two version of R2R are here HEAD master

1 files changed, 106 insertions, 0 deletions

diff --git a/.venv/lib/python3.12/site-packages/litellm/llms/databricks/chat/transformation.py b/.venv/lib/python3.12/site-packages/litellm/llms/databricks/chat/transformation.py
new file mode 100644
index 00000000..94e02034
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/litellm/llms/databricks/chat/transformation.py
@@ -0,0 +1,106 @@
+"""
+Translates from OpenAI's `/v1/chat/completions` to Databricks' `/chat/completions`
+"""
+
+from typing import List, Optional, Union
+
+from pydantic import BaseModel
+
+from litellm.litellm_core_utils.prompt_templates.common_utils import (
+    handle_messages_with_content_list_to_str_conversion,
+    strip_name_from_messages,
+)
+from litellm.types.llms.openai import AllMessageValues
+from litellm.types.utils import ProviderField
+
+from ...openai_like.chat.transformation import OpenAILikeChatConfig
+
+
+class DatabricksConfig(OpenAILikeChatConfig):
+    """
+    Reference: https://docs.databricks.com/en/machine-learning/foundation-models/api-reference.html#chat-request
+    """
+
+    max_tokens: Optional[int] = None
+    temperature: Optional[int] = None
+    top_p: Optional[int] = None
+    top_k: Optional[int] = None
+    stop: Optional[Union[List[str], str]] = None
+    n: Optional[int] = None
+
+    def __init__(
+        self,
+        max_tokens: Optional[int] = None,
+        temperature: Optional[int] = None,
+        top_p: Optional[int] = None,
+        top_k: Optional[int] = None,
+        stop: Optional[Union[List[str], str]] = None,
+        n: 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_required_params(self) -> List[ProviderField]:
+        """For a given provider, return it's required fields with a description"""
+        return [
+            ProviderField(
+                field_name="api_key",
+                field_type="string",
+                field_description="Your Databricks API Key.",
+                field_value="dapi...",
+            ),
+            ProviderField(
+                field_name="api_base",
+                field_type="string",
+                field_description="Your Databricks API Base.",
+                field_value="https://adb-..",
+            ),
+        ]
+
+    def get_supported_openai_params(self, model: Optional[str] = None) -> list:
+        return [
+            "stream",
+            "stop",
+            "temperature",
+            "top_p",
+            "max_tokens",
+            "max_completion_tokens",
+            "n",
+            "response_format",
+            "tools",
+            "tool_choice",
+        ]
+
+    def _should_fake_stream(self, optional_params: dict) -> bool:
+        """
+        Databricks doesn't support 'response_format' while streaming
+        """
+        if optional_params.get("response_format") is not None:
+            return True
+
+        return False
+
+    def _transform_messages(
+        self, messages: List[AllMessageValues], model: str
+    ) -> List[AllMessageValues]:
+        """
+        Databricks does not support:
+        - content in list format.
+        - 'name' in user message.
+        """
+        new_messages = []
+        for idx, message in enumerate(messages):
+            if isinstance(message, BaseModel):
+                _message = message.model_dump(exclude_none=True)
+            else:
+                _message = message
+            new_messages.append(_message)
+        new_messages = handle_messages_with_content_list_to_str_conversion(new_messages)
+        new_messages = strip_name_from_messages(new_messages)
+        return super()._transform_messages(messages=new_messages, model=model)