npx skills add ...
npx skills add github/awesome-copilot --skill arize-ai-provider-integration
npx skills add github/awesome-copilot --skill arize-ai-provider-integration
Creates, reads, updates, and deletes Arize AI integrations that store LLM provider credentials used by evaluators and other Arize features. Supports any LLM provider (e.g. OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Vertex AI, Gemini, NVIDIA NIM). Use when the user mentions AI integration, LLM provider credentials, create integration, list integrations, update credentials, delete integration, or connecting an LLM provider to Arize.
SPACE— Most--spaceflags and theARIZE_SPACEenv var accept a space name (e.g.,my-workspace) or a base64 space ID (e.g.,U3BhY2U6...). Find yours withax spaces list. Note:ai-integrations createdoes not accept--space— AI integrations are account-scoped. Use--spaceonly withlist,get,update, anddelete.
openAI, anthropic, awsBedrock)TGxtSW50ZWdyYXRpb246MTI6YUJjRA==); required for evaluator creation and other downstream operationsdefault (provider API key), proxy_with_headers (proxy via custom headers), or bearer_token (bearer token auth)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.md401 Unauthorized / missing API key → run ax profiles show to inspect the current profile. If the profile is missing or the API key is wrong, follow references/ax-profiles.md to create/update it. If the user doesn't have their key, direct them to https://app.arize.com/admin > API Keysax spaces list to pick by name, or ask the userax ai-integrations list --space SPACE to check for platform-managed credentials. If none exist, ask the user to provide the key or create an integration via the arize-ai-provider-integration skill.env files or search the filesystem for credentials. Use ax profiles for Arize credentials and ax ai-integrations for LLM provider keys. If credentials are not available through these channels, ask the user.List all integrations accessible in a space:
Filter by name (case-insensitive substring match):
Paginate large result sets:
Key flags:
| Flag | Description |
|---|---|
--space | Space name or ID to filter integrations |
--name | Case-insensitive substring filter on integration name |
--limit | Max results (1–100, default 15) |
--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 |
Use this to inspect an integration's full configuration or to confirm its ID after creation.
Before creating, always list integrations first — the user may already have a suitable one:
If no suitable integration exists, create one. The required flags depend on the provider.
AWS Bedrock uses IAM role-based auth. Provide the ARN of the role Arize should assume via --provider-metadata:
Vertex AI uses GCP service account credentials. Provide the GCP project and region via --provider-metadata:
| Provider | Required extra flags |
|---|---|
openAI | --api-key <key> |
anthropic | --api-key <key> |
azureOpenAI | --api-key <key>, --base-url <azure-endpoint> |
awsBedrock | --provider-metadata '{"role_arn": "<arn>"}' |
vertexAI | --provider-metadata '{"project_id": "<gcp-project>", "location": "<region>"}' |
gemini | --api-key <key> |
nvidiaNim | --api-key <key>, --base-url <nim-endpoint> |
custom | --base-url <endpoint> |
| Flag | Description |
|---|---|
--model-name | Allowed model name (repeat for multiple, e.g. --model-name gpt-4o --model-name gpt-4o-mini); omit to allow all models |
--enable-default-models | Enable the provider's default model list |
--function-calling-enabled | Enable tool/function calling support |
--auth-type | Authentication type: default, proxy_with_headers, or bearer_token |
--headers | Custom headers as JSON object or file path (for proxy auth) |
--provider-metadata | Provider-specific metadata as JSON object or file path |
Capture the returned integration ID (e.g., TGxtSW50ZWdyYXRpb246MTI6YUJjRA==) — it is needed for evaluator creation and other downstream commands. If you missed it, retrieve it:
update is a partial update — only the flags you provide are changed. Omitted fields stay as-is.
Add --space SPACE when using a name instead of ID. Any flag accepted by create can be passed to update.
Warning: Deletion is permanent. Evaluators that reference this integration will no longer be able to run.
Omit --force to get a confirmation prompt instead of deleting immediately.
| 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 SPACE |
has_api_key: false after create | Credentials were not saved — re-run update with the correct --api-key or --provider-metadata |
| 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 |
arize-evaluatorarize-experimentSee references/ax-profiles.md § Save Credentials for Future Use.
ax ai-integrations get NAME_OR_ID
ax ai-integrations get NAME_OR_ID -o json
ax ai-integrations get NAME_OR_ID --space SPACE # required when using name instead of IDax ai-integrations create \
--name "My OpenAI Integration" \
--provider openAI \
--api-key $OPENAI_API_KEYax ai-integrations create \
--name "My Anthropic Integration" \
--provider anthropic \
--api-key $ANTHROPIC_API_KEYax ai-integrations create \
--name "My Azure OpenAI Integration" \
--provider azureOpenAI \
--api-key $AZURE_OPENAI_API_KEY \
--base-url "https://my-resource.openai.azure.com/"ax ai-integrations create \
--name "My Bedrock Integration" \
--provider awsBedrock \
--provider-metadata '{"role_arn": "arn:aws:iam::123456789012:role/ArizeBedrockRole"}'ax ai-integrations create \
--name "My Vertex AI Integration" \
--provider vertexAI \
--provider-metadata '{"project_id": "my-gcp-project", "location": "us-central1"}'ax ai-integrations create \
--name "My Gemini Integration" \
--provider gemini \
--api-key $GEMINI_API_KEYax ai-integrations create \
--name "My NVIDIA NIM Integration" \
--provider nvidiaNim \
--api-key $NVIDIA_API_KEY \
--base-url "https://integrate.api.nvidia.com/v1"ax ai-integrations create \
--name "My Custom Integration" \
--provider custom \
--base-url "https://my-llm-proxy.example.com/v1" \
--api-key $CUSTOM_LLM_API_KEYax ai-integrations list --space SPACE -o json
# or by name/ID directly:
ax ai-integrations get NAME_OR_ID# Rename
ax ai-integrations update NAME_OR_ID --name "New Name"
# Rotate the API key
ax ai-integrations update NAME_OR_ID --api-key $OPENAI_API_KEY
# Change the model list (replaces all existing model names)
ax ai-integrations update NAME_OR_ID --model-name gpt-4o --model-name gpt-4o-mini
# Update base URL (for Azure, custom, or NIM)
ax ai-integrations update NAME_OR_ID --base-url "https://new-endpoint.example.com/v1"ax ai-integrations delete NAME_OR_ID --force
ax ai-integrations delete NAME_OR_ID --space SPACE --force # required when using name instead of ID