use pyo3::prelude::*;
use tetnus_llm::{LoRALinear, SimpleTransformer, Trainer, ModelConfig};
use tetnus_core::Tensor;

#[pyclass(name = "LoRALinear")]
pub struct PyLoRALinear {
    inner: LoRALinear,
}

#[pymethods]
impl PyLoRALinear {
    #[new]
    fn new(in_features: usize, out_features: usize, rank: usize, alpha: f32) -> Self {
        Self {
            inner: LoRALinear::new(in_features, out_features, rank, alpha),
        }
    }

    fn forward(&self, x: &Bound<'_, PyAny>) -> PyResult<PyObject> {
        // Placeholder - would extract Tensor from Python object
        // For now, just return a dummy tensor
        Ok(x.clone().unbind())
    }
}

#[pyclass(name = "SimpleTransformer")]
pub struct PySimpleTransformer {
    inner: SimpleTransformer,
}

#[pymethods]
impl PySimpleTransformer {
    #[new]
    fn new(hidden_size: usize, num_layers: usize) -> Self {
        let config = ModelConfig {
            vocab_size: 1000,
            hidden_size,
            num_layers,
            num_heads: 4,
            intermediate_size: hidden_size * 4,
            max_seq_len: 512,
        };
        Self {
            inner: SimpleTransformer::new(config),
        }
    }

    fn apply_lora(&mut self, rank: usize, alpha: f32) {
        self.inner.apply_lora(rank, alpha);
    }

    fn forward(&self, x: &Bound<'_, PyAny>) -> PyResult<PyObject> {
        // Placeholder
        Ok(x.clone().unbind())
    }
}

#[pyclass(name = "Trainer")]
pub struct PyTrainer {
    inner: Trainer,
}

#[pymethods]
impl PyTrainer {
    #[new]
    fn new(hidden_size: usize, num_layers: usize, rank: usize, alpha: f32) -> Self {
        // Create a new model for the trainer
        let mut model  = PySimpleTransformer::new(hidden_size, num_layers);
        model.apply_lora(rank, alpha);

        Self {
            inner: Trainer::new(model.inner),
        }
    }

    fn train_step(&mut self, _inputs: &Bound<'_, PyAny>, _targets: &Bound<'_, PyAny>) -> PyResult<f32> {
        // For now, return a dummy loss
        // In a full implementation, would extract Tensors from PyAny
        Ok(0.5)
    }
}

pub fn register_tetnus_llm_module(py: Python, parent_module: &Bound<'_, PyModule>) -> PyResult<()> {
    let m = PyModule::new(py, "llm")?;
    m.add_class::<PyLoRALinear>()?;
    m.add_class::<PySimpleTransformer>()?;
    m.add_class::<PyTrainer>()?;
    parent_module.add_submodule(&m)?;
    Ok(())
}
