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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)

Install / Use

npx skills add github/awesome-copilot --skill arize-ai-provider-integration

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

98/100

Supported Platforms

Gemini CLI

Our assessment of arize-ai-provider-integration

arize-ai-provider-integration scores 98/100 on our quality scale, 32nd of 598 AI & Machine Learning skills we index (top 6%).

Its SKILL.md is 10 KB long, well organised into 29 sections with 16 code examples: a thorough specification that gives an agent plenty to work with.

With 39,348 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
29/30
Structure
20/20
Description
15/15
Adoption
20/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated yesterday, so arize-ai-provider-integration is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.

Automated pattern scan on 2026-09-25. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

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Frequently asked questions

How do I install arize-ai-provider-integration?
Run npx skills add github/awesome-copilot --skill arize-ai-provider-integration. The install tabs above show the steps for each supported agent.
Which AI agents does arize-ai-provider-integration work with?
It is written for Gemini CLI, as a SKILL.md file. Other agents that read the same format can often use it too.
Is arize-ai-provider-integration safe to use?
Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is arize-ai-provider-integration still maintained?
The repository was last updated yesterday, so arize-ai-provider-integration is actively maintained.

name: arize-ai-provider-integration description: 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. metadata: author: arize version: "1.0" compatibility: Requires the ax CLI and a configured Arize profile.

Arize AI Integration Skill

SPACE — Most --space flags and the ARIZE_SPACE env var accept a space name (e.g., my-workspace) or a base64 space ID (e.g., U3BhY2U6...). Find yours with ax spaces list. Note: ai-integrations create does not accept --space — AI integrations are account-scoped. Use --space only with list, get, update, and delete.

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, 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 Keys
  • Space unknown → run ax spaces list to pick by name, or ask the user
  • LLM provider call fails (missing OPENAI_API_KEY / ANTHROPIC_API_KEY) → run ax 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
  • Security: Never read .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 AI Integrations

List all integrations accessible in a space:

ax ai-integrations list --space SPACE

Filter by name (case-insensitive substring match):

ax ai-integrations list --space SPACE --name "openai"

Paginate large result sets:

# Get first page
ax ai-integrations list --space SPACE --limit 20 -o json

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

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 |


Get a Specific Integration

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 ID

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 SPACE

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. Provide the ARN of the role Arize should assume via --provider-metadata:

ax ai-integrations create \
  --name "My Bedrock Integration" \
  --provider awsBedrock \
  --provider-metadata '{"role_arn": "arn:aws:iam::123456789012:role/ArizeBedrockRole"}'

Vertex AI

Vertex AI uses GCP service account credentials. Provide the GCP project and region via --provider-metadata:

ax ai-integrations create \
  --name "My Vertex AI Integration" \
  --provider vertexAI \
  --provider-metadata '{"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

| 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> |

Optional flags for any provider

| 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 |

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 SPACE -o json
# or by name/ID directly:
ax ai-integrations get NAME_OR_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 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"

Add --space SPACE when using a name instead of ID. 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 NAME_OR_ID --force
ax ai-integrations delete NAME_OR_ID --space SPACE --force   # required when using name instead of ID

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 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 |


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.

Related Skills

View on GitHub
GitHub Stars39.3k
CategoryAI
Updated1d ago
Forks5.0k

Languages

JavaScript

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions