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.

Type Parameters

Hierarchy

Implements

Constructors

Properties

CallOptions: CallOptions
ParsedCallOptions: Omit<CallOptions, never>
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: number = 0

Penalizes repeated tokens according to frequency

modelName: string = "gpt-3.5-turbo"

Model name to use

n: number = 1

Number of completions to generate for each prompt

presencePenalty: number = 0

Penalizes repeated tokens

streaming: boolean = false

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

temperature: number = 1

Sampling temperature to use

topP: number = 1

Total probability mass of tokens to consider at each step

verbose: boolean

Whether to print out response text.

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/

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}/

azureOpenAIApiKey?: string

API key to use when making requests to Azure OpenAI.

azureOpenAIApiVersion?: string

API version to use when making requests to Azure OpenAI.

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}/

callbacks?: Callbacks
logitBias?: Record<string, number>

Dictionary used to adjust the probability of specific tokens being generated

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.

metadata?: Record<string, unknown>
modelKwargs?: Record<string, any>

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

openAIApiKey?: string

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

organization?: string
stop?: string[]

List of stop words to use when generating

tags?: string[]
timeout?: number

Timeout to use when making requests to OpenAI.

user?: string

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

lc_runnable: boolean = true

Accessors

Methods

  • 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>

  • 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.

  • Parameters

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

  • Get the identifying parameters for the model

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

  • Predicts the next message based on a text input.

    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.

  • 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>

  • Helper 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.

    Type Parameters

    Parameters

    • inputGenerator: AsyncGenerator<I, any, unknown>
    • transformer: ((generator, runManager?, options?) => AsyncGenerator<O, any, unknown>)
        • (generator, runManager?, options?): AsyncGenerator<O, any, unknown>
        • Parameters

          • generator: AsyncGenerator<I, any, unknown>
          • Optional runManager: CallbackManagerForChainRun
          • Optional options: Partial<CallOptions>

          Returns AsyncGenerator<O, any, unknown>

    • Optional options: CallOptions & {
          runType?: string;
      }

    Returns AsyncGenerator<O, any, unknown>

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