fix(catalog): marked cerebras gemma vision capable

Mapped Cerebras gemma-4-31b dynamic discovery to include image input capability and covered the OpenAI Chat Completions image_url serialization path.

Fixes #3854

packages/ai/test/openai-completions-tool-result-images.test.ts

@@ -2,6 +2,7 @@ import { describe, expect, it } from "bun:test";
 import { convertMessages } from "@oh-my-pi/pi-ai/providers/openai-completions";
 import { NON_VISION_IMAGE_PLACEHOLDER } from "@oh-my-pi/pi-ai/providers/vision-guard";
 import type { AssistantMessage, Context, Model, ToolResultMessage, Usage } from "@oh-my-pi/pi-ai/types";
+import { buildModel } from "@oh-my-pi/pi-catalog/build";
 import { getBundledModel } from "@oh-my-pi/pi-catalog/models";
 import type { ResolvedOpenAICompat } from "@oh-my-pi/pi-catalog/types";
 
@@ -75,6 +76,48 @@ function buildToolResult(toolCallId: string, timestamp: number): ToolResultMessa
 }
 
 describe("openai-completions convertMessages", () => {
+	it("serializes Cerebras gemma image inputs as Chat Completions data URIs", () => {
+		const model = buildModel({
+			id: "gemma-4-31b",
+			name: "Gemma 4 31B",
+			api: "openai-completions",
+			provider: "cerebras",
+			baseUrl: "https://api.cerebras.ai/v1",
+			reasoning: false,
+			input: ["text", "image"],
+			cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
+			contextWindow: 128_000,
+			maxTokens: 8_192,
+		});
+		const context: Context = {
+			messages: [
+				{
+					role: "user",
+					content: [
+						{ type: "text", text: "Identify the shapes and colors. Return JSON only." },
+						{ type: "image", mimeType: "image/png", data: "ZmFrZQ==" },
+					],
+					timestamp: 1,
+				},
+			],
+		};
+
+		const messages = convertMessages(model, context, compat);
+
+		expect(messages).toEqual([
+			{
+				role: "user",
+				content: [
+					{ type: "text", text: "Identify the shapes and colors. Return JSON only." },
+					{
+						type: "image_url",
+						image_url: { url: "data:image/png;base64,ZmFrZQ==" },
+					},
+				],
+			},
+		]);
+	});
+
 	it("batches tool-result images after consecutive tool results", () => {
 		const baseModel = getBundledModel("openai", "gpt-4o-mini") as Model<"openai-completions">;
 		const model: Model<"openai-completions"> = {

packages/catalog/CHANGELOG.md

@@ -2,6 +2,10 @@
 
 ## [Unreleased]
 
+### Fixed
+
+- Fixed Cerebras `gemma-4-31b` dynamic discovery to mark the model as image-capable so attached images are serialized as OpenAI Chat Completions `image_url` data URIs. ([#3854](https://github.com/can1357/oh-my-pi/issues/3854))
+
 ## [16.2.6] - 2026-06-29
 
 ### Fixed

packages/catalog/src/provider-models/openai-compat.ts

@@ -803,6 +803,18 @@ export function groqModelManagerOptions(config?: GroqModelManagerConfig): ModelM
 // 3. Cerebras
 // ---------------------------------------------------------------------------
 
+const CEREBRAS_IMAGE_INPUT_MODEL_IDS = new Set(["gemma-4-31b"]);
+
+function applyCerebrasDiscoveryOverrides(model: ModelSpec<"openai-completions">): ModelSpec<"openai-completions"> {
+	if (!CEREBRAS_IMAGE_INPUT_MODEL_IDS.has(model.id)) {
+		return model;
+	}
+	return {
+		...model,
+		input: ["text", "image"],
+	};
+}
+
 export interface CerebrasModelManagerConfig {
 	apiKey?: string;
 	baseUrl?: string;
@@ -812,7 +824,27 @@ export interface CerebrasModelManagerConfig {
 export function cerebrasModelManagerOptions(
 	config?: CerebrasModelManagerConfig,
 ): ModelManagerOptions<"openai-completions"> {
-	return createSimpleOpenAICompletionsOptions("cerebras", "https://api.cerebras.ai/v1", config);
+	const apiKey = config?.apiKey;
+	const baseUrl = config?.baseUrl ?? "https://api.cerebras.ai/v1";
+	const references = createBundledReferenceMap<"openai-completions">("cerebras");
+	return {
+		providerId: "cerebras",
+		...(apiKey && {
+			fetchDynamicModels: () =>
+				fetchOpenAICompatibleModels({
+					api: "openai-completions",
+					provider: "cerebras",
+					baseUrl,
+					apiKey,
+					mapModel: (entry, defaults) => {
+						const reference = references.get(defaults.id);
+						const model = mapWithBundledReference(entry, defaults, reference);
+						return applyCerebrasDiscoveryOverrides(model);
+					},
+					fetch: config?.fetch,
+				}),
+		}),
+	};
 }
 
 // ---------------------------------------------------------------------------

packages/catalog/test/cerebras-provider.test.ts

@@ -0,0 +1,41 @@
+import { describe, expect, test } from "bun:test";
+import { cerebrasModelManagerOptions } from "@oh-my-pi/pi-catalog/provider-models/openai-compat";
+import type { FetchImpl } from "@oh-my-pi/pi-catalog/types";
+
+describe("Cerebras provider discovery", () => {
+	test("discovers gemma-4-31b as image-capable", async () => {
+		const calls: Array<{ url: string; authorization: string | null }> = [];
+		const fetchMock: FetchImpl = async (input: string | URL | Request, init?: RequestInit) => {
+			const headers = new Headers(init?.headers);
+			calls.push({
+				url: String(input),
+				authorization: headers.get("authorization"),
+			});
+			return new Response(
+				JSON.stringify({
+					data: [
+						{ id: "gemma-4-31b", object: "model" },
+						{ id: "llama3.1-8b", object: "model" },
+					],
+				}),
+				{ status: 200, headers: { "content-type": "application/json" } },
+			);
+		};
+
+		const options = cerebrasModelManagerOptions({ apiKey: "cerebras-test-key", fetch: fetchMock });
+		const models = await options.fetchDynamicModels?.();
+
+		expect(calls).toEqual([
+			{
+				url: "https://api.cerebras.ai/v1/models",
+				authorization: "Bearer cerebras-test-key",
+			},
+		]);
+		expect(models?.find(model => model.id === "gemma-4-31b")).toMatchObject({
+			provider: "cerebras",
+			api: "openai-completions",
+			input: ["text", "image"],
+		});
+		expect(models?.find(model => model.id === "llama3.1-8b")?.input).toEqual(["text"]);
+	});
+});