refactor(hub): 手搓 agent loop 换成 Vercel AI SDK

将 provider/runner/tools 三件手搓轮子替换为 AI SDK v7 的 generateText + tool:
- 删 openrouter-provider.ts(翻译层消失)、provider.ts 自定义消息类型
- runner.ts 循环体改为 generateText({stopWhen: stepCountIs}),保留 RunRequest/RunResult 公共签名
- tools.ts ToolRegistry 改为 ToolFactory + build(ctx, names?) 按 role 白名单构建 tools record
- workspace/cph/feishu 工具改写为 tool() 定义,execute 闭包捕获 per-run ToolContext
- transcript.ts 改为 ModelMessage[] JSONL(0.0.0 cutover,无迁移)
- server.ts/trigger.ts 接 modelFactory + toolWhitelist
- 测试:helpers 写 MockLanguageModel implements LanguageModelV4;5 个测试改写 + 新增 runner.test.ts
- 移除未使用的 openai 依赖
- ADR-0017 Consequences 同步:loop 委托给 AI SDK,provider seam 是 LanguageModel

tsc 干净,54 tests 全过。

hub/test/integration/helpers.ts

@@ -3,12 +3,19 @@
  *
  * Each test gets a clean DB (tables truncated before the test), a mock
  * FeishuRuntime (sendText/sendCard are no-ops that record calls), and a mock
- * AgentProvider (chat() returns a fixed "stop" response — no real network).
+ * AI SDK model factory (doGenerate() returns canned responses - no network).
  */
 import { PrismaClient } from "@prisma/client";
 import type { FastifyBaseLogger } from "fastify";
-import type { FeishuRuntime } from "../src/feishu/client.js";
-import type { AgentProvider, ChatRequest, ChatResponse, Message } from "../src/agent/provider.js";
+import type {
+  LanguageModelV4,
+  LanguageModelV4CallOptions,
+  LanguageModelV4Content,
+  LanguageModelV4GenerateResult,
+  LanguageModelV4StreamResult,
+} from "@ai-sdk/provider";
+import type { FeishuRuntime } from "../../src/feishu/client.js";
+import type { ModelFactory } from "../../src/agent/runner.js";
 
 export const TEST_DATABASE_URL = "postgresql://paradigm:paradigm@127.0.0.1:5432/cph_hub_test";
 
@@ -84,19 +91,82 @@ export function mockFeishuRuntime(): MockFeishuRuntime {
   return rt;
 }
 
-/** A provider that always returns a fixed "stop" response — no network. */
-export class MockProvider implements AgentProvider {
-  readonly id = "mock";
-  readonly calls: ChatRequest[] = [];
+export interface MockToolCall {
+  readonly toolCallId: string;
+  readonly toolName: string;
+  readonly input: unknown;
+}
 
-  async chat(req: ChatRequest): Promise<ChatResponse> {
-    this.calls.push(req);
-    const message: Message = {
-      role: "assistant",
-      parts: [{ type: "text", text: "mock response" }],
+export interface MockModelResponse {
+  readonly text?: string;
+  readonly toolCalls?: readonly MockToolCall[];
+  readonly finishReason?: "stop" | "length" | "content-filter" | "tool-calls" | "error" | "other";
+  readonly inputTokens?: number;
+  readonly outputTokens?: number;
+}
+
+export class MockLanguageModel implements LanguageModelV4 {
+  readonly specificationVersion = "v4";
+  readonly provider = "mock";
+  readonly supportedUrls: Record<string, RegExp[]> = {};
+  readonly calls: LanguageModelV4CallOptions[] = [];
+
+  constructor(
+    readonly modelId: string,
+    private readonly responses: readonly MockModelResponse[] = [{ text: "mock response" }],
+  ) {}
+
+  async doGenerate(options: LanguageModelV4CallOptions): Promise<LanguageModelV4GenerateResult> {
+    this.calls.push(options);
+    const configured = this.responses[this.calls.length - 1];
+    const last = this.responses[this.responses.length - 1];
+    const response =
+      configured ??
+      ((last?.toolCalls?.length ?? 0) > 0
+        ? { text: "mock response" }
+        : last ?? { text: "mock response" });
+    const content: LanguageModelV4Content[] = [];
+    if (response.text !== undefined) {
+      content.push({ type: "text", text: response.text });
+    }
+    for (const call of response.toolCalls ?? []) {
+      content.push({
+        type: "tool-call",
+        toolCallId: call.toolCallId,
+        toolName: call.toolName,
+        input: JSON.stringify(call.input),
+      });
+    }
+    const finishReason = response.finishReason ?? ((response.toolCalls?.length ?? 0) > 0 ? "tool-calls" : "stop");
+    return {
+      content,
+      finishReason: { unified: finishReason, raw: finishReason },
+      usage: {
+        inputTokens: { total: response.inputTokens ?? 10, noCache: undefined, cacheRead: undefined, cacheWrite: undefined },
+        outputTokens: { total: response.outputTokens ?? 5, text: undefined, reasoning: undefined },
+      },
+      response: { id: `mock-${this.calls.length}`, timestamp: new Date(), modelId: this.modelId },
+      warnings: [],
     };
-    return { finishReason: "stop", message, usage: { inputTokens: 10, outputTokens: 5 } };
   }
+
+  async doStream(_options: LanguageModelV4CallOptions): Promise<LanguageModelV4StreamResult> {
+    throw new Error("MockLanguageModel does not implement streaming");
+  }
+}
+
+export function createMockModelFactory(
+  responses: readonly MockModelResponse[] = [{ text: "mock response" }],
+): { readonly modelFactory: ModelFactory; readonly models: ReadonlyMap<string, MockLanguageModel> } {
+  const models = new Map<string, MockLanguageModel>();
+  return {
+    models,
+    modelFactory: (modelId) => {
+      const model = new MockLanguageModel(modelId, responses);
+      models.set(modelId, model);
+      return model;
+    },
+  };
 }
 
 /** Create a project + binding + user + grant for a test. */