The async caller should be used by subclasses to make any async calls, which will thus benefit from the concurrency and retry logic.
Whether to print out response text.
Optional cacheOptional callbacksOptional maxOptional metadataOptional tagsOptional temperatureOptional topKOptional topPOptional trimStatic inputsProtected lc_Keys that the language model accepts as call options.
Default 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<LlamaCppCallOptions> | Partial<LlamaCppCallOptions>[]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<LlamaCppCallOptions> | Partial<LlamaCppCallOptions>[]Optional batchOptions: RunnableBatchOptions & { Optional options: Partial<LlamaCppCallOptions> | Partial<LlamaCppCallOptions>[]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[] | LlamaCppCallOptionsThe 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[] | LlamaCppCallOptionsThe 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[] | LlamaCppCallOptionsThe 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[] | LlamaCppCallOptionsThe 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
Invokes the chat model with a single input.
The input for the language model.
Optional options: LlamaCppCallOptionsThe 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[] | LlamaCppCallOptionsThe 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[] | LlamaCppCallOptionsThe 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<LlamaCppCallOptions>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<LlamaCppCallOptions>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 isProtected _buildProtected _callOptional options: Partial<LlamaCppCallOptions> & { Protected _convertProtected _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 _separateOptional options: Partial<LlamaCppCallOptions>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<LlamaCppCallOptions>Optional options: LlamaCppCallOptions & { Static Protected _convertGenerated using TypeDoc
To use this model you need to have the
node-llama-cppmodule installed. This can be installed usingnpm install -S node-llama-cppand the minimum version supported in version 2.0.0. This also requires that have a locally built version of Llama2 installed.