#ifndef HUMANUS_LLM_H
#define HUMANUS_LLM_H

#include "config.h"
#include "logger.h"
#include "schema.h"
#include "mcp/common/httplib.h"
#include <map>
#include <string>
#include <memory>
#include <vector>
#include <functional>
#include <stdexcept>
#include <future>

namespace humanus {

class LLM {
private:
    static std::map<std::string, std::shared_ptr<LLM>> _instances;

    std::unique_ptr<httplib::Client> client_;

    std::shared_ptr<LLMSettings> llm_config_;

    std::shared_ptr<ToolHelper> tool_helper_;
    
public:
    // Constructor
    LLM(const std::string& config_name, const std::shared_ptr<LLMSettings>& llm_config = nullptr, const std::shared_ptr<ToolHelper>& tool_helper = nullptr) : llm_config_(llm_config), tool_helper_(tool_helper) {
        if (!llm_config_) {
            if (Config::get_instance().llm().find(config_name) == Config::get_instance().llm().end()) {
                throw std::invalid_argument("LLM config not found: " + config_name);
            }
            llm_config_ = std::make_shared<LLMSettings>(Config::get_instance().llm().at(config_name));
        }
        if (!llm_config_->oai_tool_support && !tool_helper_) {
            if (Config::get_instance().tool_helper().find(config_name) == Config::get_instance().tool_helper().end()) {
                throw std::invalid_argument("Tool helper config not found: " + config_name);
            }
            tool_helper_ = std::make_shared<ToolHelper>(Config::get_instance().tool_helper().at(config_name));
        }
        client_ = std::make_unique<httplib::Client>(llm_config_->base_url);
        client_->set_default_headers({
            {"Authorization", "Bearer " + llm_config_->api_key}
        });
        client_->set_read_timeout(llm_config_->timeout);
    }
    
    // Get the singleton instance
    static std::shared_ptr<LLM> get_instance(const std::string& config_name = "default", const std::shared_ptr<LLMSettings>& llm_config = nullptr) {
        if (_instances.find(config_name) == _instances.end()) {
            _instances[config_name] = std::make_shared<LLM>(config_name, llm_config);
        }
        return _instances[config_name];
    }
    
    /**
     * @brief Format the message list to the format that LLM can accept
     * @param messages Message object message list
     * @return The formatted message list
     * @throws std::invalid_argument If the message format is invalid or missing necessary fields
     * @throws std::runtime_error If the message type is not supported
     */
    json format_messages(const std::vector<Message>& messages) {
        json formatted_messages = json::array();

        auto concat_content = [](const json& lhs, const json& rhs) -> json {
            if (lhs.is_string() && rhs.is_string()) {
                return lhs.get<std::string>() + "\n" + rhs.get<std::string>(); // Maybe other delimiter?
            }
            json res = json::array();
            if (lhs.is_string()) {
                res.push_back({
                    {"type", "text"},
                    {"text", lhs.get<std::string>()}
                });
            } else if (lhs.is_array()) {
                res.insert(res.end(), lhs.begin(), lhs.end());
            }
            if (rhs.is_string()) {
                res.push_back({
                    {"type", "text"},
                    {"text", rhs.get<std::string>()}
                });
            } else if (rhs.is_array()) {
                res.insert(res.end(), rhs.begin(), rhs.end());
            }
            return res;
        };

        for (const auto& message : messages) {
            if (message.content.empty() && message.tool_calls.empty()) {
                continue;
            }
            formatted_messages.push_back(message.to_json());
            if (!llm_config_->oai_tool_support) {
                if (formatted_messages.back()["role"] == "tool") {
                    std::string tool_results_str = formatted_messages.back().dump(2);
                    formatted_messages.back() = {
                        {"role", "user"},
                        {"content", tool_results_str}
                    };
                } else if (!formatted_messages.back()["tool_calls"].empty()) {
                    if (formatted_messages.back()["content"].is_null()) {
                        formatted_messages.back()["content"] = "";
                    }
                    std::string tool_calls_str = tool_helper_->dump(formatted_messages.back()["tool_calls"]);
                    formatted_messages.back().erase("tool_calls");
                    formatted_messages.back()["content"] = concat_content(formatted_messages.back()["content"], tool_calls_str);
                }
            }
        }

        for (const auto& message : formatted_messages) {
            if (message["role"] != "user" && message["role"] != "assistant" && message["role"] != "system" && message["role"] != "tool") {
                throw std::invalid_argument("Invalid role: " + message["role"].get<std::string>());
            }
        }
        
        size_t i = 0, j = -1;
        for (; i < formatted_messages.size(); i++) {
            if (i == 0 || formatted_messages[i]["role"] != formatted_messages[j]["role"]) {
                formatted_messages[++j] = formatted_messages[i];
            } else {
                formatted_messages[j]["content"] = concat_content(formatted_messages[j]["content"], formatted_messages[i]["content"]);
            }
        }

        formatted_messages.erase(formatted_messages.begin() + j + 1, formatted_messages.end());

        return formatted_messages;
    }
    
    /**
     * @brief Send a request to the LLM and get the reply
     * @param messages The conversation message list
     * @param system_prompt Optional system message
     * @param max_retries The maximum number of retries
     * @return The generated assistant content
     * @throws std::invalid_argument If the message is invalid or the reply is empty
     * @throws std::runtime_error If the API call fails
     */
    std::string ask(
        const std::vector<Message>& messages,
        const std::string& system_prompt = "",
        int max_retries = 3
    ) {
        json formatted_messages = json::array();

        if (!system_prompt.empty()) {
            formatted_messages.push_back({
                {"role", "system"},
                {"content", system_prompt}
            });
        }
        
        json _formatted_messages = format_messages(messages);
        formatted_messages.insert(formatted_messages.end(), _formatted_messages.begin(), _formatted_messages.end());

        json body = {
            {"model", llm_config_->model},
            {"messages", formatted_messages},
            {"temperature", llm_config_->temperature},
            {"max_tokens", llm_config_->max_tokens}
        };
        
        std::string body_str = body.dump();

        int retry = 0;

        while (retry <= max_retries) {
            // send request
            auto res = client_->Post(llm_config_->end_point, body_str, "application/json");

            if (!res) {
                logger->error("Failed to send request: " + httplib::to_string(res.error()));
            } else if (res->status == 200) {
                try {
                    json json_data = json::parse(res->body);
                    return json_data["choices"][0]["message"]["content"].get<std::string>();
                } catch (const std::exception& e) {
                    logger->error("Failed to parse response: " + std::string(e.what()));
                }
            } else {
                logger->error("Failed to send request: status=" + std::to_string(res->status) + ", body=" + res->body);
            }

            retry++;

            if (retry > max_retries) {
                break;
            }

            // wait for a while before retrying
            std::this_thread::sleep_for(std::chrono::milliseconds(500));

            logger->info("Retrying " + std::to_string(retry) + "/" + std::to_string(max_retries));
        }

        throw std::runtime_error("Failed to get response from LLM");
    }
    
    /**
     * @brief Send a request to the LLM with tool functions
     * @param messages The conversation message list
     * @param system_prompt Optional system message
     * @param next_step_prompt Optinonal prompt message for the next step
     * @param timeout The request timeout (seconds)
     * @param tools The tool list
     * @param tool_choice The tool choice strategy
     * @param max_retries The maximum number of retries
     * @return The generated assistant message (content, tool_calls)
     * @throws std::invalid_argument If the tool, tool choice or message is invalid
     * @throws std::runtime_error If the API call fails
     */
    json ask_tool(
        const std::vector<Message>& messages,
        const std::string& system_prompt = "",
        const std::string& next_step_prompt = "",
        const json& tools = {},
        const std::string& tool_choice = "auto",
        int max_retries = 3
    ) {
        if (tool_choice != "none" && tool_choice != "auto" && tool_choice != "required") {
            throw std::invalid_argument("Invalid tool_choice: " + tool_choice);
        }

        json formatted_messages = json::array();

        if (!system_prompt.empty()) {
            formatted_messages.push_back({
                {"role", "system"},
                {"content", system_prompt}
            });
        }
        
        json _formatted_messages = format_messages(messages);
        formatted_messages.insert(formatted_messages.end(), _formatted_messages.begin(), _formatted_messages.end());

        if (!next_step_prompt.empty()) {
            if (formatted_messages.empty() || formatted_messages.back()["role"] != "user") {
                formatted_messages.push_back({
                    {"role", "user"},
                    {"content", next_step_prompt}
                });
            } else {
                if (formatted_messages.back()["content"].is_string()) {
                    formatted_messages.back()["content"] = formatted_messages.back()["content"].get<std::string>() + "\n\n" + next_step_prompt;
                } else if (formatted_messages.back()["content"].is_array()) {
                    formatted_messages.back()["content"].push_back({
                        {"type", "text"},
                        {"text", next_step_prompt}
                    });
                }
            }
        }

        if (!tools.empty()) {
            for (const json& tool : tools) {
                if (!tool.contains("type")) {
                    throw std::invalid_argument("Tool must contain 'type' field but got: " + tool.dump(2));
                }
            }
            if (tool_choice == "required" && tools.empty()) {
                throw std::invalid_argument("No tool available for required tool choice");
            }
            if (!tools.is_array()) {
                throw std::invalid_argument("Tools must be an array");
            }
        }
        
        json body = {
            {"model", llm_config_->model},
            {"messages", formatted_messages},
            {"temperature", llm_config_->temperature},
            {"max_tokens", llm_config_->max_tokens},
            {"tool_choice", tool_choice}
        };

        if (llm_config_->oai_tool_support) {
            body["tools"] = tools;
        } else {
            if (body["messages"].empty() || body["messages"].back()["role"] != "user") {
                body["messages"].push_back({
                    {"role", "user"},
                    {"content", tool_helper_->hint(tools.dump(2))}
                });
            } else if (body["messages"].back()["content"].is_string()) {
                body["messages"].back()["content"] = body["messages"].back()["content"].get<std::string>() + "\n\n" + tool_helper_->hint(tools.dump(2));
            } else if (body["messages"].back()["content"].is_array()) {
                body["messages"].back()["content"].push_back({
                    {"type", "text"},
                    {"text", tool_helper_->hint(tools.dump(2))}
                });
            }
        }
        
        std::string body_str = body.dump();

        int retry = 0;

        while (retry <= max_retries) {
            // send request
            auto res = client_->Post(llm_config_->end_point, body_str, "application/json");

            if (!res) {
                logger->error("Failed to send request: " + httplib::to_string(res.error()));
            } else if (res->status == 200) {
                try {
                    json json_data = json::parse(res->body);
                    json message = json_data["choices"][0]["message"];
                    if (!llm_config_->oai_tool_support && message["content"].is_string()) {
                        message = tool_helper_->parse(message["content"].get<std::string>());
                    }
                    return message;
                } catch (const std::exception& e) {
                    logger->error("Failed to parse response: " + std::string(e.what()));
                }
            } else {
                logger->error("Failed to send request: status=" + std::to_string(res->status) + ", body=" + res->body);
            }

            retry++;

            if (retry > max_retries) {
                break;
            }

            // wait for a while before retrying
            std::this_thread::sleep_for(std::chrono::milliseconds(500));

            logger->info("Retrying " + std::to_string(retry) + "/" + std::to_string(max_retries));
        }

        throw std::runtime_error("Failed to get response from LLM");
    }
};

} // namespace humanus

#endif // HUMANUS_LLM_H