Bases: OpenAILike
Apertis LLM.
Apertis provides a unified API gateway to access multiple LLM providers
including OpenAI, Anthropic, Google, and more through an OpenAI-compatible
interface.
Supported Endpoints
/v1/chat/completions - OpenAI Chat Completions format (default)/v1/responses - OpenAI Responses format compatible/v1/messages - Anthropic format compatible
To instantiate the Apertis class, you will need an API key. You can set
the API key either as an environment variable APERTIS_API_KEY or directly
in the class constructor.
You can obtain an API key at https://api.apertis.ai/token
Examples:
pip install llama-index-llms-apertis
from llama_index.llms.apertis import Apertis
llm = Apertis(
api_key="<your-api-key>",
model="gpt-5.2",
)
response = llm.complete("Hello World!")
print(str(response))
Source code in llama_index/llms/apertis/base.py
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95 | class Apertis(OpenAILike):
"""
Apertis LLM.
Apertis provides a unified API gateway to access multiple LLM providers
including OpenAI, Anthropic, Google, and more through an OpenAI-compatible
interface.
Supported Endpoints:
- `/v1/chat/completions` - OpenAI Chat Completions format (default)
- `/v1/responses` - OpenAI Responses format compatible
- `/v1/messages` - Anthropic format compatible
To instantiate the `Apertis` class, you will need an API key. You can set
the API key either as an environment variable `APERTIS_API_KEY` or directly
in the class constructor.
You can obtain an API key at https://api.apertis.ai/token
Examples:
`pip install llama-index-llms-apertis`
```python
from llama_index.llms.apertis import Apertis
llm = Apertis(
api_key="<your-api-key>",
model="gpt-5.2",
)
response = llm.complete("Hello World!")
print(str(response))
```
"""
model: str = Field(
description="The model to use. Supports models from OpenAI, Anthropic, Google, and more."
)
context_window: int = Field(
default=DEFAULT_CONTEXT_WINDOW,
description="The maximum number of context tokens for the model.",
gt=0,
)
is_chat_model: bool = Field(
default=True,
description=LLMMetadata.model_fields["is_chat_model"].description,
)
def __init__(
self,
model: str = DEFAULT_MODEL,
temperature: float = DEFAULT_TEMPERATURE,
max_tokens: int = DEFAULT_NUM_OUTPUTS,
additional_kwargs: Optional[Dict[str, Any]] = None,
max_retries: int = 5,
api_base: Optional[str] = DEFAULT_API_BASE,
api_key: Optional[str] = None,
**kwargs: Any,
) -> None:
additional_kwargs = additional_kwargs or {}
api_base = get_from_param_or_env("api_base", api_base, "APERTIS_API_BASE")
api_key = get_from_param_or_env("api_key", api_key, "APERTIS_API_KEY")
super().__init__(
model=model,
temperature=temperature,
max_tokens=max_tokens,
api_base=api_base,
api_key=api_key,
additional_kwargs=additional_kwargs,
max_retries=max_retries,
**kwargs,
)
@classmethod
def class_name(cls) -> str:
return "Apertis_LLM"
|