import { describe, expect, it } from "vitest";
import {
  applyOpenAiGeneration,
  applyRejectedGenerationField,
  classifyChatModel,
  classifyGlmThinking,
  fetchWithGenerationCompat,
  forceReasoningEffortNoneWhenTools,
  isReasoningMandatoryError,
  isToolsReasoningEffortConflictError,
  modelRejectsDisabledReasoning,
  parseRejectedGenerationField,
  sanitizeReasoningEffort,
  sanitizeVerbosity,
} from "../src/llm/generation-compat.js";
import { buildRequestBody, extractMessageParts, openRouterSessionId } from "../src/llm/client.js";
import type { LlmConfig } from "../src/config/env.js";

const stGeneration = {
  temperature: 1,
  topP: 0.95,
  topK: 40,
  minP: 0.05,
  frequencyPenalty: 0,
  presencePenalty: 0,
  repetitionPenalty: 1.05,
  maxOutputTokens: 60000,
  seed: -1,
  reasoningEffort: "auto",
  verbosity: "auto",
};

describe("sanitizeReasoningEffort", () => {
  it("omits SillyTavern auto and empty values", () => {
    expect(sanitizeReasoningEffort("auto")).toBeUndefined();
    expect(sanitizeReasoningEffort("AUTO")).toBeUndefined();
    expect(sanitizeReasoningEffort("")).toBeUndefined();
    expect(sanitizeReasoningEffort("  ")).toBeUndefined();
    expect(sanitizeReasoningEffort(undefined)).toBeUndefined();
  });

  it("keeps values the provider enum accepts", () => {
    expect(sanitizeReasoningEffort("none")).toBe("none");
    expect(sanitizeReasoningEffort("minimal")).toBe("minimal");
    expect(sanitizeReasoningEffort("low")).toBe("low");
    expect(sanitizeReasoningEffort("medium")).toBe("medium");
    expect(sanitizeReasoningEffort("high")).toBe("high");
    expect(sanitizeReasoningEffort("xhigh")).toBe("xhigh");
    expect(sanitizeReasoningEffort("max")).toBe("max");
  });

  it("maps SillyTavern min to minimal and ignores unknown values", () => {
    expect(sanitizeReasoningEffort("min")).toBe("minimal");
    expect(sanitizeReasoningEffort("MIN")).toBe("minimal");
    expect(sanitizeReasoningEffort("unknown")).toBeUndefined();
  });
});

describe("sanitizeVerbosity", () => {
  it("omits auto and unknown values", () => {
    expect(sanitizeVerbosity("auto")).toBeUndefined();
    expect(sanitizeVerbosity("loud")).toBeUndefined();
    expect(sanitizeVerbosity("medium")).toBe("medium");
  });
});

describe("classifyChatModel", () => {
  it("treats o-series, gpt-5, kimi-k2.5 and deepseek-reasoner as no-sampling", () => {
    expect(classifyChatModel("o3-mini").omitSampling).toBe(true);
    expect(classifyChatModel("openai/o4-mini").omitSampling).toBe(true);
    expect(classifyChatModel("gpt-5").omitSampling).toBe(true);
    expect(classifyChatModel("deepseek-reasoner").omitSampling).toBe(true);
    expect(classifyChatModel("kimi-k2.5").omitSampling).toBe(true);
  });

  it("keeps sampling for ordinary chat models", () => {
    expect(classifyChatModel("gpt-4o").omitSampling).toBe(false);
    expect(classifyChatModel("deepseek-v4-pro").omitSampling).toBe(false);
    expect(classifyChatModel("gpt-5-chat-latest").omitSampling).toBe(false);
  });
});

describe("classifyGlmThinking", () => {
  it("classifies glm generations", () => {
    expect(classifyGlmThinking("glm-5.3")).toBe("effort_lhm_always_on");
    expect(classifyGlmThinking("ZHIPU/GLM-5.3-Flash")).toBe(
      "effort_lhm_always_on",
    );
    expect(classifyGlmThinking("glm-5.2")).toBe("effort_full");
    expect(classifyGlmThinking("glm-5.1")).toBe("thinking_only");
    expect(classifyGlmThinking("glm-4.7")).toBe("thinking_only");
    expect(classifyGlmThinking("gpt-5")).toBe("none");
  });
});

describe("applyOpenAiGeneration", () => {
  it("does not send ST extras or auto sentinels on a chat model", () => {
    const body: Record<string, unknown> = { model: "deepseek-v4-pro" };
    applyOpenAiGeneration(body, stGeneration, "deepseek-v4-pro");
    expect(body.temperature).toBe(1);
    expect(body.top_p).toBe(0.95);
    expect(body.max_tokens).toBe(60000);
    expect(body.top_k).toBeUndefined();
    expect(body.min_p).toBeUndefined();
    expect(body.repetition_penalty).toBeUndefined();
    expect(body.reasoning_effort).toBeUndefined();
    expect(body.verbosity).toBeUndefined();
    expect(body.seed).toBeUndefined();
  });

  it("drops sampling params for reasoning models and uses max_completion_tokens", () => {
    const body: Record<string, unknown> = { model: "o3-mini" };
    applyOpenAiGeneration(body, stGeneration, "o3-mini");
    expect(body.temperature).toBeUndefined();
    expect(body.top_p).toBeUndefined();
    expect(body.frequency_penalty).toBeUndefined();
    expect(body.presence_penalty).toBeUndefined();
    expect(body.max_tokens).toBeUndefined();
    expect(body.max_completion_tokens).toBe(60000);
  });

  it("maps glm-5.3 none/medium to low/high and always enables thinking", () => {
    const noneBody: Record<string, unknown> = { model: "glm-5.3" };
    applyOpenAiGeneration(noneBody, { reasoningEffort: "none" }, "glm-5.3");
    expect(noneBody.thinking).toEqual({ type: "enabled" });
    expect(noneBody.reasoning_effort).toBe("low");

    const midBody: Record<string, unknown> = { model: "glm-5.3" };
    applyOpenAiGeneration(midBody, { reasoningEffort: "medium" }, "glm-5.3");
    expect(midBody.reasoning_effort).toBe("high");
  });

  it("uses thinking only for older glm and omits reasoning_effort", () => {
    const body: Record<string, unknown> = { model: "glm-5.1" };
    applyOpenAiGeneration(body, { reasoningEffort: "high" }, "glm-5.1");
    expect(body.thinking).toEqual({ type: "enabled" });
    expect(body.reasoning_effort).toBeUndefined();
  });
});

describe("forceReasoningEffortNoneWhenTools", () => {
  it("forces none when tools are present on non-glm", () => {
    const body: Record<string, unknown> = {
      model: "gpt-5.6-luna",
      tools: [{ type: "function", function: { name: "x" } }],
      reasoning_effort: "high",
    };
    forceReasoningEffortNoneWhenTools(body);
    expect(body.reasoning_effort).toBe("none");
  });

  it("sets none even when effort was omitted on non-glm", () => {
    const body: Record<string, unknown> = {
      model: "gpt-4o",
      tools: [{ type: "function", function: { name: "x" } }],
    };
    forceReasoningEffortNoneWhenTools(body);
    expect(body.reasoning_effort).toBe("none");
  });

  it("keeps a legal glm-5.3 effort instead of none", () => {
    const body: Record<string, unknown> = {
      model: "glm-5.3",
      tools: [{ type: "function", function: { name: "x" } }],
      reasoning_effort: "high",
    };
    forceReasoningEffortNoneWhenTools(body);
    expect(body.reasoning_effort).toBe("high");
    expect(body.thinking).toEqual({ type: "enabled" });
  });

  it("disables thinking for older glm tools calls", () => {
    const body: Record<string, unknown> = {
      model: "glm-5.1",
      tools: [{ type: "function", function: { name: "x" } }],
      reasoning_effort: "high",
    };
    forceReasoningEffortNoneWhenTools(body);
    expect(body.reasoning_effort).toBeUndefined();
    expect(body.thinking).toEqual({ type: "disabled" });
  });

  it("keeps gemini 3.8 on low when tools would otherwise disable reasoning", () => {
    const body: Record<string, unknown> = {
      model: "google/gemini-3.8-flash",
      tools: [{ type: "function", function: { name: "x" } }],
    };
    forceReasoningEffortNoneWhenTools(body, "google/gemini-3.8-flash");
    expect(body.reasoning_effort).toBe("low");
    expect(body.reasoning).toEqual({ effort: "low" });
  });

  it("maps gemini 3.8 max down to high and keeps medium", () => {
    const maxBody: Record<string, unknown> = {
      model: "google/gemini-3.8-flash",
      tools: [{ type: "function", function: { name: "x" } }],
      reasoning_effort: "max",
    };
    forceReasoningEffortNoneWhenTools(maxBody, "google/gemini-3.8-flash");
    expect(maxBody.reasoning_effort).toBe("high");
    expect(maxBody.reasoning).toEqual({ effort: "high" });

    const midBody: Record<string, unknown> = { model: "google/gemini-3.8-flash" };
    applyOpenAiGeneration(midBody, { reasoningEffort: "medium" }, "google/gemini-3.8-flash");
    expect(midBody.reasoning_effort).toBe("medium");
    expect(midBody.reasoning).toEqual({ effort: "medium" });
  });

  it("leaves body alone without tools", () => {
    const body: Record<string, unknown> = { reasoning_effort: "high" };
    forceReasoningEffortNoneWhenTools(body);
    expect(body.reasoning_effort).toBe("high");
  });
});

describe("isReasoningMandatoryError", () => {
  it("detects the OpenRouter mandatory-reasoning payload", () => {
    expect(modelRejectsDisabledReasoning("google/gemini-3.8-flash")).toBe(true);
    expect(modelRejectsDisabledReasoning("gemini-2.5-flash")).toBe(false);
    expect(
      isReasoningMandatoryError(
        JSON.stringify({
          error: {
            message:
              "Reasoning is mandatory for this endpoint and cannot be disabled.",
            code: 400,
            metadata: { provider_name: null },
          },
        }),
        400,
      ),
    ).toBe(true);
  });
});

describe("isToolsReasoningEffortConflictError", () => {
  it("detects gpt-5.6-luna style conflict", () => {
    const text = JSON.stringify({
      error: {
        message:
          "Provider API error: Function tools with reasoning_effort are not supported for gpt-5.6-luna in /v1/chat/completions. To use function tools, use /v1/responses or set reasoning_effort to 'none'.",
        type: "invalid_request_error",
      },
    });
    expect(isToolsReasoningEffortConflictError(text, 400)).toBe(true);
  });

  it("ignores unrelated 400s", () => {
    expect(
      isToolsReasoningEffortConflictError(
        JSON.stringify({
          error: {
            message: "Unsupported parameter: temperature",
            param: "temperature",
          },
        }),
        400,
      ),
    ).toBe(false);
  });
});

describe("parseRejectedGenerationField", () => {
  it("reads OpenAI unsupported parameter errors", () => {
    expect(
      parseRejectedGenerationField(
        JSON.stringify({
          error: {
            message:
              "Unsupported parameter: 'temperature' is not supported with this model.",
            param: "temperature",
          },
        }),
      ),
    ).toBe("temperature");
  });

  it("reads strict JSON deserializer unknown variant errors", () => {
    expect(
      parseRejectedGenerationField(
        JSON.stringify({
          error: {
            message:
              "Failed to deserialize the JSON body into the target type: reasoning_effort: unknown variant `auto`, expected one of `none`, `minimal`",
          },
        }),
      ),
    ).toBe("reasoning_effort");
  });

  it("drops top_p when temperature and top_p are mutually exclusive", () => {
    expect(
      parseRejectedGenerationField(
        "temperature and top_p cannot both be specified for this model",
      ),
    ).toBe("top_p");
  });
});

describe("applyRejectedGenerationField", () => {
  it("renames max_completion_tokens to max_tokens once", () => {
    const body: Record<string, unknown> = { max_completion_tokens: 100 };
    const tried = new Set<string>();
    expect(
      applyRejectedGenerationField(body, "max_completion_tokens", tried),
    ).toBe(true);
    expect(body.max_tokens).toBe(100);
    expect(body.max_completion_tokens).toBeUndefined();
    expect(applyRejectedGenerationField(body, "max_tokens", tried)).toBe(true);
    expect(body.max_completion_tokens).toBeUndefined();
    expect(body.max_tokens).toBeUndefined();
  });

  it("sets reasoning_effort to none when tools are present on non-glm", () => {
    const body: Record<string, unknown> = {
      model: "gpt-5.6-luna",
      tools: [{ type: "function" }],
      reasoning_effort: "high",
    };
    const tried = new Set<string>();
    expect(
      applyRejectedGenerationField(body, "reasoning_effort", tried),
    ).toBe(true);
    expect(body.reasoning_effort).toBe("none");
  });
});

describe("fetchWithGenerationCompat", () => {
  it("retries a 400 after stripping the rejected field", async () => {
    const sent: Array<Record<string, unknown>> = [];
    const response = await fetchWithGenerationCompat(async (body) => {
      sent.push({ ...body });
      if ("temperature" in body) {
        return new Response(
          JSON.stringify({
            error: {
              message: "Unsupported parameter: 'temperature'",
              param: "temperature",
            },
          }),
          { status: 400 },
        );
      }
      return new Response(JSON.stringify({ ok: true }), { status: 200 });
    }, { model: "o3", temperature: 1, messages: [] });

    expect(response.ok).toBe(true);
    expect(sent).toHaveLength(2);
    expect(sent[0].temperature).toBe(1);
    expect(sent[1].temperature).toBeUndefined();
  });

  it("retries tools+reasoning conflict by setting none", async () => {
    const sent: Array<Record<string, unknown>> = [];
    const response = await fetchWithGenerationCompat(async (body) => {
      sent.push({ ...body });
      if (body.reasoning_effort !== "none") {
        return new Response(
          JSON.stringify({
            error: {
              message:
                "Function tools with reasoning_effort are not supported for gpt-5.6-luna. Set reasoning_effort to 'none'.",
            },
          }),
          { status: 400 },
        );
      }
      return new Response(JSON.stringify({ ok: true }), { status: 200 });
    }, {
      model: "gpt-5.6-luna",
      tools: [{ type: "function", function: { name: "run" } }],
      messages: [],
    });

    expect(response.ok).toBe(true);
    expect(sent).toHaveLength(2);
    expect(sent[0].reasoning_effort).toBeUndefined();
    expect(sent[1].reasoning_effort).toBe("none");
  });

  it("retries a mandatory-reasoning 400 by lifting none to low", async () => {
    const sent: Array<Record<string, unknown>> = [];
    const response = await fetchWithGenerationCompat(async (body) => {
      sent.push({ ...body });
      if (body.reasoning_effort === "none") {
        return new Response(
          JSON.stringify({
            error: {
              message:
                "Reasoning is mandatory for this endpoint and cannot be disabled.",
              code: 400,
              metadata: { provider_name: null },
            },
          }),
          { status: 400 },
        );
      }
      return new Response(JSON.stringify({ ok: true }), { status: 200 });
    }, {
      model: "google/gemini-3.8-flash",
      tools: [{ type: "function", function: { name: "run" } }],
      reasoning_effort: "none",
      messages: [],
    });

    expect(response.ok).toBe(true);
    expect(sent).toHaveLength(2);
    expect(sent[1].reasoning_effort).toBe("low");
    expect(sent[1].reasoning).toEqual({ effort: "low" });
  });
});

describe("extractMessageParts", () => {
  it("keeps reply_user when arguments are an object and id is missing", () => {
    const parts = extractMessageParts({
      content: [{ type: "text", text: "同一次请求里的说明" }],
      tool_calls: [
        {
          type: "function",
          function: { name: "reply_user", arguments: { text: "形成了气氛" } },
        },
      ],
    });
    expect(parts.toolCalls).toEqual([
      { id: "call-0", name: "reply_user", arguments: JSON.stringify({ text: "形成了气氛" }) },
    ]);
    expect(parts.content).toBe("同一次请求里的说明");
  });
});

describe("buildRequestBody", () => {
  const messages = [{ role: "user" as const, content: "hi" }];

  it("does not send reasoning_effort when the preset says auto", () => {
    const config: LlmConfig = {
      baseUrl: "https://example.test/v1",
      apiKey: "k",
      model: "deepseek-v4-pro",
    };
    const body = buildRequestBody(config, messages, {
      generation: { reasoningEffort: "auto", temperature: 0.5 },
    });
    expect(body.reasoning_effort).toBeUndefined();
    expect(body.temperature).toBe(0.5);
  });

  it("sends a supported effort value", () => {
    const config: LlmConfig = {
      baseUrl: "https://example.test/v1",
      apiKey: "k",
      model: "gpt-5",
    };
    const body = buildRequestBody(config, messages, {
      generation: { reasoningEffort: "High" },
    });
    expect(body.reasoning_effort).toBe("high");
    expect(body.temperature).toBeUndefined();
  });

  it("uses profile default reasoningEffort when generation omits it", () => {
    const config: LlmConfig = {
      baseUrl: "https://example.test/v1",
      apiKey: "k",
      model: "glm-5.3",
      reasoningEffort: "high",
    };
    const body = buildRequestBody(config, messages, {
      generation: { temperature: 1 },
    });
    expect(body.reasoning_effort).toBe("high");
    expect(body.thinking).toEqual({ type: "enabled" });
  });

  it("lets generation reasoningEffort override the profile default", () => {
    const config: LlmConfig = {
      baseUrl: "https://example.test/v1",
      apiKey: "k",
      model: "glm-5.3",
      reasoningEffort: "max",
    };
    const body = buildRequestBody(config, messages, {
      generation: { reasoningEffort: "low" },
    });
    expect(body.reasoning_effort).toBe("low");
  });

  it("maps gemini 3.8 none and minimal to low", () => {
    const config: LlmConfig = {
      baseUrl: "https://openrouter.ai/api/v1",
      apiKey: "k",
      model: "google/gemini-3.8-flash",
      reasoningEffort: "none",
    };
    const body = buildRequestBody(config, messages, {});
    expect(body.reasoning_effort).toBe("low");
    expect(body.reasoning).toEqual({ effort: "low" });

    const minimal = buildRequestBody(
      { ...config, reasoningEffort: "minimal" },
      messages,
      {},
    );
    expect(minimal.reasoning_effort).toBe("low");
  });

  it("uses low for gemini 3.8 tool calls when effort is omitted", () => {
    const config: LlmConfig = {
      baseUrl: "https://openrouter.ai/api/v1",
      apiKey: "k",
      model: "google/gemini-3.8-flash",
    };
    const body = buildRequestBody(config, messages, {
      tools: [
        {
          type: "function",
          function: { name: "run_worker", parameters: { type: "object" } },
        },
      ],
    });
    expect(body.reasoning_effort).toBe("low");
    expect(body.reasoning).toEqual({ effort: "low" });
  });

  it("forces reasoning_effort none when tools are attached on non-glm", () => {
    const config: LlmConfig = {
      baseUrl: "https://example.test/v1",
      apiKey: "k",
      model: "gpt-5.6-luna",
      reasoningEffort: "high",
    };
    const body = buildRequestBody(config, messages, {
      tools: [
        {
          type: "function",
          function: { name: "run_worker", parameters: { type: "object" } },
        },
      ],
    });
    expect(body.reasoning_effort).toBe("none");
    expect(body.tools).toHaveLength(1);
  });

  it("keeps glm-5.3 effort when tools are attached", () => {
    const config: LlmConfig = {
      baseUrl: "https://example.test/v1",
      apiKey: "k",
      model: "glm-5.3",
      reasoningEffort: "max",
    };
    const body = buildRequestBody(config, messages, {
      tools: [
        {
          type: "function",
          function: { name: "run_worker", parameters: { type: "object" } },
        },
      ],
    });
    expect(body.reasoning_effort).toBe("max");
    expect(body.thinking).toEqual({ type: "enabled" });
  });

  it("adds the word json when json_object prompts omit it", () => {
    const config: LlmConfig = {
      baseUrl: "https://example.test/v1",
      apiKey: "k",
      model: "gpt-4o",
    };
    const body = buildRequestBody(
      config,
      [{ role: "user", content: "只输出对象，列出候选。" }],
      { responseFormat: "json_object" },
    );
    expect(body.response_format).toEqual({ type: "json_object" });
    const sent = body.messages as Array<{ role: string; content: string }>;
    expect(sent[0]).toEqual({
      role: "system",
      content: "请用 JSON 对象回复。",
    });
    expect(sent.some((message) => /json/i.test(message.content))).toBe(true);
  });

  it("appends the json hint to an existing system message", () => {
    const config: LlmConfig = {
      baseUrl: "https://example.test/v1",
      apiKey: "k",
      model: "gpt-4o",
    };
    const body = buildRequestBody(
      config,
      [
        { role: "system", content: "你正在提取文风包。" },
        { role: "user", content: "写得冷一点。" },
      ],
      { responseFormat: "json_object" },
    );
    const sent = body.messages as Array<{ role: string; content: string }>;
    expect(sent[0]?.content).toContain("你正在提取文风包。");
    expect(sent[0]?.content).toContain("请用 JSON 对象回复。");
    expect(sent[1]?.content).toBe("写得冷一点。");
  });

  it("leaves a json_object prompt unchanged when it already says json", () => {
    const config: LlmConfig = {
      baseUrl: "https://example.test/v1",
      apiKey: "k",
      model: "gpt-4o",
    };
    const messages = [
      { role: "system" as const, content: "输出一个 JSON 对象。" },
      { role: "user" as const, content: "继续。" },
    ];
    const body = buildRequestBody(config, messages, {
      responseFormat: "json_object",
    });
    expect(body.messages).toBe(messages);
  });

  it("writes session_id only for OpenRouter", () => {
    const openrouter: LlmConfig = {
      baseUrl: "https://openrouter.ai/api/v1",
      apiKey: "k",
      model: "google/gemini-3.8-flash",
    };
    const direct: LlmConfig = {
      baseUrl: "https://api.deepseek.com/v1",
      apiKey: "k",
      model: "deepseek-v4-pro",
    };
    const id = "9b76dcb6-0703-4b0d-ba75-faa985b532b4";
    expect(buildRequestBody(openrouter, messages, { sessionId: id }).session_id).toBe(id);
    expect(buildRequestBody(direct, messages, { sessionId: id }).session_id).toBeUndefined();
    expect(buildRequestBody(openrouter, messages, {}).session_id).toBeUndefined();
    expect(openRouterSessionId(openrouter.baseUrl, `  ${"a".repeat(300)}  `)).toHaveLength(256);
  });

  it("does not forward top_k from an imported ST preset", () => {
    const config: LlmConfig = {
      baseUrl: "https://example.test/v1",
      apiKey: "k",
      model: "deepseek-v4-pro",
    };
    const body = buildRequestBody(config, messages, {
      generation: stGeneration,
    });
    expect(body.top_k).toBeUndefined();
    expect(body.min_p).toBeUndefined();
  });
});