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arize-ai-provider-integration

INVOKE THIS SKILL when creating, reading, updating, or deleting Arize AI integrations. Covers listing integrations, creating integrations for any supported LLM provider (OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Vertex AI, Gemini, NVIDIA NIM, custom), updating credentials or metadata, and deleting integrations using the ax CLI.

インストール方法を見る

含まれるファイル(3)

  • SKILL.md8.7 KB
  • references/ax-profiles.md4.4 KB
  • references/ax-setup.md1.5 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

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:

ax ai-integrations list --space-id SPACE_ID

Filter by name (case-insensitive substring match):

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

Paginate large result sets:

# 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:

FlagDescription
--space-idSpace to list integrations in
--nameCase-insensitive substring filter on integration name
--limitMax results (1–100, default 50)
--cursorPagination token from a previous response
-o, --outputOutput format: table (default) or json

Response fields:

FieldDescription
idBase64 integration ID — copy this for downstream commands
nameHuman-readable name
providerLLM provider enum (see Supported Providers below)
has_api_keytrue if credentials are stored
model_namesAllowed model list, or null if all models are enabled
enable_default_modelsWhether default models for this provider are allowed
function_calling_enabledWhether tool/function calling is enabled
auth_typeAuthentication method: default, proxy_with_headers, or bearer_token

Get a Specific Integration

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:

ax ai-integrations list --space-id SPACE_ID

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

OpenAI

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

Anthropic

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

Azure OpenAI

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:

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:

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

Gemini

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

NVIDIA NIM

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)

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

ProviderRequired 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

FlagDescription
--model-namesComma-separated list of allowed model names; omit to allow all models
--enable-default-models / --no-default-modelsEnable or disable the provider's default model list
--function-calling / --no-function-callingEnable 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:

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.

# 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.

ax ai-integrations delete INT_ID --force

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


Troubleshooting

ProblemSolution
ax: command not foundSee references/ax-setup.md
401 UnauthorizedAPI key may not have access to this space. Verify key and space ID at https://app.arize.com/admin > API Keys
No profile foundRun ax profiles show --expand; set ARIZE_API_KEY env var or write ~/.arize/config.toml
Integration not foundVerify with ax ai-integrations list --space-id SPACE_ID
has_api_key: false after createCredentials were not saved — re-run update with the correct --api-key or --role-arn
Evaluator runs fail with LLM errorsCheck integration credentials with ax ai-integrations get INT_ID; rotate the API key if needed
provider mismatchCannot 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.

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