test(tools): polish image auth regression and fix agents vitest routing

scripts/test-projects.test-support.mjs

@@ -53,6 +53,10 @@ const AGENTS_PI_EMBEDDED_VITEST_CONFIG = "test/vitest/vitest.agents-pi-embedded.
 const AGENTS_SUPPORT_VITEST_CONFIG = "test/vitest/vitest.agents-support.config.ts";
 const AGENTS_TOOLS_VITEST_CONFIG = "test/vitest/vitest.agents-tools.config.ts";
 const AGENTS_VITEST_CONFIG = "test/vitest/vitest.agents.config.ts";
+const AGENTS_CORE_VITEST_CONFIG = "test/vitest/vitest.agents-core.config.ts";
+const AGENTS_PI_EMBEDDED_VITEST_CONFIG = "test/vitest/vitest.agents-pi-embedded.config.ts";
+const AGENTS_SUPPORT_VITEST_CONFIG = "test/vitest/vitest.agents-support.config.ts";
+const AGENTS_TOOLS_VITEST_CONFIG = "test/vitest/vitest.agents-tools.config.ts";
 const ACP_VITEST_CONFIG = "test/vitest/vitest.acp.config.ts";
 const AUTO_REPLY_CORE_VITEST_CONFIG = "test/vitest/vitest.auto-reply-core.config.ts";
 const AUTO_REPLY_VITEST_CONFIG = "test/vitest/vitest.auto-reply.config.ts";
@@ -240,6 +244,10 @@ const VITEST_CONFIG_BY_KIND = {
   agentSupport: AGENTS_SUPPORT_VITEST_CONFIG,
   agentTools: AGENTS_TOOLS_VITEST_CONFIG,
   agent: AGENTS_VITEST_CONFIG,
+  agentsCore: AGENTS_CORE_VITEST_CONFIG,
+  agentsPiEmbedded: AGENTS_PI_EMBEDDED_VITEST_CONFIG,
+  agentsSupport: AGENTS_SUPPORT_VITEST_CONFIG,
+  agentsTools: AGENTS_TOOLS_VITEST_CONFIG,
   autoReplyCore: AUTO_REPLY_CORE_VITEST_CONFIG,
   autoReplyReply: AUTO_REPLY_REPLY_VITEST_CONFIG,
   autoReplyTopLevel: AUTO_REPLY_TOP_LEVEL_VITEST_CONFIG,
@@ -1713,6 +1721,10 @@ export function buildVitestRunPlans(
     "agentSupport",
     "agentTools",
     "agent",
+    "agentsCore",
+    "agentsPiEmbedded",
+    "agentsSupport",
+    "agentsTools",
     "plugin",
     "ui",
     "uiE2e",

src/agents/tools/image-tool.custom-provider-auth.regression.test.ts

@@ -0,0 +1,185 @@
+import fs from "node:fs/promises";
+import os from "node:os";
+import path from "node:path";
+import { afterEach, beforeEach, describe, expect, it, vi } from "vitest";
+import type { OpenClawConfig } from "../../config/config.js";
+import type { ModelDefinitionConfig } from "../../config/types.models.js";
+import type { ImageDescriptionRequest } from "../../plugin-sdk/media-understanding.js";
+import { getApiKeyForModel, hasUsableCustomProviderApiKey } from "../model-auth.js";
+import { resolveImageToolFactoryAvailable } from "../openclaw-tools.media-factory-plan.js";
+import { createImageTool, resolveImageModelConfigForTool, testing } from "./image-tool.js";
+import { hasProviderAuthForTool } from "./model-config.helpers.js";
+
+const USER_PROVIDER = "hatchery-qwen3.6-plus";
+const USER_MODEL = "qwen3.6-plus";
+const USER_PRIMARY = `${USER_PROVIDER}/${USER_MODEL}`;
+const CONFIG_API_KEY = "sk-user-configured-key"; // pragma: allowlist secret
+
+const ONE_PIXEL_PNG_B64 =
+  "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";
+
+function makeVisionModel(id: string): ModelDefinitionConfig {
+  return {
+    id,
+    name: id,
+    reasoning: false,
+    input: ["text", "image"],
+    cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
+    contextWindow: 128_000,
+    maxTokens: 8_192,
+  };
+}
+
+function createUserReportedConfig(params?: { includeApiKey?: boolean }): OpenClawConfig {
+  const includeApiKey = params?.includeApiKey ?? true;
+  return {
+    agents: {
+      defaults: {
+        model: { primary: USER_PRIMARY },
+      },
+    },
+    models: {
+      providers: {
+        [USER_PROVIDER]: {
+          baseUrl: "https://example.com/v1",
+          api: "openai-completions",
+          ...(includeApiKey ? { apiKey: CONFIG_API_KEY } : {}),
+          models: [makeVisionModel(USER_MODEL)],
+        },
+      },
+    },
+  };
+}
+
+async function withEmptyAgentDir<T>(run: (agentDir: string) => Promise<T>): Promise<T> {
+  const agentDir = await fs.mkdtemp(path.join(os.tmpdir(), "openclaw-image-auth-regression-"));
+  try {
+    return await run(agentDir);
+  } finally {
+    await fs.rm(agentDir, { recursive: true, force: true });
+  }
+}
+
+describe("image custom provider auth regression", () => {
+  const priorFetch = global.fetch;
+
+  beforeEach(() => {
+    for (const key of Object.keys(process.env)) {
+      if (key.endsWith("_API_KEY") || key.endsWith("_OAUTH_TOKEN")) {
+        vi.stubEnv(key, "");
+      }
+    }
+    testing.setProviderDepsForTest({
+      buildProviderRegistry: () => new Map(),
+      getMediaUnderstandingProvider: () => undefined,
+      describeImageWithModel: async (params: ImageDescriptionRequest) => ({
+        text: `seen:${params.provider}/${params.model}`,
+        model: params.model,
+      }),
+      describeImagesWithModel: async (params) => ({
+        text: `seen:${params.provider}/${params.model}`,
+        model: params.model,
+      }),
+      resolveAutoMediaKeyProviders: () => [],
+      resolveDefaultMediaModel: () => undefined,
+    });
+  });
+
+  afterEach(() => {
+    vi.unstubAllEnvs();
+    global.fetch = priorFetch;
+    testing.setProviderDepsForTest(undefined);
+  });
+
+  it("uses real model-auth to accept config-only custom provider credentials", async () => {
+    const cfg = createUserReportedConfig();
+    expect(hasUsableCustomProviderApiKey(cfg, USER_PROVIDER)).toBe(true);
+    expect(hasProviderAuthForTool({ provider: USER_PROVIDER, cfg })).toBe(true);
+  });
+
+  it("auto-discovers the user-reported vision model without env key or auth profile", async () => {
+    await withEmptyAgentDir(async (agentDir) => {
+      const cfg = createUserReportedConfig();
+      expect(resolveImageModelConfigForTool({ cfg, agentDir })).toEqual({
+        primary: USER_PRIMARY,
+      });
+    });
+  });
+
+  it("registers the image tool on the production factory path when the primary model has vision", async () => {
+    await withEmptyAgentDir(async (agentDir) => {
+      const cfg = createUserReportedConfig();
+      expect(
+        resolveImageToolFactoryAvailable({
+          config: cfg,
+          agentDir,
+          modelHasVision: true,
+        }),
+      ).toBe(true);
+    });
+  });
+
+  it("executes deferred image tool discovery with config-backed auth and runtime key resolution", async () => {
+    await withEmptyAgentDir(async (agentDir) => {
+      const cfg = createUserReportedConfig();
+      const auth = await getApiKeyForModel({
+        model: {
+          id: USER_MODEL,
+          name: USER_MODEL,
+          provider: USER_PROVIDER,
+          api: "openai-completions",
+          baseUrl: "https://example.com/v1",
+          reasoning: false,
+          input: ["text", "image"],
+          cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
+          contextWindow: 128_000,
+          maxTokens: 8_192,
+        },
+        cfg,
+        agentDir,
+      });
+      expect(auth.apiKey).toBe(CONFIG_API_KEY);
+      expect(auth.source).toContain("models.json");
+
+      const tool = createImageTool({
+        config: cfg,
+        agentDir,
+        deferAutoModelResolution: true,
+        modelHasVision: true,
+      });
+      expect(typeof tool?.execute).toBe("function");
+
+      const result = await tool!.execute("regression-1", {
+        prompt: "Read this screenshot.",
+        image: `data:image/png;base64,${ONE_PIXEL_PNG_B64}`,
+      });
+
+      const payload = result as { content?: Array<{ type?: string; text?: string }> };
+      const text = payload.content?.find((entry) => entry.type === "text")?.text ?? "";
+      expect(text).toContain(`seen:${USER_PRIMARY}`);
+      expect(text).not.toMatch(/No image model is configured/i);
+    });
+  });
+
+  it("still rejects the same config when apiKey is missing", async () => {
+    await withEmptyAgentDir(async (agentDir) => {
+      const cfg = createUserReportedConfig({ includeApiKey: false });
+      expect(hasUsableCustomProviderApiKey(cfg, USER_PROVIDER)).toBe(false);
+      expect(hasProviderAuthForTool({ provider: USER_PROVIDER, cfg })).toBe(false);
+      expect(resolveImageModelConfigForTool({ cfg, agentDir })).toBeNull();
+
+      const tool = createImageTool({
+        config: cfg,
+        agentDir,
+        deferAutoModelResolution: true,
+        modelHasVision: true,
+      });
+      await expect(
+        tool!.execute("regression-2", {
+          prompt: "Read this screenshot.",
+          image: `data:image/png;base64,${ONE_PIXEL_PNG_B64}`,
+        }),
+      ).rejects.toThrow(/No image model is configured/);
+    });
+  });
+});

test/scripts/test-projects.test.ts

@@ -936,6 +936,24 @@ describe("scripts/test-projects changed-target routing", () => {
     expect(repoSourceReads.length).toBeLessThan(100);
   });
 
+  it.each([
+    "test/vitest/vitest.agents-core.config.ts",
+    "test/vitest/vitest.agents-pi-embedded.config.ts",
+    "test/vitest/vitest.agents-support.config.ts",
+    "test/vitest/vitest.agents-tools.config.ts",
+  ])("routes split agents vitest config %s to itself", (target) => {
+    const plans = buildVitestRunPlans([target], process.cwd());
+
+    expect(plans).toEqual([
+      {
+        config: target,
+        forwardedArgs: [],
+        includePatterns: null,
+        watchMode: false,
+      },
+    ]);
+  });
+
   it.each([
     "src/gateway/gateway.test.ts",
     "src/gateway/server.startup-matrix-migration.integration.test.ts",