Optional
apiThe version of the API functions. Part of the path.
Optional
authOptional
cacheOptional
callbackOptional
callbacksOptional
concurrencyOptional
customIf you are planning to connect to a model that lives under a custom endpoint provide the "customModelURL" which will override the automatic URL building
This is necessary in cases when you want to point to a fine-tuned model or a model that has been hidden under VertexAI Endpoints.
In those cases, specifying the GoogleVertexAIModelParams.model
param
will not be necessary and will be ignored.
Optional
endpointHostname for the API call
Optional
locationRegion where the LLM is stored
Optional
maxThe maximum number of concurrent calls that can be made.
Defaults to Infinity
, which means no limit.
Optional
maxMaximum number of tokens to generate in the completion.
Optional
maxThe maximum number of retries that can be made for a single call, with an exponential backoff between each attempt. Defaults to 6.
Optional
metadataOptional
modelModel to use
Optional
onCustom handler to handle failed attempts. Takes the originally thrown error object as input, and should itself throw an error if the input error is not retryable.
Optional
tagsOptional
temperatureSampling temperature to use
Optional
topKTop-k changes how the model selects tokens for output.
A top-k of 1 means the selected token is the most probable among all tokens in the model’s vocabulary (also called greedy decoding), while a top-k of 3 means that the next token is selected from among the 3 most probable tokens (using temperature).
Optional
topPTop-p changes how the model selects tokens for output.
Tokens are selected from most probable to least until the sum of their probabilities equals the top-p value.
For example, if tokens A, B, and C have a probability of .3, .2, and .1 and the top-p value is .5, then the model will select either A or B as the next token (using temperature).
Optional
verbose
Interface representing the input to the Google Vertex AI model.