mirror of
https://github.com/BerriAI/litellm.git
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5ad57dd54b
* rename OpenAI -> openai * fix file rename * fix rename changes * fix organization of openai/transcription * fix import OA fine tuning API * fix openai ft handler * fix handler import
133 lines
4.9 KiB
Python
133 lines
4.9 KiB
Python
import types
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from typing import Literal, Optional, Tuple, Union
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from litellm.secret_managers.main import get_secret_str
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from ...openai.chat.gpt_transformation import OpenAIGPTConfig
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from ..embed.fireworks_ai_transformation import FireworksAIEmbeddingConfig
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class FireworksAIConfig(OpenAIGPTConfig):
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"""
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Reference: https://docs.fireworks.ai/api-reference/post-chatcompletions
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The class `FireworksAIConfig` provides configuration for the Fireworks's Chat Completions API interface. Below are the parameters:
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"""
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tools: Optional[list] = None
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tool_choice: Optional[Union[str, dict]] = None
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max_tokens: Optional[int] = None
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temperature: Optional[int] = None
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top_p: Optional[int] = None
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top_k: Optional[int] = None
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frequency_penalty: Optional[int] = None
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presence_penalty: Optional[int] = None
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n: Optional[int] = None
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stop: Optional[Union[str, list]] = None
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response_format: Optional[dict] = None
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user: Optional[str] = None
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logprobs: Optional[int] = None
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# Non OpenAI parameters - Fireworks AI only params
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prompt_truncate_length: Optional[int] = None
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context_length_exceeded_behavior: Optional[Literal["error", "truncate"]] = None
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def __init__(
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self,
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tools: Optional[list] = None,
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tool_choice: Optional[Union[str, dict]] = None,
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max_tokens: Optional[int] = None,
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temperature: Optional[int] = None,
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top_p: Optional[int] = None,
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top_k: Optional[int] = None,
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frequency_penalty: Optional[int] = None,
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presence_penalty: Optional[int] = None,
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n: Optional[int] = None,
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stop: Optional[Union[str, list]] = None,
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response_format: Optional[dict] = None,
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user: Optional[str] = None,
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logprobs: Optional[int] = None,
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prompt_truncate_length: Optional[int] = None,
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context_length_exceeded_behavior: Optional[Literal["error", "truncate"]] = None,
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) -> None:
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locals_ = locals().copy()
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for key, value in locals_.items():
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if key != "self" and value is not None:
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setattr(self.__class__, key, value)
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@classmethod
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def get_config(cls):
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return super().get_config()
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def get_supported_openai_params(self, model: str):
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return [
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"stream",
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"tools",
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"tool_choice",
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"max_completion_tokens",
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"max_tokens",
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"temperature",
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"top_p",
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"top_k",
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"frequency_penalty",
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"presence_penalty",
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"n",
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"stop",
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"response_format",
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"user",
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"logprobs",
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"prompt_truncate_length",
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"context_length_exceeded_behavior",
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]
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def map_openai_params(
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self,
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non_default_params: dict,
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optional_params: dict,
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model: str,
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drop_params: bool,
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) -> dict:
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supported_openai_params = self.get_supported_openai_params(model=model)
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for param, value in non_default_params.items():
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if param == "tool_choice":
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if value == "required":
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# relevant issue: https://github.com/BerriAI/litellm/issues/4416
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optional_params["tool_choice"] = "any"
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else:
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# pass through the value of tool choice
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optional_params["tool_choice"] = value
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elif (
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param == "response_format" and value.get("type", None) == "json_schema"
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):
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optional_params["response_format"] = {
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"type": "json_object",
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"schema": value["json_schema"]["schema"],
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}
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elif param == "max_completion_tokens":
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optional_params["max_tokens"] = value
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elif param in supported_openai_params:
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if value is not None:
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optional_params[param] = value
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return optional_params
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def _get_openai_compatible_provider_info(
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self, model: str, api_base: Optional[str], api_key: Optional[str]
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) -> Tuple[str, Optional[str], Optional[str]]:
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if FireworksAIEmbeddingConfig().is_fireworks_embedding_model(model=model):
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# fireworks embeddings models do not require accounts/fireworks prefix https://docs.fireworks.ai/api-reference/creates-an-embedding-vector-representing-the-input-text
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pass
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elif not model.startswith("accounts/"):
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model = f"accounts/fireworks/models/{model}"
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api_base = (
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api_base
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or get_secret_str("FIREWORKS_API_BASE")
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or "https://api.fireworks.ai/inference/v1"
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) # type: ignore
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dynamic_api_key = api_key or (
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get_secret_str("FIREWORKS_API_KEY")
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or get_secret_str("FIREWORKS_AI_API_KEY")
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or get_secret_str("FIREWORKSAI_API_KEY")
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or get_secret_str("FIREWORKS_AI_TOKEN")
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)
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return model, api_base, dynamic_api_key
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