src/bsh_engine.cpp

#include "bsh_engine.hpp"

namespace bsh {

Engine::Engine() : initialized_(false) {}

Engine::~Engine() = default;

void Engine::initialize() {
    initialized_ = true;
}

void Engine::process(const Tensor& input, Tensor& output) {
    if (!initialized_) {
        throw std::runtime_error("Engine not initialized");
    }
    
    if (input.rows() != output.rows() || input.cols() != output.cols()) {
        throw std::runtime_error("Input/output tensor dimension mismatch");
    }
    
    // Copy input to output for now (placeholder)
    for (size_t i = 0; i < input.size(); ++i) {
        output.data()[i] = input.data()[i];
    }
}

void Engine::shutdown() {
    state_.clear();
    initialized_ = false;
}

std::string Engine::get_version() const {
    return "BSH_Engine v1.0.0";
}

std::string Engine::get_status() const {
    return initialized_ ? "READY" : "UNINITIALIZED";
}

void Engine::apply_attention(const Tensor& query, const Tensor& key,
                             const Tensor& value, Tensor& output) {
    // Placeholder attention implementation
    // In production, this would compute: softmax(Q*K^T/sqrt(d_k)) * V
}

} // namespace bsh