Optional
allowed_Allowed functions to call when the mode is "any". If empty, any one of the provided functions are called.
Optional
callbacksCallbacks for this call and any sub-calls (eg. a Chain calling an LLM). Tags are passed to all callbacks, metadata is passed to handle*Start callbacks.
Optional
configurableRuntime values for attributes previously made configurable on this Runnable, or sub-Runnables.
Optional
convertOptional
maxMaximum number of parallel calls to make.
Optional
maxMaximum number of tokens to generate in the completion.
Optional
metadataMetadata for this call and any sub-calls (eg. a Chain calling an LLM). Keys should be strings, values should be JSON-serializable.
Optional
modelModel to use
Optional
modelModel to use
Alias for model
Optional
recursionMaximum number of times a call can recurse. If not provided, defaults to 25.
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
runUnique identifier for the tracer run for this call. If not provided, a new UUID will be generated.
Optional
runName for the tracer run for this call. Defaults to the name of the class.
Optional
safetyOptional
safetyOptional
signalAbort signal for this call. If provided, the call will be aborted when the signal is aborted.
Optional
stopStop tokens to use for this call. If not provided, the default stop tokens for the model will be used.
Optional
stopOptional
streamWhether or not to include usage data, like token counts in the streamed response chunks.
Optional
streamingWhether or not to stream.
Optional
tagsTags for this call and any sub-calls (eg. a Chain calling an LLM). You can use these to filter calls.
Optional
temperatureSampling temperature to use
Optional
timeoutTimeout for this call in milliseconds.
Optional
tool_Specifies how the chat model should use tools.
undefined
Possible values:
- "auto": The model may choose to use any of the provided tools, or none.
- "any": The model must use one of the provided tools.
- "none": The model must not use any tools.
- A string (not "auto", "any", or "none"): The name of a specific tool the model must use.
- An object: A custom schema specifying tool choice parameters. Specific to the provider.
Note: Not all providers support tool_choice. An error will be thrown
if used with an unsupported model.
Optional
toolsOptional
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).
The params which can be passed to the API at request time.