Integrations

The integrations client methods are currently in ALPHA. The API may change without notice. A one-time warning is emitted on first use.

Manage Arize integrations. Integrations are polymorphic: LLM integrations configure a model provider (OpenAI, Anthropic, Gemini, AWS Bedrock, Custom, Vertex AI, NVIDIA NIM, LiteLLM, Fireworks, or Together AI), while AGENT integrations connect a customer-hosted agent exposed at an HTTPS endpoint.

Key Capabilities

List integrations of every type, or filter to a single type
Retrieve an integration by name or ID
Create LLM integrations for any supported provider
Create agent integrations for customer-hosted agents
Update LLM or agent integrations without replacing the entire resource
Delete integrations

Integration Types

Integration names are unique per (account, type). When resolving an integration by name, pass integration_type to disambiguate.

`IntegrationType` value	Description
`LLM`	Model-provider integration
`AGENT`	Customer-hosted agent integration

List Integrations

List all integrations you have access to. When integration_type is omitted, integrations of every type are returned in one merged list (most recently created first).

from arize.integrations.types import IntegrationType

resp = client.integrations.list(
    integration_type=IntegrationType.LLM,  # optional; omit for all types
    name="openai",                          # optional substring filter
    space="your-space-name-or-id",          # optional
    limit=50,
)

for integration in resp.integrations:
    print(integration.id, integration.name)

For details on pagination, field introspection, and data conversion (to dict/JSON/DataFrame), see Response Objects.

Create an LLM Integration

Create an LLM integration by passing the provider-specific config. All 10 providers are supported — construct the matching Create*Config for the provider you want.

OpenAI

from arize.integrations.types import CreateOpenAiConfig

integration = client.integrations.create_llm(
    name="my-openai",
    config=CreateOpenAiConfig(
        provider="OPEN_AI",
        api_key="sk-...",
    ),
)

print(integration.id, integration.name)

Anthropic

from arize.integrations.types import CreateAnthropicConfig

integration = client.integrations.create_llm(
    name="my-anthropic",
    config=CreateAnthropicConfig(
        provider="ANTHROPIC",
        api_key="sk-ant-...",
    ),
)

AWS Bedrock

AWS Bedrock nests an auth config (CreateAwsBedrockDefaultAuth, CreateAwsBedrockBearerTokenAuth, or CreateAwsBedrockProxyWithHeadersAuth).

from arize.integrations.types import (
    CreateAwsBedrockConfig,
    CreateAwsBedrockDefaultAuth,
)

integration = client.integrations.create_llm(
    name="my-bedrock",
    config=CreateAwsBedrockConfig(
        provider="AWS_BEDROCK",
        auth=CreateAwsBedrockDefaultAuth(
            auth_type="DEFAULT",
            role_arn="arn:aws:iam::123456789012:role/my-role",
        ),
        model_names=["anthropic.claude-3-5-sonnet-20241022-v2:0"],
    ),
)

The remaining providers use CreateGeminiConfig, CreateCustomConfig, CreateVertexAiConfig, CreateNvidiaNimConfig, CreateLiteLlmConfig, CreateFireworksConfig, and CreateTogetherAiConfig. A pre-wrapped CreateLlmConfig union is also accepted.

Create an Agent Integration

Agent integrations connect a customer-hosted agent exposed at an HTTPS endpoint. Provide a JSON Schema (Draft-07) describing the endpoint’s request body.

integration = client.integrations.create_agent(
    name="my-agent",
    endpoint="https://agents.example.com/replay",
    input_schema={
        "type": "object",
        "properties": {"prompt": {"type": "string"}},
        "required": ["prompt"],
    },
    description="Customer support agent",  # optional
    headers={"X-Api-Key": "secret"},       # optional; encrypted at rest, never returned
)

print(integration.id, integration.name)

Get an Integration

Retrieve an integration by name or ID. When resolving by name, pass integration_type (names are unique per (account, type)).

from arize.integrations.types import IntegrationType

integration = client.integrations.get(
    integration="my-openai",
    integration_type=IntegrationType.LLM,  # required when resolving by name
    space="your-space-name-or-id",          # optional visibility filter
)

print(integration.id, integration.name)

Update an LLM Integration

Only the fields you pass are sent to the server; omitted fields are left unchanged. The provider is immutable, and config fields are provider-conditional (the server rejects fields that don’t apply to the stored provider). Pass None to clear a nullable field (api_key, base_url, headers).

integration = client.integrations.update_llm(
    integration="my-openai",
    space="your-space-name-or-id",  # optional visibility filter
    name="my-openai-renamed",
    api_key="sk-new-key",
)

print(integration.name)

Update an Agent Integration

Only the fields you pass are sent; omitted fields are left unchanged. Collection fields (headers, request_presets, scopings) replace the existing values when provided. Pass None to clear a nullable field (description, headers).

integration = client.integrations.update_agent(
    integration="my-agent",
    space="your-space-name-or-id",  # optional visibility filter
    endpoint="https://agents.example.com/v2/replay",
    description="Updated description",
)

print(integration.name)

Delete an Integration

Delete an integration by name or ID. This operation is irreversible. When resolving by name, pass integration_type.

from arize.integrations.types import IntegrationType

client.integrations.delete(
    integration="my-openai",
    integration_type=IntegrationType.LLM,  # required when resolving by name
    space="your-space-name-or-id",          # optional visibility filter
)

print("Integration deleted")

Skills

MCP server

API reference

API clients

Key Capabilities

Integration Types

List Integrations

Create an LLM Integration

OpenAI

Anthropic

AWS Bedrock

Create an Agent Integration

Get an Integration

Update an LLM Integration

Update an Agent Integration

Delete an Integration

​Key Capabilities

​Integration Types

​List Integrations

​Create an LLM Integration

​OpenAI

​Anthropic

​AWS Bedrock

​Create an Agent Integration

​Get an Integration

​Update an LLM Integration

​Update an Agent Integration

​Delete an Integration

Key Capabilities

Integration Types

List Integrations

Create an LLM Integration

OpenAI

Anthropic

AWS Bedrock

Create an Agent Integration

Get an Integration

Update an LLM Integration

Update an Agent Integration

Delete an Integration