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import time |
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from typing import TYPE_CHECKING, Any, List, Optional, Union |
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import httpx |
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from litellm.llms.base_llm.chat.transformation import BaseLLMException |
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from litellm.llms.openai.chat.gpt_transformation import OpenAIGPTConfig |
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from litellm.types.llms.openai import AllMessageValues |
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from litellm.types.utils import ModelResponse, Usage |
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from ..common_utils import OobaboogaError |
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if TYPE_CHECKING: |
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from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj |
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LoggingClass = LiteLLMLoggingObj |
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else: |
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LoggingClass = Any |
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class OobaboogaConfig(OpenAIGPTConfig): |
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def get_error_class( |
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self, |
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error_message: str, |
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status_code: int, |
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headers: Optional[Union[dict, httpx.Headers]] = None, |
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) -> BaseLLMException: |
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return OobaboogaError( |
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status_code=status_code, message=error_message, headers=headers |
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) |
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def transform_response( |
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self, |
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model: str, |
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raw_response: httpx.Response, |
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model_response: ModelResponse, |
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logging_obj: LoggingClass, |
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request_data: dict, |
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messages: List[AllMessageValues], |
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optional_params: dict, |
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litellm_params: dict, |
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encoding: Any, |
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api_key: Optional[str] = None, |
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json_mode: Optional[bool] = None, |
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) -> ModelResponse: |
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logging_obj.post_call( |
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input=messages, |
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api_key=api_key, |
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original_response=raw_response.text, |
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additional_args={"complete_input_dict": request_data}, |
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) |
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try: |
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completion_response = raw_response.json() |
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except Exception: |
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raise OobaboogaError( |
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message=raw_response.text, status_code=raw_response.status_code |
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) |
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if "error" in completion_response: |
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raise OobaboogaError( |
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message=completion_response["error"], |
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status_code=raw_response.status_code, |
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) |
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else: |
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try: |
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model_response.choices[0].message.content = completion_response["choices"][0]["message"]["content"] |
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except Exception as e: |
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raise OobaboogaError( |
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message=str(e), |
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status_code=raw_response.status_code, |
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) |
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model_response.created = int(time.time()) |
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model_response.model = model |
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usage = Usage( |
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prompt_tokens=completion_response["usage"]["prompt_tokens"], |
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completion_tokens=completion_response["usage"]["completion_tokens"], |
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total_tokens=completion_response["usage"]["total_tokens"], |
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) |
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setattr(model_response, "usage", usage) |
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return model_response |
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def validate_environment( |
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self, |
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headers: dict, |
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model: str, |
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messages: List[AllMessageValues], |
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optional_params: dict, |
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api_key: Optional[str] = None, |
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api_base: Optional[str] = None, |
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) -> dict: |
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headers = { |
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"accept": "application/json", |
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"content-type": "application/json", |
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} |
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if api_key is not None: |
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headers["Authorization"] = f"Token {api_key}" |
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return headers |
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