feat(docs): add documentation site and demo features

- Introduced a new documentation site for Cursor BYOK using Next.js and Fumadocs. - Added a product demo page with a corresponding Vite configuration. - Implemented a demo API to simulate LLM calls and responses. - Enhanced the Makefile to include new build and development commands for the documentation. - Updated package.json scripts for building and running the documentation site. - Created various components and layouts for the documentation structure, including blog and user documentation sections. - Added styling for the new components and layouts to ensure a cohesive design. - Included a README and other necessary files for local development and deployment.
2026-10-08 15:43:10 +08:00 · 2026-08-27 21:45:28 +08:00
parent ee915ee760
commit c5d578c5b1
70 changed files with 13299 additions and 567 deletions
@@ -0,0 +1,287 @@
+import type {
+  CallDetail,
+  CursorHarnessStatus,
+  LlmCall,
+  Model,
+  Overview,
+  OverviewTokenUsageBucket,
+  ProxySettings,
+  StatisticsStorage,
+  TabSettings,
+} from "../api";
+
+const API_ROOT = "/__byok-api__/api";
+const FIXED_NOW = Date.UTC(2026, 7, 27, 8, 0, 0);
+
+const models: Model[] = [
+  createModel({ hash: "mock-claude-sonnet", order: 1, name: "Claude Sonnet 4", type: "anthropic", url: "https://api.anthropic.com", modelId: "claude-sonnet-4-20250514" }),
+  createModel({ hash: "mock-claude-opus", order: 2, name: "Claude Opus 4", type: "anthropic", url: "https://api.anthropic.com", modelId: "claude-opus-4-20250514" }),
+  createModel({ hash: "mock-gpt", order: 3, name: "GPT-5.2", type: "openai", url: "https://api.openai.com", modelId: "gpt-5.2" }),
+  createModel({ hash: "mock-o3", order: 4, name: "o3", type: "openai", url: "https://api.openai.com", modelId: "o3" }),
+  createModel({ hash: "mock-deepseek-v3", order: 5, name: "DeepSeek V3.2", type: "openai", url: "https://api.deepseek.com", modelId: "deepseek-chat", endpoint: "/v1/chat/completions" }),
+  createModel({ hash: "mock-deepseek-r1", order: 6, name: "DeepSeek R1", type: "openai", url: "https://api.deepseek.com", modelId: "deepseek-reasoner", endpoint: "/v1/chat/completions" }),
+  createModel({ hash: "mock-gemini-pro", order: 7, name: "Gemini 2.5 Pro", type: "openai", url: "https://generativelanguage.googleapis.com", modelId: "gemini-2.5-pro", endpoint: "/v1beta/openai/chat/completions" }),
+  createModel({ hash: "mock-gemini-flash", order: 8, name: "Gemini 2.5 Flash", type: "openai", url: "https://generativelanguage.googleapis.com", modelId: "gemini-2.5-flash", endpoint: "/v1beta/openai/chat/completions" }),
+  createModel({ hash: "mock-qwen-max", order: 9, name: "Qwen3 Max", type: "openai", url: "https://dashscope.aliyuncs.com/compatible-mode", modelId: "qwen3-max", endpoint: "/v1/chat/completions" }),
+  createModel({ hash: "mock-qwen-plus", order: 10, name: "Qwen Plus", type: "openai", url: "https://dashscope.aliyuncs.com/compatible-mode", modelId: "qwen-plus", endpoint: "/v1/chat/completions" }),
+  createModel({ hash: "mock-kimi-k2", order: 11, name: "Kimi K2", type: "openai", url: "https://api.moonshot.cn", modelId: "kimi-k2-0711-preview", endpoint: "/v1/chat/completions" }),
+  createModel({ hash: "mock-kimi-128k", order: 12, name: "Moonshot V1 128K", type: "openai", url: "https://api.moonshot.cn", modelId: "moonshot-v1-128k", endpoint: "/v1/chat/completions" }),
+  createModel({ hash: "mock-glm-45", order: 13, name: "GLM-4.5", type: "openai", url: "https://open.bigmodel.cn", modelId: "glm-4.5", endpoint: "/api/paas/v4/chat/completions" }),
+  createModel({ hash: "mock-glm-air", order: 14, name: "GLM-4.5-Air", type: "openai", url: "https://open.bigmodel.cn", modelId: "glm-4.5-air", endpoint: "/api/paas/v4/chat/completions" }),
+  createModel({ hash: "mock-mistral-large", order: 15, name: "Mistral Large", type: "openai", url: "https://api.mistral.ai", modelId: "mistral-large-latest", endpoint: "/v1/chat/completions" }),
+  createModel({ hash: "mock-mistral-small", order: 16, name: "Mistral Small", type: "openai", url: "https://api.mistral.ai", modelId: "mistral-small-latest", endpoint: "/v1/chat/completions" }),
+];
+
+const calls: LlmCall[] = Array.from({ length: 24 }, (_, index) => {
+  const model = models[index % models.length];
+  const failed = index === 7 || index === 19;
+  return {
+    call_kind: "provider_llm",
+    route: "local_byok",
+    call_id: `mock-call-${String(index + 1).padStart(3, "0")}`,
+    run_id: `mock-run-${Math.floor(index / 3) + 1}`,
+    conversation_id: `mock-conversation-${Math.floor(index / 4) + 1}`,
+    provider_call_index: index + 1,
+    model_hash: model.model_hash,
+    provider_type: model.type,
+    provider_url: model.base_url,
+    request_type: model.type === "anthropic" ? "messages" : "responses",
+    request_url: model.type === "anthropic" ? `${model.base_url}/v1/messages` : `${model.base_url}${model.openai_endpoint}`,
+    model_id: model.model_id,
+    display_name: model.display_name,
+    reasoning_effort: index % 2 === 0 ? "high" : null,
+    fast: index % 3 === 0,
+    status: failed ? "failed" : "completed",
+    finish_reason: failed ? null : "stop",
+    created_at_ms: FIXED_NOW - index * 3 * 60_000,
+    ttfb_ms: 210 + index * 13,
+    ttft_ms: 370 + index * 17,
+    duration_ms: failed ? 812 : 1_420 + index * 71,
+    input_tokens: 4_800 + index * 337,
+    output_tokens: failed ? 0 : 820 + index * 43,
+    total_tokens: failed ? 4_800 + index * 337 : 5_620 + index * 380,
+    cache_read_tokens: 3_100 + index * 251,
+    cache_write_tokens: 320 + index * 19,
+    reasoning_tokens: index % 2 === 0 ? 420 + index * 11 : null,
+    message_count: 14 + (index % 8),
+    tool_count: 3 + (index % 5),
+    http_status: failed ? 429 : 200,
+    error_kind: failed ? "provider_rate_limit" : null,
+    error_message: failed ? "Mock provider rate limit" : null,
+    detailed: true,
+  };
+});
+
+const harnessStatus: CursorHarnessStatus = {
+  platform: "macos",
+  ca: "ready",
+  configured_models: models.length,
+  enabled_models: models.length,
+  integration: "enabled",
+  proxy_url: "http://127.0.0.1:54321",
+  ca_install_command: null,
+};
+
+let detailed = true;
+let portSettings = { proxy_port: 0, service_port: 0 };
+let proxySettings: ProxySettings = {
+  mode: "system",
+  address: "",
+  auth_enabled: false,
+  username: "",
+  has_password: false,
+};
+let tabSettings: TabSettings = { mode: "public", address: "" };
+let storage: StatisticsStorage = { bytes: 26_004_480, call_count: calls.length, trace_count: calls.length };
+
+export function installDemoApi() {
+  const nativeFetch = window.fetch.bind(window);
+
+  window.fetch = async (input, init) => {
+    const requestUrl = input instanceof Request ? input.url : input instanceof URL ? input.href : input;
+    const url = new URL(requestUrl, window.location.href);
+    if (!url.pathname.startsWith(API_ROOT)) return nativeFetch(input, init);
+
+    const path = url.pathname.slice(API_ROOT.length) || "/";
+    const method = (init?.method ?? (input instanceof Request ? input.method : "GET")).toUpperCase();
+    const body = await readBody(input, init);
+
+    if (path === "/ads") return json({ slots: [] });
+    if (path === "/models" && method === "GET") return json(models);
+    if (path === "/models" && method === "POST") return json(models);
+    if (path === "/models/order") return json(models);
+    if (path === "/models/discover") return json({ models: models.map((model) => model.model_id) });
+    if (path === "/models/import-v0049" && method === "GET") {
+      return json({ source: "demo", total: 0, new_models: 0, existing_models: 0, models: [] });
+    }
+    if (path === "/models/import-v0049") return json({ imported: 0, skipped: 0, total: 0 });
+    if (/^\/models\/[^/]+\/test\/[^/]+$/.test(path) && method === "POST") {
+      return json({ duration_ms: 1_284, first_text_ms: 418, output_tokens: 42, tokens_per_second: 38.6, tokens_estimated: false, output: "Mock connectivity test passed." });
+    }
+    if (/^\/models\/[^/]+\/test\/[^/]+$/.test(path) || /^\/models\/[^/]+$/.test(path)) {
+      return method === "DELETE" ? empty() : json(models[0]);
+    }
+    if (path === "/overview") return json(createOverview(url.searchParams));
+    if (path === "/llm-calls") return json(calls);
+    if (path.startsWith("/llm-calls/")) return json(createCallDetail(path.slice("/llm-calls/".length)));
+    if (path === "/harness/cursor/status") return json(harnessStatus);
+    if (path === "/harness/cursor/ca/initialize" || path === "/harness/cursor/enabled") return json(harnessStatus);
+    if (path === "/settings/observability" && method === "GET") return json({ detailed });
+    if (path === "/settings/observability") {
+      detailed = Boolean((body as { detailed?: unknown } | null)?.detailed);
+      return json({ detailed });
+    }
+    if (path === "/settings/ports" && method === "GET") return json(portSettings);
+    if (path === "/settings/ports") {
+      portSettings = body as typeof portSettings;
+      return json(portSettings);
+    }
+    if (path === "/settings/storage/statistics" && method === "GET") return json(storage);
+    if (path === "/settings/storage/statistics") {
+      storage = { bytes: 0, call_count: 0, trace_count: 0 };
+      return json(storage);
+    }
+    if (path === "/settings/proxy" && method === "GET") return json(proxySettings);
+    if (path === "/settings/proxy") {
+      const next = body as Partial<ProxySettings>;
+      proxySettings = { ...proxySettings, ...next, has_password: Boolean(next.has_password) };
+      return json(proxySettings);
+    }
+    if (path === "/settings/tab" && method === "GET") return json(tabSettings);
+    if (path === "/settings/tab") {
+      tabSettings = body as TabSettings;
+      return json(tabSettings);
+    }
+    if (path === "/settings/desktop" && method === "GET") return json({ silent_start: false, show_dock_icon: true });
+    if (path === "/settings/desktop") return json(body);
+    if (path === "/desktop/open-external-url") {
+      const target = (body as { url?: string } | null)?.url;
+      if (target) {
+        const next = new URL(target, window.location.href);
+        if (next.origin === window.location.origin && next.hash) window.location.hash = next.hash;
+      }
+      return empty();
+    }
+    if (path.endsWith("/dismissals")) return empty();
+
+    return json({ message: `Unhandled demo endpoint: ${method} ${path}` }, 404);
+  };
+}
+
+function createModel({ hash, order, name, type, url, modelId, endpoint = "/v1/responses" }: {
+  hash: string;
+  order: number;
+  name: string;
+  type: Model["type"];
+  url: string;
+  modelId: string;
+  endpoint?: string;
+}): Model {
+  return {
+    model_hash: hash,
+    sort_order: order,
+    display_name: name,
+    type,
+    base_url: url,
+    use_full_url: false,
+    api_key: "demo-key",
+    tooltip_data: `${name} Mock 通道`,
+    model_id: modelId,
+    reasoning_effort: type === "openai" ? "high" : null,
+    openai_endpoint: type === "openai" ? endpoint : "",
+    openai_extra_params_enabled: false,
+    openai_extra_params: {},
+    custom_headers_enabled: false,
+    custom_headers: {},
+    anthropic_extra_params_enabled: false,
+    anthropic_extra_params: {},
+    context_window_tokens: 200_000,
+    max_completion_tokens: type === "openai" ? 32_000 : null,
+    anthropic_max_tokens: type === "anthropic" ? 32_000 : null,
+    anthropic_thinking_effort: type === "anthropic" ? "high" : null,
+    thinking_budget_tokens: null,
+    created_at_ms: FIXED_NOW - order * 86_400_000,
+    updated_at_ms: FIXED_NOW,
+  };
+}
+
+function createOverview(params: URLSearchParams): Overview {
+  const start = Number(params.get("start_ms"));
+  const end = Number(params.get("end_ms"));
+  const duration = Number.isFinite(start) && Number.isFinite(end) && end > start ? end - start : 365 * 86_400_000;
+  const granularity = duration <= 2 * 60 * 60_000 ? "minute" : duration <= 2 * 86_400_000 ? "hour" : "day";
+  const step = granularity === "minute" ? 60_000 : granularity === "hour" ? 3_600_000 : 86_400_000;
+  const count = granularity === "minute" ? Math.min(60, Math.max(10, Math.ceil(duration / step))) : granularity === "hour" ? Math.min(24, Math.max(8, Math.ceil(duration / step))) : Math.min(365, Math.max(7, Math.ceil(duration / step)));
+  const series = createSeries(count, step, Number.isFinite(end) && end > 0 ? end : FIXED_NOW);
+  const totals = series.reduce((sum, bucket) => ({
+    input: sum.input + bucket.input_tokens,
+    cacheRead: sum.cacheRead + bucket.cache_read_tokens,
+    cacheWrite: sum.cacheWrite + bucket.cache_write_tokens,
+    output: sum.output + bucket.output_tokens,
+  }), { input: 0, cacheRead: 0, cacheWrite: 0, output: 0 });
+  const llmCalls = Math.max(12, Math.round(count * 5.4));
+
+  return {
+    metrics: {
+      llm_calls: llmCalls,
+      successful_calls: llmCalls - Math.max(1, Math.floor(llmCalls * 0.008)),
+      failed_calls: Math.max(1, Math.floor(llmCalls * 0.008)),
+      token_usage: totals.input + totals.cacheRead + totals.cacheWrite + totals.output,
+      prompt_tokens: totals.input + totals.cacheRead + totals.cacheWrite,
+      input_tokens: totals.input,
+      cache_read_tokens: totals.cacheRead,
+      cache_write_tokens: totals.cacheWrite,
+      output_tokens: totals.output,
+    },
+    token_usage_granularity: granularity,
+    token_usage_series: series,
+  };
+}
+
+function createSeries(count: number, step: number, end: number): OverviewTokenUsageBucket[] {
+  return Array.from({ length: count }, (_, index) => {
+    const wave = 0.72 + ((index * 17) % 31) / 50;
+    return {
+      bucket_start_ms: end - (count - index) * step,
+      input_tokens: Math.round(18_000 * wave),
+      cache_read_tokens: Math.round(62_000 * wave),
+      cache_write_tokens: Math.round(7_500 * wave),
+      output_tokens: Math.round(12_500 * wave),
+    };
+  });
+}
+
+function createCallDetail(id: string): CallDetail {
+  const call = calls.find((item) => item.call_id === decodeURIComponent(id)) ?? calls[0];
+  return {
+    call,
+    request: {
+      headers: { authorization: "Bearer sk-demo-••••", "content-type": "application/json" },
+      body: { model: call.model_id, stream: true, messages: [{ role: "user", content: "Mock Agent request" }] },
+      byte_count: 8_426,
+    },
+    response_chunks: [
+      { seq: 1, received_offset_ms: 418, data: "event: response.created", byte_count: 128 },
+      { seq: 2, received_offset_ms: 512, data: "event: response.output_text.delta", byte_count: 256 },
+    ],
+    cursor_trace: null,
+  };
+}
+
+async function readBody(input: RequestInfo | URL, init?: RequestInit): Promise<unknown> {
+  const raw = init?.body ?? (input instanceof Request ? await input.clone().text() : null);
+  if (typeof raw !== "string" || raw.length === 0) return null;
+  try { return JSON.parse(raw) as unknown; }
+  catch { return raw; }
+}
+
+function json(value: unknown, status = 200) {
+  return new Response(JSON.stringify(value), {
+    status,
+    headers: { "content-type": "application/json" },
+  });
+}
+
+function empty() {
+  return new Response(null, { status: 204 });
+}