llama-index

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from typing import Any, Dict, Optional
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from llama_index.legacy.bridge.pydantic import Field
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from llama_index.legacy.constants import (
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    DEFAULT_CONTEXT_WINDOW,
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    DEFAULT_NUM_OUTPUTS,
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    DEFAULT_TEMPERATURE,
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)
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from llama_index.legacy.core.llms.types import LLMMetadata
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from llama_index.legacy.llms.generic_utils import get_from_param_or_env
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from llama_index.legacy.llms.openai_like import OpenAILike
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DEFAULT_API_BASE = "https://openrouter.ai/api/v1"
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DEFAULT_MODEL = "gryphe/mythomax-l2-13b"
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class OpenRouter(OpenAILike):
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    model: str = Field(
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        description="The OpenRouter model to use. See https://openrouter.ai/models for options."
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    )
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    context_window: int = Field(
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        default=DEFAULT_CONTEXT_WINDOW,
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        description="The maximum number of context tokens for the model. See https://openrouter.ai/models for options.",
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        gt=0,
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    )
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    is_chat_model: bool = Field(
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        default=True,
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        description=LLMMetadata.__fields__["is_chat_model"].field_info.description,
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    )
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    def __init__(
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        self,
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        model: str = DEFAULT_MODEL,
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        temperature: float = DEFAULT_TEMPERATURE,
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        max_tokens: int = DEFAULT_NUM_OUTPUTS,
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        additional_kwargs: Optional[Dict[str, Any]] = None,
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        max_retries: int = 5,
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        api_base: Optional[str] = DEFAULT_API_BASE,
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        api_key: Optional[str] = None,
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        **kwargs: Any,
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    ) -> None:
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        additional_kwargs = additional_kwargs or {}
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        api_base = get_from_param_or_env("api_base", api_base, "OPENROUTER_API_BASE")
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        api_key = get_from_param_or_env("api_key", api_key, "OPENROUTER_API_KEY")
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        super().__init__(
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            model=model,
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            temperature=temperature,
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            max_tokens=max_tokens,
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            api_base=api_base,
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            api_key=api_key,
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            additional_kwargs=additional_kwargs,
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            max_retries=max_retries,
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            **kwargs,
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        )
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    @classmethod
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    def class_name(cls) -> str:
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        return "OpenRouter_LLM"
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