model_executor.h

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#pragma once
 
#include <knp/core/impexp.h>
#include <knp/framework/backend_loader.h>
#include <knp/framework/io/input_converter.h>
#include <knp/framework/model.h>
#include <knp/framework/model_loader.h>
#include <knp/framework/monitoring/observer.h>
 
#include <filesystem>
#include <functional>
#include <memory>
#include <unordered_map>
#include <utility>
#include <vector>
 
 
namespace knp::framework
{
class KNP_DECLSPEC ModelExecutor
{
public:
    ModelExecutor(
        knp::framework::Model &model, std::shared_ptr<core::Backend> backend, ModelLoader::InputChannelMap i_map)
        : loader_(backend, i_map)
    {
        loader_.load(model);
    }
 
public:
    void start();
 
    void start(core::Backend::RunPredicate run_predicate);
 
    void stop();
 
public:
    template <class Message>
    void add_observer(monitoring::MessageProcessor<Message> &&message_processor, const std::vector<core::UID> &senders)
    {
        observers_.emplace_back(monitoring::MessageObserver<Message>(
            get_backend()->get_message_bus().create_endpoint(), std::move(message_processor), core::UID{true}));
 
        std::visit([&senders](auto &entity) { entity.subscribe(senders); }, observers_.back());
    }
 
    void start_learning() { get_backend()->start_learning(); }
 
    void stop_learning() { get_backend()->stop_learning(); }
 
    std::shared_ptr<core::Backend> get_backend() { return loader_.get_backend(); }
 
    auto &get_loader() { return loader_; }
 
private:
    knp::core::BaseData base_;
    ModelLoader loader_;
 
    std::vector<monitoring::AnyObserverVariant> observers_;
};
}  // namespace knp::framework