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Switching from OpenAI or Anthropic

From OpenAI

Change the base URL, the key and the model name. Nothing else.

python
from openai import OpenAI

# Before
client = OpenAI(api_key="sk-...")

# After
client = OpenAI(base_url="https://api.continuumlabs.ai/v1", api_key="cl-your-key")

reply = client.chat.completions.create(model="glm-5.2", messages=[{"role": "user", "content": "Hello"}])

If your code reads the OPENAI_BASE_URL and OPENAI_API_KEY environment variables, you can switch without changing code at all.

bash
export OPENAI_BASE_URL=https://api.continuumlabs.ai/v1
export OPENAI_API_KEY=cl-your-key

What is different

  • Model names. Use one of our models. OpenAI model names such as gpt-4o are not available.
  • Endpoints. We support chat completions, embeddings and listing models. The Responses API, Assistants, images and audio endpoints are not available yet.
  • Parameters. Common parameters work: temperature, max_tokens, top_p, stop, tools, tool_choice, response_format and stream. Support for less common ones depends on the model.

From Anthropic

Anthropic's API uses a different request format. Switch to the OpenAI SDK, which takes a few lines to change.

AnthropicContinuum
client.messages.create(...)client.chat.completions.create(...)
system="..." as its own fieldA message with "role": "system" first in messages
max_tokens (required)max_tokens (optional)
response.content[0].textresponse.choices[0].message.content
tools with input_schematools with "type": "function" and parameters
stop_reasonchoices[0].finish_reason
python
# Before, with Anthropic
message = anthropic.messages.create(
    model="claude-...", max_tokens=1024, system="You are concise.",
    messages=[{"role": "user", "content": "Hello"}],
)
text = message.content[0].text

# After, with Continuum
reply = client.chat.completions.create(
    model="glm-5.2",
    messages=[{"role": "system", "content": "You are concise."}, {"role": "user", "content": "Hello"}],
)
text = reply.choices[0].message.content

Choosing a model

Open models differ in what they are best at. Try your own prompts in the playground before you switch, and see the scorecard for how each model does on real Australian tasks.