_ptr(), adapter.adapter_ptr, *scale)
};
if result != 0 {
return Err(MullamaError::LoRAError(format!(
"Failed to apply LoRA adapter at index {}",
idx
)));
}
}
}
Ok(())
}
/// Activate an adapter with a specific scale
///
/// # Arguments
/// * `adapter_index` - Index of the adapter to activate
/// * `scale` - Scale factor to apply (overrides adapter's default scale)
pub fn activate_adapter(
&mut self,
adapter_index: usize,
scale: f32,
) -> Result<(), MullamaError> {
if adapter_index >= self.adapters.len() {
return Err(MullamaError::InvalidInput(format!(
"Adapter index {} out of range",
adapter_index
)));
}
// Remove if already active
self.active_adapters
.retain(|(idx, _)| *idx != adapter_index);
// Add with new scale
self.active_adapters.push((adapter_index, scale));
Ok(())
}
/// Deactivate an adapter
pub fn deactivate_adapter(&mut self, adapter_index: usize) {
self.active_adapters
.retain(|(idx, _)| *idx != adapter_index);
}
/// Get list of active adapters
pub fn active_adapters(&self) -> &[(usize, f32)] {
&self.active_adapters
}
/// Get adapter by index
pub fn get_adapter(&self, index: usize) -> Option<&LoRAAdapter> {
self.adapters.get(index)
}
/// Get mutable adapter by index
pub fn get_adapter_mut(&mut self, index: usize) -> Option<&mut LoRAAdapter> {
self.adapters.get_mut(index)
}
/// Get the number of loaded adapters
pub fn adapter_count(&self) -> usize {
self.adapters.len()
}
/// Clear all adapters
pub fn clear(&mut self) {
self.adapters.clear();
self.active_adapters.clear();
}
/// Create a preset configuration for common LoRA scenarios
pub fn create_preset(preset: LoRAPreset) -> Self {
let manager = Self::new();
match preset {
LoRAPreset::ChatAssistant => {
// Example preset - in practice, these would be real adapter files
// manager.load_adapter("adapters/chat_assistant.bin", 0.8).ok();
// manager.load_adapter("adapters/helpful_responses.bin", 0.6).ok();
}
LoRAPreset::CodeGeneration => {
// manager.load_adapter("adapters/code_completion.bin", 0.9).ok();
// manager.load_adapter("adapters/documentation.bin", 0.5).ok();
}
LoRAPreset::CreativeWriting => {
// manager.load_adapter("adapters/creative_style.bin", 1.0).ok();
// manager.load_adapter("adapters/narrative_flow.bin", 0.7).ok();
}
}
manager
}
}
impl Default for LoRAManager {
fn default() -> Self {
Self::new()
}
}
/// Preset LoRA configurations for common use cases
#[derive(Debug, Clone, Copy)]
pub enum LoRAPreset {
/// Optimized for chat assistant behavior
ChatAssistant,
/// Optimized for code generation
CodeGeneration,
/// Optimized for creative writing
CreativeWriting,
}
/// LoRA adapter composition for combining multiple adapters
#[derive(Debug)]
pub struct LoRAComposition {
adapters: Vec<(LoRAAdapter, f32)>, // (adapter, weight)
composition_mode: CompositionMode,
}
#[derive(Debug, Clone, Copy)]
pub enum CompositionMode {
/// Add adapter effects together
Additive,
/// Multiply adapter effects
Multiplicative,
/// Use weighted average
Average,
}
impl LoRAComposition {
/// Create a new LoRA composition
pub fn new(mode: CompositionMode) -> Self {
Self {
adapters: Vec::new(),
composition_mode: mode,
}
}
/// Add an adapter to the composition
pub fn add_adapter(&mut self, adapter: LoRAAdapter, weight: f32) {
self.adapters.push((adapter, weight));
}
/// Get the composition mode
pub fn mode(&self) -> CompositionMode {
self.composition_mode
}
/// Get the number of adapters in the composition
pub fn adapter_count(&self) -> usize {
self.adapters.len()
}
/// Apply the composition to calculate effective scales
pub fn calculate_effective_scales(&self) -> Vec<f32> {
match self.composition_mode {
CompositionMode::Additive => self
.adapters
.iter()
.map(|(adapter, weight)| adapter.scale() * weight)
.collect(),
CompositionMode::Multiplicative => {
let product: f32 = self
.adapters
.iter()
.map(|(adapter, weight)| adapter.scale() * weight)
.product();
vec![product; self.adapters.len()]
}
CompositionMode::Average => {
let sum: f32 = self
.adapters
.iter()
.map(|(adapter, weight)| adapter.scale() * weight)
.sum();
let avg = sum / self.adapters.len() as f32;
vec![avg; self.adapters.len()]
}
}
}
}
/// LoRA training utilities (for future implementation)
pub mod training {
use super::*;
/// Parameters for LoRA training
#[derive(Debug, Clone)]
pub struct LoRATrainingParams {
pub rank: usize,
pub alpha: f32,
pub dropout: f32,
pub learning_rate: f32,
pub target_modules: Vec<String>,
}
impl Default for LoRATrainingParams {
fn default() -> Self {
Self {
rank: 16,
alpha: 32.0,
dropout: 0.1,
learning_rate: 1e-4,
target_modules: vec![
"q_proj".to_string(),
"v_proj".to_string(),
"k_proj".to_string(),
"o_proj".to_string(),
],
}
}
}
/// LoRA trainer (placeholder for future implementation)
#[allow(dead_code)]
pub struct LoRATrainer {
params: LoRATrainingParams,
}
impl LoRATrainer {
pub fn new(params: LoRATrainingParams) -> Self {
Self { params }
}
/// Train a LoRA adapter (placeholder)
pub fn train(&self, _training_data: &[String]) -> Result<LoRAAdapter, MullamaError> {
// This would be implemented with actual training logic
Err(MullamaError::NotImplemented(
"LoRA training not yet implemented".to_string(),
))
}
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_lora_manager() {
let manager = LoRAManager::new();
assert_eq!(manager.adapter_count(), 0);
assert_eq!(manager.active_adapters().len(), 0);
}
#[test]
fn test_lora_composition() {
let composition = LoRAComposition::new(CompositionMode::Additive);
assert_eq!(composition.adapter_count(), 0);
assert!(matches!(composition.mode(), CompositionMode::Additive));
}
#[test]
fn test_lora_preset() {
let manager = LoRAManager::create_preset(LoRAPreset::ChatAssistant);
// This would have adapters in a real implementation
assert_eq!(manager.adapter_count(), 0);
}
}