class OpenRouter(OpenAILike):
"""
OpenRouter LLM.
To instantiate the `OpenRouter` class, you will need to provide an API key. You can set the API key either as an environment variable `OPENROUTER_API_KEY` or directly in the class
constructor. If setting it in the class constructor, it would look like this:
If you haven't signed up for an API key yet, you can do so on the OpenRouter website at (https://openrouter.ai). Once you have your API key, you can use the `OpenRouter` class to interact
with the LLM for tasks like chatting, streaming, and completing prompts.
Examples:
`pip install llama-index-llms-openrouter`
```python
from llama_index.llms.openrouter import OpenRouter
llm = OpenRouter(
api_key="<your-api-key>",
max_tokens=256,
context_window=4096,
model="gryphe/mythomax-l2-13b",
)
response = llm.complete("Hello World!")
print(str(response))
```
"""
model: str = Field(
description="The OpenRouter model to use. See https://openrouter.ai/models for options."
)
context_window: int = Field(
default=DEFAULT_CONTEXT_WINDOW,
description="The maximum number of context tokens for the model. See https://openrouter.ai/models for options.",
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, "OPENROUTER_API_BASE")
api_key = get_from_param_or_env("api_key", api_key, "OPENROUTER_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 "OpenRouter_LLM"
