Setting up Integrations

Setup integrations to services that provide LLMs as an API. Configure your API keys once to access multiple AI providers across the platform.

Getting Started

Navigate to Settings > Platform Integrations to configure your LLM providers. Each provider requires an API key that creates secure environment variables for your models.

LLM Providers

OpenAI

Models available: o4-mini, o3, o3-mini, etc

1. Click the OpenAI card
2. Enter your API key from platform.openai.com
3. Test connection and save

Anthropic

Models available: claude-4-opus, claude-4-sonnet, claude-3.7-sonnet, etc

1. Click the Anthropic card
2. Enter your API key from console.anthropic.com
3. Test connection and save

Azure AI

Models available: o4-mini, o3, o3-mini, etc

1. Click the Azure AI card
2. Enter your Azure OpenAI API key
3. Test connection and save

Amazon Bedrock

Models available: amazon.titan-text-premier-v1:0, amazon.titan-text-express-v1, amazon.titan-text-lite-v1, etc

1. Click the Amazon Bedrock card
2. Configure AWS credentials:
   • Access Key ID: Your AWS access key
   • Secret Access Key: Your AWS secret key
   • Session Token: Optional temporary session token
   • Default Region: AWS region (e.g., us-east-1)
3. Test connection and save

DeepSeek

Models available: deepseek-r1, deepseek-v3, deepseek-v2.5

1. Click the DeepSeek card
2. Get your API key from DeepSeek Platform
3. Enter your API key in the field
4. Click “Test Connection” to verify
5. Click “Save” to complete setup

Google Vertex AI

Models available: gemini-2.5-pro, gemini-2.5-flash, gemini-2.0-flash, etc

1. Click the Google Vertex AI card
2. Upload service account JSON key
3. Test connection and save

Hugging Face

Models available: llama-3.1-8b-instruct, llama-3.1-70b-instruct, llama-3.1-405b-instruct, etc

1. Click the Hugging Face card
2. Enter your HF token from huggingface.co/settings/tokens
3. Test connection and save

Nvidia NIM

Models available: llama-3.1-nemotron-instruct-70b, llama-3.3-nemotron-super-49b-reasoning, llama-3.1-nemotron-ultra-253b-v1-reasoning, etc

1. Click the Nvidia NIM card
2. Enter your Nvidia API key
3. Test connection and save

GitHub Models

Models available: o4-mini, o3, o3-mini, etc

1. Click the GitHub Models card
2. Enter your GitHub token
3. Test connection and save

Integration Status

• Active: Ready to use in model registration
• Inactive: Needs configuration or has connection issues

Setting Up API Keys

Each integration creates environment variables that you can use in your model code:

• OpenAI: OPENAI_API_KEY
• Anthropic: ANTHROPIC_API_KEY
• Azure AI: AZURE_ENDPOINT
• DeepSeek: DEEPSEEK_API_KEY
• Google Vertex AI: GOOGLE_API_TOKEN
• Hugging Face: HUGGING_FACE_HUB_TOKEN
• GitHub Models: GITHUB_TOKEN
• Amazon Bedrock: AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_SESSION_TOKEN, AWS_DEFAULT_REGION

Using Environment Variables

Once configured, the environment variables are automatically available in your model code:

import os

# Access your API keys
openai_key = os.getenv("OPENAI_API_KEY")
anthropic_key = os.getenv("ANTHROPIC_API_KEY")
azure_endpoint = os.getenv("AZURE_ENDPOINT")
deepseek_key = os.getenv("DEEPSEEK_API_KEY")
google_token = os.getenv("GOOGLE_API_TOKEN")
hf_token = os.getenv("HUGGING_FACE_HUB_TOKEN")
github_token = os.getenv("GITHUB_TOKEN")

# AWS Bedrock credentials
aws_access_key = os.getenv("AWS_ACCESS_KEY_ID")
aws_secret_key = os.getenv("AWS_SECRET_ACCESS_KEY")
aws_session_token = os.getenv("AWS_SESSION_TOKEN")
aws_region = os.getenv("AWS_DEFAULT_REGION")

Need Help?

• Use “Test Connection” to verify your API keys
• Check provider documentation for API key setup
• Ensure proper permissions for your API keys