two version of R2R are here HEAD master

1 files changed, 294 insertions, 0 deletions

diff --git a/.venv/lib/python3.12/site-packages/litellm/llms/azure/chat/gpt_transformation.py b/.venv/lib/python3.12/site-packages/litellm/llms/azure/chat/gpt_transformation.py
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+++ b/.venv/lib/python3.12/site-packages/litellm/llms/azure/chat/gpt_transformation.py
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+from typing import TYPE_CHECKING, Any, List, Optional, Union
+
+from httpx._models import Headers, Response
+
+import litellm
+from litellm.litellm_core_utils.prompt_templates.factory import (
+    convert_to_azure_openai_messages,
+)
+from litellm.llms.base_llm.chat.transformation import BaseLLMException
+from litellm.types.utils import ModelResponse
+from litellm.utils import supports_response_schema
+
+from ....exceptions import UnsupportedParamsError
+from ....types.llms.openai import AllMessageValues
+from ...base_llm.chat.transformation import BaseConfig
+from ..common_utils import AzureOpenAIError
+
+if TYPE_CHECKING:
+    from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
+
+    LoggingClass = LiteLLMLoggingObj
+else:
+    LoggingClass = Any
+
+
+class AzureOpenAIConfig(BaseConfig):
+    """
+    Reference: https://learn.microsoft.com/en-us/azure/ai-services/openai/reference#chat-completions
+
+    The class `AzureOpenAIConfig` provides configuration for the OpenAI's Chat API interface, for use with Azure. Below are the parameters::
+
+    - `frequency_penalty` (number or null): Defaults to 0. Allows a value between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, thereby minimizing repetition.
+
+    - `function_call` (string or object): This optional parameter controls how the model calls functions.
+
+    - `functions` (array): An optional parameter. It is a list of functions for which the model may generate JSON inputs.
+
+    - `logit_bias` (map): This optional parameter modifies the likelihood of specified tokens appearing in the completion.
+
+    - `max_tokens` (integer or null): This optional parameter helps to set the maximum number of tokens to generate in the chat completion.
+
+    - `n` (integer or null): This optional parameter helps to set how many chat completion choices to generate for each input message.
+
+    - `presence_penalty` (number or null): Defaults to 0. It penalizes new tokens based on if they appear in the text so far, hence increasing the model's likelihood to talk about new topics.
+
+    - `stop` (string / array / null): Specifies up to 4 sequences where the API will stop generating further tokens.
+
+    - `temperature` (number or null): Defines the sampling temperature to use, varying between 0 and 2.
+
+    - `top_p` (number or null): An alternative to sampling with temperature, used for nucleus sampling.
+    """
+
+    def __init__(
+        self,
+        frequency_penalty: Optional[int] = None,
+        function_call: Optional[Union[str, dict]] = None,
+        functions: Optional[list] = None,
+        logit_bias: Optional[dict] = None,
+        max_tokens: Optional[int] = None,
+        n: Optional[int] = None,
+        presence_penalty: Optional[int] = None,
+        stop: Optional[Union[str, list]] = None,
+        temperature: Optional[int] = None,
+        top_p: Optional[int] = None,
+    ) -> None:
+        locals_ = locals().copy()
+        for key, value in locals_.items():
+            if key != "self" and value is not None:
+                setattr(self.__class__, key, value)
+
+    @classmethod
+    def get_config(cls):
+        return super().get_config()
+
+    def get_supported_openai_params(self, model: str) -> List[str]:
+        return [
+            "temperature",
+            "n",
+            "stream",
+            "stream_options",
+            "stop",
+            "max_tokens",
+            "max_completion_tokens",
+            "tools",
+            "tool_choice",
+            "presence_penalty",
+            "frequency_penalty",
+            "logit_bias",
+            "user",
+            "function_call",
+            "functions",
+            "tools",
+            "tool_choice",
+            "top_p",
+            "logprobs",
+            "top_logprobs",
+            "response_format",
+            "seed",
+            "extra_headers",
+            "parallel_tool_calls",
+            "prediction",
+            "modalities",
+            "audio",
+        ]
+
+    def _is_response_format_supported_model(self, model: str) -> bool:
+        """
+        - all 4o models are supported
+        - check if 'supports_response_format' is True from get_model_info
+        - [TODO] support smart retries for 3.5 models (some supported, some not)
+        """
+        if "4o" in model:
+            return True
+        elif supports_response_schema(model):
+            return True
+
+        return False
+
+    def _is_response_format_supported_api_version(
+        self, api_version_year: str, api_version_month: str
+    ) -> bool:
+        """
+        - check if api_version is supported for response_format
+        """
+
+        is_supported = int(api_version_year) <= 2024 and int(api_version_month) >= 8
+
+        return is_supported
+
+    def map_openai_params(
+        self,
+        non_default_params: dict,
+        optional_params: dict,
+        model: str,
+        drop_params: bool,
+        api_version: str = "",
+    ) -> dict:
+        supported_openai_params = self.get_supported_openai_params(model)
+
+        api_version_times = api_version.split("-")
+        api_version_year = api_version_times[0]
+        api_version_month = api_version_times[1]
+        api_version_day = api_version_times[2]
+        for param, value in non_default_params.items():
+            if param == "tool_choice":
+                """
+                This parameter requires API version 2023-12-01-preview or later
+
+                tool_choice='required' is not supported as of 2024-05-01-preview
+                """
+                ## check if api version supports this param ##
+                if (
+                    api_version_year < "2023"
+                    or (api_version_year == "2023" and api_version_month < "12")
+                    or (
+                        api_version_year == "2023"
+                        and api_version_month == "12"
+                        and api_version_day < "01"
+                    )
+                ):
+                    if litellm.drop_params is True or (
+                        drop_params is not None and drop_params is True
+                    ):
+                        pass
+                    else:
+                        raise UnsupportedParamsError(
+                            status_code=400,
+                            message=f"""Azure does not support 'tool_choice', for api_version={api_version}. Bump your API version to '2023-12-01-preview' or later. This parameter requires 'api_version="2023-12-01-preview"' or later. Azure API Reference: https://learn.microsoft.com/en-us/azure/ai-services/openai/reference#chat-completions""",
+                        )
+                elif value == "required" and (
+                    api_version_year == "2024" and api_version_month <= "05"
+                ):  ## check if tool_choice value is supported ##
+                    if litellm.drop_params is True or (
+                        drop_params is not None and drop_params is True
+                    ):
+                        pass
+                    else:
+                        raise UnsupportedParamsError(
+                            status_code=400,
+                            message=f"Azure does not support '{value}' as a {param} param, for api_version={api_version}. To drop 'tool_choice=required' for calls with this Azure API version, set `litellm.drop_params=True` or for proxy:\n\n`litellm_settings:\n drop_params: true`\nAzure API Reference: https://learn.microsoft.com/en-us/azure/ai-services/openai/reference#chat-completions",
+                        )
+                else:
+                    optional_params["tool_choice"] = value
+            elif param == "response_format" and isinstance(value, dict):
+                _is_response_format_supported_model = (
+                    self._is_response_format_supported_model(model)
+                )
+
+                is_response_format_supported_api_version = (
+                    self._is_response_format_supported_api_version(
+                        api_version_year, api_version_month
+                    )
+                )
+                is_response_format_supported = (
+                    is_response_format_supported_api_version
+                    and _is_response_format_supported_model
+                )
+                optional_params = self._add_response_format_to_tools(
+                    optional_params=optional_params,
+                    value=value,
+                    is_response_format_supported=is_response_format_supported,
+                )
+            elif param == "tools" and isinstance(value, list):
+                optional_params.setdefault("tools", [])
+                optional_params["tools"].extend(value)
+            elif param in supported_openai_params:
+                optional_params[param] = value
+
+        return optional_params
+
+    def transform_request(
+        self,
+        model: str,
+        messages: List[AllMessageValues],
+        optional_params: dict,
+        litellm_params: dict,
+        headers: dict,
+    ) -> dict:
+        messages = convert_to_azure_openai_messages(messages)
+        return {
+            "model": model,
+            "messages": messages,
+            **optional_params,
+        }
+
+    def transform_response(
+        self,
+        model: str,
+        raw_response: Response,
+        model_response: ModelResponse,
+        logging_obj: LoggingClass,
+        request_data: dict,
+        messages: List[AllMessageValues],
+        optional_params: dict,
+        litellm_params: dict,
+        encoding: Any,
+        api_key: Optional[str] = None,
+        json_mode: Optional[bool] = None,
+    ) -> ModelResponse:
+        raise NotImplementedError(
+            "Azure OpenAI handler.py has custom logic for transforming response, as it uses the OpenAI SDK."
+        )
+
+    def get_mapped_special_auth_params(self) -> dict:
+        return {"token": "azure_ad_token"}
+
+    def map_special_auth_params(self, non_default_params: dict, optional_params: dict):
+        for param, value in non_default_params.items():
+            if param == "token":
+                optional_params["azure_ad_token"] = value
+        return optional_params
+
+    def get_eu_regions(self) -> List[str]:
+        """
+        Source: https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/models#gpt-4-and-gpt-4-turbo-model-availability
+        """
+        return ["europe", "sweden", "switzerland", "france", "uk"]
+
+    def get_us_regions(self) -> List[str]:
+        """
+        Source: https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/models#gpt-4-and-gpt-4-turbo-model-availability
+        """
+        return [
+            "us",
+            "eastus",
+            "eastus2",
+            "eastus2euap",
+            "eastus3",
+            "southcentralus",
+            "westus",
+            "westus2",
+            "westus3",
+            "westus4",
+        ]
+
+    def get_error_class(
+        self, error_message: str, status_code: int, headers: Union[dict, Headers]
+    ) -> BaseLLMException:
+        return AzureOpenAIError(
+            message=error_message, status_code=status_code, headers=headers
+        )
+
+    def validate_environment(
+        self,
+        headers: dict,
+        model: str,
+        messages: List[AllMessageValues],
+        optional_params: dict,
+        api_key: Optional[str] = None,
+        api_base: Optional[str] = None,
+    ) -> dict:
+        raise NotImplementedError(
+            "Azure OpenAI has custom logic for validating environment, as it uses the OpenAI SDK."
+        )