Optional
apiOptional
apiSome APIs allow an API key instead
Optional
apiOptional
apiThe version of the API functions. Part of the path.
Optional
authOptional
cacheOptional
callbackOptional
callbacksOptional
convertOptional
endpointHostname for the API call (if this is running on GCP)
Optional
locationRegion where the LLM is stored (if this is running on GCP)
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
modelModel to use
Alias for model
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
platformWhat platform to run the service on. If not specified, the class should determine this from other means. Either way, the platform actually used will be in the "platform" getter.
Optional
responseAvailable for gemini-1.5-pro
.
The output format of the generated candidate text.
Supported MIME types:
text/plain
: Text output.application/json
: JSON response in the candidates.Optional
safetyOptional
safetyOptional
stopOptional
streamWhether or not to include usage data, like token counts in the streamed response chunks.
Optional
streamingWhether or not to stream.
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
Input to chat model class.