Class ChatOpenAI<CallOptions>

Wrapper around OpenAI large language models that use the Chat endpoint.

To use you should have the openai package installed, with the OPENAI_API_KEY environment variable set.

To use with Azure you should have the openai package installed, with the AZURE_OPENAI_API_KEY, AZURE_OPENAI_API_INSTANCE_NAME, AZURE_OPENAI_API_DEPLOYMENT_NAME and AZURE_OPENAI_API_VERSION environment variable set. AZURE_OPENAI_BASE_PATH is optional and will override AZURE_OPENAI_API_INSTANCE_NAME if you need to use a custom endpoint.

Remarks

Any parameters that are valid to be passed to openai.createChatCompletion can be passed through modelKwargs, even if not explicitly available on this class.

Example

// Create a new instance of ChatOpenAI with specific temperature and model name settings
const model = new ChatOpenAI({
  temperature: 0.9,
  modelName: "ft:gpt-3.5-turbo-0613:{ORG_NAME}::{MODEL_ID}",
});

// Invoke the model with a message and await the response
const message = await model.invoke("Hi there!");

// Log the response to the console
console.log(message);

Type Parameters

Hierarchy

Implements

Constructors

constructor

Properties

ParsedCallOptions caller frequencyPenalty modelName n presencePenalty streaming temperature topP verbose azureOpenAIApiDeploymentName? azureOpenAIApiInstanceName? azureOpenAIApiKey? azureOpenAIApiVersion? azureOpenAIBasePath? cache? callbacks? logitBias? maxTokens? metadata? modelKwargs? name? openAIApiKey? organization? stop? tags? timeout? user?

Accessors

callKeys

Methods

assign batch bind call callPrompt completionWithRetry generate generatePrompt getName getNumTokens getNumTokensFromMessages identifyingParams invocationParams invoke map pick pipe predict predictMessages serialize stream streamLog toJSON toJSONNotImplemented transform withConfig withFallbacks withListeners withRetry deserialize isRunnable

Constructors

constructor

Properties

ParsedCallOptions

ParsedCallOptions: Omit<CallOptions, never>

caller

caller: AsyncCaller

The async caller should be used by subclasses to make any async calls, which will thus benefit from the concurrency and retry logic.

frequencyPenalty

frequencyPenalty: number

Penalizes repeated tokens according to frequency

modelName

modelName: string

Model name to use

n

n: number

Number of completions to generate for each prompt

presencePenalty

presencePenalty: number

Penalizes repeated tokens

streaming

streaming: boolean

Whether to stream the results or not. Enabling disables tokenUsage reporting

temperature

temperature: number

Sampling temperature to use

topP

topP: number

Total probability mass of tokens to consider at each step

verbose

verbose: boolean

Whether to print out response text.

Optional azureOpenAIApiDeploymentName

azureOpenAIApiDeploymentName?: string

Azure OpenAI API deployment name to use for completions when making requests to Azure OpenAI. This is the name of the deployment you created in the Azure portal. e.g. "my-openai-deployment" this will be used in the endpoint URL: https://{InstanceName}.openai.azure.com/openai/deployments/my-openai-deployment/

Optional azureOpenAIApiInstanceName

azureOpenAIApiInstanceName?: string

Azure OpenAI API instance name to use when making requests to Azure OpenAI. this is the name of the instance you created in the Azure portal. e.g. "my-openai-instance" this will be used in the endpoint URL: https://my-openai-instance.openai.azure.com/openai/deployments/{DeploymentName}/

Optional azureOpenAIApiKey

azureOpenAIApiKey?: string

API key to use when making requests to Azure OpenAI.

Optional azureOpenAIApiVersion

azureOpenAIApiVersion?: string

API version to use when making requests to Azure OpenAI.

Optional azureOpenAIBasePath

azureOpenAIBasePath?: string

Custom endpoint for Azure OpenAI API. This is useful in case you have a deployment in another region. e.g. setting this value to "https://westeurope.api.cognitive.microsoft.com/openai/deployments" will be result in the endpoint URL: https://westeurope.api.cognitive.microsoft.com/openai/deployments/{DeploymentName}/

Optional cache

cache?: BaseCache<Generation[]>

Optional callbacks

callbacks?: Callbacks

Optional logitBias

logitBias?: Record<string, number>

Dictionary used to adjust the probability of specific tokens being generated

Optional maxTokens

maxTokens?: number

Maximum number of tokens to generate in the completion. -1 returns as many tokens as possible given the prompt and the model's maximum context size.

Optional metadata

metadata?: Record<string, unknown>

Optional modelKwargs

modelKwargs?: Record<string, any>

Holds any additional parameters that are valid to pass to openai.createCompletion that are not explicitly specified on this class.

Optional name

name?: string

Optional openAIApiKey

openAIApiKey?: string

API key to use when making requests to OpenAI. Defaults to the value of OPENAI_API_KEY environment variable.

Optional organization

organization?: string

Optional stop

stop?: string[]

List of stop words to use when generating

Optional tags

tags?: string[]

Optional timeout

timeout?: number

Timeout to use when making requests to OpenAI.

Optional user

user?: string

Unique string identifier representing your end-user, which can help OpenAI to monitor and detect abuse.

Accessors

callKeys

  • get callKeys(): string[]

  • Keys that the language model accepts as call options.

    Returns string[]

Methods

assign

  • Assigns new fields to the dict output of this runnable. Returns a new runnable.

    Parameters

    • mapping: RunnableMapLike<Record<string, unknown>, Record<string, unknown>>

    Returns RunnableSequence<any, any>

batch

  • Default implementation of batch, which calls invoke N times. Subclasses should override this method if they can batch more efficiently.

    Parameters

    • inputs: BaseLanguageModelInput[]

      Array of inputs to each batch call.

    • Optional options: Partial<CallOptions> | Partial<CallOptions>[]

      Either a single call options object to apply to each batch call or an array for each call.

    • Optional batchOptions: RunnableBatchOptions & {
          returnExceptions?: false;
      }

    Returns Promise<BaseMessageChunk[]>

    An array of RunOutputs, or mixed RunOutputs and errors if batchOptions.returnExceptions is set

  • Parameters

    Returns Promise<(Error | BaseMessageChunk)[]>

  • Parameters

    Returns Promise<(Error | BaseMessageChunk)[]>

bind

call

  • Parameters

    • messages: BaseMessageLike[]

      An array of BaseMessage instances.

    • Optional options: string[] | CallOptions

      The call options or an array of stop sequences.

    • Optional callbacks: Callbacks

      The callbacks for the language model.

    Returns Promise<BaseMessage>

    A Promise that resolves to a BaseMessage.

    ⚠️ Deprecated ⚠️

    Use .invoke() 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.

    Makes a single call to the chat model.

callPrompt

  • Parameters

    • promptValue: BasePromptValueInterface

      The value of the prompt.

    • Optional options: string[] | CallOptions

      The call options or an array of stop sequences.

    • Optional callbacks: Callbacks

      The callbacks for the language model.

    Returns Promise<BaseMessage>

    A Promise that resolves to a BaseMessage.

    Deprecated

    Use .invoke() instead. Will be removed in 0.2.0.

    Makes a single call to the chat model with a prompt value.

completionWithRetry

  • Calls the OpenAI API with retry logic in case of failures.

    Parameters

    • request: ChatCompletionCreateParamsStreaming

      The request to send to the OpenAI API.

    • Optional options: OpenAICoreRequestOptions

      Optional configuration for the API call.

    Returns Promise<AsyncIterable<ChatCompletionChunk>>

    The response from the OpenAI API.

  • Parameters

    • request: ChatCompletionCreateParamsNonStreaming
    • Optional options: OpenAICoreRequestOptions

    Returns Promise<ChatCompletion>

generate

  • Generates chat based on the input messages.

    Parameters

    • messages: BaseMessageLike[][]

      An array of arrays of BaseMessage instances.

    • Optional options: string[] | CallOptions

      The call options or an array of stop sequences.

    • Optional callbacks: Callbacks

      The callbacks for the language model.

    Returns Promise<LLMResult>

    A Promise that resolves to an LLMResult.

generatePrompt

  • Generates a prompt based on the input prompt values.

    Parameters

    • promptValues: BasePromptValueInterface[]

      An array of BasePromptValue instances.

    • Optional options: string[] | CallOptions

      The call options or an array of stop sequences.

    • Optional callbacks: Callbacks

      The callbacks for the language model.

    Returns Promise<LLMResult>

    A Promise that resolves to an LLMResult.

getName

  • Parameters

    • Optional suffix: string

    Returns string

getNumTokens

  • Parameters

    Returns Promise<number>

getNumTokensFromMessages

  • Parameters

    Returns Promise<{
        countPerMessage: number[];
        totalCount: number;
    }>

identifyingParams

  • Get the identifying parameters for the model

    Returns Omit<ChatCompletionCreateParams, "messages"> & {
        model_name: string;
    } & ClientOptions

invocationParams

  • Get the parameters used to invoke the model

    Parameters

    • Optional options: Omit<CallOptions, never>

    Returns Omit<ChatCompletionCreateParams, "messages">

invoke

  • Invokes the chat model with a single input.

    Parameters

    • input: BaseLanguageModelInput

      The input for the language model.

    • Optional options: CallOptions

      The call options.

    Returns Promise<BaseMessageChunk>

    A Promise that resolves to a BaseMessageChunk.

map

pick

  • Pick keys from the dict output of this runnable. Returns a new runnable.

    Parameters

    • keys: string | string[]

    Returns RunnableSequence<any, any>

pipe

  • Create a new runnable sequence that runs each individual runnable in series, piping the output of one runnable into another runnable or runnable-like.

    Type Parameters

    • NewRunOutput

    Parameters

    Returns RunnableSequence<BaseLanguageModelInput, Exclude<NewRunOutput, Error>>

    A new runnable sequence.

predict

  • Parameters

    • text: string

      The text input.

    • Optional options: string[] | CallOptions

      The call options or an array of stop sequences.

    • Optional callbacks: Callbacks

      The callbacks for the language model.

    Returns Promise<string>

    A Promise that resolves to a string.

    Deprecated

    Use .invoke() instead. Will be removed in 0.2.0.

    Predicts the next message based on a text input.

predictMessages

  • Parameters

    • messages: BaseMessage[]

      An array of BaseMessage instances.

    • Optional options: string[] | CallOptions

      The call options or an array of stop sequences.

    • Optional callbacks: Callbacks

      The callbacks for the language model.

    Returns Promise<BaseMessage>

    A Promise that resolves to a BaseMessage.

    Deprecated

    Use .invoke() instead. Will be removed in 0.2.0.

    Predicts the next message based on the input messages.

serialize

stream

  • Stream output in chunks.

    Parameters

    Returns Promise<IterableReadableStream<BaseMessageChunk>>

    A readable stream that is also an iterable.

streamLog

  • 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.

    Parameters

    • input: BaseLanguageModelInput
    • Optional options: Partial<CallOptions>
    • Optional streamOptions: Omit<LogStreamCallbackHandlerInput, "autoClose">

    Returns AsyncGenerator<RunLogPatch, any, unknown>

toJSON

toJSONNotImplemented

transform

  • 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.

    Parameters

    Returns AsyncGenerator<BaseMessageChunk, any, unknown>

withConfig

withFallbacks

withListeners

  • 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.

    Parameters

    • params: {
          onEnd?: ((run, config?) => void | Promise<void>);
          onError?: ((run, config?) => void | Promise<void>);
          onStart?: ((run, config?) => void | Promise<void>);
      }

      The object containing the callback functions.

      • Optional onEnd?: ((run, config?) => void | Promise<void>)
          • (run, config?): void | Promise<void>

          • Called after the runnable finishes running, with the Run object.

            Parameters

            Returns void | Promise<void>

      • Optional onError?: ((run, config?) => void | Promise<void>)
          • (run, config?): void | Promise<void>

          • Called if the runnable throws an error, with the Run object.

            Parameters

            Returns void | Promise<void>

      • Optional onStart?: ((run, config?) => void | Promise<void>)
          • (run, config?): void | Promise<void>

          • Called before the runnable starts running, with the Run object.

            Parameters

            Returns void | Promise<void>

    Returns Runnable<BaseLanguageModelInput, BaseMessageChunk, CallOptions>

withRetry

Static deserialize

Static isRunnable

Settings

Member Visibility

Theme

On This Page

Generated using TypeDoc