arize-ai-provider-integration

# Arize AI Integration Skill

## Concepts

- **AI Integration** = stored LLM provider credentials registered in Arize; used by evaluators to call a judge model and by other Arize features that need to invoke an LLM on your behalf
- **Provider** = the LLM service backing the integration (e.g., `openAI`, `anthropic`, `awsBedrock`)
- **Integration ID** = a base64-encoded global identifier for an integration (e.g., `TGxtSW50ZWdyYXRpb246MTI6YUJjRA==`); required for evaluator creation and other downstream operations
- **Scoping** = visibility rules controlling which spaces or users can use an integration
- **Auth type** = how Arize authenticates with the provider: `default` (provider API key), `proxy_with_headers` (proxy via custom headers), or `bearer_token` (bearer token auth)

## Prerequisites

Proceed directly with the task — run the `ax` command you need. Do NOT check versions, env vars, or profiles upfront.

If an `ax` command fails, troubleshoot based on the error:
- `command not found` or version error → see references/ax-setup.md
- `401 Unauthorized` / missing API key → run `ax profiles show` to inspect the current profile. If the profile is missing or the API key is wrong: check `.env` for `ARIZE_API_KEY` and use it to create/update the profile via references/ax-profiles.md. If `.env` has no key either, ask the user for their Arize API key (https://app.arize.com/admin > API Keys)
- Space ID unknown → check `.env` for `ARIZE_SPACE_ID`, or run `ax spaces list -o json`, or ask the user
- LLM provider call fails (missing OPENAI_API_KEY / ANTHROPIC_API_KEY) → check `.env`, load if present, otherwise ask the user

---

## List AI Integrations

List all integrations accessible in a space:

```bash
ax ai-integrations list --space-id SPACE_ID
```

Filter by name (case-insensitive substring match):

```bash
ax ai-integrations list --space-id SPACE_ID --name "openai"
```

Paginate large result sets:

```bash
# Get first page
ax ai-integrations list --space-id SPACE_ID --limit 20 -o json

# Get next page using cursor from previous response
ax ai-integrations list --space-id SPACE_ID --limit 20 --cursor CURSOR_TOKEN -o json
```

**Key flags:**

| Flag | Description |
|------|-------------|
| `--space-id` | Space to list integrations in |
| `--name` | Case-insensitive substring filter on integration name |
| `--limit` | Max results (1–100, default 50) |
| `--cursor` | Pagination token from a previous response |
| `-o, --output` | Output format: `table` (default) or `json` |

**Response fields:**

| Field | Description |
|-------|-------------|
| `id` | Base64 integration ID — copy this for downstream commands |
| `name` | Human-readable name |
| `provider` | LLM provider enum (see Supported Providers below) |
| `has_api_key` | `true` if credentials are stored |
| `model_names` | Allowed model list, or `null` if all models are enabled |
| `enable_default_models` | Whether default models for this provider are allowed |
| `function_calling_enabled` | Whether tool/function calling is enabled |
| `auth_type` | Authentication method: `default`, `proxy_with_headers`, or `bearer_token` |

---

## Get a Specific Integration

```bash
ax ai-integrations get INT_ID
ax ai-integrations get INT_ID -o json
```

Use this to inspect an integration's full configuration or to confirm its ID after creation.

---

## Create an AI Integration

Before creating, always list integrations first — the user may already have a suitable one:

```bash
ax ai-integrations list --space-id SPACE_ID
```

If no suitable integration exists, create one. The required flags depend on the provider.

### OpenAI

```bash
ax ai-integrations create \
  --name "My OpenAI Integration" \
  --provider openAI \
  --api-key $OPENAI_API_KEY
```

### Anthropic

```bash
ax ai-integrations create \
  --name "My Anthropic Integration" \
  --provider anthropic \
  --api-key $ANTHROPIC_API_KEY
```

### Azure OpenAI

```bash
ax ai-integrations create \
  --name "My Azure OpenAI Integration" \
  --provider azureOpenAI \
  --api-key $AZURE_OPENAI_API_KEY \
  --base-url "https://my-resource.openai.azure.com/"
```

### AWS Bedrock

AWS Bedrock uses IAM role-based auth instead of an API key. Provide the ARN of the role Arize should assume:

```bash
ax ai-integrations create \
  --name "My Bedrock Integration" \
  --provider awsBedrock \
  --role-arn "arn:aws:iam::123456789012:role/ArizeBedrockRole"
```

### Vertex AI

Vertex AI uses GCP service account credentials. Provide the GCP project and region:

```bash
ax ai-integrations create \
  --name "My Vertex AI Integration" \
  --provider vertexAI \
  --project-id "my-gcp-project" \
  --location "us-central1"
```

### Gemini

```bash
ax ai-integrations create \
  --name "My Gemini Integration" \
  --provider gemini \
  --api-key $GEMINI_API_KEY
```

### NVIDIA NIM

```bash
ax ai-integrations create \
  --name "My NVIDIA NIM Integration" \
  --provider nvidiaNim \
  --api-key $NVIDIA_API_KEY \
  --base-url "https://integrate.api.nvidia.com/v1"
```

### Custom (OpenAI-compatible endpoint)

```bash
ax ai-integrations create \
  --name "My Custom Integration" \
  --provider custom \
  --base-url "https://my-llm-proxy.example.com/v1" \
  --api-key $CUSTOM_LLM_API_KEY
```

### Supported Providers

| Provider | Required extra flags |
|----------|---------------------|
| `openAI` | `--api-key <key>` |
| `anthropic` | `--api-key <key>` |
| `azureOpenAI` | `--api-key <key>`, `--base-url <azure-endpoint>` |
| `awsBedrock` | `--role-arn <arn>` |
| `vertexAI` | `--project-id <gcp-project>`, `--location <region>` |
| `gemini` | `--api-key <key>` |
| `nvidiaNim` | `--api-key <key>`, `--base-url <nim-endpoint>` |
| `custom` | `--base-url <endpoint>` |

### Optional flags for any provider

| Flag | Description |
|------|-------------|
| `--model-names` | Comma-separated list of allowed model names; omit to allow all models |
| `--enable-default-models` / `--no-default-models` | Enable or disable the provider's default model list |
| `--function-calling` / `--no-function-calling` | Enable or disable tool/function calling support |

### After creation

Capture the returned integration ID (e.g., `TGxtSW50ZWdyYXRpb246MTI6YUJjRA==`) — it is needed for evaluator creation and other downstream commands. If you missed it, retrieve it:

```bash
ax ai-integrations list --space-id SPACE_ID -o json
# or, if you know the ID:
ax ai-integrations get INT_ID
```

---

## Update an AI Integration

`update` is a partial update — only the flags you provide are changed. Omitted fields stay as-is.

```bash
# Rename
ax ai-integrations update INT_ID --name "New Name"

# Rotate the API key
ax ai-integrations update INT_ID --api-key $OPENAI_API_KEY

# Change the model list
ax ai-integrations update INT_ID --model-names "gpt-4o,gpt-4o-mini"

# Update base URL (for Azure, custom, or NIM)
ax ai-integrations update INT_ID --base-url "https://new-endpoint.example.com/v1"
```

Any flag accepted by `create` can be passed to `update`.

---

## Delete an AI Integration

**Warning:** Deletion is permanent. Evaluators that reference this integration will no longer be able to run.

```bash
ax ai-integrations delete INT_ID --force
```

Omit `--force` to get a confirmation prompt instead of deleting immediately.

---

## Troubleshooting

| Problem | Solution |
|---------|----------|
| `ax: command not found` | See references/ax-setup.md |
| `401 Unauthorized` | API key may not have access to this space. Verify key and space ID at https://app.arize.com/admin > API Keys |
| `No profile found` | Run `ax profiles show --expand`; set `ARIZE_API_KEY` env var or write `~/.arize/config.toml` |
| `Integration not found` | Verify with `ax ai-integrations list --space-id SPACE_ID` |
| `has_api_key: false` after create | Credentials were not saved — re-run `update` with the correct `--api-key` or `--role-arn` |
| Evaluator runs fail with LLM errors | Check integration credentials with `ax ai-integrations get INT_ID`; rotate the API key if needed |
| `provider` mismatch | Cannot change provider after creation — delete and recreate with the correct provider |

---

## Related Skills

- **arize-evaluator**: Create LLM-as-judge evaluators that use an AI integration → use `arize-evaluator`
- **arize-experiment**: Run experiments that use evaluators backed by an AI integration → use `arize-experiment`

---

## Save Credentials for Future Use

See references/ax-profiles.md § Save Credentials for Future Use.