feat(labs): unlock native Codex vision for lab OCR

Image input rides the ChatGPT-OAuth codex/responses endpoint via the
input_image content block (protocol spec 2b) — no vision API key. The
codex client folds params.images into input_image blocks alongside the
input_text; text-only calls keep the prior byte-identical wire. The
vision gate now resolves codex capability against the working slug
(GPT-5.x / gpt-4o-class multimodal) instead of a blanket false, with the
OCR capability resolver feeding the codex slug rather than the user's
aiModel. A non-multimodal slug or an image-block rejection degrades to a
clean extract failure / local-OCR text mode.

src/lib/ai/__tests__/codex-client.test.ts

@@ -196,4 +196,66 @@ describe("CodexClient", () => {
     ).rejects.toThrow("Codex request failed (500)");
     expect(onRefresh).not.toHaveBeenCalled();
   });
+
+  it("emits input_image content blocks when images are present", async () => {
+    const mockFetch = vi
+      .fn()
+      .mockResolvedValue(
+        sseResponse([messageDoneEvent('{"summary":"ok"}'), completedEvent(50)]),
+      );
+    vi.stubGlobal("fetch", mockFetch);
+
+    const client = new CodexClient({
+      accessToken: "test-token",
+      accountId: "acct-test",
+      onTokenRefresh: vi
+        .fn()
+        .mockResolvedValue({ accessToken: "x", accountId: "acct-test" }),
+    });
+
+    await client.generateCompletion({
+      systemPrompt: "Transcribe.",
+      userPrompt: "Read this report.",
+      images: [{ mediaType: "image/png", dataBase64: "QUJD" }],
+    });
+
+    const body = JSON.parse(mockFetch.mock.calls[0][1].body);
+    const content = body.input[0].content;
+    expect(content[0]).toEqual({
+      type: "input_text",
+      text: "Read this report.",
+    });
+    expect(content[1]).toEqual({
+      type: "input_image",
+      image_url: "data:image/png;base64,QUJD",
+      detail: "high",
+    });
+  });
+
+  it("keeps the text-only content shape when no images are present", async () => {
+    const mockFetch = vi
+      .fn()
+      .mockResolvedValue(
+        sseResponse([messageDoneEvent('{"summary":"ok"}'), completedEvent(50)]),
+      );
+    vi.stubGlobal("fetch", mockFetch);
+
+    const client = new CodexClient({
+      accessToken: "test-token",
+      accountId: "acct-test",
+      onTokenRefresh: vi
+        .fn()
+        .mockResolvedValue({ accessToken: "x", accountId: "acct-test" }),
+    });
+
+    await client.generateCompletion({
+      systemPrompt: "Answer.",
+      userPrompt: "Plain text only.",
+    });
+
+    const body = JSON.parse(mockFetch.mock.calls[0][1].body);
+    expect(body.input[0].content).toEqual([
+      { type: "input_text", text: "Plain text only." },
+    ]);
+  });
 });

src/lib/ai/__tests__/vision-capability.test.ts

@@ -54,8 +54,24 @@ describe("supportsVisionForConfig", () => {
     expect(supportsVisionForConfig("local", null)).toBe(true);
   });
 
-  it("never reports vision for codex or none", () => {
-    expect(supportsVisionForConfig("codex", "gpt-4o")).toBe(false);
+  it("reports vision for codex only on multimodal slugs", () => {
+    for (const model of [
+      "gpt-5.5",
+      "gpt-5.4",
+      "gpt-5.4-mini",
+      "gpt-4o",
+      "gpt-4.1",
+      "o1",
+    ]) {
+      expect(supportsVisionForConfig("codex", model)).toBe(true);
+    }
+    // Non-multimodal / unknown slugs and a missing slug → false.
+    expect(supportsVisionForConfig("codex", "gpt-4")).toBe(false);
+    expect(supportsVisionForConfig("codex", "gpt-3.5-turbo")).toBe(false);
+    expect(supportsVisionForConfig("codex", null)).toBe(false);
+  });
+
+  it("never reports vision for none", () => {
     expect(supportsVisionForConfig("none", "gpt-4o")).toBe(false);
   });
 });

src/lib/ai/codex-client.ts

@@ -52,6 +52,20 @@ const DEFAULT_SLUG_FALLBACK_CHAIN = [
   "gpt-5.2", // legacy floor
 ] as const;
 
+/**
+ * The slug the codex vision gate reasons about *before* a request runs: the
+ * cached working slug if one is live, else the first chain entry. Lets the
+ * Lab-OCR capability resolver decide whether codex can read images without
+ * standing up a client or making a network call. Best-effort — the actual
+ * routed slug may differ once the chain walk runs, which the runtime probe +
+ * graceful fallback (text/local OCR) covers.
+ */
+export function resolveCodexVisionSlug(): string | null {
+  const cached = getCachedCodexSlug();
+  if (cached) return cached;
+  return loadFallbackChain()[0] ?? null;
+}
+
 function loadFallbackChain(): string[] {
   const envChain = process.env.CODEX_MODEL_FALLBACK_CHAIN?.trim();
   const fromEnv = envChain
@@ -291,6 +305,31 @@ export class CodexClient implements AIProvider {
   ): Promise<Response> {
     const sessionId = randomUUID();
     const threadId = randomUUID();
+
+    // v1.18.11 — fold vision inputs (Lab-OCR) into the user turn when present.
+    // The Codex/ChatGPT-OAuth backend accepts the `input_image` content block
+    // on this same `codex/responses` endpoint (docs/codex-protocol-spec.md
+    // §2b: `image_url` accepts a `data:<mime>;base64,...` URL, `detail`
+    // defaults to "high"). Image INPUT consumes the ChatGPT plan allocation —
+    // no API key is required (an API key only matters for image GENERATION).
+    // When no images are present the content is byte-identical to the prior
+    // text-only wire, so every text caller (Coach, insights, status cards) is
+    // untouched. The image is UNTRUSTED data to transcribe, framed as such by
+    // the system prompt. Documents (PDF) are NOT folded in — `input_image` is
+    // image-only; the OCR route gates PDFs to Anthropic.
+    const images = params.images ?? [];
+    const content: Array<
+      | { type: "input_text"; text: string }
+      | { type: "input_image"; image_url: string; detail: "high" }
+    > = [{ type: "input_text", text: params.userPrompt }];
+    for (const img of images) {
+      content.push({
+        type: "input_image",
+        image_url: `data:${img.mediaType};base64,${img.dataBase64}`,
+        detail: "high",
+      });
+    }
+
     return safeFetch(
       CODEX_ENDPOINT,
       {
@@ -314,7 +353,7 @@ export class CodexClient implements AIProvider {
             {
               type: "message",
               role: "user",
-              content: [{ type: "input_text", text: params.userPrompt }],
+              content,
             },
           ],
           tools: [],

src/lib/ai/vision-capability.ts

@@ -56,6 +56,31 @@ function openaiSupportsVision(model: string): boolean {
   );
 }
 
+/**
+ * Codex (ChatGPT-OAuth) vision models. Image INPUT is reachable over the
+ * `codex/responses` endpoint (docs/codex-protocol-spec.md §2b) on a multimodal
+ * slug — no API key needed. The accepted GPT-5.x line is text+vision; the older
+ * `-codex` specialist slugs and the legacy `gpt-4`-class non-multimodal pins
+ * are text-only. The slug we test is the codex client's resolved working slug
+ * (cached or chain head), so a slug rotation onto a non-vision model degrades
+ * to false rather than 400-ing the user at the image block.
+ *
+ * `gpt-4o` / `o*` are folded in for completeness (a future codex slug could
+ * land there), reusing the same multimodal families the OpenAI gate accepts.
+ */
+function codexSupportsVision(model: string): boolean {
+  const m = model.toLowerCase();
+  return (
+    m.startsWith("gpt-5") || // GPT-5.x line is multimodal (text + vision)
+    m.startsWith("gpt-4o") ||
+    m.startsWith("gpt-4.1") ||
+    m.startsWith("gpt-4-turbo") ||
+    m.startsWith("o1") ||
+    m.startsWith("o3") ||
+    m.startsWith("o4")
+  );
+}
+
 /**
  * Logical provider tags the OCR path reasons about. Mirrors the
  * `ProviderChainType` vocabulary plus the legacy `admin-key` single-provider
@@ -79,8 +104,11 @@ export type VisionProviderType =
  *                           configuring a self-hosted model and we cannot sniff
  *                           its capabilities; a non-vision local model surfaces
  *                           a clear extract failure rather than a silent gate.
- *  - codex / none         → false (no vision over the Codex wire; nothing
- *                           configured).
+ *  - codex                → vision when the resolved codex slug is a
+ *                           multimodal model (GPT-5.x / gpt-4o-class). Image
+ *                           input rides the ChatGPT plan — no API key. A
+ *                           non-multimodal slug (or unknown) → false.
+ *  - none                 → false (nothing configured).
  */
 export function supportsVisionForConfig(
   providerType: VisionProviderType,
@@ -96,6 +124,7 @@ export function supportsVisionForConfig(
     case "local":
       return true;
     case "codex":
+      return model ? codexSupportsVision(model) : false;
     case "none":
     default:
       return false;

src/lib/labs/ocr-capability.ts

@@ -11,6 +11,7 @@
  */
 import type { ProviderChainResolved } from "@/lib/ai/provider-runner";
 import { resolveProvider, resolveProviderChain } from "@/lib/ai/provider";
+import { resolveCodexVisionSlug } from "@/lib/ai/codex-client";
 import { prisma } from "@/lib/db";
 import {
   supportsPdfForProvider,
@@ -31,6 +32,10 @@ function modelForEntry(
   providerType: ProviderChainResolved["providerType"],
   ctx: ModelContext,
 ): string | null {
+  // Codex resolves its working slug at request time from the OAuth slug
+  // fallback chain — NOT from the user's `aiModel`. Use the cached/chain-head
+  // slug so the codex vision gate tests the model that actually runs.
+  if (providerType === "codex") return resolveCodexVisionSlug();
   return providerType === "admin-openai" ? ctx.adminModel : ctx.userModel;
 }