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Overview

The Unified API standardises how your AI applications interact with leading AI models. It exposes a single OpenAI compatible endpoint for accessing 7 major AI providers eliminating vendor lock-in and enabling easy switching between providers. You can use the familiar OpenAI API format, request structure, and response schema regardless of the underlying provider. This approach delivers:

Vendor Independence

Swap providers instantly without code changes. Avoid vendor lock in and maintain flexibility in your AI strategy.

Reduced Development Cost

Integrate once and access many models. Minimise engineering effort and lower ongoing maintenance costs.

Operational Simplicity

Centralised management and monitoring for all AI providers. Streamline operations and simplify troubleshooting.

Strategic Flexibility

Leverage each provider’s unique strengths. Easily adapt to new capabilities and optimise for your use cases.
By adopting the Unified API, organisations can focus on building innovative AI applications rather than managing complex integrations, ultimately accelerating their AI transformation journey while maintaining full control over their AI strategy.

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How it Works

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Supported Providers

ProviderDescription
OpenAIAccess OpenAI’s GPT models made available by OpenAI API
AnthropicConnect to Anthropic’s Claude models available in Anthropic API
Amazon BedrockIntegrate AWS Bedrock models Claude, Llama, Titan etc. available in AWS Bedrock API
Azure OpenAIAccess Azure hosted OpenAI models available in Azure OpenAI API
Azure AI InferenceLeverage custom Azure AI Inference models available in Azure AI Inference API
Google AIIntegrate Google Gemini models available in Google AI API
Google Vertex AIAccess custom deployed Vertex AI models available in Google Vertex Model Garden

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Implementation Examples (for Each Provider)

All examples use the OpenAI SDK with provider specific headers to route requests through the AI Gateway.

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OpenAI

Access OpenAI’s GPT models made available by OpenAI API
openai_example.py
from openai import OpenAI

client = OpenAI(
    api_key="YOUR_OPENAI_API_KEY",
    base_url="https://gateway.altrum.ai/v1",
    default_headers={
        "x-provider-name": "openai",
        "x-altrumai-key": "YOUR_ALTRUMAI_API_KEY"
    }
)

response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[
        {"role": "user", "content": "What is the capital of France?"}
    ]
)

print(response.choices[0].message.content)

​
Anthropic

Access Anthropic Claude models made available by Anthropic API
anthropic_example.py
from openai import OpenAI

client = OpenAI(
    api_key="",
    base_url="https://gateway.altrum.ai/v1",
    default_headers={
        "x-api-key": "YOUR_ANTHROPIC_API_KEY",
        "x-provider-name": "anthropic",
        "x-altrumai-key": "YOUR_ALTRUMAI_API_KEY"
    }
)

response = client.chat.completions.create(
    model="claude-3-opus-20240229",
    messages=[
        {"role": "user", "content": "Explain quantum computing in simple terms."}
    ]
)

print(response.choices[0].message.content)

​
Amazon Bedrock

Access Amazon Bedrock models made available by AWS Bedrock API
bedrock_example.py
from openai import OpenAI

client = OpenAI(
    api_key="unused-placeholder",  # Not used, credentials via headers
    base_url="https://gateway.altrum.ai/v1",
    default_headers={
        "x-provider-name": "bedrock",
        "x-bedrock-access-key-id": "YOUR_AWS_ACCESS_KEY_ID",
        "x-bedrock-secret-access-key": "YOUR_AWS_SECRET_ACCESS_KEY",
        "x-bedrock-region": "YOUR_AWS_REGION",
        "x-bedrock-session-token": "YOUR_AWS_SESSION_TOKEN",  # Optional
        "x-altrumai-key": "YOUR_ALTRUMAI_API_KEY"
    }
)

response = client.chat.completions.create(
    model="anthropic.claude-v2",
    messages=[
        {"role": "user", "content": "Give me a list of 5 creative startup ideas in the AI space."}
    ]
)

print(response.choices[0].message.content)

​
Azure OpenAI

Access Azure OpenAI models made available by Azure OpenAI API
azure_openai_example.py
from openai import OpenAI

client = OpenAI(
    api_key="unused-placeholder",  # Authentication via headers
    base_url="https://gateway.altrum.ai/v1",
    default_headers={
        "x-provider-name": "azure_openai",
        "x-azure-api-key": "YOUR_AZURE_API_KEY",
        "x-azure-resource-name": "YOUR_AZURE_RESOURCE_NAME",
        "x-azure-deployment-id": "YOUR_AZURE_DEPLOYMENT_ID",
        "x-azure-api-version": "2024-02-15-preview",
        "x-altrumai-key": "YOUR_ALTRUMAI_API_KEY"
    }
)

response = client.chat.completions.create(
    model="gpt-35-turbo",
    messages=[
        {"role": "user", "content": "What are the advantages of using managed Kubernetes services?"}
    ]
)

print(response.choices[0].message.content)

​
Azure AI Inference

Access Azure AI Inference models made available by Azure AI Inference API
azure_ai_inference_example.py
from openai import OpenAI

client = OpenAI(
    api_key="unused-placeholder",  # Authentication via headers
    base_url="https://gateway.altrum.ai/v1",
    default_headers={
        "x-provider-name": "azure_ai_inference",
        "x-altrumai-key": "YOUR_ALTRUMAI_API_KEY",
        "x-azure-ai-token": "YOUR_AZURE_AI_INFERENCE_API_KEY",
        "x-azure-ai-endpoint": "YOUR_AZURE_AI_INFERENCE_ENDPOINT"
    }
)

response = client.chat.completions.create(
    model="phi-2",
    messages=[
        {"role": "user", "content": "Summarise the main benefits of using serverless architectures."}
    ]
)

print(response.choices[0].message.content)

​
Google AI

Access Google Gemini models made available by Google AI API
google_ai_example.py
from openai import OpenAI

client = OpenAI(
    api_key="unused-placeholder",  # Authentication via headers
    base_url="https://gateway.altrum.ai/v1",
    default_headers={
        "x-provider-name": "google",
        "x-goog-api-key": "YOUR_GOOGLE_API_KEY",
        "x-altrumai-key": "YOUR_ALTRUMAI_API_KEY"
    }
)

response = client.chat.completions.create(
    model="gemini-1.5-pro",
    messages=[
        {"role": "user", "content": "How can AI help improve energy efficiency in smart buildings?"}
    ]
)

print(response.choices[0].message.content)

​
Google Vertex AI

Access Google Vertex AI models made available by Google Vertex AI API
google_vertex_ai_example.py
from openai import OpenAI

client = OpenAI(
    api_key="unused-placeholder",  # Authentication via headers
    base_url="https://gateway.altrum.ai/v1",
    default_headers={
        "x-provider-name": "google_vertex_ai",
        "x-api-key": "YOUR_GOOGLE_VERTEX_AI_API_KEY",
        "x-endpoint-base": "YOUR_GOOGLE_VERTEX_AI_ENDPOINT_BASE",
        "x-project-id": "YOUR_GOOGLE_VERTEX_AI_PROJECT_ID",
        "x-location": "YOUR_GOOGLE_VERTEX_AI_LOCATION",
        "x-altrumai-key": "YOUR_ALTRUMAI_API_KEY"
    }
)

response = client.chat.completions.create(
    model="google.models.text-bison",
    messages=[
        {"role": "user", "content": "List three practical applications of generative AI in education."}
    ]
)

print(response.choices[0].message.content)