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The OpenAILike class lets you connect to any LLM provider that implements the OpenAI chat completions API. This includes self-hosted models (vLLM, Ollama, LiteLLM), cloud providers with OpenAI-compatible endpoints, and custom proxies.

​
Basic Usage

from definable.model import OpenAILike
from definable.model.message import Message

model = OpenAILike(
    id="my-model",
    api_key="your-api-key",
    base_url="https://your-provider.com/v1",
)

response = model.invoke(
    messages=[Message(role="user", content="Hello!")],
    assistant_message=Message(role="assistant", content=""),
)
print(response.content)

​
Parameters

​
id
str
required
Model identifier as expected by the target provider.
​
api_key
str
API key for authentication.
​
base_url
str
required
The base URL of the OpenAI-compatible API endpoint.
​
name
str
Human-readable name for this model instance.
​
provider
str
Provider name for logging and metrics.
​
supports_native_structured_outputs
bool
default:"false"
Whether the provider supports OpenAI-style structured outputs.

​
Examples

​
Ollama

model = OpenAILike(
    id="llama3.2",
    base_url="http://localhost:11434/v1",
    name="Ollama Llama",
    provider="Ollama",
)

​
vLLM

model = OpenAILike(
    id="meta-llama/Llama-3-8b-chat-hf",
    base_url="http://localhost:8000/v1",
    name="vLLM Llama",
    provider="vLLM",
)

​
LiteLLM Proxy

model = OpenAILike(
    id="gpt-4o",
    api_key="your-litellm-key",
    base_url="http://localhost:4000/v1",
    name="LiteLLM Proxy",
    provider="LiteLLM",
)

​
Azure OpenAI

model = OpenAILike(
    id="gpt-4o",
    api_key="your-azure-key",
    base_url="https://your-resource.openai.azure.com/openai/deployments/gpt-4o",
    provider="Azure",
)

​
Streaming

from definable.model.message import Message

for chunk in model.invoke_stream(
    messages=[Message(role="user", content="Tell me a joke.")],
    assistant_message=Message(role="assistant", content=""),
):
    if chunk.content:
        print(chunk.content, end="", flush=True)

​
Creating Custom Provider Classes

For repeated use, subclass OpenAILike: 
from definable.model.openai.like import OpenAILike

class MyProviderChat(OpenAILike):
    id: str = "my-default-model"
    name: str = "MyProvider"
    provider: str = "MyProvider"
    base_url: str = "https://api.myprovider.com/v1"
    supports_native_structured_outputs: bool = True
This is exactly how DeepSeekChat, MoonshotChat, and xAI are implemented internally.