chore: initial snapshot for gitea/github upload
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from typing import Any, Dict, Optional, Tuple
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from litellm.llms.gemini.count_tokens.handler import GoogleAIStudioTokenCounter
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from litellm.llms.vertex_ai.vertex_llm_base import VertexBase
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class VertexAITokenCounter(GoogleAIStudioTokenCounter, VertexBase):
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async def validate_environment(
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self,
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api_base: Optional[str] = None,
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api_key: Optional[str] = None,
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headers: Optional[Dict[str, Any]] = None,
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model: str = "",
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litellm_params: Optional[Dict[str, Any]] = None,
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) -> Tuple[Dict[str, Any], str]:
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"""
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Returns a Tuple of headers and url for the Vertex AI countTokens endpoint.
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"""
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litellm_params = litellm_params or {}
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vertex_credentials = self.get_vertex_ai_credentials(
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litellm_params=litellm_params
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)
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vertex_project = self.get_vertex_ai_project(litellm_params=litellm_params)
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vertex_location = self.get_vertex_ai_location(litellm_params=litellm_params)
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should_use_v1beta1_features = self.is_using_v1beta1_features(litellm_params)
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_auth_header, vertex_project = await self._ensure_access_token_async(
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credentials=vertex_credentials,
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project_id=vertex_project,
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custom_llm_provider="vertex_ai",
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)
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auth_header, api_base = self._get_token_and_url(
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model=model,
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gemini_api_key=None,
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auth_header=_auth_header,
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vertex_project=vertex_project,
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vertex_location=vertex_location,
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vertex_credentials=vertex_credentials,
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stream=False,
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custom_llm_provider="vertex_ai",
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api_base=None,
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should_use_v1beta1_features=should_use_v1beta1_features,
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mode="count_tokens",
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)
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headers = {
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"Authorization": f"Bearer {auth_header}",
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}
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return headers, api_base
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