Optional fields: GooglePaLMChatInputThe async caller should be used by subclasses to make any async calls, which will thus benefit from the concurrency and retry logic.
A path to the module that contains the class, eg. ["langchain", "llms"] Usually should be the same as the entrypoint the class is exported from.
Model Name to use
Note: The format must follow the pattern - models/{model}
Whether to print out response text.
Optional apiGoogle Palm API key to use
Optional cacheOptional callbacksOptional metadataOptional tagsOptional temperatureControls the randomness of the output.
Values can range from [0.0,1.0], inclusive. A value closer to 1.0 will produce responses that are more varied and creative, while a value closer to 0.0 will typically result in less surprising responses from the model.
Note: The default value varies by model
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).
Note: The default value varies by model
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).
Note: The default value varies by model
Protected lc_Keys that the language model accepts as call options.
A map of aliases for constructor args. Keys are the attribute names, e.g. "foo". Values are the alias that will replace the key in serialization. This is used to eg. make argument names match Python.
A map of additional attributes to merge with constructor args. Keys are the attribute names, e.g. "foo". Values are the attribute values, which will be serialized. These attributes need to be accepted by the constructor as arguments.
The final serialized identifier for the module.
A map of secrets, which will be omitted from serialization. Keys are paths to the secret in constructor args, e.g. "foo.bar.baz". Values are the secret ids, which will be used when deserializing.
Internal method that handles batching and configuration for a runnable It takes a function, input values, and optional configuration, and returns a promise that resolves to the output values.
The function to be executed for each input value.
Optional options: Partial<BaseLanguageModelCallOptions>[]Optional runManagers: (undefined | CallbackManagerForChainRun)[]Optional batchOptions: RunnableBatchOptionsOptional options: Partial<BaseLanguageModelCallOptions & { Optional batchOptions: RunnableBatchOptionsA promise that resolves to the output values.
Optional runManager: CallbackManagerForLLMRunDefault streaming implementation. Subclasses should override this method if they support streaming output.
Optional options: BaseLanguageModelCallOptionsOptional _runManager: CallbackManagerForLLMRunDefault implementation of batch, which calls invoke N times. Subclasses should override this method if they can batch more efficiently.
Array of inputs to each batch call.
Optional options: Partial<BaseLanguageModelCallOptions> | Partial<BaseLanguageModelCallOptions>[]Either a single call options object to apply to each batch call or an array for each call.
Optional batchOptions: RunnableBatchOptions & { An array of RunOutputs, or mixed RunOutputs and errors if batchOptions.returnExceptions is set
Optional options: Partial<BaseLanguageModelCallOptions> | Partial<BaseLanguageModelCallOptions>[]Optional batchOptions: RunnableBatchOptions & { Optional options: Partial<BaseLanguageModelCallOptions> | Partial<BaseLanguageModelCallOptions>[]Optional batchOptions: RunnableBatchOptionsBind arguments to a Runnable, returning a new Runnable.
A new RunnableBinding that, when invoked, will apply the bound args.
Makes a single call to the chat model.
An array of BaseMessage instances.
Optional options: string[] | BaseLanguageModelCallOptionsThe call options or an array of stop sequences.
Optional callbacks: CallbacksThe callbacks for the language model.
A Promise that resolves to a BaseMessage.
Makes a single call to the chat model with a prompt value.
The value of the prompt.
Optional options: string[] | BaseLanguageModelCallOptionsThe call options or an array of stop sequences.
Optional callbacks: CallbacksThe callbacks for the language model.
A Promise that resolves to a BaseMessage.
Generates chat based on the input messages.
An array of arrays of BaseMessage instances.
Optional options: string[] | BaseLanguageModelCallOptionsThe call options or an array of stop sequences.
Optional callbacks: CallbacksThe callbacks for the language model.
A Promise that resolves to an LLMResult.
Generates a prompt based on the input prompt values.
An array of BasePromptValue instances.
Optional options: string[] | BaseLanguageModelCallOptionsThe call options or an array of stop sequences.
Optional callbacks: CallbacksThe callbacks for the language model.
A Promise that resolves to an LLMResult.
Get the parameters used to invoke the model
Optional _options: Omit<BaseLanguageModelCallOptions, never>Invokes the chat model with a single input.
The input for the language model.
Optional options: BaseLanguageModelCallOptionsThe call options.
A Promise that resolves to a BaseMessageChunk.
Return a new Runnable that maps a list of inputs to a list of outputs, by calling invoke() with each input.
Create a new runnable sequence that runs each individual runnable in series, piping the output of one runnable into another runnable or runnable-like.
A runnable, function, or object whose values are functions or runnables.
A new runnable sequence.
Predicts the next message based on a text input.
The text input.
Optional options: string[] | BaseLanguageModelCallOptionsThe call options or an array of stop sequences.
Optional callbacks: CallbacksThe callbacks for the language model.
A Promise that resolves to a string.
Predicts the next message based on the input messages.
An array of BaseMessage instances.
Optional options: string[] | BaseLanguageModelCallOptionsThe call options or an array of stop sequences.
Optional callbacks: CallbacksThe callbacks for the language model.
A Promise that resolves to a BaseMessage.
Return a json-like object representing this LLM.
Stream output in chunks.
Optional options: Partial<BaseLanguageModelCallOptions>A readable stream that is also an iterable.
Stream all output from a runnable, as reported to the callback system. This includes all inner runs of LLMs, Retrievers, Tools, etc. Output is streamed as Log objects, which include a list of jsonpatch ops that describe how the state of the run has changed in each step, and the final state of the run. The jsonpatch ops can be applied in order to construct state.
Optional options: Partial<BaseLanguageModelCallOptions>Optional streamOptions: Omit<LogStreamCallbackHandlerInput, "autoClose">Default implementation of transform, which buffers input and then calls stream. Subclasses should override this method if they can start producing output while input is still being generated.
Bind config to a Runnable, returning a new Runnable.
New configuration parameters to attach to the new runnable.
A new RunnableBinding with a config matching what's passed.
Create a new runnable from the current one that will try invoking other passed fallback runnables if the initial invocation fails.
Other runnables to call if the runnable errors.
A new RunnableWithFallbacks.
Add retry logic to an existing runnable.
Optional fields: { Optional onOptional stopA new RunnableRetry that, when invoked, will retry according to the parameters.
Static deserializeLoad an LLM from a json-like object describing it.
Static isStatic lc_Protected _callOptional options: Partial<BaseLanguageModelCallOptions> & { Protected _generateProtected _getProtected _getProtected _getCreate a unique cache key for a specific call to a specific language model.
Call options for the model
A unique cache key.
Protected _mapProtected _mapProtected _separateOptional options: Partial<BaseLanguageModelCallOptions>Protected _transformHelper method to transform an Iterator of Input values into an Iterator of
Output values, with callbacks.
Use this to implement stream() or transform() in Runnable subclasses.
Optional runManager: CallbackManagerForChainRunOptional options: Partial<BaseLanguageModelCallOptions>Optional options: BaseLanguageModelCallOptions & { Static Protected _convertGenerated using TypeDoc
A class that wraps the Google Palm chat model.