two version of R2R are here HEAD master

1 files changed, 119 insertions, 0 deletions

diff --git a/.venv/lib/python3.12/site-packages/litellm/llms/deepinfra/chat/transformation.py b/.venv/lib/python3.12/site-packages/litellm/llms/deepinfra/chat/transformation.py
new file mode 100644
index 00000000..429759fa
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/litellm/llms/deepinfra/chat/transformation.py
@@ -0,0 +1,119 @@
+from typing import Optional, Tuple, Union
+
+import litellm
+from litellm.llms.openai.chat.gpt_transformation import OpenAIGPTConfig
+from litellm.secret_managers.main import get_secret_str
+
+
+class DeepInfraConfig(OpenAIGPTConfig):
+    """
+    Reference: https://deepinfra.com/docs/advanced/openai_api
+
+    The class `DeepInfra` provides configuration for the DeepInfra's Chat Completions API interface. Below are the parameters:
+    """
+
+    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
+    response_format: Optional[dict] = None
+    tools: Optional[list] = None
+    tool_choice: Optional[Union[str, dict]] = None
+
+    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,
+        response_format: Optional[dict] = None,
+        tools: Optional[list] = None,
+        tool_choice: Optional[Union[str, dict]] = 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):
+        return [
+            "stream",
+            "frequency_penalty",
+            "function_call",
+            "functions",
+            "logit_bias",
+            "max_tokens",
+            "max_completion_tokens",
+            "n",
+            "presence_penalty",
+            "stop",
+            "temperature",
+            "top_p",
+            "response_format",
+            "tools",
+            "tool_choice",
+        ]
+
+    def map_openai_params(
+        self,
+        non_default_params: dict,
+        optional_params: dict,
+        model: str,
+        drop_params: bool,
+    ) -> dict:
+        supported_openai_params = self.get_supported_openai_params(model=model)
+        for param, value in non_default_params.items():
+            if (
+                param == "temperature"
+                and value == 0
+                and model == "mistralai/Mistral-7B-Instruct-v0.1"
+            ):  # this model does no support temperature == 0
+                value = 0.0001  # close to 0
+            if param == "tool_choice":
+                if (
+                    value != "auto" and value != "none"
+                ):  # https://deepinfra.com/docs/advanced/function_calling
+                    ## UNSUPPORTED TOOL CHOICE VALUE
+                    if litellm.drop_params is True or drop_params is True:
+                        value = None
+                    else:
+                        raise litellm.utils.UnsupportedParamsError(
+                            message="Deepinfra doesn't support tool_choice={}. To drop unsupported openai params from the call, set `litellm.drop_params = True`".format(
+                                value
+                            ),
+                            status_code=400,
+                        )
+            elif param == "max_completion_tokens":
+                optional_params["max_tokens"] = value
+            elif param in supported_openai_params:
+                if value is not None:
+                    optional_params[param] = value
+        return optional_params
+
+    def _get_openai_compatible_provider_info(
+        self, api_base: Optional[str], api_key: Optional[str]
+    ) -> Tuple[Optional[str], Optional[str]]:
+        # deepinfra is openai compatible, we just need to set this to custom_openai and have the api_base be https://api.endpoints.anyscale.com/v1
+        api_base = (
+            api_base
+            or get_secret_str("DEEPINFRA_API_BASE")
+            or "https://api.deepinfra.com/v1/openai"
+        )
+        dynamic_api_key = api_key or get_secret_str("DEEPINFRA_API_KEY")
+        return api_base, dynamic_api_key