feat(create): 创作对话 - 接入推理展示与可折叠生成详情

Refs #243

web/test/text-reasoning-stream.test.ts

@@ -0,0 +1,77 @@
+import { afterEach, describe, expect, test } from "bun:test";
+import React from "react";
+import { renderToStaticMarkup } from "react-dom/server";
+
+import { GenerationToolCard } from "../src/components/ai/generation-tool-card";
+import type { ModelProtocol } from "../src/lib/model-protocols";
+import { requestImageQuestion } from "../src/services/api/image";
+import { createModelChannel, defaultConfig, type AiConfig } from "../src/stores/use-config-store";
+
+const originalFetch = globalThis.fetch;
+
+afterEach(() => {
+    globalThis.fetch = originalFetch;
+});
+
+function reasoningConfig(protocol: ModelProtocol | undefined, apiFormat: "openai" | "gemini" = "openai"): AiConfig {
+    const channel = createModelChannel({
+        id: "reasoning",
+        name: "Reasoning",
+        baseUrl: "https://reasoning.example/v1",
+        apiKey: "synthetic-test-key",
+        apiFormat,
+        interfaceType: apiFormat === "gemini" ? undefined : protocol,
+        models: ["reasoner"],
+        modelCosts: [{ model: "reasoner", capability: "text", ...(protocol ? { protocol } : {}), billingMode: "fixed_request", unitPriceMicrocredits: 0 }],
+    });
+    return { ...defaultConfig, channels: [channel], model: "reasoning::reasoner", textModel: "reasoning::reasoner" };
+}
+
+function streamResponse(events: unknown[]) {
+    const body = `${events.map((event) => `data: ${JSON.stringify(event)}`).join("\n\n")}\n\n`;
+    return new Response(body, { headers: { "Content-Type": "text/event-stream" } });
+}
+
+async function requestWithReasoning(config: AiConfig, events: unknown[]) {
+    globalThis.fetch = (async () => streamResponse(events)) as typeof fetch;
+    let content = "";
+    let reasoning = "";
+    const result = await requestImageQuestion(config, [{ role: "user", content: "请回答" }], (value) => { content = value; }, { onReasoning: (value) => { reasoning = value; } });
+    return { result, content, reasoning };
+}
+
+describe("text reasoning streams", () => {
+    test("separates Responses reasoning summaries from answer text", async () => {
+        const output = await requestWithReasoning(reasoningConfig("openai-response"), [
+            { type: "response.reasoning_summary_text.delta", delta: "先分析" },
+            { type: "response.output_text.delta", delta: "最终答案" },
+        ]);
+
+        expect(output).toEqual({ result: "最终答案", content: "最终答案", reasoning: "先分析" });
+    });
+
+    test("separates Chat Completions reasoning_content from answer text", async () => {
+        const output = await requestWithReasoning(reasoningConfig("chat-completion"), [
+            { choices: [{ delta: { reasoning_content: "推理过程" } }] },
+            { choices: [{ delta: { content: "回答内容" } }] },
+        ]);
+
+        expect(output).toEqual({ result: "回答内容", content: "回答内容", reasoning: "推理过程" });
+    });
+
+    test("does not duplicate Gemini thought parts into visible content", async () => {
+        const output = await requestWithReasoning(reasoningConfig(undefined, "gemini"), [
+            { candidates: [{ content: { parts: [{ text: "内部思考", thought: true }, { text: "可见回答" }] } }] },
+        ]);
+
+        expect(output).toEqual({ result: "可见回答", content: "可见回答", reasoning: "内部思考" });
+    });
+
+    test("keeps single results open and collapses completed bulk results on restore", () => {
+        const single = renderToStaticMarkup(React.createElement(GenerationToolCard, { status: "completed", heading: "图像生成" }, React.createElement("span", null, "单图结果")));
+        const bulk = renderToStaticMarkup(React.createElement(GenerationToolCard, { status: "completed", isBulk: true, heading: "图像生成" }, React.createElement("span", null, "批量结果")));
+
+        expect(single).toContain("单图结果");
+        expect(bulk).not.toContain("批量结果");
+    });
+});