Skyvern/docs/sdk-reference/error-handling.mdx

---
title: Error Handling
subtitle: Handle API errors, timeouts, and configure retries
description: Handle API errors, timeouts, and configure retries in the Skyvern Python SDK. Covers error types, exception handling, HTTP and completion timeouts, retry configuration, and run failure vs API error patterns.
slug: sdk-reference/error-handling
keywords:
  - BadRequestError
  - ForbiddenError
  - NotFoundError
  - ConflictError
  - UnprocessableEntityError
  - timeout
  - retry
  - polling
  - run status
  - failure
---

The SDK raises typed exceptions for API errors. All errors extend `ApiError` and include the HTTP status code, response headers, and body.

---

## Error types

| Exception | Status Code | When it's raised |
|-----------|-------------|------------------|
| `BadRequestError` | 400 | Invalid request parameters. |
| `ForbiddenError` | 403 | Invalid or missing API key. |
| `NotFoundError` | 404 | Resource (run, workflow, session) not found. |
| `ConflictError` | 409 | Resource conflict (e.g., duplicate creation). |
| `UnprocessableEntityError` | 422 | Request validation failed. |
| `ApiError` | Any | Base class for all API errors. Catch this as a fallback. |

The specific error classes live in `skyvern.client.errors`. The base `ApiError` class lives in `skyvern.client.core`:

```python
from skyvern.client.core import ApiError
from skyvern.client.errors import (
    BadRequestError,
    ForbiddenError,
    NotFoundError,
    ConflictError,
    UnprocessableEntityError,
)
```

---

## Catching errors

```python
from skyvern import Skyvern
from skyvern.client.core import ApiError
from skyvern.client.errors import NotFoundError

client = Skyvern(api_key="YOUR_API_KEY")

try:
    run = await client.get_run("tsk_nonexistent")
except NotFoundError as e:
    print(f"Run not found: {e.body}")
except ApiError as e:
    print(f"API error {e.status_code}: {e.body}")
```

### Error properties

Every error has these attributes:

| Property | Type | Description |
|----------|------|-------------|
| `status_code` | `int \| None` | HTTP status code. |
| `body` | `Any` | Response body (usually a dict with error details). |
| `headers` | `dict[str, str] \| None` | Response headers. |

---

## Timeouts

Two different timeouts apply:

### HTTP request timeout

Controls how long the SDK waits for the HTTP response from the Skyvern API. Set it in the constructor or per-request:

```python
# Global timeout (applies to all requests)
client = Skyvern(api_key="YOUR_API_KEY", timeout=30.0)

# Per-request timeout
from skyvern.client.core import RequestOptions

result = await client.get_run(
    "tsk_abc123",
    request_options=RequestOptions(timeout_in_seconds=10),
)
```

### Completion timeout

Controls how long `wait_for_completion` polls before giving up. This is separate from the HTTP timeout:

```python
try:
    result = await client.run_task(
        prompt="Extract data",
        url="https://example.com",
        wait_for_completion=True,
        timeout=300,  # Give up after 5 minutes
    )
except TimeoutError:
    print("Task didn't complete in time")
```

The completion timeout raises Python's built-in `TimeoutError` (via `asyncio.timeout`), not `ApiError`.

---

## Retries

Configure automatic retries for transient failures using `RequestOptions`:

```python
from skyvern.client.core import RequestOptions

result = await client.run_task(
    prompt="Extract product data",
    url="https://example.com/products",
    request_options=RequestOptions(max_retries=3),
)
```

Retries apply to the HTTP request level (network errors, 5xx responses). They do not retry the entire task if it fails at the AI level — use `get_run` to check the status and re-run if needed.

---

## Run failure vs API errors

There are two distinct failure modes:

**API error** — The HTTP request itself failed. The SDK raises an exception.

```python
from skyvern.client.core import ApiError

try:
    result = await client.run_task(prompt="...")
except ApiError as e:
    print(f"API call failed: {e.status_code}")
```

**Run failure** — The API call succeeded, but the task/workflow failed during execution. No exception is raised. Check the `status` field:

```python
result = await client.run_task(
    prompt="Fill out the form",
    url="https://example.com",
    wait_for_completion=True,
)

if result.status == "failed":
    print(f"Task failed: {result.failure_reason}")
elif result.status == "timed_out":
    print(f"Task exceeded step limit after {result.step_count} steps")
elif result.status == "completed":
    print(f"Success: {result.output}")
```

### Run statuses

| Status | Description |
|--------|-------------|
| `created` | Run initialized, not yet queued. |
| `queued` | Waiting for an available browser. |
| `running` | AI is executing. |
| `completed` | Finished successfully. |
| `failed` | Encountered an error during execution. |
| `terminated` | Manually stopped. |
| `timed_out` | Exceeded step limit (`max_steps`). |
| `canceled` | Canceled before starting. |