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refactor(utils.py): make it clearer how vertex ai params are handled '
'
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Krrish Dholakia
parent
409bd5b4ab
commit
32d94feddd
4 changed files with 74 additions and 42 deletions
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@ -87,6 +87,60 @@ class VertexAIConfig:
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and v is not None
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}
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def get_supported_openai_params(self):
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return [
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"temperature",
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"top_p",
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"max_tokens",
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"stream",
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"tools",
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"tool_choice",
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"response_format",
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"n",
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"stop",
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]
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def map_openai_params(self, non_default_params: dict, optional_params: dict):
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for param, value in non_default_params.items():
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if param == "temperature":
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optional_params["temperature"] = value
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if param == "top_p":
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optional_params["top_p"] = value
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if param == "stream":
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optional_params["stream"] = value
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if param == "n":
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optional_params["candidate_count"] = value
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if param == "stop":
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if isinstance(value, str):
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optional_params["stop_sequences"] = [value]
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elif isinstance(value, list):
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optional_params["stop_sequences"] = value
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if param == "max_tokens":
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optional_params["max_output_tokens"] = value
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if param == "response_format" and value["type"] == "json_object":
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optional_params["response_mime_type"] = "application/json"
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if param == "tools" and isinstance(value, list):
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from vertexai.preview import generative_models
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gtool_func_declarations = []
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for tool in value:
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gtool_func_declaration = generative_models.FunctionDeclaration(
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name=tool["function"]["name"],
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description=tool["function"].get("description", ""),
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parameters=tool["function"].get("parameters", {}),
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)
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gtool_func_declarations.append(gtool_func_declaration)
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optional_params["tools"] = [
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generative_models.Tool(
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function_declarations=gtool_func_declarations
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)
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]
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if param == "tool_choice" and (
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isinstance(value, str) or isinstance(value, dict)
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):
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pass
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return optional_params
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import asyncio
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@ -1012,6 +1012,7 @@
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"litellm_provider": "vertex_ai-language-models",
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"mode": "chat",
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"supports_function_calling": true,
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"supports_tool_choice": true,
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"source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models"
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},
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"gemini-1.5-pro-preview-0215": {
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@ -1023,6 +1024,7 @@
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"litellm_provider": "vertex_ai-language-models",
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"mode": "chat",
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"supports_function_calling": true,
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"supports_tool_choice": true,
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"source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models"
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},
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"gemini-1.5-pro-preview-0409": {
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@ -1034,6 +1036,7 @@
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"litellm_provider": "vertex_ai-language-models",
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"mode": "chat",
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"supports_function_calling": true,
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"supports_tool_choice": true,
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"source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models"
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},
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"gemini-experimental": {
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@ -1045,6 +1048,7 @@
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"litellm_provider": "vertex_ai-language-models",
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"mode": "chat",
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"supports_function_calling": false,
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"supports_tool_choice": true,
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"source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models"
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},
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"gemini-pro-vision": {
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@ -1271,6 +1275,7 @@
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"mode": "chat",
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"supports_function_calling": true,
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"supports_vision": true,
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"supports_tool_choice": true,
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"source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models"
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},
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"gemini/gemini-1.5-pro-latest": {
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@ -1283,6 +1288,7 @@
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"mode": "chat",
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"supports_function_calling": true,
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"supports_vision": true,
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"supports_tool_choice": true,
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"source": "https://ai.google.dev/models/gemini"
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},
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"gemini/gemini-pro-vision": {
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@ -4878,37 +4878,11 @@ def get_optional_params(
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)
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_check_valid_arg(supported_params=supported_params)
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if temperature is not None:
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optional_params["temperature"] = temperature
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if top_p is not None:
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optional_params["top_p"] = top_p
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if stream:
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optional_params["stream"] = stream
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if n is not None:
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optional_params["candidate_count"] = n
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if stop is not None:
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if isinstance(stop, str):
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optional_params["stop_sequences"] = [stop]
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elif isinstance(stop, list):
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optional_params["stop_sequences"] = stop
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if max_tokens is not None:
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optional_params["max_output_tokens"] = max_tokens
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if response_format is not None and response_format["type"] == "json_object":
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optional_params["response_mime_type"] = "application/json"
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if tools is not None and isinstance(tools, list):
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from vertexai.preview import generative_models
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gtool_func_declarations = []
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for tool in tools:
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gtool_func_declaration = generative_models.FunctionDeclaration(
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name=tool["function"]["name"],
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description=tool["function"].get("description", ""),
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parameters=tool["function"].get("parameters", {}),
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optional_params = litellm.VertexAIConfig().map_openai_params(
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non_default_params=non_default_params,
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optional_params=optional_params,
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)
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gtool_func_declarations.append(gtool_func_declaration)
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optional_params["tools"] = [
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generative_models.Tool(function_declarations=gtool_func_declarations)
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]
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print_verbose(
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f"(end) INSIDE THE VERTEX AI OPTIONAL PARAM BLOCK - optional_params: {optional_params}"
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)
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@ -5610,17 +5584,7 @@ def get_supported_openai_params(model: str, custom_llm_provider: str):
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elif custom_llm_provider == "palm" or custom_llm_provider == "gemini":
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return ["temperature", "top_p", "stream", "n", "stop", "max_tokens"]
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elif custom_llm_provider == "vertex_ai":
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return [
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"temperature",
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"top_p",
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"max_tokens",
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"stream",
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"tools",
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"tool_choice",
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"response_format",
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"n",
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"stop",
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]
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return litellm.VertexAIConfig().get_supported_openai_params()
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elif custom_llm_provider == "sagemaker":
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return ["stream", "temperature", "max_tokens", "top_p", "stop", "n"]
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elif custom_llm_provider == "aleph_alpha":
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@ -10595,7 +10559,9 @@ def trim_messages(
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if max_tokens is None:
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# Check if model is valid
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if model in litellm.model_cost:
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max_tokens_for_model = litellm.model_cost[model].get("max_input_tokens", litellm.model_cost[model]["max_tokens"])
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max_tokens_for_model = litellm.model_cost[model].get(
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"max_input_tokens", litellm.model_cost[model]["max_tokens"]
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)
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max_tokens = int(max_tokens_for_model * trim_ratio)
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else:
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# if user did not specify max (input) tokens
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@ -1012,6 +1012,7 @@
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"litellm_provider": "vertex_ai-language-models",
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"mode": "chat",
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"supports_function_calling": true,
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"supports_tool_choice": true,
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"source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models"
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},
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"gemini-1.5-pro-preview-0215": {
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@ -1023,6 +1024,7 @@
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"litellm_provider": "vertex_ai-language-models",
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"mode": "chat",
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"supports_function_calling": true,
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"supports_tool_choice": true,
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"source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models"
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},
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"gemini-1.5-pro-preview-0409": {
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@ -1034,6 +1036,7 @@
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"litellm_provider": "vertex_ai-language-models",
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"mode": "chat",
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"supports_function_calling": true,
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"supports_tool_choice": true,
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"source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models"
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},
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"gemini-experimental": {
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@ -1045,6 +1048,7 @@
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"litellm_provider": "vertex_ai-language-models",
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"mode": "chat",
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"supports_function_calling": false,
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"supports_tool_choice": true,
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"source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models"
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},
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"gemini-pro-vision": {
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@ -1271,6 +1275,7 @@
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"mode": "chat",
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"supports_function_calling": true,
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"supports_vision": true,
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"supports_tool_choice": true,
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"source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models"
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},
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"gemini/gemini-1.5-pro-latest": {
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@ -1283,6 +1288,7 @@
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"mode": "chat",
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"supports_function_calling": true,
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"supports_vision": true,
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"supports_tool_choice": true,
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"source": "https://ai.google.dev/models/gemini"
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},
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"gemini/gemini-pro-vision": {
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