import { resolveModel } from "../settings";
import type { AppSettings, PolishResult, PolishTask } from "../types";

const RESULT_SCHEMA = {
  type: "object",
  additionalProperties: false,
  required: ["zh", "en", "notes"],
  properties: {
    zh: { type: "string" },
    en: { type: "string" },
    notes: { type: "string" },
  },
};

export async function polishTask(task: PolishTask, settings: AppSettings): Promise<PolishResult> {
  return polishBrowser(task, settings);
}

export async function polishBrowser(task: PolishTask, settings: AppSettings): Promise<PolishResult> {
  if (!settings.apiKey.trim()) {
    throw new Error("请填写浏览器 API Key，或在个人设置里选择已保存的连接。");
  }
  const apiMode = resolveApiMode(settings.baseURL, settings.apiMode);
  const endpoint = resolveEndpoint(settings.baseURL, apiMode);
  const response = await fetch(endpoint, {
    method: "POST",
    headers: buildHeaders(settings, endpoint),
    body: JSON.stringify(buildModelBody(task.raw, settings, apiMode, endpoint)),
  });
  const payload = await response.json().catch(() => null);
  if (!response.ok) {
    throw new Error(extractError(payload) || `HTTP ${response.status}`);
  }
  const text = apiMode === "chat"
    ? String(payload?.choices?.[0]?.message?.content || "")
    : extractResponsesText(payload);
  return normalizeResult(parseJsonText(text));
}

export function createSystemPrompt(): string {
  return [
    "你是一位专业的任务描述润色专家。",
    "将原始任务改写成真实、自然、目标导向的用户请求。",
    "不要泄露具体操作路径、API 名称、按钮位置或实现策略。",
    "保留用户自然需要的业务上下文、人名、文件名、对象名和期望结果。",
    "输出 JSON：{\"zh\":\"简体中文润色结果\",\"en\":\"自然英文请求\",\"notes\":\"中文修改说明\"}。",
  ].join("\n");
}

function buildHeaders(settings: AppSettings, endpoint: string): HeadersInit {
  const headers: Record<string, string> = { "Content-Type": "application/json" };
  if (/azure\.com/i.test(endpoint)) headers["api-key"] = settings.apiKey;
  else headers.Authorization = `Bearer ${settings.apiKey}`;
  return headers;
}

function buildModelBody(raw: string, settings: AppSettings, apiMode: "chat" | "responses", endpoint: string) {
  const model = resolveModel(settings);
  if (!model) throw new Error("请在设置里选择模型。");
  if (apiMode === "chat") {
    const body: Record<string, unknown> = {
      model,
      messages: [
        { role: "system", content: createSystemPrompt() },
        { role: "user", content: raw },
      ],
      temperature: clamp(settings.temperature, 0, 2),
      top_p: clamp(settings.topP, 0, 1),
      max_tokens: clamp(settings.maxTokens, 1, 131072),
      response_format: { type: "json_object" },
      stream: false,
    };
    if (/bigmodel\.cn|zhipuai/i.test(endpoint)) {
      body.thinking = { type: settings.enableThinking ? "enabled" : "disabled" };
    } else {
      body.chat_template_kwargs = {
        enable_thinking: settings.enableThinking,
        clear_thinking: settings.clearThinking,
      };
    }
    return body;
  }
  return {
    model,
    store: false,
    temperature: clamp(settings.temperature, 0, 2),
    input: [
      { role: "system", content: [{ type: "input_text", text: createSystemPrompt() }] },
      { role: "user", content: [{ type: "input_text", text: raw }] },
    ],
    text: {
      format: {
        type: "json_schema",
        name: "task_polisher_result",
        strict: true,
        schema: RESULT_SCHEMA,
      },
    },
  };
}

function resolveApiMode(baseURL: string, fallback: "chat" | "responses"): "chat" | "responses" {
  if (/\/chat\/completions(\/?|$)/i.test(baseURL)) return "chat";
  if (/\/responses(\/?|$)/i.test(baseURL)) return "responses";
  return fallback === "responses" ? "responses" : "chat";
}

function resolveEndpoint(baseURL: string, apiMode: "chat" | "responses"): string {
  const suffix = apiMode === "chat" ? "/chat/completions" : "/responses";
  const value = String(baseURL || "").trim();
  if (!value) return "https://api.openai.com/v1" + suffix;
  let trimmed = value.replace(/\/+$/g, "");
  trimmed = trimmed.replace(/\/(responses|chat\/completions)$/i, "");
  if (/\/v\d+$/i.test(trimmed) || /\/openai\/v\d+$/i.test(trimmed)) {
    return trimmed + suffix;
  }
  return trimmed + "/v1" + suffix;
}

function extractResponsesText(payload: unknown): string {
  const value = payload as {
    output_text?: string;
    output?: Array<{ content?: Array<{ text?: string; type?: string }> }>;
  };
  if (value?.output_text) return value.output_text;
  return (value?.output || [])
    .flatMap((item) => item.content || [])
    .map((content) => content.text || "")
    .join("");
}

function normalizeResult(value: unknown): PolishResult {
  const raw = value as Partial<PolishResult> & { notes?: string | string[] };
  return {
    zh: String(raw?.zh || "").trim(),
    en: String(raw?.en || "").trim(),
    notes: Array.isArray(raw?.notes) ? raw.notes.join("\n") : String(raw?.notes || "").trim(),
  };
}

function parseJsonText(text: string): unknown {
  const cleaned = String(text || "")
    .trim()
    .replace(/^```json\s*/i, "")
    .replace(/^```\s*/i, "")
    .replace(/```\s*$/i, "")
    .trim();
  try {
    return JSON.parse(cleaned);
  } catch {
    const start = cleaned.indexOf("{");
    const end = cleaned.lastIndexOf("}");
    if (start >= 0 && end > start) return JSON.parse(cleaned.slice(start, end + 1));
    throw new Error("模型返回非 JSON，无法解析润色结果。");
  }
}

function extractError(payload: unknown): string {
  const value = payload as { error?: { message?: string } | string; message?: string };
  if (typeof value?.error === "string") return value.error;
  return value?.error?.message || value?.message || "";
}

function clamp(value: number, min: number, max: number): number {
  const parsed = Number(value);
  if (!Number.isFinite(parsed)) return min;
  return Math.min(max, Math.max(min, parsed));
}