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feat(ai): expose Jev on Vercel AI Gateway and OpenCode Zen

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Vercel evaluation models are generated from the AI Gateway catalog and
routed through its TypeSafe-compatible /typesafe/v1/systemone endpoint.
OpenCode Zen's jev-1.13 and jev-1.13-free are routed through
/zen/v1/systemone.
This commit is contained in:
Armin Ronacher
2026-09-29 15:32:10 +02:00
parent 5257d0d5f3
commit 33e2033543
7 changed files with 123 additions and 16 deletions
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packages/ai/CHANGELOG.md
+1
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@@ -16,6 +16,7 @@
- Added support for models of every type in `ModelsStoreEntry.models`. Stored and fetched models of unknown types are dropped instead of failing a refresh.
- Added classifier models and `Models.classify()` with a provider-neutral JEV-style `choice`/`score`/`bool` contract. The built-in TypeSafe provider exposes models.dev's `jev-latest` through the System One API and translates public `bool` questions to TypeSafe's `noul` wire format.
- Added Jev classifier models on OpenRouter (`typesafe/jev-1.13`, `~typesafe/jev-latest`) through its TypeSafe-compatible System One endpoint, and on Cloudflare Workers AI (`typesafe/jev`) through the new `cloudflare-workers-ai-system-one` classifier API.
- Added Jev classifier models on Vercel AI Gateway (`typesafe-ai/jev`, generated from its evaluation model catalog) and OpenCode Zen (`jev-1.13`, `jev-1.13-free`) through their TypeSafe-compatible System One endpoints.
- Added a runtime chat-model check to the `Models` stream entry points so non-chat models fail with a clear `ModelsError` instead of a missing-api stream error.
- Added array-based `models.all.json` and `providers/{id}.all.json` variants to the generated and published JSON catalog, allowing the same upstream ID once per model type; the existing keyed `models.json` and `providers/{id}.json` stay chat-only for released clients.
- Added `onProviderStreamEvent` to observe parsed provider stream events before normalization, including provider-specific fields not retained in assistant messages ([#9784](https://github.com/earendil-works/pi/issues/9784)).
packages/ai/README.md
+2
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@@ -897,6 +897,8 @@ Classifier models consume structured JSON state and answer one or more typed que
| `typesafe` | `jev-latest` | `TYPESAFE_API_KEY` |
| `openrouter` | `typesafe/jev-1.13`, `~typesafe/jev-latest` | `OPENROUTER_API_KEY` or OpenRouter OAuth |
| `cloudflare-workers-ai` | `typesafe/jev` | `CLOUDFLARE_API_KEY` and `CLOUDFLARE_ACCOUNT_ID` |
| `vercel-ai-gateway` | `typesafe-ai/jev` | `AI_GATEWAY_API_KEY` |
| `opencode` | `jev-1.13`, `jev-1.13-free` | `OPENCODE_API_KEY` |
```typescript
import { builtinModels } from '@earendil-works/pi-ai/providers/all';
packages/ai/scripts/generate-models.ts
+67 -6
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@@ -151,6 +151,7 @@ interface NvidiaNimModelListItem {
interface AiGatewayModel {
id: string;
name?: string;
type?: string;
context_window?: number;
max_tokens?: number;
tags?: string[];
@@ -222,6 +223,9 @@ const TOGETHER_TOGGLE_REASONING_LEVEL_MAP = {
const AI_GATEWAY_MODELS_URL = "https://ai-gateway.vercel.sh/v1";
const AI_GATEWAY_BASE_URL = "https://ai-gateway.vercel.sh";
// TypeSafe-compatible System One endpoint for evaluation models.
// https://vercel.com/docs/ai-gateway/sdks-and-apis/typesafe
const AI_GATEWAY_TYPESAFE_BASE_URL = "https://ai-gateway.vercel.sh/typesafe/v1";
const VERTEX_BASE_URL = "https://{location}-aiplatform.googleapis.com";
const NVIDIA_BASE_URL = "https://integrate.api.nvidia.com/v1";
const NVIDIA_HEADERS = {
@@ -1328,13 +1332,17 @@ async function fetchRadiusModels(): Promise<Model<"pi-messages">[]> {
}
}
async function fetchAiGatewayModels(): Promise<Model<any>[]> {
async function fetchAiGatewayModels(): Promise<{
chat: Model<any>[];
classifiers: ClassifierModel<"typesafe-system-one">[];
}> {
try {
console.log("Fetching models from Vercel AI Gateway API...");
const response = await fetch(`${AI_GATEWAY_MODELS_URL}/models`);
if (!response.ok) throw new Error(`Vercel AI Gateway API returned ${response.status}`);
const data = await response.json();
const models: Model<any>[] = [];
const classifiers: ClassifierModel<"typesafe-system-one">[] = [];
const toNumber = (value: string | number | undefined): number => {
if (typeof value === "number") {
@@ -1346,6 +1354,27 @@ async function fetchAiGatewayModels(): Promise<Model<any>[]> {
const items = Array.isArray(data.data) ? (data.data as AiGatewayModel[]) : [];
for (const model of items) {
// Evaluation models such as TypeSafe's Jev are served through the
// TypeSafe-compatible System One endpoint.
if (model.type === "evaluation") {
classifiers.push({
type: "classifier",
id: model.id,
name: model.name || model.id,
api: "typesafe-system-one",
provider: "vercel-ai-gateway",
baseUrl: AI_GATEWAY_TYPESAFE_BASE_URL,
input: ["text"],
cost: {
input: roundCost(toNumber(model.pricing?.input) * 1_000_000),
output: roundCost(toNumber(model.pricing?.output) * 1_000_000),
cacheRead: 0,
cacheWrite: 0,
},
contextWindow: model.context_window || 4096,
});
continue;
}
const tags = Array.isArray(model.tags) ? model.tags : [];
// Only include models that support tools
if (!tags.includes("tool-use")) continue;
@@ -1380,12 +1409,14 @@ async function fetchAiGatewayModels(): Promise<Model<any>[]> {
});
}
console.log(`Fetched ${models.length} tool-capable models from Vercel AI Gateway`);
return models;
console.log(
`Fetched ${models.length} tool-capable and ${classifiers.length} classifier models from Vercel AI Gateway`,
);
return { chat: models, classifiers };
} catch (error) {
console.error("Failed to fetch Vercel AI Gateway models:", error);
if (generatorOptions.strict) throw error;
return [];
return { chat: [], classifiers: [] };
}
}
@@ -2665,6 +2696,34 @@ async function loadModelsDevClassifierModels(): Promise<ClassifierModel<"typesaf
// Workers AI has no unauthenticated catalog and models.dev does not list its
// System One models yet. Cloudflare publishes pricing only in the dashboard.
// https://developers.cloudflare.com/ai/models/typesafe/jev/
// OpenCode Zen serves Jev through its TypeSafe-compatible System One endpoint.
// Neither its /zen/v1/models listing nor models.dev carries metadata for it.
// https://opencode.ai/docs/zen
const OPENCODE_CLASSIFIER_MODELS: ClassifierModel<"typesafe-system-one">[] = [
{
type: "classifier",
id: "jev-1.13",
name: "Jev 1.13",
api: "typesafe-system-one",
provider: "opencode",
baseUrl: "https://opencode.ai/zen/v1",
input: ["text"],
cost: { input: 0.042, output: 0, cacheRead: 0, cacheWrite: 0 },
contextWindow: 32000,
},
{
type: "classifier",
id: "jev-1.13-free",
name: "Jev 1.13 Free",
api: "typesafe-system-one",
provider: "opencode",
baseUrl: "https://opencode.ai/zen/v1",
input: ["text"],
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
contextWindow: 32000,
},
];
const CLOUDFLARE_WORKERS_AI_CLASSIFIER_MODELS: ClassifierModel<"cloudflare-workers-ai-system-one">[] = [
{
type: "classifier",
@@ -2688,11 +2747,11 @@ async function generateModels() {
const modelsDevModels = await loadModelsDevData();
const modelsDevClassifierModels = await loadModelsDevClassifierModels();
const openRouterCatalog = await fetchOpenRouterModels();
const aiGatewayModels = await fetchAiGatewayModels();
const aiGatewayCatalog = await fetchAiGatewayModels();
const radiusModels = await fetchRadiusModels();
// Combine chat models (models.dev has priority where sources overlap).
const allModels = [...modelsDevModels, ...openRouterCatalog.chat, ...aiGatewayModels, ...radiusModels].filter(
const allModels = [...modelsDevModels, ...openRouterCatalog.chat, ...aiGatewayCatalog.chat, ...radiusModels].filter(
(model) =>
!(model.provider === "xai" && XAI_BUILTIN_EXCLUDED_MODEL_IDS.has(model.id)) &&
!((model.provider === "opencode" || model.provider === "opencode-go") && model.id === "gpt-5.3-codex-spark"),
@@ -3357,6 +3416,8 @@ async function generateModels() {
const classifierModels: ClassifierModel<ClassifierApi>[] = [
...modelsDevClassifierModels,
...openRouterCatalog.classifiers,
...aiGatewayCatalog.classifiers,
...OPENCODE_CLASSIFIER_MODELS,
...CLOUDFLARE_WORKERS_AI_CLASSIFIER_MODELS,
];
for (const model of classifierModels) {
packages/ai/src/providers/opencode.ts
+9 -6
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@@ -2,24 +2,27 @@ import { anthropicMessagesApi } from "../api/anthropic-messages.lazy.ts";
import { googleGenerativeAIApi } from "../api/google-generative-ai.lazy.ts";
import { openAICompletionsApi } from "../api/openai-completions.lazy.ts";
import { openAIResponsesApi } from "../api/openai-responses.lazy.ts";
import { typesafeSystemOneApi } from "../api/typesafe-system-one.lazy.ts";
import { envApiKeyAuth } from "../auth/helpers.ts";
import { createProvider, type Provider } from "../models.ts";
import { OPENCODE_MODELS } from "./opencode.models.ts";
import { OPENCODE_CLASSIFIER_MODELS, OPENCODE_MODELS } from "./opencode.models.ts";
import { withOpenCodeSessionHeader } from "./opencode-headers.ts";
export function opencodeProvider(): Provider<
"anthropic-messages" | "google-generative-ai" | "openai-completions" | "openai-responses"
> {
return createProvider({
type OpenCodeApi = "anthropic-messages" | "google-generative-ai" | "openai-completions" | "openai-responses";
export function opencodeProvider(): Provider<OpenCodeApi> {
return createProvider<OpenCodeApi>({
id: "opencode",
name: "OpenCode Zen",
auth: { apiKey: envApiKeyAuth("OpenCode API key", ["OPENCODE_API_KEY"]) },
models: Object.values(OPENCODE_MODELS),
models: [...Object.values(OPENCODE_MODELS), ...Object.values(OPENCODE_CLASSIFIER_MODELS)],
api: {
"anthropic-messages": withOpenCodeSessionHeader(anthropicMessagesApi()),
"google-generative-ai": withOpenCodeSessionHeader(googleGenerativeAIApi()),
"openai-completions": withOpenCodeSessionHeader(openAICompletionsApi()),
"openai-responses": withOpenCodeSessionHeader(openAIResponsesApi()),
},
// OpenCode Zen serves TypeSafe's System One protocol at /zen/v1/systemone.
classifiers: { "typesafe-system-one": typesafeSystemOneApi() },
});
}
packages/ai/src/providers/vercel-ai-gateway.ts
+6 -3
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@@ -1,15 +1,18 @@
import { anthropicMessagesApi } from "../api/anthropic-messages.lazy.ts";
import { typesafeSystemOneApi } from "../api/typesafe-system-one.lazy.ts";
import { envApiKeyAuth } from "../auth/helpers.ts";
import { createProvider, type Provider } from "../models.ts";
import { VERCEL_AI_GATEWAY_MODELS } from "./vercel-ai-gateway.models.ts";
import { VERCEL_AI_GATEWAY_CLASSIFIER_MODELS, VERCEL_AI_GATEWAY_MODELS } from "./vercel-ai-gateway.models.ts";
export function vercelAIGatewayProvider(): Provider<"anthropic-messages"> {
return createProvider({
return createProvider<"anthropic-messages">({
id: "vercel-ai-gateway",
name: "Vercel AI Gateway",
baseUrl: "https://ai-gateway.vercel.sh",
auth: { apiKey: envApiKeyAuth("Vercel AI Gateway API key", ["AI_GATEWAY_API_KEY"]) },
models: Object.values(VERCEL_AI_GATEWAY_MODELS),
models: [...Object.values(VERCEL_AI_GATEWAY_MODELS), ...Object.values(VERCEL_AI_GATEWAY_CLASSIFIER_MODELS)],
api: anthropicMessagesApi(),
// AI Gateway serves TypeSafe's System One protocol at /typesafe/v1/systemone.
classifiers: { "typesafe-system-one": typesafeSystemOneApi() },
});
}
packages/ai/test/classifier-models.test.ts
+35
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@@ -127,6 +127,41 @@ describe("Models with classifier models", () => {
expect(models.getModelOfType("classifier", "typesafe", "jev-latest")).toEqual(jev);
});
it.each([
["vercel-ai-gateway", "typesafe-ai/jev", "https://ai-gateway.vercel.sh/typesafe/v1/systemone"],
["opencode", "jev-1.13", "https://opencode.ai/zen/v1/systemone"],
["opencode", "jev-1.13-free", "https://opencode.ai/zen/v1/systemone"],
])("routes %s Jev (%s) to its TypeSafe-compatible endpoint", async (provider, id, url) => {
const models = builtinModels();
const jev = models.getModelOfType("classifier", provider, id);
if (!jev) throw new Error(`missing ${provider} Jev model`);
expect(jev).toMatchObject({ api: "typesafe-system-one", contextWindow: 32000 });
expect(models.getModel(provider, id)).toBeUndefined();
const requests: Array<{ url: string; body: Record<string, unknown>; authorization: string | null }> = [];
const result = await models.classify(jev, context, {
apiKey: "secret",
fetch: async (input, init) => {
requests.push({
url: String(input),
body: JSON.parse(String(init?.body)) as Record<string, unknown>,
authorization: new Headers(init?.headers).get("authorization"),
});
return Response.json({ model: id, answers: { approved: { type: "noul", noul: 0.8 } } });
},
});
expect(requests).toEqual([
{
url,
body: expect.objectContaining({ model: id, state: context.state }),
authorization: "Bearer secret",
},
]);
expect(result.stopReason).toBe("stop");
expect(result.answers.approved).toEqual({ type: "bool", probability: 0.8 });
});
it("routes OpenRouter classifier models through the System One API", () => {
const models = builtinModels();
for (const model of getBuiltinClassifierModels("openrouter")) {
packages/coding-agent/docs/models.md
+3 -1
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@@ -102,13 +102,15 @@ Compatibility settings should describe verified differences in the endpoint's re
## Use classifier models
Classifier models do not chat. They answer typed questions about JSON state: pick one of several choices, answer yes or no, or give a score, each with probabilities. Pi includes TypeSafe's Jev model from three providers:
Classifier models do not chat. They answer typed questions about JSON state: pick one of several choices, answer yes or no, or give a score, each with probabilities. Pi includes TypeSafe's Jev model from these providers:
| Provider | Model IDs | Authentication |
|---|---|---|
| `typesafe` | `jev-latest` | `TYPESAFE_API_KEY` |
| `openrouter` | `typesafe/jev-1.13`, `~typesafe/jev-latest` | `OPENROUTER_API_KEY` or `/login` |
| `cloudflare-workers-ai` | `typesafe/jev` | `CLOUDFLARE_API_KEY` and `CLOUDFLARE_ACCOUNT_ID` |
| `vercel-ai-gateway` | `typesafe-ai/jev` | `AI_GATEWAY_API_KEY` |
| `opencode` | `jev-1.13`, `jev-1.13-free` | `OPENCODE_API_KEY` |
Chat models on a [llama.cpp router](llama-cpp.md#classification) are also listed as classifier models.