wafer_AI/docs/serverless/router-setup.md

Documentation Index

Fetch the complete documentation index at: https://docs.wafer.ai/llms.txt Use this file to discover all available pages before exploring further.

Router Setup

Use Wafer through Vercel AI Gateway, OpenRouter, and TrueFoundry AI Gateway.

Use these setup paths when your app already sends traffic through a model router or gateway. The router owns the API key, base URL, model slug, billing, and routing policy; Wafer serves the underlying model capacity.

For direct Wafer Serverless API usage, use API Reference. For coding agents and local harnesses, use Agent Setup.

Vercel

Wafer is available through Vercel AI Gateway for GLM 5.2 Fast.

Use the Vercel AI SDK model slug:

import { streamText } from "ai";

const result = streamText({
  model: "zai/glm-5.2-fast",
  prompt: "Why is the sky blue?",
});

See Vercel's GLM 5.2 Fast via Wafer changelog for provider-specific details.

OpenRouter

Wafer is listed as a provider on OpenRouter.

Use OpenRouter when you want Wafer models behind OpenRouter's unified API key, catalog, usage tracking, and routing controls.

OpenRouter model slugs are model-level slugs, not provider-specific slugs. To prefer GLM 5.2 Fast on Wafer, use z-ai/glm-5.2 and put the Wafer Fast provider endpoint first with provider.order: ["wafer/fast"].

Use the full endpoint slug `wafer/fast`. The base slug `wafer` matches all Wafer endpoints for this model, including the standard Wafer endpoint. Fallbacks remain enabled, so OpenRouter can route to another available endpoint if Wafer Fast is unavailable.

curl -sS "https://openrouter.ai/api/v1/chat/completions" \
  -H "Authorization: Bearer <YOUR_OPENROUTER_API_KEY>" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "z-ai/glm-5.2",
    "provider": {
      "order": ["wafer/fast"]
    },
    "messages": [
      {"role": "user", "content": "Reply with the single word: ready."}
    ]
  }'

See OpenRouter's Quickstart for the API shape and Provider Routing for provider selection controls.

TrueFoundry

TrueFoundry AI Gateway is the proxy layer that sits between your applications and the LLM providers and MCP Servers. It is an enterprise-grade platform that enables users to access 1000+ LLMs using a unified interface while taking care of observability and governance.

Wafer is available natively in TrueFoundry AI Gateway. See TrueFoundry's Wafer provider docs for the source setup flow.

In TrueFoundry, go to **AI Gateway** → **Models**, select **Wafer**, and add your Wafer account.

The default Wafer base URL is `https://pass.wafer.ai/v1`. Change it only if Wafer directs you to a different endpoint. Add your Wafer API key for authentication. Zero Data Retention is enabled by default; when enabled, TrueFoundry sends `Wafer-ZDR: required` on requests.

Add collaborators to the account if other users or teams should be able to access it.

Click **+ Add Models** and register the Wafer model IDs you want TrueFoundry to expose. For each model, set a display name, the exact Wafer model ID, and select **Chat** as the model type.

Common Wafer model IDs include `GLM-5.2`, `glm5.2-fast`, and `GLM-5.1`.

Use the TrueFoundry model ID format `your-wafer-account/model-display-name` through TrueFoundry's OpenAI-compatible `/chat/completions` API:

```python theme={null}
from openai import OpenAI

client = OpenAI(
    api_key="your_truefoundry_api_key",
    base_url="{GATEWAY_BASE_URL}",
)

response = client.chat.completions.create(
    model="my-wafer-account/GLM-5.2",
    messages=[{"role": "user", "content": "Hello, how are you?"}],
)

print(response.choices[0].message.content)
```