105 lines
3.6 KiB
Python
105 lines
3.6 KiB
Python
"""
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Databricks Responses API configuration.
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Inherits from OpenAIResponsesAPIConfig since Databricks' Responses API
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is compatible with OpenAI's for GPT models.
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Reference: https://docs.databricks.com/aws/en/machine-learning/foundation-model-apis/api-reference
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"""
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import os
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from typing import TYPE_CHECKING, Any, Dict, Optional, Union
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from litellm.llms.databricks.common_utils import DatabricksBase
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from litellm.llms.openai.responses.transformation import OpenAIResponsesAPIConfig
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from litellm.types.llms.openai import ResponseInputParam
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from litellm.types.router import GenericLiteLLMParams
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from litellm.types.utils import LlmProviders
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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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LiteLLMLoggingObj = _LiteLLMLoggingObj
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else:
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LiteLLMLoggingObj = Any
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class DatabricksResponsesAPIConfig(DatabricksBase, OpenAIResponsesAPIConfig):
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"""
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Configuration for Databricks Responses API.
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Inherits from OpenAIResponsesAPIConfig since Databricks' Responses API
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is largely compatible with OpenAI's for GPT models.
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Note: The Responses API on Databricks is only compatible with OpenAI GPT models.
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"""
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@property
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def custom_llm_provider(self) -> LlmProviders:
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return LlmProviders.DATABRICKS
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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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litellm_params: Optional[GenericLiteLLMParams],
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) -> dict:
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litellm_params = litellm_params or GenericLiteLLMParams()
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api_key = litellm_params.api_key or os.getenv("DATABRICKS_API_KEY")
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api_base = litellm_params.api_base or os.getenv("DATABRICKS_API_BASE")
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# Reuse Databricks auth logic (OAuth M2M, PAT, SDK fallback).
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# custom_endpoint=False allows SDK auth fallback; the appended
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# /chat/completions suffix is harmless since we discard api_base
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# here and build the URL separately in get_complete_url().
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_, headers = self.databricks_validate_environment(
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api_key=api_key,
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api_base=api_base,
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endpoint_type="chat_completions",
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custom_endpoint=False,
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headers=headers,
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)
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headers["Content-Type"] = "application/json"
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return headers
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def get_complete_url(
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self,
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api_base: Optional[str],
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litellm_params: dict,
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) -> str:
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api_base = api_base or os.getenv("DATABRICKS_API_BASE")
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api_base = self._get_api_base(api_base)
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api_base = api_base.rstrip("/")
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return f"{api_base}/responses"
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def transform_responses_api_request(
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self,
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model: str,
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input: Union[str, ResponseInputParam],
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response_api_optional_request_params: Dict,
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litellm_params: GenericLiteLLMParams,
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headers: dict,
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) -> Dict:
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"""
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Transform request for Databricks Responses API.
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Strips the 'databricks/' prefix from model name if present,
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then delegates to OpenAI's transformation.
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"""
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# Strip provider prefix if present (e.g., "databricks/databricks-gpt-5-nano" -> "databricks-gpt-5-nano")
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if model.startswith("databricks/"):
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model = model[len("databricks/") :]
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return super().transform_responses_api_request(
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model=model,
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input=input,
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response_api_optional_request_params=response_api_optional_request_params,
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litellm_params=litellm_params,
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headers=headers,
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)
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def supports_native_websocket(self) -> bool:
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"""Databricks does not support native WebSocket for Responses API"""
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return False
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