Optionalallowed_Allowed functions to call when the mode is "any". If empty, any one of the provided functions are called.
OptionalcallbacksCallbacks 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.
OptionalconfigurableRuntime values for attributes previously made configurable on this Runnable, or sub-Runnables.
OptionalconvertOptionalmaxMaximum number of parallel calls to make.
OptionalmaxMaximum number of tokens to generate in the completion.
OptionalmetadataMetadata for this call and any sub-calls (eg. a Chain calling an LLM). Keys should be strings, values should be JSON-serializable.
OptionalmodelModel to use
OptionalmodelModel to use
Alias for model
OptionalrecursionMaximum number of times a call can recurse. If not provided, defaults to 25.
OptionalresponseAvailable 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.OptionalrunUnique identifier for the tracer run for this call. If not provided, a new UUID will be generated.
OptionalrunName for the tracer run for this call. Defaults to the name of the class.
OptionalsafetyOptionalsafetyOptionalsignalAbort signal for this call. If provided, the call will be aborted when the signal is aborted.
OptionalstopStop tokens to use for this call. If not provided, the default stop tokens for the model will be used.
OptionalstopOptionalstreamWhether or not to include usage data, like token counts in the streamed response chunks.
OptionalstreamingWhether or not to stream.
OptionaltagsTags for this call and any sub-calls (eg. a Chain calling an LLM). You can use these to filter calls.
OptionaltemperatureSampling temperature to use
OptionaltimeoutTimeout for this call in milliseconds.
Optionaltool_Specifies how the chat model should use tools.
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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.
OptionaltoolsOptionaltopKTop-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).
OptionaltopPTop-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.