The LLM to use
The retriever to use for retrieving stored thoughts and insights.
Whether to print out response text.
Optional callbacksOptional memoryOptional metadataOptional nameOptional tagsOptional config: (RunnableConfig | Callbacks)[]Use .batch() instead. Will be removed in 0.2.0.
This feature is deprecated and will be removed in the future.
It is not recommended for use.
Call the chain on all inputs in the list
Assigns new fields to the dict output of this runnable. Returns a new runnable.
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<RunnableConfig> | Partial<RunnableConfig>[]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<RunnableConfig> | Partial<RunnableConfig>[]Optional batchOptions: RunnableBatchOptions & { Optional options: Partial<RunnableConfig> | Partial<RunnableConfig>[]Optional batchOptions: RunnableBatchOptionsBind arguments to a Runnable, returning a new Runnable.
A new RunnableBinding that, when invoked, will apply the bound args.
Optional config: RunnableConfig | CallbacksOptional tags: string[]Use .invoke() instead. Will be removed in 0.2.0.
Run the core logic of this chain and add to output if desired.
Wraps _call and handles memory.
This method breaks down the chat history into chunks of messages. Each chunk consists of a sequence of messages ending with an AI message and the subsequent user response, if any.
The chat history to be chunked.
An array of message chunks. Each chunk includes a sequence of messages and the subsequent user response.
The method iterates over the chat history and pushes each message into a temporary array. When it encounters an AI message, it checks for a subsequent user message. If a user message is found, it is considered as the user response to the AI message. If no user message is found after the AI message, the user response is undefined. The method then pushes the chunk (sequence of messages and user response) into the result array. This process continues until all messages in the chat history have been processed.
Invoke the chain with the provided input and returns the output.
Input values for the chain run.
Optional config: RunnableConfigOptional configuration for the Runnable.
Promise that resolves with the output of the chain run.
Return a new Runnable that maps a list of inputs to a list of outputs, by calling invoke() with each input.
Pick keys from the dict output of this runnable. Returns a new runnable.
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.
Optional config: RunnableConfig | CallbacksUse .invoke() instead. Will be removed in 0.2.0.
Return a json-like object representing this chain.
Stream output in chunks.
Optional options: Partial<RunnableConfig>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<RunnableConfig>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.
Bind lifecycle listeners to a Runnable, returning a new Runnable. The Run object contains information about the run, including its id, type, input, output, error, startTime, endTime, and any tags or metadata added to the run.
The object containing the callback functions.
Optional onCalled after the runnable finishes running, with the Run object.
Optional config: RunnableConfigOptional onCalled if the runnable throws an error, with the Run object.
Optional config: RunnableConfigOptional onCalled before the runnable starts running, with the Run object.
Optional config: RunnableConfigAdd retry logic to an existing runnable.
Optional fields: { Optional onOptional stopA new RunnableRetry that, when invoked, will retry according to the parameters.
Static deserializeLoad a chain from a json-like object describing it.
Static fromLLMStatic method that creates a ViolationOfExpectationsChain instance from a ChatOpenAI and retriever. It also accepts optional options to customize the chain.
The ChatOpenAI instance.
The retriever used for similarity search.
Optional options: Partial<Omit<ViolationOfExpectationsChainInput, "llm" | "retriever">>Optional options to customize the chain.
A new instance of ViolationOfExpectationsChain.
Static isGenerated using TypeDoc
Chain that generates key insights/facts of a user based on a a chat conversation with an AI.