Wrapper around OpenAI large language models.

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.

Remarks

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

Example

const model = new OpenAI({
modelName: "gpt-4",
temperature: 0.7,
maxTokens: 1000,
maxRetries: 5,
});

const res = await model.invoke(
"Question: What would be a good company name for a company that makes colorful socks?\nAnswer:"
);
console.log({ res });

Hierarchy (view full)

Constructors

Properties

batchSize: number = 20

Batch size to use when passing multiple documents to generate

frequencyPenalty: number = 0

Penalizes repeated tokens according to frequency

maxTokens: number = 256

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.

model: string = "gpt-3.5-turbo-instruct"

Model name to use

modelName: string = "gpt-3.5-turbo-instruct"

Model name to use Alias for model

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 = 0.7

Sampling temperature to use

topP: number = 1

Total probability mass of tokens to consider at each step

apiKey?: string

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

azureADTokenProvider?: (() => Promise<string>)

Type declaration

    • (): Promise<string>
    • Returns Promise<string>

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}/

bestOf?: number

Generates bestOf completions server side and returns the "best"

logitBias?: Record<string, number>

Dictionary used to adjust the probability of specific tokens being generated

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. Alias for apiKey

organization?: string
stop?: string[]

List of stop words to use when generating Alias for stopSequences

stopSequences?: string[]

List of stop words to use when generating

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.

client: OpenAI
clientConfig: ClientOptions

Accessors

Methods

  • Get the identifying parameters for the model

    Returns Omit<CompletionCreateParams, "prompt"> & {
        model_name: string;
    } & ClientOptions

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