Class: ChatOpenAI

chat_models.ChatOpenAI

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.

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.

Hierarchy

• BaseChatModel

  ↳ ChatOpenAI

Implements

• OpenAIInput

Constructors

constructor

• new ChatOpenAI(fields?, configuration?)

Parameters

Name	Type
fields?	Partial<OpenAIInput> & BaseLanguageModelParams & { cache?: boolean ; concurrency?: number ; openAIApiKey?: string }
configuration?	ConfigurationParameters

Overrides

BaseChatModel.constructor

Defined in

langchain/src/chat_models/openai.ts:165

Properties

callbackManager

• callbackManager: CallbackManager

Inherited from

BaseChatModel.callbackManager

Defined in

langchain/src/base_language/index.ts:34

---

caller

• Protected 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.

Inherited from

BaseChatModel.caller

Defined in

langchain/src/base_language/index.ts:40

---

frequencyPenalty

• frequencyPenalty: number = 0

Penalizes repeated tokens according to frequency

Implementation of

OpenAIInput.frequencyPenalty

Defined in

langchain/src/chat_models/openai.ts:141

---

logitBias

• Optional logitBias: Record<string, number>

Dictionary used to adjust the probability of specific tokens being generated

Implementation of

OpenAIInput.logitBias

Defined in

langchain/src/chat_models/openai.ts:147

---

maxTokens

• Optional maxTokens: number

Maximum number of tokens to generate in the completion. If not specified, defaults to the maximum number of tokens allowed by the model.

Implementation of

OpenAIInput.maxTokens

Defined in

langchain/src/chat_models/openai.ts:159

---

modelKwargs

• Optional modelKwargs: Kwargs

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

Implementation of

OpenAIInput.modelKwargs

Defined in

langchain/src/chat_models/openai.ts:151

---

modelName

• modelName: string = "gpt-3.5-turbo"

Model name to use

Implementation of

OpenAIInput.modelName

Defined in

langchain/src/chat_models/openai.ts:149

---

n

• n: number = 1

Number of chat completions to generate for each prompt

Implementation of

OpenAIInput.n

Defined in

langchain/src/chat_models/openai.ts:145

---

presencePenalty

• presencePenalty: number = 0

Penalizes repeated tokens

Implementation of

OpenAIInput.presencePenalty

Defined in

langchain/src/chat_models/openai.ts:143

---

stop

• Optional stop: string[]

List of stop words to use when generating

Implementation of

OpenAIInput.stop

Defined in

langchain/src/chat_models/openai.ts:153

---

streaming

• streaming: boolean = false

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

Implementation of

OpenAIInput.streaming

Defined in

langchain/src/chat_models/openai.ts:157

---

temperature

• temperature: number = 1

Sampling temperature to use, between 0 and 2, defaults to 1

Implementation of

OpenAIInput.temperature

Defined in

langchain/src/chat_models/openai.ts:137

---

timeout

• Optional timeout: number

Timeout to use when making requests to OpenAI.

Implementation of

OpenAIInput.timeout

Defined in

langchain/src/chat_models/openai.ts:155

---

topP

• topP: number = 1

Total probability mass of tokens to consider at each step, between 0 and 1, defaults to 1

Implementation of

OpenAIInput.topP

Defined in

langchain/src/chat_models/openai.ts:139

---

verbose

• verbose: boolean

Whether to print out response text.

Inherited from

BaseChatModel.verbose

Defined in

langchain/src/base_language/index.ts:32

Methods

_combineLLMOutput

▸ _combineLLMOutput(...llmOutputs): OpenAILLMOutput

Parameters

Name	Type
...llmOutputs	OpenAILLMOutput[]

Returns

OpenAILLMOutput

Overrides

BaseChatModel._combineLLMOutput

Defined in

langchain/src/chat_models/openai.ts:452

---

_generate

▸ _generate(messages, stop?): Promise<ChatResult>

Call out to OpenAI's endpoint with k unique prompts

Example

import { OpenAI } from "langchain/llms";
const openai = new OpenAI();
const response = await openai.generate(["Tell me a joke."]);

Parameters

Name	Type	Description
messages	BaseChatMessage[]	The messages to pass into the model.
stop?	string[]	Optional list of stop words to use when generating.

Returns

Promise<ChatResult>

The full LLM output.

Overrides

BaseChatModel._generate

Defined in

langchain/src/chat_models/openai.ts:258

---

_identifyingParams

▸ _identifyingParams(): Object

Get the identifying parameters of the LLM.

Returns

Object

Name	Type
model_name	string

Overrides

BaseChatModel._identifyingParams

Defined in

langchain/src/chat_models/openai.ts:228

---

_llmType

▸ _llmType(): string

Returns

string

Overrides

BaseChatModel._llmType

Defined in

langchain/src/chat_models/openai.ts:448

---

_modelType

▸ _modelType(): string

Returns

string

Inherited from

BaseChatModel._modelType

Defined in

langchain/src/chat_models/base.ts:76

---

call

▸ call(messages, stop?): Promise<BaseChatMessage>

Parameters

Name	Type
messages	BaseChatMessage[]
stop?	string[]

Returns

Promise<BaseChatMessage>

Inherited from

BaseChatModel.call

Defined in

langchain/src/chat_models/base.ts:97

---

callPrompt

▸ callPrompt(promptValue, stop?): Promise<BaseChatMessage>

Parameters

Name	Type
promptValue	BasePromptValue
stop?	string[]

Returns

Promise<BaseChatMessage>

Inherited from

BaseChatModel.callPrompt

Defined in

langchain/src/chat_models/base.ts:106

---

generate

▸ generate(messages, stop?): Promise<LLMResult>

Parameters

Name	Type
messages	BaseChatMessage[][]
stop?	string[]

Returns

Promise<LLMResult>

Inherited from

BaseChatModel.generate

Defined in

langchain/src/chat_models/base.ts:39

---

generatePrompt

▸ generatePrompt(promptValues, stop?): Promise<LLMResult>

Parameters

Name	Type
promptValues	BasePromptValue[]
stop?	string[]

Returns

Promise<LLMResult>

Inherited from

BaseChatModel.generatePrompt

Defined in

langchain/src/chat_models/base.ts:82

---

getNumTokens

▸ getNumTokens(text): Promise<number>

Parameters

Name	Type
text	string

Returns

Promise<number>

Inherited from

BaseChatModel.getNumTokens

Defined in

langchain/src/base_language/index.ts:62

---

getNumTokensFromMessages

▸ getNumTokensFromMessages(messages): Promise<{ countPerMessage: number[] ; totalCount: number }>

Parameters

Name	Type
messages	BaseChatMessage[]

Returns

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

Defined in

langchain/src/chat_models/openai.ts:394

---

identifyingParams

▸ identifyingParams(): Object

Get the identifying parameters for the model

Returns

Object

Name	Type
model_name	string

Defined in

langchain/src/chat_models/openai.ts:239

---

invocationParams

▸ invocationParams(): Omit<CreateChatCompletionRequest, "messages"> & Kwargs

Get the parameters used to invoke the model

Returns

Omit<CreateChatCompletionRequest, "messages"> & Kwargs

Defined in

langchain/src/chat_models/openai.ts:212

---

serialize

▸ serialize(): SerializedLLM

Return a json-like object representing this LLM.

Returns

SerializedLLM

Inherited from

BaseChatModel.serialize

Defined in

langchain/src/base_language/index.ts:92

---

deserialize

▸ Static deserialize(data): Promise<BaseLanguageModel>

Load an LLM from a json-like object describing it.

Parameters

Name	Type
data	SerializedLLM

Returns

Promise<BaseLanguageModel>

Inherited from

BaseChatModel.deserialize

Defined in

langchain/src/base_language/index.ts:103