c49efdf528
Do not collapse consecutive underscores in uniqueName so mcp__server__tool is sent intact to Kiro, attach reverse map on request translation, and restore client tool names in responses.
189 lines
11 KiB
JavaScript
189 lines
11 KiB
JavaScript
// Fixes for agent clients (Claude Code) driving non-Anthropic upstreams:
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// - tool-result images survive the Claude → OpenAI / Kiro request translation
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// - Kiro tool calls stream back under the client's own (unsanitized) names
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// - the client's thinking `display` is kept on Claude-format upstreams
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import { describe, it, expect } from "vitest";
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import "./registerAll.js";
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import { translateRequest, translateResponse, initState } from "../../open-sse/translator/index.js";
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import { FORMATS } from "../../open-sse/translator/formats.js";
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import { applyThinking } from "../../open-sse/translator/concerns/thinkingUnified.js";
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import { kiroToClaudeResponse } from "../../open-sse/translator/response/kiro-to-claude.js";
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import { kiroToOpenAIResponse } from "../../open-sse/translator/response/kiro-to-openai.js";
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import { selectAnthropicBeta } from "../../open-sse/providers/shared.js";
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import { hoistToolResultImages } from "../../open-sse/translator/formats/claude.js";
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import { openaiToCommandCodeRequest } from "../../open-sse/translator/request/openai-to-commandcode.js";
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const PNG = "iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mNkYPhfDwAChwGA60e6kgAAAABJRU5ErkJggg==";
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const screenshotTurn = (extraTools = []) => ({
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tools: [
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{ name: "mcp__browser__computer", description: "browser", input_schema: { type: "object", properties: {} } },
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...extraTools,
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],
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messages: [
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{ role: "user", content: "take a screenshot" },
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{ role: "assistant", content: [{ type: "tool_use", id: "toolu_1", name: "mcp__browser__computer", input: { action: "screenshot" } }] },
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{
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role: "user",
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content: [{
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type: "tool_result",
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tool_use_id: "toolu_1",
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content: [
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{ type: "text", text: "Successfully captured screenshot (1x1, png)" },
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{ type: "image", source: { type: "base64", media_type: "image/png", data: PNG } },
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],
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}],
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},
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],
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});
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describe("tool-result images reach OpenAI-format upstreams", () => {
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it("emits the tool message text and a follow-up user message carrying the image", () => {
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const out = translateRequest(FORMATS.CLAUDE, FORMATS.OPENAI, "gpt-x", screenshotTurn(), true, null, "openai");
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const toolMsg = out.messages.find((m) => m.role === "tool");
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expect(toolMsg.tool_call_id).toBe("toolu_1");
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expect(toolMsg.content).toBe("Successfully captured screenshot (1x1, png)");
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expect(toolMsg.content).not.toContain(PNG);
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const follow = out.messages[out.messages.indexOf(toolMsg) + 1];
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expect(follow.role).toBe("user");
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const image = follow.content.find((p) => p.type === "image_url");
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expect(image.image_url.url).toBe(`data:image/png;base64,${PNG}`);
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expect(follow.content.find((p) => p.type === "text").text).toContain("toolu_1");
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});
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it("does not dump base64 into a tool message that had no text", () => {
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const body = screenshotTurn();
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body.messages[2].content[0].content = [{ type: "image", source: { type: "base64", media_type: "image/png", data: PNG } }];
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const out = translateRequest(FORMATS.CLAUDE, FORMATS.OPENAI, "gpt-x", body, true, null, "openai");
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const toolMsg = out.messages.find((m) => m.role === "tool");
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expect(toolMsg.content).toBe("");
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expect(out.messages.some((m) => Array.isArray(m.content) && m.content.some((p) => p.type === "image_url"))).toBe(true);
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});
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it("leaves text-only tool results exactly as before", () => {
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const body = screenshotTurn();
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body.messages[2].content[0].content = "plain result";
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const out = translateRequest(FORMATS.CLAUDE, FORMATS.OPENAI, "gpt-x", body, true, null, "openai");
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const toolMsg = out.messages.find((m) => m.role === "tool");
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expect(toolMsg.content).toBe("plain result");
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expect(out.messages[out.messages.length - 1]).toBe(toolMsg);
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});
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it("forwards tool-result images to Kiro as user images", () => {
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const out = translateRequest(FORMATS.CLAUDE, FORMATS.KIRO, "claude-sonnet-4.5", screenshotTurn(), true, null, "kiro");
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const json = JSON.stringify(out.conversationState);
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expect(json).toContain(PNG);
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expect(json).toContain("Successfully captured screenshot");
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});
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});
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describe("Kiro tool names round-trip", () => {
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it("returns the sanitized→original map on the translated body", () => {
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const body = screenshotTurn();
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body.tools = [{ name: "mcp.browser.computer", description: "browser", input_schema: { type: "object", properties: {} } }];
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const out = translateRequest(FORMATS.CLAUDE, FORMATS.KIRO, "claude-sonnet-4.5", body, true, null, "kiro");
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expect(out._toolNameMap).toBeInstanceOf(Map);
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expect(out._toolNameMap.get("mcp_browser_computer")).toBe("mcp.browser.computer");
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const wire = JSON.parse(JSON.stringify(out.conversationState));
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expect(JSON.stringify(wire)).toContain("mcp_browser_computer");
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expect(JSON.stringify(wire)).not.toContain("mcp.browser.computer");
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});
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it("omits the map when no name changed", () => {
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const body = screenshotTurn();
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body.tools = [{ name: "plain_tool", description: "x", input_schema: { type: "object", properties: {} } }];
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body.messages[1].content[0].name = "plain_tool";
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const out = translateRequest(FORMATS.CLAUDE, FORMATS.KIRO, "claude-sonnet-4.5", body, true, null, "kiro");
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expect(out._toolNameMap).toBeUndefined();
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});
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it("restores the client name on streamed Claude tool_use blocks", () => {
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const state = { ...initState(FORMATS.CLAUDE), toolNameMap: new Map([["mcp_browser_computer", "mcp__browser__computer"]]) };
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const chunk = {
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id: "c1", object: "chat.completion.chunk", created: 1, model: "claude-sonnet-4.5",
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choices: [{ index: 0, delta: { tool_calls: [{ index: 0, id: "call_1", type: "function", function: { name: "mcp_browser_computer", arguments: "" } }] }, finish_reason: null }],
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};
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const events = kiroToClaudeResponse(chunk, state);
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const start = events.find((e) => e.type === "content_block_start" && e.content_block?.type === "tool_use");
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expect(start.content_block.name).toBe("mcp__browser__computer");
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});
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it("passes unknown names through untouched", () => {
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const state = { ...initState(FORMATS.CLAUDE), toolNameMap: new Map([["mcp_browser_computer", "mcp__browser__computer"]]) };
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const chunk = {
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id: "c1", object: "chat.completion.chunk", created: 1, model: "claude-sonnet-4.5",
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choices: [{ index: 0, delta: { tool_calls: [{ index: 0, id: "call_2", type: "function", function: { name: "other_tool", arguments: "" } }] }, finish_reason: null }],
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};
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const events = kiroToClaudeResponse(chunk, state);
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const start = events.find((e) => e.type === "content_block_start" && e.content_block?.type === "tool_use");
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expect(start.content_block.name).toBe("other_tool");
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});
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it("restores the client name on OpenAI chunks passed through kiro-to-openai", () => {
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const state = { ...initState(FORMATS.OPENAI), toolNameMap: new Map([["mcp_browser_computer", "mcp__browser__computer"]]) };
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const chunk = {
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id: "c1", object: "chat.completion.chunk", created: 1, model: "claude-sonnet-4.5",
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choices: [{ index: 0, delta: { tool_calls: [{ index: 0, id: "call_1", type: "function", function: { name: "mcp_browser_computer", arguments: "{}" } }] }, finish_reason: null }],
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};
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const out = kiroToOpenAIResponse(chunk, state);
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expect(out.choices[0].delta.tool_calls[0].function.name).toBe("mcp__browser__computer");
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expect(kiroToOpenAIResponse(chunk, initState(FORMATS.OPENAI))).toBe(chunk);
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});
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});
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describe("thinking display is preserved for Claude-format upstreams", () => {
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it("keeps display on adaptive thinking", () => {
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const body = { model: "claude-sonnet-5", thinking: { type: "adaptive", display: "summarized" }, output_config: { effort: "high" }, messages: [] };
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applyThinking(FORMATS.CLAUDE, "claude-sonnet-5", body, "claude");
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expect(body.thinking).toEqual({ type: "adaptive", display: "summarized" });
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expect(body.output_config).toEqual({ effort: "high" });
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});
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it("keeps display on budget thinking and omits it when the client sent none", () => {
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const withDisplay = { model: "claude-haiku-4-5-20251001", thinking: { type: "adaptive", display: "omitted" }, output_config: { effort: "low" }, messages: [] };
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applyThinking(FORMATS.CLAUDE, "claude-haiku-4-5-20251001", withDisplay, "claude");
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expect(withDisplay.thinking.type).toBe("enabled");
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expect(withDisplay.thinking.display).toBe("omitted");
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const without = { model: "claude-sonnet-5", thinking: { type: "adaptive" }, output_config: { effort: "high" }, messages: [] };
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applyThinking(FORMATS.CLAUDE, "claude-sonnet-5", without, "claude");
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expect(without.thinking).toEqual({ type: "adaptive" });
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});
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});
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describe("redact-thinking beta follows the client's display request", () => {
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it("keeps redact-thinking by default and drops it for summarized display", () => {
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expect(selectAnthropicBeta("claude-sonnet-5")).toContain("redact-thinking-2026-02-12");
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expect(selectAnthropicBeta("claude-sonnet-5", { thinking: { type: "adaptive", display: "omitted" } })).toContain("redact-thinking-2026-02-12");
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const summarized = selectAnthropicBeta("claude-sonnet-5", { thinking: { type: "adaptive", display: "summarized" } });
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expect(summarized).not.toContain("redact-thinking-2026-02-12");
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expect(summarized).toContain("interleaved-thinking-2025-05-14");
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expect(summarized).toContain("effort-2025-11-24");
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});
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});
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describe("tool-result images reach Anthropic-compatible and Command Code upstreams", () => {
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it("hoists a tool_result image into the same user turn after the results", () => {
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const body = screenshotTurn();
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const out = hoistToolResultImages(body);
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const user = out.messages[2];
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expect(user.content[0].type).toBe("tool_result");
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expect(user.content[0].content.every((c) => c.type !== "image")).toBe(true);
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expect(user.content.some((c) => c.type === "image" && c.source?.data === PNG)).toBe(true);
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expect(user.content.find((c) => c.type === "text" && /toolu_1/.test(c.text))).toBeTruthy();
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// No image: untouched object identity.
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const plain = { messages: [{ role: "user", content: [{ type: "tool_result", tool_use_id: "x", content: "ok" }] }] };
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expect(hoistToolResultImages(plain)).toBe(plain);
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});
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it("sends an image block to Command Code instead of a placeholder", () => {
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const openaiBody = translateRequest(FORMATS.CLAUDE, FORMATS.OPENAI, "muse-spark", screenshotTurn(), true, null, "commandcode");
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const out = openaiToCommandCodeRequest("muse-spark", openaiBody, true);
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const json = JSON.stringify(out);
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expect(json).not.toContain("[image omitted]");
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expect(json).toContain(`"type":"image"`);
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expect(json).toContain(`data:image/png;base64,${PNG}`);
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expect(json).toContain(`"mediaType":"image/png"`);
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});
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});
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