Apertis Docs
Apertis Docs

Help & Security

Migration Guides

This guide helps you migrate to Apertis from other API providers or update between API versions.

Updated
Reading time
4 min
Ask ClaudeAsk ChatGPTOpen in Cursor
View as Markdown

On this page

Migrating from OpenAI

Apertis is fully compatible with the OpenAI API format, making migration straightforward.

Step 1: Update Base URL

The only required change is updating the base URL:

Python:

from openai import OpenAI

# Before (OpenAI)
client = OpenAI(
    api_key="sk-openai-key"
)

# After (Apertis)
client = OpenAI(
    api_key="sk-apertis-key",
    base_url="https://api.apertis.ai/v1"
)

Node.js:

import OpenAI from 'openai';

// Before (OpenAI)
const client = new OpenAI({
  apiKey: 'sk-openai-key'
});

// After (Apertis)
const client = new OpenAI({
  apiKey: 'sk-apertis-key',
  baseURL: 'https://api.apertis.ai/v1'
});

cURL:

# Before (OpenAI)
curl https://api.openai.com/v1/chat/completions \
  -H "Authorization: Bearer sk-openai-key" \
  ...

# After (Apertis)
curl https://api.apertis.ai/v1/chat/completions \
  -H "Authorization: Bearer sk-apertis-key" \
  ...

Step 2: Get Your Apertis API Key

  1. Sign up at api.apertis.ai
  2. Navigate to API Keys
  3. Create a new API key
  4. Store it securely

Step 3: Update Environment Variables

# Before
export OPENAI_API_KEY="sk-openai-key"

# After
export APERTIS_API_KEY="sk-apertis-key"
export APERTIS_BASE_URL="https://api.apertis.ai/v1"

Step 4: Test Your Integration

from openai import OpenAI
import os

client = OpenAI(
    api_key=os.environ.get("APERTIS_API_KEY"),
    base_url=os.environ.get("APERTIS_BASE_URL")
)

# Test with a simple request
response = client.chat.completions.create(
    model="gpt-5.5",
    messages=[{"role": "user", "content": "Hello!"}]
)

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

Model Name Mapping

Most OpenAI models are available with the same names:

OpenAI Model Apertis Model Notes
gpt-5.5 gpt-5.5 ✓ Same
gpt-5.4-mini gpt-5.4-mini ✓ Same
gpt-5.4-nano gpt-5.4-nano ✓ Same
text-embedding-3-small text-embedding-3-small ✓ Same
whisper-1 whisper-1 ✓ Same
tts-1 tts-1 ✓ Same
dall-e-3 dall-e-3 ✓ Same

Additional Models

Apertis provides access to models not available directly from OpenAI:

# Use Claude models
response = client.chat.completions.create(
    model="claude-sonnet-4-6",
    messages=[{"role": "user", "content": "Hello!"}]
)

# Use Gemini models
response = client.chat.completions.create(
    model="gemini-3.1-pro-preview",
    messages=[{"role": "user", "content": "Hello!"}]
)

Migrating from Anthropic (Claude Direct)

API Format Differences

Anthropic uses a different API format. Here's how to migrate:

Before (Anthropic SDK):

import anthropic

client = anthropic.Anthropic(api_key="sk-ant-xxx")

message = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

After (Apertis with OpenAI format):

from openai import OpenAI

client = OpenAI(
    api_key="sk-apertis-key",
    base_url="https://api.apertis.ai/v1"
)

response = client.chat.completions.create(
    model="claude-sonnet-4-6",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

Key Differences

Feature Anthropic API Apertis API
SDK anthropic openai
Response format message.content[0].text choices[0].message.content
System prompt system parameter System message in messages
Streaming Different format OpenAI SSE format

System Prompts

Anthropic format:

message = client.messages.create(
    model="claude-sonnet-4-6",
    system="You are a helpful assistant.",
    messages=[{"role": "user", "content": "Hello!"}]
)

Apertis format:

response = client.chat.completions.create(
    model="claude-sonnet-4-6",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Hello!"}
    ]
)

Response Parsing

Anthropic:

text = message.content[0].text

Apertis:

text = response.choices[0].message.content

Migrating from Azure OpenAI

Configuration Changes

Before (Azure OpenAI):

from openai import AzureOpenAI

client = AzureOpenAI(
    api_key="azure-api-key",
    api_version="2024-02-15-preview",
    azure_endpoint="https://your-resource.openai.azure.com"
)

response = client.chat.completions.create(
    model="your-deployment-name",  # Deployment name, not model
    messages=[{"role": "user", "content": "Hello!"}]
)

After (Apertis):

from openai import OpenAI

client = OpenAI(
    api_key="sk-apertis-key",
    base_url="https://api.apertis.ai/v1"
)

response = client.chat.completions.create(
    model="gpt-5.5",  # Actual model name
    messages=[{"role": "user", "content": "Hello!"}]
)

Key Differences

Feature Azure OpenAI Apertis
Client AzureOpenAI OpenAI
Model param Deployment name Model name
API versioning Required Not needed
Endpoint Custom per resource Fixed

Migrating from Google (Vertex AI / Gemini)

From Vertex AI SDK

Before (Vertex AI):

import vertexai
from vertexai.generative_models import GenerativeModel

vertexai.init(project="your-project", location="us-central1")
model = GenerativeModel("gemini-3.1-pro-preview")

response = model.generate_content("Hello!")

After (Apertis):

from openai import OpenAI

client = OpenAI(
    api_key="sk-apertis-key",
    base_url="https://api.apertis.ai/v1"
)

response = client.chat.completions.create(
    model="gemini-3.1-pro-preview",
    messages=[{"role": "user", "content": "Hello!"}]
)

From Google AI Studio

Before (Google AI SDK):

import google.generativeai as genai

genai.configure(api_key="google-api-key")
model = genai.GenerativeModel("gemini-3.1-pro-preview")

response = model.generate_content("Hello!")
text = response.text

After (Apertis):

from openai import OpenAI

client = OpenAI(
    api_key="sk-apertis-key",
    base_url="https://api.apertis.ai/v1"
)

response = client.chat.completions.create(
    model="gemini-3.1-pro-preview",
    messages=[{"role": "user", "content": "Hello!"}]
)
text = response.choices[0].message.content

Migrating from Other Providers

LiteLLM

If you're using LiteLLM, you can switch to Apertis:

Before (LiteLLM):

from litellm import completion

response = completion(
    model="gpt-5.5",
    messages=[{"role": "user", "content": "Hello!"}]
)

After (Apertis):

from openai import OpenAI

client = OpenAI(
    api_key="sk-apertis-key",
    base_url="https://api.apertis.ai/v1"
)

response = client.chat.completions.create(
    model="gpt-5.5",
    messages=[{"role": "user", "content": "Hello!"}]
)

OpenRouter

Before (OpenRouter):

from openai import OpenAI

client = OpenAI(
    api_key="sk-or-xxx",
    base_url="https://openrouter.ai/api/v1"
)

After (Apertis):

from openai import OpenAI

client = OpenAI(
    api_key="sk-apertis-key",
    base_url="https://api.apertis.ai/v1"
)

Framework Migrations

LangChain

from langchain_openai import ChatOpenAI

# Before
llm = ChatOpenAI(model="gpt-5.5")

# After
llm = ChatOpenAI(
    model="gpt-5.5",
    openai_api_key="sk-apertis-key",
    openai_api_base="https://api.apertis.ai/v1"
)

LlamaIndex

from llama_index.llms.openai import OpenAI

# Before
llm = OpenAI(model="gpt-5.5")

# After
llm = OpenAI(
    model="gpt-5.5",
    api_key="sk-apertis-key",
    api_base="https://api.apertis.ai/v1"
)

Migration Checklist

Pre-Migration

  • Sign up for Apertis account
  • Create API key
  • Review current API usage patterns
  • Identify all integration points
  • Plan testing strategy

During Migration

  • Update base URL/endpoint
  • Update API key
  • Update environment variables
  • Update model names if needed
  • Test each integration point

Post-Migration

  • Verify all features work correctly
  • Monitor error rates
  • Check response quality
  • Review billing/usage
  • Update documentation

Troubleshooting Migration Issues

Common Issues

Issue Cause Solution
401 Unauthorized Wrong API key Use Apertis key, not old provider key
Model not found Different model name Check available models
Different response format SDK mismatch Use OpenAI SDK format
Missing features Not all features supported Check documentation for alternatives

Getting Help

If you encounter issues during migration:

  1. Check the Troubleshooting Guide
  2. Review Error Codes
  3. Contact support at hi@apertis.ai