wafer_AI/docs/errors.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.

# Error Reference

> Every error code returned by the Wafer API, what causes it, and what to do about it.

When a request to Wafer fails, the response body carries a structured error
envelope you can branch on:

```json theme={null}
{
  "error": {
    "type":       "invalid_request_error",
    "code":       "tool_schema_invalid",
    "message":    "tools[0].function.parameters must be a JSON Schema object",
    "param":      "tools[0].function.parameters",
    "request_id": "req_a1b2c3d4e5f6",
    "docs_url":   "https://docs.wafer.ai/errors#tool_schema_invalid"
  }
}
```

The same envelope ships from `pass.wafer.ai` (OpenAI- and Anthropic-compatible
inference endpoints) and from `api.wafer.ai` (account, billing, and key
management). Anthropic-compatible responses wrap the same fields under
`{"type":"error","error":{...}}`.

Every response — success or failure — also carries the `x-request-id`
header. Include that ID when contacting support.

<Note>
  When you include an `x-request-id` header on your request, Wafer echoes
  it back instead of generating one, so you can correlate with your
  application logs. To keep server- and client-supplied IDs separate in
  our logs, Wafer prefixes client values with `client_`. Server-generated
  IDs match `req_<12 hex>` exactly; anything else you send is prefixed.
</Note>

## How to use this page

`type` is the coarse bucket — your SDK probably already maps it to a
typed exception class (`RateLimitError`, `BadRequestError`, etc).
`code` is the specific reason within that bucket and the right thing
to branch on programmatically. Each anchor below documents one `code`.

## Bucket: `invalid_request_error` (400 / 422)

### `schema_validation_failed`

**Status:** `422`

The request body didn't match the endpoint's schema. `error.param` points at
the offending field path (e.g. `messages[0].content`, `amount_cents`).

**What to do:** read `error.param` and `error.message`, fix the field, and
retry.

### `tool_schema_invalid`

**Status:** `400`

A function tool you passed has an invalid `parameters` block. We pre-validate
that `parameters` is a JSON Schema object (`type: "object"` with a
`properties` dict) before forwarding, because the underlying backends 400 with
unhelpful Pydantic errors.

**What to do:** confirm `tools[i].function.parameters` matches the [OpenAI
function-calling spec](https://platform.openai.com/docs/guides/function-calling).

### `tool_choice_unknown_tool`

**Status:** `400`

`tool_choice.function.name` doesn't match any tool you declared in `tools`.

**What to do:** ensure the tool name in `tool_choice` is one of the
`tools[].function.name` values in the same request.

### `orphan_tool_message`

**Status:** `400`

A `role=tool` message references a `tool_call_id` that no preceding assistant
message issued. Every `tool` message must follow an assistant message whose
`tool_calls[]` contains a matching `id`.

**What to do:** check that your conversation history is intact — every tool
result must be preceded by the assistant turn that requested it.

### `missing_tool_call_id`

**Status:** `400`

A `role=tool` message is missing its `tool_call_id` field. The field is
required so we can pair the result back to the assistant's request.

### `unsupported_parameter`

**Status:** `400`

A request parameter is not supported on the endpoint or for the selected
model (e.g. `previous_response_id`, `logit_bias` on some backends).

**What to do:** remove the parameter, or check the [Models](/serverless/setup#models)
page for per-model support.

### `unsupported_feature`

**Status:** `400`

The selected model does not support a requested feature that Wafer can detect
before dispatch. For example, models that do not advertise
`wafer.capabilities.chat_completions.n: true` reject `n > 1` with
`param: "n"`, and models without streaming tool-call support reject streaming
tool requests with `param: "tools"`.

**What to do:** remove the feature, or switch to a model whose `/v1/models`
card advertises support for that field.

### `unsupported_response_format`

**Status:** `400`

The selected model does not support the requested `response_format.type`.
For example, Fireworks-style `response_format.type = "grammar"` is only
accepted on models whose `/v1/models` card advertises
`wafer.capabilities.chat_completions.grammar: true`.

**What to do:** remove the unsupported `response_format`, or choose a model
whose `wafer.capabilities` block advertises support for that format.

### `unsupported_regex`

**Status:** `400`

The selected model or ZDR partition does not support top-level `regex`.
Wafer rejects this before dispatch instead of letting the upstream silently
ignore the constraint.

**What to do:** remove `regex`, switch to a model that advertises
`wafer.capabilities.chat_completions.regex: true`, or add
`Wafer-ZDR: required` when the model's `/v1/models` card shows regex support
only on the ZDR partition.

### `unsupported_tool_type`

**Status:** `400`

Only `tools[i].type == "function"` is supported on the OpenAI-compatible
endpoint. (Anthropic-side tool types are translated upstream.)

### `json_schema_refs_unsupported`

**Status:** `400`

The request included JSON Schema references that Wafer could not safely inline,
such as a remote `$ref`, an unresolved local `$ref`, or a recursive schema.
Wafer Serverless automatically inlines safe local references like
`#/$defs/...` and `#/definitions/...` for compatible models.

**What to do:** inline remote or recursive schemas client-side, or remove the
unsupported reference before retrying.

### `duplicate_tool_name`

**Status:** `400`

Two entries in `tools` declare the same `function.name`. Tool names must be
unique within a request.

### `context_length_exceeded`

**Status:** `400`

The request would exceed the selected model's context window. The error body
includes structured fields to help you switch models programmatically:

```json theme={null}
{
  "error": {
    "type": "invalid_request_error",
    "code": "context_length_exceeded",
    "message": "The request exceeded GLM-5.1's context window (max_model_len=202752). Reduce the prompt length, compact your conversation, or lower max_tokens. Try a model with a larger context window: Qwen3.5-397B-A17B (256K context).",
    "model": "GLM-5.1",
    "context_length_limit": 202752,
    "suggested_models": [
      {"id": "Qwen3.5-397B-A17B", "context_length": 262144}
    ],
    "request_id": "req_..."
  }
}
```

**What to do:** lower `max_tokens`, trim the prompt, or retry against one of
`suggested_models`.

### `model_not_found`

**Status:** `404`

The `model` value in your request doesn't match any model your key can
access. The error message includes the list of available models for your
key tier.

### `model_not_allowed`

**Status:** `403`

The model exists but your key isn't entitled to it (e.g. a Serverless key
hitting a model only available through a paid plan, or a key from an
account whose plan doesn't include the model).

**What to do:** pick a model from the list your key has access to, or
upgrade your plan. Call `GET https://pass.wafer.ai/v1/models` for live
availability for the bearer key.

### `invalid_zdr_header`

**Status:** `400`

The `Wafer-ZDR` request header was present but its value isn't `required`
(the only accepted value).

**What to do:** either drop the header or send `Wafer-ZDR: required`. See
[Zero Data Retention](/serverless/zero-data-retention).

### `invalid_request_tag`

**Status:** `400`

The `Wafer-Request-Tag` header was present but the value doesn't match
the allowed shape: lowercase ASCII, digits, dashes, underscores,
1–32 characters (`^[a-z0-9_-]{1,32}$`). When you send multiple
`Wafer-Request-Tag` headers on one request, the error message
identifies which value failed so you don't have to bisect.

**What to do:** confirm each header value matches the regex. Common
causes: uppercase characters, spaces, special punctuation, an empty
string, or a value longer than 32 chars. The same error fires if you
send more than 8 distinct tags on one request. See
[Request Tagging](/dedicated-endpoints/request-inspection#request-tagging).
Dedicated endpoints only — this code never fires on serverless keys
(the header is silently ignored there).

### `model_zdr_not_supported`

**Status:** `400`

The request set `Wafer-ZDR: required` against a model whose backend
doesn't support zero data retention. Currently `GLM-5.2`,
`glm5.2-fast` and `GLM-5.1` support
ZDR; other Serverless models do not.

**What to do:** drop the header to use the model without ZDR, or switch
to a ZDR-eligible model. The model list at
[Agent Setup](/serverless/setup#models) marks per-model ZDR support.

### `invalid_json_request`

**Status:** `400`

The request body wasn't valid JSON, or the JSON shape didn't include the
required top-level fields (e.g. an empty body sent to
`/v1/chat/completions`).

**What to do:** confirm `Content-Type: application/json` and that the
body parses as JSON. Common cause: an SDK serializing `None` / `undefined`
instead of a request object.

### `request_body_too_large`

**Status:** `413`

The request body exceeded the per-route size cap (50 MB).

**What to do:** for large prompts, compact your conversation, or upload
large media via the [Files API](/serverless/files-api) and reference the
returned `file_id` in your content blocks instead of inlining bytes.

## Bucket: `authentication_error` (401)

### `missing_api_key`

**Status:** `401`

No credentials on the request. Confirm the `Authorization: Bearer <key>`
header (or `x-api-key: <key>`) is present.

### `invalid_api_key`

**Status:** `401`

The key was sent but doesn't match a live Wafer key. Common causes: the
key was revoked (see [API Keys](/serverless/api-keys)), the key was
copied with surrounding whitespace, or it was generated for a different
environment.

Pass keys and Serverless keys both start with `wfr_`.

## Bucket: `permission_error` (403)

### `http_403`

**Status:** `403`

The key is valid but doesn't have access to this endpoint or resource
(e.g. a Pass key trying to hit a dedicated endpoint, or a key from a
different account).

### `files_require_user_key`

**Status:** `403`

The bearer key is a non-user-scoped legacy key and cannot upload to the
[Files API](/serverless/files-api). Only modern, user-scoped Serverless
keys can own files.

**What to do:** mint a fresh Serverless key from
[app.wafer.ai](https://app.wafer.ai) and use it for the upload. Older
keys keep working for inference; only file ownership requires a
user-scoped key.

## Bucket: `rate_limit_error` (429)

429 responses include three standard headers SDKs read for backoff:

* `Retry-After` — seconds until the next retry should be attempted
* `RateLimit-Limit` — the cap for this window
* `RateLimit-Remaining` — `0` when at-cap
* `RateLimit-Reset` — seconds until the limit resets

### `concurrency_limit_exceeded`

**Status:** `429`

Too many in-flight requests on the account. Wait briefly (1–2s) and retry
with exponential backoff. `Retry-After: 1` is set as a hint.

### `request_quota_exceeded`

**Status:** `429`

The account hit its included-request limit for the current window. The body
includes `request_limit`, `window_end`, and (when known) `plan_tier`:

```json theme={null}
{
  "error": {
    "type": "rate_limit_error",
    "code": "request_quota_exceeded",
    "message": "You have gone over your plan request limit ...",
    "request_limit": 500,
    "window_end": "2026-05-21T20:00:00+00:00",
    "plan_tier": "pro",
    "request_id": "req_..."
  }
}
```

`plan_tier` is omitted from the body when the account's plan tier isn't
known at the edge — branch on key presence, not on `null`.

**What to do:** wait for `window_end`, upgrade your plan, or enable overage
in your dashboard.

### `rate_limit_exceeded`

**Status:** `429`

A general rate-limit hit (e.g. on a control-plane endpoint). Check
`Retry-After` and back off.

### `backend_at_capacity`

**Status:** `429`

The per-route concurrency cap on the selected model was hit. This is a
backpressure signal, not an account-level throttle — other accounts can
also hit it simultaneously when a model is busy.

This code also covers the upstream queue-full case: a backend that
returns its own 503 with a "queue full" signal is rewritten to a `429`
with this code so your SDK's `RateLimitError` retry path takes over
instead of treating it as a server outage.

**What to do:** retry with exponential backoff. The condition typically
clears in 1–2 seconds. `Retry-After` is set when the upstream provided
one.

### `backend_overloaded`

**Status:** `429`

The selected backend reported itself overloaded with a 429 of its own.
Distinct from `backend_at_capacity` (which is the edge-side cap) — this
one originated upstream.

**What to do:** retry with exponential backoff.

## Bucket: `insufficient_credits` (402)

### `insufficient_credits`

**Status:** `402`

Your Wafer Serverless prepaid balance is insufficient for the request. The
body includes an estimate of available vs. required credits:

```json theme={null}
{
  "error": {
    "type": "insufficient_credits",
    "code": "insufficient_credits",
    "message": "Your Wafer Serverless balance is approximately $0.12 ...",
    "credits_available_cents": 12,
    "credits_required_cents_estimate": 50,
    "topup_url": "https://app.wafer.ai/usage",
    "request_id": "req_..."
  }
}
```

**What to do:** add credits at `topup_url`, or enable auto-top-off in your
dashboard.

## Bucket: `routing_error` / `server_error` (502 / 503 / 504)

### `no_healthy_backends`

**Status:** `503`

All backends for the requested model are currently unavailable. Oncall is
notified automatically when this fires. The error body includes the affected
`model`.

**What to do:** retry with exponential backoff. If the issue persists for
more than a minute, check [status.wafer.ai](https://status.wafer.ai) or
contact support with your `request_id`.

### `backend_timeout`

**Status:** `504`

The selected backend accepted the request but didn't produce a response in
time. The error body includes the `model`.

**What to do:** retry. Backends auto-recover; a single 504 is usually
transient.

### `backend_connect_error`

**Status:** `502`

We couldn't open a connection to the selected backend.

**What to do:** retry — our router will pick a different backend on the next
attempt.

### `backend_http_error`

**Status:** `502`

The backend returned an HTTP error we couldn't interpret. Includes `model`.

**What to do:** retry. If it persists, send us your `request_id`.

## Bucket: `internal_error` (500)

### `internal_error`

**Status:** `500`

Something on our side went wrong and the cause didn't fit any specific
bucket. The `request_id` is the load-bearing piece — send it with your bug
report and we can find the exact failure in our logs.

**What to do:** retry once. If it reproduces, file a bug with the
`request_id` and (if relevant) the request body.

## SDK quickstart

### Python (`openai`)

```python theme={null}
from openai import OpenAI, BadRequestError, RateLimitError

client = OpenAI(api_key="wfr_...", base_url="https://pass.wafer.ai/v1")

try:
    resp = client.chat.completions.create(
        model="GLM-5.1",
        messages=[{"role": "user", "content": "..."}],
    )
except BadRequestError as e:
    # e.body holds the unified envelope. Read the structured code.
    err = (e.body or {}).get("error", {})
    code = err.get("code")
    if code == "context_length_exceeded":
        # Try a suggested model
        for alt in err.get("suggested_models", []):
            print("retry with", alt["id"])
    elif code == "tool_schema_invalid":
        print("bad tool param:", err.get("param"))
    print("request_id:", err.get("request_id"))
except RateLimitError as e:
    # Honor Retry-After header from e.response.headers
    print("retry after:", e.response.headers.get("Retry-After"))
```

### Python (`anthropic`)

```python theme={null}
from anthropic import Anthropic, APIStatusError

client = Anthropic(api_key="wfr_...", base_url="https://pass.wafer.ai")

try:
    resp = client.messages.create(
        model="GLM-5.1",
        max_tokens=1024,
        messages=[{"role": "user", "content": "..."}],
    )
except APIStatusError as e:
    err = (e.body or {}).get("error", {})
    print("code:", err.get("code"), "request_id:", err.get("request_id"))
```

When filing a support ticket, always include the `request_id` (from the
`x-request-id` header or the `error.request_id` field). With that, we can
look up the exact request in our logs.