The LLM to use
The retriever to use for retrieving stored thoughts and insights.
Whether to print out response text.
Optional callbacksOptional memoryOptional metadataOptional tagsProtected lc_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 path to the module that contains the class, eg. ["langchain", "llms"] Usually should be the same as the entrypoint the class is exported from.
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<BaseCallbackConfig>[]Optional runManagers: (undefined | CallbackManagerForChainRun)[]Optional batchOptions: RunnableBatchOptionsOptional options: Partial<BaseCallbackConfig & { Optional batchOptions: RunnableBatchOptionsA promise that resolves to the output values.
This method processes a chat history to generate insights about the user.
The input values for the chain. It should contain a key for chat history.
Optional runManager: CallbackManagerForChainRunOptional callback manager for the chain run.
A promise that resolves to a list of insights about the user.
If the chat history key is not found in the input values or if the chat history is not an array of BaseMessages.
The method performs the following steps:
Default streaming implementation. Subclasses should override this method if they support streaming output.
Optional options: Partial<BaseCallbackConfig>Call the chain on all inputs in the list
Optional config: (Callbacks | BaseCallbackConfig)[]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<BaseCallbackConfig> | Partial<BaseCallbackConfig>[]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<BaseCallbackConfig> | Partial<BaseCallbackConfig>[]Optional batchOptions: RunnableBatchOptions & { Optional options: Partial<BaseCallbackConfig> | Partial<BaseCallbackConfig>[]Optional batchOptions: RunnableBatchOptionsBind arguments to a Runnable, returning a new Runnable.
A new RunnableBinding that, when invoked, will apply the bound args.
Run the core logic of this chain and add to output if desired.
Wraps _call and handles memory.
Optional config: Callbacks | BaseCallbackConfigOptional tags: string[]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: BaseCallbackConfigOptional 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.
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: Callbacks | BaseCallbackConfigReturn a json-like object representing this chain.
Stream output in chunks.
Optional options: Partial<BaseCallbackConfig>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<BaseCallbackConfig>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 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 isStatic lc_Protected _callOptional options: Partial<BaseCallbackConfig> & { Protected _formatProtected _getProtected _separateProtected _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<BaseCallbackConfig>Optional options: BaseCallbackConfig & { Generated using TypeDoc
Chain that generates key insights/facts of a user based on a a chat conversation with an AI.