Integrations

An integration is a connection to a model provider or managed agent. It holds the endpoint, the credentials and the models your routes can forward traffic to, so your applications never need the provider key themselves.


Integrations List

Open AI runtime → Integrations to see every connected provider. Integrations are shared across all projects in the organization.

ColumnDescription
StatusWhether the integration is active
NameThe friendly name you gave it, shown when picking a target in a route
ProviderThe provider type (openai, anthropic, azure, vertex, bedrock, bedrock-agentcore...)
Default model / agentThe default target. For a managed agent it is the agent reference; for AgentCore, the runtime name
ModelsHow many models the integration exposes

Click a row to open the integration and edit it.


Add an Integration

Click Add Integration. The wizard has two steps: pick the provider, then configure it.

Step 1: Pick the Provider

ByteHide AI Runtime Add Integration screen showing model provider cards for OpenAI, Anthropic, Google Gemini, Google Vertex AI, Azure OpenAI, Amazon Bedrock and moreClick to expand

The Models tab lists the model providers:

ProviderNotes
OpenAIChat Completions and the OpenAI SDKs
AnthropicClaude models, including the native Messages API
Google GeminiGemini through Google AI Studio
Google Vertex AIModels deployed on Vertex AI
Azure OpenAIModels deployed on your Azure OpenAI resource
Amazon BedrockAll Bedrock models, through the Converse and InvokeModel APIs
Mistral AI, Groq, xAI (Grok), DeepSeek, Cohere, Together AI, OpenRouter, Perplexity, Fireworks AI, Cerebras, NVIDIA NIMHosted model providers
Custom BackendYour own LLM service, a self-hosted OpenAI-compatible endpoint or an Ollama host

The Agents tab lists managed agent platforms. The gateway proxies the agent invocation and guards its input and final output:

Agent platformWhat it connects
Amazon Bedrock AgentCoreAn AgentCore Runtime, identified by its agent runtime ARN. ByteHide guards agent conversations, tool calls and MCP runtimes.
Amazon Bedrock AgentA Bedrock Agent (classic), identified by agent ID and alias ID. Marked Legacy because AWS closed it to new customers; existing agents keep working.
Azure AI Foundry AgentA managed Azure AI Foundry agent (Responses API)
Vertex AI Agent EngineA managed Google Vertex AI Agent Engine (reasoning engine)

Step 2: Configure It

ByteHide AI Runtime new OpenAI integration form with General, Connection and Models sectionsClick to expand

The form adapts to the provider. For OpenAI it has three sections:

SectionFields
GeneralIntegration name, shown when you pick a target in a route
ConnectionOptional Organization ID, Project ID and Base URL (override only for a proxy or a self-hosted gateway), and the API key
ModelsAllowed models, the Default model and Enable streaming

Allowed models restricts what clients can request through this integration. Suggestions come from the provider catalog, but you can type any model name. Requests for a model that is not in the list are rejected; leave the list empty to allow the full catalog.

Enable streaming lets clients receive the answer token by token. Turn it off to force buffered responses: the gateway collects the full reply before returning it.

Click Create integration to save.

Credentials are write-only

Provider keys are encrypted at rest and never shown again once saved. When you edit an integration, an empty secret field means unchanged, not missing.


Provider-Specific Notes

Azure OpenAI

The model a client requests is the deployment name on your Azure resource. The integration holds the resource endpoint and API version, and the gateway sends the key the way Azure expects it.

Amazon Bedrock

A Bedrock integration can authenticate with a Bedrock API key or with an IAM access key pair. Clients keep sending the Bedrock model ID (or inference profile ID) they already use.

Custom Backend

Use Custom Backend for anything not in the list: an OpenAI-compatible server, an Ollama host or an Anthropic-compatible endpoint. Point it at the base URL you would set as the SDK base_url. The same detectors apply as for any hosted provider.


Next Steps

Policies

Choose which detectors inspect the traffic

Routes

Publish a URL that forwards to this integration

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