modelfusion

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Interfaces

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Functions

ObjectStreamFromResponse

▸ ObjectStreamFromResponse<OBJECT>(«destructured»): AsyncGenerator<{ partialObject: OBJECT }, void, unknown>

Convert a Response to a lightweight ObjectStream. The response must be created using ObjectStreamResponse on the server.

Type parameters

Name
`OBJECT`

Parameters

Name	Type
`«destructured»`	`Object`
› `response`	`Response`
› `schema`	`Schema`<`OBJECT`>

Returns

AsyncGenerator<{ partialObject: OBJECT }, void, unknown>

See

ObjectStreamResponse

Defined in

packages/modelfusion/src/model-function/generate-object/ObjectStream.ts:35

classify

▸ classify<VALUE, CLASS>(args): Promise<CLASS>

Type parameters

Name	Type
`VALUE`	`VALUE`
`CLASS`	extends `null` \| `string`

Parameters

Name	Type
`args`	{ `fullResponse?`: `false` ; `model`: `Classifier`<`VALUE`, `CLASS`, `ClassifierSettings`> ; `value`: `VALUE` } & `FunctionOptions`

Returns

Promise<CLASS>

Defined in

packages/modelfusion/src/model-function/classify/classify.ts:6

▸ classify<VALUE, CLASS>(args): Promise<{ class: CLASS ; metadata: ModelCallMetadata ; rawResponse: unknown }>

Type parameters

Name	Type
`VALUE`	`VALUE`
`CLASS`	extends `null` \| `string`

Parameters

Name	Type
`args`	{ `fullResponse`: `true` ; `model`: `Classifier`<`VALUE`, `CLASS`, `ClassifierSettings`> ; `value`: `VALUE` } & `FunctionOptions`

Returns

Promise<{ class: CLASS ; metadata: ModelCallMetadata ; rawResponse: unknown }>

Defined in

packages/modelfusion/src/model-function/classify/classify.ts:13

convertDataContentToBase64String

▸ convertDataContentToBase64String(content): string

Parameters

Name	Type
`content`	`DataContent`

Returns

string

Defined in

packages/modelfusion/src/util/format/DataContent.ts:8

convertDataContentToUint8Array

▸ convertDataContentToUint8Array(content): Uint8Array

Parameters

Name	Type
`content`	`DataContent`

Returns

Uint8Array

Defined in

packages/modelfusion/src/util/format/DataContent.ts:20

cosineSimilarity

▸ cosineSimilarity(a, b): number

Calculates the cosine similarity between two vectors. They must have the same length.

Parameters

Name	Type	Description
`a`	`number`[]	The first vector.
`b`	`number`[]	The second vector.

Returns

number

The cosine similarity between the two vectors.

See

https://en.wikipedia.org/wiki/Cosine_similarity

Defined in

packages/modelfusion/src/util/cosineSimilarity.ts:11

countOpenAIChatMessageTokens

▸ countOpenAIChatMessageTokens(«destructured»): Promise<number>

Parameters

Name	Type
`«destructured»`	`Object`
› `message`	`ChatMessage`
› `model`	`OpenAIChatModelType`

Returns

Promise<number>

Defined in

packages/modelfusion/src/model-provider/openai/countOpenAIChatMessageTokens.ts:21

countOpenAIChatPromptTokens

▸ countOpenAIChatPromptTokens(«destructured»): Promise<number>

Parameters

Name	Type
`«destructured»`	`Object`
› `messages`	`ChatMessage`[]
› `model`	`OpenAIChatModelType`

Returns

Promise<number>

Defined in

packages/modelfusion/src/model-provider/openai/countOpenAIChatMessageTokens.ts:56

countTokens

▸ countTokens(tokenizer, text): Promise<number>

Count the number of tokens in the given text.

Parameters

Name	Type
`tokenizer`	`BasicTokenizer`
`text`	`string`

Returns

Promise<number>

Defined in

packages/modelfusion/src/model-function/tokenize-text/countTokens.ts:6

createChatPrompt

▸ createChatPrompt<INPUT>(promptFunction): (input: INPUT) => PromptFunction<INPUT, ChatPrompt>

Type parameters

Name
`INPUT`

Parameters

Name	Type
`promptFunction`	(`input`: `INPUT`) => `Promise`<`ChatPrompt`>

Returns

fn

▸ (input): PromptFunction<INPUT, ChatPrompt>

Parameters

Name	Type
`input`	`INPUT`

Returns

PromptFunction<INPUT, ChatPrompt>

Defined in

packages/modelfusion/src/model-function/generate-text/prompt-template/ChatPrompt.ts:125

createEventSourceStream

▸ createEventSourceStream(events): ReadableStream<any>

Parameters

Name	Type
`events`	`AsyncIterable`<`unknown`>

Returns

ReadableStream<any>

Defined in

packages/modelfusion/src/util/streaming/createEventSourceStream.ts:3

createInstructionPrompt

▸ createInstructionPrompt<INPUT>(promptFunction): (input: INPUT) => PromptFunction<INPUT, InstructionPrompt>

Type parameters

Name
`INPUT`

Parameters

Name	Type
`promptFunction`	(`input`: `INPUT`) => `Promise`<`InstructionPrompt`>

Returns

fn

▸ (input): PromptFunction<INPUT, InstructionPrompt>

Parameters

Name	Type
`input`	`INPUT`

Returns

PromptFunction<INPUT, InstructionPrompt>

Defined in

packages/modelfusion/src/model-function/generate-text/prompt-template/InstructionPrompt.ts:42

createTextPrompt

▸ createTextPrompt<INPUT>(promptFunction): (input: INPUT) => PromptFunction<INPUT, string>

Type parameters

Name
`INPUT`

Parameters

Name	Type
`promptFunction`	(`input`: `INPUT`) => `Promise`<`string`>

Returns

fn

▸ (input): PromptFunction<INPUT, string>

Parameters

Name	Type
`input`	`INPUT`

Returns

PromptFunction<INPUT, string>

Defined in

packages/modelfusion/src/model-function/generate-text/prompt-template/TextPrompt.ts:6

delay

▸ delay(delayInMs): Promise<void>

Parameters

Name	Type
`delayInMs`	`number`

Returns

Promise<void>

Defined in

packages/modelfusion/src/util/delay.ts:1

embed

▸ embed<VALUE>(args): Promise<Vector>

Generate an embedding for a single value.

Type parameters

Name
`VALUE`

Parameters

Name	Type
`args`	{ `fullResponse?`: `false` ; `model`: `EmbeddingModel`<`VALUE`, `EmbeddingModelSettings`> ; `value`: `VALUE` } & `FunctionOptions`

Returns

Promise<Vector>

A promise that resolves to a vector representing the embedding.

See

https://modelfusion.dev/guide/function/embed

Example

const embedding = await embed({
  model: openai.TextEmbedder(...),
  value: "At first, Nox didn't know what to do with the pup."
});

Defined in

packages/modelfusion/src/model-function/embed/embed.ts:133

▸ embed<VALUE>(args): Promise<{ embedding: Vector ; metadata: ModelCallMetadata ; rawResponse: unknown }>

Type parameters

Name
`VALUE`

Parameters

Name	Type
`args`	{ `fullResponse`: `true` ; `model`: `EmbeddingModel`<`VALUE`, `EmbeddingModelSettings`> ; `value`: `VALUE` } & `FunctionOptions`

Returns

Promise<{ embedding: Vector ; metadata: ModelCallMetadata ; rawResponse: unknown }>

Defined in

packages/modelfusion/src/model-function/embed/embed.ts:140

embedMany

▸ embedMany<VALUE>(args): Promise<Vector[]>

Generate embeddings for multiple values.

Type parameters

Name
`VALUE`

Parameters

Name	Type
`args`	{ `fullResponse?`: `false` ; `model`: `EmbeddingModel`<`VALUE`, `EmbeddingModelSettings`> ; `values`: `VALUE`[] } & `FunctionOptions`

Returns

Promise<Vector[]>

A promise that resolves to an array of vectors representing the embeddings.

See

https://modelfusion.dev/guide/function/embed

Example

const embeddings = await embedMany({
  embedder: openai.TextEmbedder(...),
  values: [
    "At first, Nox didn't know what to do with the pup.",
    "He keenly observed and absorbed everything around him, from the birds in the sky to the trees in the forest.",
  ]
});

Defined in

packages/modelfusion/src/model-function/embed/embed.ts:26

▸ embedMany<VALUE>(args): Promise<{ embeddings: Vector[] ; metadata: ModelCallMetadata ; rawResponse: unknown }>

Type parameters

Name
`VALUE`

Parameters

Name	Type
`args`	{ `fullResponse`: `true` ; `model`: `EmbeddingModel`<`VALUE`, `EmbeddingModelSettings`> ; `values`: `VALUE`[] } & `FunctionOptions`

Returns

Promise<{ embeddings: Vector[] ; metadata: ModelCallMetadata ; rawResponse: unknown }>

Defined in

packages/modelfusion/src/model-function/embed/embed.ts:33

executeFunction

▸ executeFunction<INPUT, OUTPUT>(fn, input, options?): Promise<OUTPUT>

Type parameters

Name
`INPUT`
`OUTPUT`

Parameters

Name	Type
`fn`	(`input`: `INPUT`, `options`: `FunctionCallOptions`) => `PromiseLike`<`OUTPUT`>
`input`	`INPUT`
`options?`	`FunctionOptions`

Returns

Promise<OUTPUT>

Defined in

packages/modelfusion/src/core/executeFunction.ts:4

executeTool

▸ executeTool<TOOL>(params): Promise<ReturnType<TOOL["execute"]>>

executeTool executes a tool with the given parameters.

Type parameters

Name	Type
`TOOL`	extends `Tool`<`any`, `any`, `any`>

Parameters

Name	Type
`params`	{ `args`: `TOOL`[`"parameters"`][`"_type"`] ; `fullResponse?`: `false` ; `tool`: `TOOL` } & `FunctionOptions`

Returns

Promise<ReturnType<TOOL["execute"]>>

Defined in

packages/modelfusion/src/tool/execute-tool/executeTool.ts:30

▸ executeTool<TOOL>(params): Promise<{ metadata: ExecuteToolMetadata ; output: Awaited<ReturnType<TOOL["execute"]>> }>

Type parameters

Name	Type
`TOOL`	extends `Tool`<`any`, `any`, `any`>

Parameters

Name	Type
`params`	{ `args`: `TOOL`[`"parameters"`][`"_type"`] ; `fullResponse`: `true` ; `tool`: `TOOL` } & `FunctionOptions`

Returns

Promise<{ metadata: ExecuteToolMetadata ; output: Awaited<ReturnType<TOOL["execute"]>> }>

Defined in

packages/modelfusion/src/tool/execute-tool/executeTool.ts:37

generateImage

▸ generateImage<PROMPT>(args): Promise<Uint8Array>

Generates an image using a prompt.

The prompt depends on the model. For example, OpenAI image models expect a string prompt, and Stability AI models expect an array of text prompts with optional weights.

Type parameters

Name
`PROMPT`

Parameters

Name	Type
`args`	{ `fullResponse?`: `false` ; `model`: `ImageGenerationModel`<`PROMPT`, `ImageGenerationModelSettings`> ; `prompt`: `PROMPT` } & `FunctionOptions`

Returns

Promise<Uint8Array>

Returns a promise that resolves to the generated image. The image is a Uint8Array containing the image data in PNG format.

See

https://modelfusion.dev/guide/function/generate-image

Example

const image = await generateImage({
  imageGenerator: stability.ImageGenerator(...),
  prompt: [
    { text: "the wicked witch of the west" },
    { text: "style of early 19th century painting", weight: 0.5 },
  ]
});

Defined in

packages/modelfusion/src/model-function/generate-image/generateImage.ts:33

▸ generateImage<PROMPT>(args): Promise<{ image: Uint8Array ; imageBase64: string ; images: Uint8Array[] ; imagesBase64: string[] ; metadata: ModelCallMetadata ; rawResponse: unknown }>

Type parameters

Name
`PROMPT`

Parameters

Name	Type
`args`	{ `fullResponse`: `true` ; `model`: `ImageGenerationModel`<`PROMPT`, `ImageGenerationModelSettings`> ; `prompt`: `PROMPT` } & `FunctionOptions`

Returns

Promise<{ image: Uint8Array ; imageBase64: string ; images: Uint8Array[] ; imagesBase64: string[] ; metadata: ModelCallMetadata ; rawResponse: unknown }>

Defined in

packages/modelfusion/src/model-function/generate-image/generateImage.ts:40

generateObject

▸ generateObject<OBJECT, PROMPT, SETTINGS>(args): Promise<OBJECT>

Generate a typed object for a prompt and a schema.

Type parameters

Name	Type
`OBJECT`	`OBJECT`
`PROMPT`	`PROMPT`
`SETTINGS`	extends `ObjectGenerationModelSettings`

Parameters

Name	Type
`args`	{ `fullResponse?`: `false` ; `model`: `ObjectGenerationModel`<`PROMPT`, `SETTINGS`> ; `prompt`: `PROMPT` \| `PromptFunction`<`unknown`, `PROMPT`> \| (`schema`: `Schema`<`OBJECT`>) => `PROMPT` \| `PromptFunction`<`unknown`, `PROMPT`> ; `schema`: `Schema`<`OBJECT`> & `JsonSchemaProducer` } & `FunctionOptions`

Returns

Promise<OBJECT>

Returns a promise that resolves to the generated object.

See

https://modelfusion.dev/guide/function/generate-object

Example

const sentiment = await generateObject({
  model: openai.ChatTextGenerator(...).asFunctionCallObjectGenerationModel(...),

  schema: zodSchema(z.object({
    sentiment: z
      .enum(["positive", "neutral", "negative"])
      .describe("Sentiment."),
  })),

  prompt: [
    openai.ChatMessage.system(
      "You are a sentiment evaluator. " +
        "Analyze the sentiment of the following product review:"
    ),
    openai.ChatMessage.user(
      "After I opened the package, I was met by a very unpleasant smell " +
        "that did not disappear even after washing. Never again!"
    ),
  ]
});

Defined in

packages/modelfusion/src/model-function/generate-object/generateObject.ts:52

▸ generateObject<OBJECT, PROMPT, SETTINGS>(args): Promise<{ metadata: ModelCallMetadata ; rawResponse: unknown ; value: OBJECT }>

Type parameters

Name	Type
`OBJECT`	`OBJECT`
`PROMPT`	`PROMPT`
`SETTINGS`	extends `ObjectGenerationModelSettings`

Parameters

Name	Type
`args`	{ `fullResponse`: `true` ; `model`: `ObjectGenerationModel`<`PROMPT`, `SETTINGS`> ; `prompt`: `PROMPT` \| `PromptFunction`<`unknown`, `PROMPT`> \| (`schema`: `Schema`<`OBJECT`>) => `PROMPT` \| `PromptFunction`<`unknown`, `PROMPT`> ; `schema`: `Schema`<`OBJECT`> & `JsonSchemaProducer` } & `FunctionOptions`

Returns

Promise<{ metadata: ModelCallMetadata ; rawResponse: unknown ; value: OBJECT }>

Defined in

packages/modelfusion/src/model-function/generate-object/generateObject.ts:67

generateSpeech

▸ generateSpeech(args): Promise<Uint8Array>

Synthesizes speech from text. Also called text-to-speech (TTS).

Parameters

Name	Type
`args`	{ `fullResponse?`: `false` ; `model`: `SpeechGenerationModel`<`SpeechGenerationModelSettings`> ; `text`: `string` } & `FunctionOptions`

Returns

Promise<Uint8Array>

A promise that resolves to a Uint8Array containing the synthesized speech.

See

https://modelfusion.dev/guide/function/generate-speech

Example

const speech = await generateSpeech({
  model: lmnt.SpeechGenerator(...),
  text: "Good evening, ladies and gentlemen! Exciting news on the airwaves tonight " +
   "as The Rolling Stones unveil 'Hackney Diamonds.'
});

Defined in

packages/modelfusion/src/model-function/generate-speech/generateSpeech.ts:26

▸ generateSpeech(args): Promise<{ metadata: ModelCallMetadata ; rawResponse: unknown ; speech: Uint8Array }>

Parameters

Name	Type
`args`	{ `fullResponse`: `true` ; `model`: `SpeechGenerationModel`<`SpeechGenerationModelSettings`> ; `text`: `string` } & `FunctionOptions`

Returns

Promise<{ metadata: ModelCallMetadata ; rawResponse: unknown ; speech: Uint8Array }>

Defined in

packages/modelfusion/src/model-function/generate-speech/generateSpeech.ts:33

generateText

▸ generateText<PROMPT>(args): Promise<string>

Generate text for a prompt and return it as a string.

The prompt depends on the model used. For instance, OpenAI completion models expect a string prompt, whereas OpenAI chat models expect an array of chat messages.

Type parameters

Name
`PROMPT`

Parameters

Name	Type
`args`	{ `fullResponse?`: `false` ; `model`: `TextGenerationModel`<`PROMPT`, `TextGenerationModelSettings`> ; `prompt`: `PROMPT` \| `PromptFunction`<`unknown`, `PROMPT`> } & `FunctionOptions`

Returns

Promise<string>

A promise that resolves to the generated text.

See

https://modelfusion.dev/guide/function/generate-text

Example

const text = await generateText({
  model: openai.CompletionTextGenerator(...),
  prompt: "Write a short story about a robot learning to love:\n\n"
});

Defined in

packages/modelfusion/src/model-function/generate-text/generateText.ts:34

▸ generateText<PROMPT>(args): Promise<{ finishReason: TextGenerationFinishReason ; metadata: ModelCallMetadata ; rawResponse: unknown ; text: string ; textGenerationResults: TextGenerationResult[] ; texts: string[] }>

Type parameters

Name
`PROMPT`

Parameters

Name	Type
`args`	{ `fullResponse`: `true` ; `model`: `TextGenerationModel`<`PROMPT`, `TextGenerationModelSettings`> ; `prompt`: `PROMPT` \| `PromptFunction`<`unknown`, `PROMPT`> } & `FunctionOptions`

Returns

Promise<{ finishReason: TextGenerationFinishReason ; metadata: ModelCallMetadata ; rawResponse: unknown ; text: string ; textGenerationResults: TextGenerationResult[] ; texts: string[] }>

Defined in

packages/modelfusion/src/model-function/generate-text/generateText.ts:41

generateToolCall

▸ generateToolCall<PARAMETERS, PROMPT, NAME, SETTINGS>(params): Promise<ToolCall<NAME, PARAMETERS>>

Type parameters

Name	Type
`PARAMETERS`	`PARAMETERS`
`PROMPT`	`PROMPT`
`NAME`	extends `string`
`SETTINGS`	extends `ToolCallGenerationModelSettings`

Parameters

Name	Type
`params`	{ `fullResponse?`: `false` ; `model`: `ToolCallGenerationModel`<`PROMPT`, `SETTINGS`> ; `prompt`: `PROMPT` \| (`tool`: `ToolDefinition`<`NAME`, `PARAMETERS`>) => `PROMPT` ; `tool`: `ToolDefinition`<`NAME`, `PARAMETERS`> } & `FunctionOptions`

Returns

Promise<ToolCall<NAME, PARAMETERS>>

Defined in

packages/modelfusion/src/tool/generate-tool-call/generateToolCall.ts:13

▸ generateToolCall<PARAMETERS, PROMPT, NAME, SETTINGS>(params): Promise<{ metadata: ModelCallMetadata ; rawResponse: unknown ; toolCall: ToolCall<NAME, PARAMETERS> }>

Type parameters

Name	Type
`PARAMETERS`	`PARAMETERS`
`PROMPT`	`PROMPT`
`NAME`	extends `string`
`SETTINGS`	extends `ToolCallGenerationModelSettings`

Parameters

Name	Type
`params`	{ `fullResponse`: `true` ; `model`: `ToolCallGenerationModel`<`PROMPT`, `SETTINGS`> ; `prompt`: `PROMPT` \| (`tool`: `ToolDefinition`<`NAME`, `PARAMETERS`>) => `PROMPT` ; `tool`: `ToolDefinition`<`NAME`, `PARAMETERS`> } & `FunctionOptions`

Returns

Promise<{ metadata: ModelCallMetadata ; rawResponse: unknown ; toolCall: ToolCall<NAME, PARAMETERS> }>

Defined in

packages/modelfusion/src/tool/generate-tool-call/generateToolCall.ts:26

generateToolCalls

▸ generateToolCalls<TOOLS, PROMPT>(params): Promise<{ text: string | null ; toolCalls: ToOutputValue<TOOLS>[] | null }>

Type parameters

Name	Type
`TOOLS`	extends `ToolDefinition`<`any`, `any`>[]
`PROMPT`	`PROMPT`

Parameters

Name	Type
`params`	{ `fullResponse?`: `false` ; `model`: `ToolCallsGenerationModel`<`PROMPT`, `ToolCallsGenerationModelSettings`> ; `prompt`: `PROMPT` \| (`tools`: `TOOLS`) => `PROMPT` ; `tools`: `TOOLS` } & `FunctionOptions`

Returns

Promise<{ text: string | null ; toolCalls: ToOutputValue<TOOLS>[] | null }>

Defined in

packages/modelfusion/src/tool/generate-tool-calls/generateToolCalls.ts:37

▸ generateToolCalls<TOOLS, PROMPT>(params): Promise<{ metadata: ModelCallMetadata ; rawResponse: unknown ; value: { text: string | null ; toolCalls: ToOutputValue<TOOLS>[] } }>

Type parameters

Name	Type
`TOOLS`	extends `ToolDefinition`<`any`, `any`>[]
`PROMPT`	`PROMPT`

Parameters

Name	Type
`params`	{ `fullResponse`: `true` ; `model`: `ToolCallsGenerationModel`<`PROMPT`, `ToolCallsGenerationModelSettings`> ; `prompt`: `PROMPT` \| (`tools`: `TOOLS`) => `PROMPT` ; `tools`: `TOOLS` } & `FunctionOptions`

Returns

Promise<{ metadata: ModelCallMetadata ; rawResponse: unknown ; value: { text: string | null ; toolCalls: ToOutputValue<TOOLS>[] } }>

Defined in

packages/modelfusion/src/tool/generate-tool-calls/generateToolCalls.ts:51

generateTranscription

▸ generateTranscription(args): Promise<string>

Transcribe audio data into text. Also called speech-to-text (STT) or automatic speech recognition (ASR).

Parameters

Name	Type
`args`	{ `audioData`: `DataContent` ; `fullResponse?`: `false` ; `mimeType`: `"audio/webm"` \| `"audio/mp3"` \| `"audio/wav"` \| `"audio/mp4"` \| `"audio/mpeg"` \| `"audio/mpga"` \| `"audio/ogg"` \| `"audio/oga"` \| `"audio/flac"` \| `"audio/m4a"` \| `string` & ; `model`: `TranscriptionModel`<`TranscriptionModelSettings`> } & `FunctionOptions`

Returns

Promise<string>

A promise that resolves to the transcribed text.

See

https://modelfusion.dev/guide/function/generate-transcription

Example

const audioData = await fs.promises.readFile("data/test.mp3");

const transcription = await generateTranscription({
  model: openai.Transcriber({ model: "whisper-1" }),
  mimeType: "audio/mp3",
  audioData,
});

Defined in

packages/modelfusion/src/model-function/generate-transcription/generateTranscription.ts:31

▸ generateTranscription(args): Promise<{ metadata: ModelCallMetadata ; rawResponse: unknown ; value: string }>

Parameters

Name	Type
`args`	{ `audioData`: `DataContent` ; `fullResponse`: `true` ; `mimeType`: `"audio/webm"` \| `"audio/mp3"` \| `"audio/wav"` \| `"audio/mp4"` \| `"audio/mpeg"` \| `"audio/mpga"` \| `"audio/ogg"` \| `"audio/oga"` \| `"audio/flac"` \| `"audio/m4a"` \| `string` & ; `model`: `TranscriptionModel`<`TranscriptionModelSettings`> } & `FunctionOptions`

Returns

Promise<{ metadata: ModelCallMetadata ; rawResponse: unknown ; value: string }>

Defined in

packages/modelfusion/src/model-function/generate-transcription/generateTranscription.ts:39

getAudioFileExtension

▸ getAudioFileExtension(mimeType): "mp3" | "flac" | "webm" | "wav" | "mp4" | "mpeg" | "ogg" | "m4a"

Parameters

Name	Type
`mimeType`	`string`

Returns

"mp3" | "flac" | "webm" | "wav" | "mp4" | "mpeg" | "ogg" | "m4a"

Defined in

packages/modelfusion/src/util/audio/getAudioFileExtension.ts:1

getOpenAIChatModelInformation

▸ getOpenAIChatModelInformation(model): Object

Parameters

Name	Type
`model`	`OpenAIChatModelType`

Returns

Object

Name	Type
`baseModel`	`OpenAIChatBaseModelType`
`contextWindowSize`	`number`
`isFineTuned`	`boolean`

Defined in

packages/modelfusion/src/model-provider/openai/OpenAIChatModel.ts:47

getOpenAICompletionModelInformation

▸ getOpenAICompletionModelInformation(model): Object

Parameters

Name	Type
`model`	`"gpt-3.5-turbo-instruct"`

Returns

Object

Name	Type
`contextWindowSize`	`number`

Defined in

packages/modelfusion/src/model-provider/openai/OpenAICompletionModel.ts:29

getRun

▸ getRun(run?): Promise<Run | undefined>

Returns the run stored in an AsyncLocalStorage if running in Node.js. It can be set with withRun().

Parameters

Name	Type
`run?`	`Run`

Returns

Promise<Run | undefined>

Defined in

packages/modelfusion/src/core/getRun.ts:39

isPromptFunction

▸ isPromptFunction<INPUT, PROMPT>(fn): fn is PromptFunction<INPUT, PROMPT>

Checks if a function is a PromptFunction by checking for the unique symbol.

Type parameters

Name
`INPUT`
`PROMPT`

Parameters

Name	Type	Description
`fn`	`unknown`	The function to check.

Returns

fn is PromptFunction<INPUT, PROMPT>

True if the function is a PromptFunction, false otherwise.

Defined in

packages/modelfusion/src/core/PromptFunction.ts:47

mapBasicPromptToAutomatic1111Format

▸ mapBasicPromptToAutomatic1111Format(): PromptTemplate<string, Automatic1111ImageGenerationPrompt>

Formats a basic text prompt as an Automatic1111 prompt.

Returns

PromptTemplate<string, Automatic1111ImageGenerationPrompt>

Defined in

packages/modelfusion/src/model-provider/automatic1111/Automatic1111ImageGenerationPrompt.ts:11

mapBasicPromptToStabilityFormat

▸ mapBasicPromptToStabilityFormat(): PromptTemplate<string, StabilityImageGenerationPrompt>

Formats a basic text prompt as a Stability prompt.

Returns

PromptTemplate<string, StabilityImageGenerationPrompt>

Defined in

packages/modelfusion/src/model-provider/stability/StabilityImageGenerationPrompt.ts:11

markAsPromptFunction

▸ markAsPromptFunction<INPUT, PROMPT>(fn): PromptFunction<INPUT, PROMPT>

Marks a function as a PromptFunction by setting a unique symbol.

Type parameters

Name
`INPUT`
`PROMPT`

Parameters

Name	Type	Description
`fn`	() => `PromiseLike`<{ `input`: `INPUT` ; `prompt`: `PROMPT` }>	The function to mark.

Returns

PromptFunction<INPUT, PROMPT>

The marked function.

Defined in

packages/modelfusion/src/core/PromptFunction.ts:29

parseJSON

▸ parseJSON(text): unknown

Parses a JSON string into an unknown object.

Parameters

Name	Type	Description
`text`	`Object`	The JSON string to parse.
`text.text`	`string`	-

Returns

unknown

The parsed JSON object.

Defined in

packages/modelfusion/src/core/schema/parseJSON.ts:13

▸ parseJSON<T>(«destructured»): T

Parses a JSON string into a strongly-typed object using the provided schema.

Type parameters

Name	Description
`T`	The type of the object to parse the JSON into.

Parameters

Name	Type
`«destructured»`	`Object`
› `schema`	`Schema`<`T`>
› `text`	`string`

Returns

T

The parsed object.

Defined in

packages/modelfusion/src/core/schema/parseJSON.ts:22

retrieve

▸ retrieve<OBJECT, QUERY>(retriever, query, options?): Promise<OBJECT[]>

Type parameters

Name
`OBJECT`
`QUERY`

Parameters

Name	Type
`retriever`	`Retriever`<`OBJECT`, `QUERY`>
`query`	`QUERY`
`options?`	`FunctionOptions`

Returns

Promise<OBJECT[]>

Defined in

packages/modelfusion/src/retriever/retrieve.ts:5

runTool

▸ runTool<PROMPT, TOOL>(«destructured»): Promise<ToolCallResult<TOOL["name"], TOOL["parameters"], Awaited<ReturnType<TOOL["execute"]>>>>

runTool uses generateToolCall to generate parameters for a tool and then executes the tool with the parameters using executeTool.

Type parameters

Name	Type
`PROMPT`	`PROMPT`
`TOOL`	extends `Tool`<`string`, `any`, `any`>

Parameters

Name	Type
`«destructured»`	{ `model`: `ToolCallGenerationModel`<`PROMPT`, `ToolCallGenerationModelSettings`> ; `prompt`: `PROMPT` \| (`tool`: `TOOL`) => `PROMPT` ; `tool`: `TOOL` } & `FunctionOptions`

Returns

Promise<ToolCallResult<TOOL["name"], TOOL["parameters"], Awaited<ReturnType<TOOL["execute"]>>>>

The result contains the name of the tool (tool property), the parameters (parameters property, typed), and the result of the tool execution (result property, typed).

See

Defined in

packages/modelfusion/src/tool/run-tool/runTool.ts:23

runTools

▸ runTools<PROMPT, TOOLS>(«destructured»): Promise<{ text: string | null ; toolResults: ToOutputValue<TOOLS>[] | null }>

Type parameters

Name	Type
`PROMPT`	`PROMPT`
`TOOLS`	extends `Tool`<`any`, `any`, `any`>[]

Parameters

Name	Type
`«destructured»`	{ `model`: `ToolCallsGenerationModel`<`PROMPT`, `ToolCallsGenerationModelSettings`> ; `prompt`: `PROMPT` \| (`tools`: `TOOLS`) => `PROMPT` ; `tools`: `TOOLS` } & `FunctionOptions`

Returns

Promise<{ text: string | null ; toolResults: ToOutputValue<TOOLS>[] | null }>

Defined in

packages/modelfusion/src/tool/run-tools/runTools.ts:43

safeParseJSON

▸ safeParseJSON(text): { success: true ; value: unknown } | { error: JSONParseError | TypeValidationError ; success: false }

Safely parses a JSON string and returns the result as an object of type unknown.

Parameters

Name	Type	Description
`text`	`Object`	The JSON string to parse.
`text.text`	`string`	-

Returns

{ success: true ; value: unknown } | { error: JSONParseError | TypeValidationError ; success: false }

Either an object with success: true and the parsed data, or an object with success: false and the error that occurred.

Defined in

packages/modelfusion/src/core/schema/parseJSON.ts:62

▸ safeParseJSON<T>(«destructured»): { success: true ; value: T } | { error: JSONParseError | TypeValidationError ; success: false }

Safely parses a JSON string into a strongly-typed object, using a provided schema to validate the object.

Type parameters

Name	Description
`T`	The type of the object to parse the JSON into.

Parameters

Name	Type
`«destructured»`	`Object`
› `schema`	`Schema`<`T`>
› `text`	`string`

Returns

{ success: true ; value: T } | { error: JSONParseError | TypeValidationError ; success: false }

An object with either a success flag and the parsed and typed data, or a success flag and an error object.

Defined in

packages/modelfusion/src/core/schema/parseJSON.ts:77

safeValidateTypes

▸ safeValidateTypes<T>(«destructured»): { success: true ; value: T } | { error: TypeValidationError ; success: false }

Safely validates the types of an unknown object using a schema and return a strongly-typed object.

Type parameters

Name	Description
`T`	The type of the object to validate.

Parameters

Name	Type
`«destructured»`	`Object`
› `schema`	`Schema`<`T`>
› `value`	`unknown`

Returns

{ success: true ; value: T } | { error: TypeValidationError ; success: false }

An object with either a success flag and the parsed and typed data, or a success flag and an error object.

Defined in

packages/modelfusion/src/core/schema/validateTypes.ts:49

splitAtCharacter

▸ splitAtCharacter(«destructured»): SplitFunction

Splits text recursively until the resulting chunks are smaller than the maxCharactersPerChunk. The text is recursively split in the middle, so that all chunks are roughtly the same size.

Parameters

Name	Type
`«destructured»`	`Object`
› `maxCharactersPerChunk`	`number`

Returns

SplitFunction

Defined in

packages/modelfusion/src/text-chunk/split/splitRecursively.ts:37

splitAtToken

▸ splitAtToken(«destructured»): SplitFunction

Splits text recursively until the resulting chunks are smaller than the maxTokensPerChunk, while respecting the token boundaries. The text is recursively split in the middle, so that all chunks are roughtly the same size.

Parameters

Name	Type
`«destructured»`	`Object`
› `maxTokensPerChunk`	`number`
› `tokenizer`	`FullTokenizer`

Returns

SplitFunction

Defined in

packages/modelfusion/src/text-chunk/split/splitRecursively.ts:54

splitOnSeparator

▸ splitOnSeparator(«destructured»): SplitFunction

Splits text on a separator string.

Parameters

Name	Type
`«destructured»`	`Object`
› `separator`	`string`

Returns

SplitFunction

Defined in

packages/modelfusion/src/text-chunk/split/splitOnSeparator.ts:6

splitTextChunk

▸ splitTextChunk<CHUNK>(splitFunction, input): Promise<CHUNK[]>

Type parameters

Name	Type
`CHUNK`	extends `TextChunk`

Parameters

Name	Type
`splitFunction`	`SplitFunction`
`input`	`CHUNK`

Returns

Promise<CHUNK[]>

Defined in

packages/modelfusion/src/text-chunk/split/splitTextChunks.ts:14

splitTextChunks

▸ splitTextChunks<CHUNK>(splitFunction, inputs): Promise<CHUNK[]>

Type parameters

Name	Type
`CHUNK`	extends `TextChunk`

Parameters

Name	Type
`splitFunction`	`SplitFunction`
`inputs`	`CHUNK`[]

Returns

Promise<CHUNK[]>

Defined in

packages/modelfusion/src/text-chunk/split/splitTextChunks.ts:4

streamObject

▸ streamObject<OBJECT, PROMPT>(args): Promise<ObjectStream<OBJECT>>

Generate and stream an object for a prompt and a schema.

Type parameters

Name
`OBJECT`
`PROMPT`

Parameters

Name	Type
`args`	{ `fullResponse?`: `false` ; `model`: `ObjectStreamingModel`<`PROMPT`, `ObjectGenerationModelSettings`> ; `prompt`: `PROMPT` \| `PromptFunction`<`unknown`, `PROMPT`> \| (`schema`: `Schema`<`OBJECT`>) => `PROMPT` \| `PromptFunction`<`unknown`, `PROMPT`> ; `schema`: `Schema`<`OBJECT`> & `JsonSchemaProducer` } & `FunctionOptions`

Returns

Promise<ObjectStream<OBJECT>>

See

https://modelfusion.dev/guide/function/generate-object

Example

const objectStream = await streamObject({
  model: openai.ChatTextGenerator(...).asFunctionCallObjectGenerationModel(...),
  schema: zodSchema(
    z.array(
      z.object({
        name: z.string(),
        class: z
          .string()
          .describe("Character class, e.g. warrior, mage, or thief."),
        description: z.string(),
      })
    ),
  prompt: [
    openai.ChatMessage.user(
      "Generate 3 character descriptions for a fantasy role playing game."
    ),
  ]
});

for await (const { partialObject } of objectStream) {
  // ...
}

Defined in

packages/modelfusion/src/model-function/generate-object/streamObject.ts:51

▸ streamObject<OBJECT, PROMPT>(args): Promise<{ metadata: Omit<ModelCallMetadata, "durationInMs" | "finishTimestamp"> ; objectPromise: PromiseLike<OBJECT> ; objectStream: ObjectStream<OBJECT> }>

Type parameters

Name
`OBJECT`
`PROMPT`

Parameters

Name	Type
`args`	{ `fullResponse`: `true` ; `model`: `ObjectStreamingModel`<`PROMPT`, `ObjectGenerationModelSettings`> ; `prompt`: `PROMPT` \| `PromptFunction`<`unknown`, `PROMPT`> \| (`schema`: `Schema`<`OBJECT`>) => `PROMPT` \| `PromptFunction`<`unknown`, `PROMPT`> ; `schema`: `Schema`<`OBJECT`> & `JsonSchemaProducer` } & `FunctionOptions`

Returns

Promise<{ metadata: Omit<ModelCallMetadata, "durationInMs" | "finishTimestamp"> ; objectPromise: PromiseLike<OBJECT> ; objectStream: ObjectStream<OBJECT> }>

Defined in

packages/modelfusion/src/model-function/generate-object/streamObject.ts:62

streamSpeech

▸ streamSpeech(args): Promise<AsyncIterable<Uint8Array>>

Stream synthesized speech from text. Also called text-to-speech (TTS). Duplex streaming where both the input and output are streamed is supported.

Parameters

Name	Type
`args`	{ `fullResponse?`: `false` ; `model`: `StreamingSpeechGenerationModel`<`SpeechGenerationModelSettings`> ; `text`: `string` \| `AsyncIterable`<`string`> } & `FunctionOptions`

Returns

Promise<AsyncIterable<Uint8Array>>

An async iterable promise that contains the synthesized speech chunks.

See

https://modelfusion.dev/guide/function/generate-speech

Example

const textStream = await streamText(...);

const speechStream = await streamSpeech({
  model: elevenlabs.SpeechGenerator(...),
  text: textStream
});

for await (const speechPart of speechStream) {
  // ...
}

Defined in

packages/modelfusion/src/model-function/generate-speech/streamSpeech.ts:34

▸ streamSpeech(args): Promise<{ metadata: Omit<ModelCallMetadata, "durationInMs" | "finishTimestamp"> ; speechStream: AsyncIterable<Uint8Array> }>

Parameters

Name	Type
`args`	{ `fullResponse`: `true` ; `model`: `StreamingSpeechGenerationModel`<`SpeechGenerationModelSettings`> ; `text`: `string` \| `AsyncIterable`<`string`> } & `FunctionOptions`

Returns

Promise<{ metadata: Omit<ModelCallMetadata, "durationInMs" | "finishTimestamp"> ; speechStream: AsyncIterable<Uint8Array> }>

Defined in

packages/modelfusion/src/model-function/generate-speech/streamSpeech.ts:41

streamText

▸ streamText<PROMPT>(args): Promise<AsyncIterable<string>>

Stream the generated text for a prompt as an async iterable.

The prompt depends on the model used. For instance, OpenAI completion models expect a string prompt, whereas OpenAI chat models expect an array of chat messages.

Type parameters

Name
`PROMPT`

Parameters

Name	Type
`args`	{ `fullResponse?`: `false` ; `model`: `TextStreamingModel`<`PROMPT`, `TextGenerationModelSettings`> ; `prompt`: `PROMPT` \| `PromptFunction`<`unknown`, `PROMPT`> } & `FunctionOptions`

Returns

Promise<AsyncIterable<string>>

An async iterable promise that yields the generated text.

See

https://modelfusion.dev/guide/function/generate-text

Example

const textStream = await streamText({
  model: openai.CompletionTextGenerator(...),
  prompt: "Write a short story about a robot learning to love:\n\n"
});

for await (const textPart of textStream) {
  // ...
}

Defined in

packages/modelfusion/src/model-function/generate-text/streamText.ts:32

▸ streamText<PROMPT>(args): Promise<{ metadata: Omit<ModelCallMetadata, "durationInMs" | "finishTimestamp"> ; textPromise: PromiseLike<string> ; textStream: AsyncIterable<string> }>

Type parameters

Name
`PROMPT`

Parameters

Name	Type
`args`	{ `fullResponse`: `true` ; `model`: `TextStreamingModel`<`PROMPT`, `TextGenerationModelSettings`> ; `prompt`: `PROMPT` \| `PromptFunction`<`unknown`, `PROMPT`> } & `FunctionOptions`

Returns

Promise<{ metadata: Omit<ModelCallMetadata, "durationInMs" | "finishTimestamp"> ; textPromise: PromiseLike<string> ; textStream: AsyncIterable<string> }>

Defined in

packages/modelfusion/src/model-function/generate-text/streamText.ts:39

trimChatPrompt

▸ trimChatPrompt(«destructured»): Promise<ChatPrompt>

Keeps only the most recent messages in the prompt, while leaving enough space for the completion.

It will remove user-ai message pairs that don't fit. The result is always a valid chat prompt.

When the minimal chat prompt (system message + last user message) is already too long, it will only return this minimal chat prompt.

Parameters

Name	Type
`«destructured»`	`Object`
› `model`	`TextGenerationModel`<`ChatPrompt`, `TextGenerationModelSettings`> & `HasTokenizer`<`ChatPrompt`> & `HasContextWindowSize`
› `prompt`	`ChatPrompt`
› `tokenLimit?`	`number`

Returns

Promise<ChatPrompt>

See

https://modelfusion.dev/guide/function/generate-text#limiting-the-chat-length

Defined in

packages/modelfusion/src/model-function/generate-text/prompt-template/trimChatPrompt.ts:19

uncheckedSchema

▸ uncheckedSchema<OBJECT>(jsonSchema?): UncheckedSchema<OBJECT>

Type parameters

Name
`OBJECT`

Parameters

Name	Type
`jsonSchema?`	`unknown`

Returns

UncheckedSchema<OBJECT>

Defined in

packages/modelfusion/src/core/schema/UncheckedSchema.ts:4

upsertIntoVectorIndex

▸ upsertIntoVectorIndex<VALUE, OBJECT>(«destructured», options?): Promise<void>

Type parameters

Name
`VALUE`
`OBJECT`

Parameters

Name	Type	Default value
`«destructured»`	`Object`	`undefined`
› `embeddingModel`	`EmbeddingModel`<`VALUE`, `EmbeddingModelSettings`>	`undefined`
› `generateId?`	() => `string`	`createId`
› `getId?`	(`object`: `OBJECT`, `index`: `number`) => `undefined` \| `string`	`undefined`
› `getValueToEmbed`	(`object`: `OBJECT`, `index`: `number`) => `VALUE`	`undefined`
› `objects`	`OBJECT`[]	`undefined`
› `vectorIndex`	`VectorIndex`<`OBJECT`, `unknown`, `unknown`>	`undefined`
`options?`	`FunctionOptions`	`undefined`

Returns

Promise<void>

Defined in

packages/modelfusion/src/vector-index/upsertIntoVectorIndex.ts:11

validateContentIsString

▸ validateContentIsString(content, prompt): string

Parameters

Name	Type
`content`	`unknown`
`prompt`	`unknown`

Returns

string

Defined in

packages/modelfusion/src/model-function/generate-text/prompt-template/ContentPart.ts:42

validateTypes

▸ validateTypes<T>(«destructured»): T

Validates the types of an unknown object using a schema and return a strongly-typed object.

Type parameters

Name	Description
`T`	The type of the object to validate.

Parameters

Name	Type
`«destructured»`	`Object`
› `schema`	`Schema`<`T`>
› `value`	`unknown`

Returns

T

The typed object.

Defined in

packages/modelfusion/src/core/schema/validateTypes.ts:13

withRun

▸ withRun(run, callback): Promise<void>

Stores the run in an AsyncLocalStorage if running in Node.js. It can be retrieved with getRun().

Parameters

Name	Type
`run`	`Run`
`callback`	(`run`: `Run`) => `PromiseLike`<`void`>

Returns

Promise<void>

Defined in

packages/modelfusion/src/core/getRun.ts:47

zodSchema

▸ zodSchema<OBJECT>(zodSchema): ZodSchema<OBJECT>

Type parameters

Name
`OBJECT`

Parameters

Name	Type
`zodSchema`	`ZodType`<`OBJECT`, `ZodTypeDef`, `OBJECT`>

Returns

ZodSchema<OBJECT>

Defined in

packages/modelfusion/src/core/schema/ZodSchema.ts:7

Variables

CHAT_MODEL_CONTEXT_WINDOW_SIZES

• Const CHAT_MODEL_CONTEXT_WINDOW_SIZES: Object

Type declaration

Name	Type
`gpt-3.5-turbo`	`4096`
`gpt-3.5-turbo-0125`	`16385`
`gpt-3.5-turbo-0301`	`4096`
`gpt-3.5-turbo-0613`	`4096`
`gpt-3.5-turbo-1106`	`16385`
`gpt-3.5-turbo-16k`	`16384`
`gpt-3.5-turbo-16k-0613`	`16384`
`gpt-4`	`8192`
`gpt-4-0125-preview`	`128000`
`gpt-4-0314`	`8192`
`gpt-4-0613`	`8192`
`gpt-4-1106-preview`	`128000`
`gpt-4-32k`	`32768`
`gpt-4-32k-0314`	`32768`
`gpt-4-32k-0613`	`32768`
`gpt-4-turbo-preview`	`128000`
`gpt-4-vision-preview`	`128000`

Defined in

packages/modelfusion/src/model-provider/openai/OpenAIChatModel.ts:27

COHERE_TEXT_EMBEDDING_MODELS

• Const COHERE_TEXT_EMBEDDING_MODELS: Object

Type declaration

Name	Type
`embed-english-light-v2.0`	{ `contextWindowSize`: `number` = 512; `dimensions`: `number` = 1024 }
`embed-english-light-v2.0.contextWindowSize`	`number`
`embed-english-light-v2.0.dimensions`	`number`
`embed-english-light-v3.0`	{ `contextWindowSize`: `number` = 512; `dimensions`: `number` = 384 }
`embed-english-light-v3.0.contextWindowSize`	`number`
`embed-english-light-v3.0.dimensions`	`number`
`embed-english-v2.0`	{ `contextWindowSize`: `number` = 512; `dimensions`: `number` = 4096 }
`embed-english-v2.0.contextWindowSize`	`number`
`embed-english-v2.0.dimensions`	`number`
`embed-english-v3.0`	{ `contextWindowSize`: `number` = 512; `dimensions`: `number` = 1024 }
`embed-english-v3.0.contextWindowSize`	`number`
`embed-english-v3.0.dimensions`	`number`
`embed-multilingual-light-v3.0`	{ `contextWindowSize`: `number` = 512; `dimensions`: `number` = 384 }
`embed-multilingual-light-v3.0.contextWindowSize`	`number`
`embed-multilingual-light-v3.0.dimensions`	`number`
`embed-multilingual-v2.0`	{ `contextWindowSize`: `number` = 256; `dimensions`: `number` = 768 }
`embed-multilingual-v2.0.contextWindowSize`	`number`
`embed-multilingual-v2.0.dimensions`	`number`
`embed-multilingual-v3.0`	{ `contextWindowSize`: `number` = 512; `dimensions`: `number` = 1024 }
`embed-multilingual-v3.0.contextWindowSize`	`number`
`embed-multilingual-v3.0.dimensions`	`number`

Defined in

packages/modelfusion/src/model-provider/cohere/CohereTextEmbeddingModel.ts:20

COHERE_TEXT_GENERATION_MODELS

• Const COHERE_TEXT_GENERATION_MODELS: Object

Type declaration

Name	Type
`command`	{ `contextWindowSize`: `number` = 4096 }
`command.contextWindowSize`	`number`
`command-light`	{ `contextWindowSize`: `number` = 4096 }
`command-light.contextWindowSize`	`number`

Defined in

packages/modelfusion/src/model-provider/cohere/CohereTextGenerationModel.ts:32

ChatMessage

• ChatMessage: Object

Type declaration

Name	Type
`assistant`	(`__namedParameters`: { `text`: `null` \| `string` ; `toolResults`: `null` \| `ToolCallResult`<`string`, `unknown`, `unknown`>[] }) => `ChatMessage`
`tool`	(`__namedParameters`: { `toolResults`: `null` \| `ToolCallResult`<`string`, `unknown`, `unknown`>[] }) => `ChatMessage`
`user`	(`__namedParameters`: { `text`: `string` }) => `ChatMessage`

Defined in

packages/modelfusion/src/model-function/generate-text/prompt-template/ChatPrompt.ts:49

packages/modelfusion/src/model-function/generate-text/prompt-template/ChatPrompt.ts:54

CohereTextGenerationResponseFormat

• Const CohereTextGenerationResponseFormat: Object

Type declaration

Name	Type	Description
`deltaIterable`	{ `handler`: (`__namedParameters`: { `response`: `Response` }) => `Promise`<`AsyncIterable`<`Delta`<{ `is_finished`: `false` ; `text`: `string` } \| { `finish_reason`: `string` ; `is_finished`: `true` ; `response`: { `generations`: { `finish_reason?`: `string` ; `id`: `string` ; `text`: `string` }[] ; `id`: `string` ; `meta?`: { `api_version`: { `version`: `string` } } ; `prompt`: `string` } = cohereTextGenerationResponseSchema }>>> ; `stream`: `boolean` = true }	Returns an async iterable over the full deltas (all choices, including full current state at time of event) of the response stream.
`deltaIterable.handler`	(`__namedParameters`: { `response`: `Response` }) => `Promise`<`AsyncIterable`<`Delta`<{ `is_finished`: `false` ; `text`: `string` } \| { `finish_reason`: `string` ; `is_finished`: `true` ; `response`: { `generations`: { `finish_reason?`: `string` ; `id`: `string` ; `text`: `string` }[] ; `id`: `string` ; `meta?`: { `api_version`: { `version`: `string` } } ; `prompt`: `string` } = cohereTextGenerationResponseSchema }>>>	-
`deltaIterable.stream`	`boolean`	-
`json`	{ `handler`: `ResponseHandler`<{ `generations`: { `finish_reason?`: `string` ; `id`: `string` ; `text`: `string` }[] ; `id`: `string` ; `meta?`: { `api_version`: { `version`: `string` } } ; `prompt`: `string` }> ; `stream`: `boolean` = false }	Returns the response as a JSON object.
`json.handler`	`ResponseHandler`<{ `generations`: { `finish_reason?`: `string` ; `id`: `string` ; `text`: `string` }[] ; `id`: `string` ; `meta?`: { `api_version`: { `version`: `string` } } ; `prompt`: `string` }>	-
`json.stream`	`boolean`	-

Defined in

packages/modelfusion/src/model-provider/cohere/CohereTextGenerationModel.ts:315

LlamaCppCompletionResponseFormat

• Const LlamaCppCompletionResponseFormat: Object

Type declaration

Name	Type	Description
`deltaIterable`	{ `handler`: (`__namedParameters`: { `response`: `Response` }) => `Promise`<`AsyncIterable`<`Delta`<{ `content`: `string` ; `generation_settings`: { `frequency_penalty`: `number` ; `ignore_eos`: `boolean` ; `logit_bias`: `number`[] ; `mirostat`: `number` ; `mirostat_eta`: `number` ; `mirostat_tau`: `number` ; `model`: `string` ; `n_ctx`: `number` ; `n_keep`: `number` ; `n_predict`: `number` ; `n_probs`: `number` ; `penalize_nl`: `boolean` ; `presence_penalty`: `number` ; `repeat_last_n`: `number` ; `repeat_penalty`: `number` ; `seed`: `number` ; `stop`: `string`[] ; `stream`: `boolean` ; `temperature?`: `number` ; `tfs_z`: `number` ; `top_k`: `number` ; `top_p`: `number` ; `typical_p`: `number` } ; `model`: `string` ; `prompt`: `string` ; `stop`: `true` ; `stopped_eos`: `boolean` ; `stopped_limit`: `boolean` ; `stopped_word`: `boolean` ; `stopping_word`: `string` ; `timings`: { `predicted_ms`: `number` ; `predicted_n`: `number` ; `predicted_per_second`: `null` \| `number` ; `predicted_per_token_ms`: `null` \| `number` ; `prompt_ms?`: `null` \| `number` ; `prompt_n`: `number` ; `prompt_per_second`: `null` \| `number` ; `prompt_per_token_ms`: `null` \| `number` } ; `tokens_cached`: `number` ; `tokens_evaluated`: `number` ; `tokens_predicted`: `number` ; `truncated`: `boolean` } \| { `content`: `string` ; `stop`: `false` }>>> ; `stream`: `true` = true }	Returns an async iterable over the full deltas (all choices, including full current state at time of event) of the response stream.
`deltaIterable.handler`	(`__namedParameters`: { `response`: `Response` }) => `Promise`<`AsyncIterable`<`Delta`<{ `content`: `string` ; `generation_settings`: { `frequency_penalty`: `number` ; `ignore_eos`: `boolean` ; `logit_bias`: `number`[] ; `mirostat`: `number` ; `mirostat_eta`: `number` ; `mirostat_tau`: `number` ; `model`: `string` ; `n_ctx`: `number` ; `n_keep`: `number` ; `n_predict`: `number` ; `n_probs`: `number` ; `penalize_nl`: `boolean` ; `presence_penalty`: `number` ; `repeat_last_n`: `number` ; `repeat_penalty`: `number` ; `seed`: `number` ; `stop`: `string`[] ; `stream`: `boolean` ; `temperature?`: `number` ; `tfs_z`: `number` ; `top_k`: `number` ; `top_p`: `number` ; `typical_p`: `number` } ; `model`: `string` ; `prompt`: `string` ; `stop`: `true` ; `stopped_eos`: `boolean` ; `stopped_limit`: `boolean` ; `stopped_word`: `boolean` ; `stopping_word`: `string` ; `timings`: { `predicted_ms`: `number` ; `predicted_n`: `number` ; `predicted_per_second`: `null` \| `number` ; `predicted_per_token_ms`: `null` \| `number` ; `prompt_ms?`: `null` \| `number` ; `prompt_n`: `number` ; `prompt_per_second`: `null` \| `number` ; `prompt_per_token_ms`: `null` \| `number` } ; `tokens_cached`: `number` ; `tokens_evaluated`: `number` ; `tokens_predicted`: `number` ; `truncated`: `boolean` } \| { `content`: `string` ; `stop`: `false` }>>>	-
`deltaIterable.stream`	`true`	-
`json`	{ `handler`: `ResponseHandler`<{ `content`: `string` ; `generation_settings`: { `frequency_penalty`: `number` ; `ignore_eos`: `boolean` ; `logit_bias`: `number`[] ; `mirostat`: `number` ; `mirostat_eta`: `number` ; `mirostat_tau`: `number` ; `model`: `string` ; `n_ctx`: `number` ; `n_keep`: `number` ; `n_predict`: `number` ; `n_probs`: `number` ; `penalize_nl`: `boolean` ; `presence_penalty`: `number` ; `repeat_last_n`: `number` ; `repeat_penalty`: `number` ; `seed`: `number` ; `stop`: `string`[] ; `stream`: `boolean` ; `temperature?`: `number` ; `tfs_z`: `number` ; `top_k`: `number` ; `top_p`: `number` ; `typical_p`: `number` } ; `model`: `string` ; `prompt`: `string` ; `stop`: `true` ; `stopped_eos`: `boolean` ; `stopped_limit`: `boolean` ; `stopped_word`: `boolean` ; `stopping_word`: `string` ; `timings`: { `predicted_ms`: `number` ; `predicted_n`: `number` ; `predicted_per_second`: `null` \| `number` ; `predicted_per_token_ms`: `null` \| `number` ; `prompt_ms?`: `null` \| `number` ; `prompt_n`: `number` ; `prompt_per_second`: `null` \| `number` ; `prompt_per_token_ms`: `null` \| `number` } ; `tokens_cached`: `number` ; `tokens_evaluated`: `number` ; `tokens_predicted`: `number` ; `truncated`: `boolean` }> ; `stream`: `false` = false }	Returns the response as a JSON object.
`json.handler`	`ResponseHandler`<{ `content`: `string` ; `generation_settings`: { `frequency_penalty`: `number` ; `ignore_eos`: `boolean` ; `logit_bias`: `number`[] ; `mirostat`: `number` ; `mirostat_eta`: `number` ; `mirostat_tau`: `number` ; `model`: `string` ; `n_ctx`: `number` ; `n_keep`: `number` ; `n_predict`: `number` ; `n_probs`: `number` ; `penalize_nl`: `boolean` ; `presence_penalty`: `number` ; `repeat_last_n`: `number` ; `repeat_penalty`: `number` ; `seed`: `number` ; `stop`: `string`[] ; `stream`: `boolean` ; `temperature?`: `number` ; `tfs_z`: `number` ; `top_k`: `number` ; `top_p`: `number` ; `typical_p`: `number` } ; `model`: `string` ; `prompt`: `string` ; `stop`: `true` ; `stopped_eos`: `boolean` ; `stopped_limit`: `boolean` ; `stopped_word`: `boolean` ; `stopping_word`: `string` ; `timings`: { `predicted_ms`: `number` ; `predicted_n`: `number` ; `predicted_per_second`: `null` \| `number` ; `predicted_per_token_ms`: `null` \| `number` ; `prompt_ms?`: `null` \| `number` ; `prompt_n`: `number` ; `prompt_per_second`: `null` \| `number` ; `prompt_per_token_ms`: `null` \| `number` } ; `tokens_cached`: `number` ; `tokens_evaluated`: `number` ; `tokens_predicted`: `number` ; `truncated`: `boolean` }>	-
`json.stream`	`false`	-

Defined in

packages/modelfusion/src/model-provider/llamacpp/LlamaCppCompletionModel.ts:593

MistralChatResponseFormat

• Const MistralChatResponseFormat: Object

Type declaration

Name	Type	Description
`json`	{ `handler`: `ResponseHandler`<{ `choices`: { `finish_reason`: `"length"` \| `"stop"` \| `"model_length"` ; `index`: `number` ; `message`: { `content`: `string` ; `role`: `"user"` \| `"assistant"` } }[] ; `created`: `number` ; `id`: `string` ; `model`: `string` ; `object`: `string` ; `usage`: { `completion_tokens`: `number` ; `prompt_tokens`: `number` ; `total_tokens`: `number` } }> ; `stream`: `boolean` = false }	Returns the response as a JSON object.
`json.handler`	`ResponseHandler`<{ `choices`: { `finish_reason`: `"length"` \| `"stop"` \| `"model_length"` ; `index`: `number` ; `message`: { `content`: `string` ; `role`: `"user"` \| `"assistant"` } }[] ; `created`: `number` ; `id`: `string` ; `model`: `string` ; `object`: `string` ; `usage`: { `completion_tokens`: `number` ; `prompt_tokens`: `number` ; `total_tokens`: `number` } }>	-
`json.stream`	`boolean`	-
`textDeltaIterable`	{ `handler`: (`__namedParameters`: { `response`: `Response` }) => `Promise`<`AsyncIterable`<`Delta`<{ `choices`: { `delta`: { `content?`: `null` \| `string` ; `role?`: `null` \| `"user"` \| `"assistant"` } ; `finish_reason?`: `null` \| `"length"` \| `"stop"` \| `"model_length"` ; `index`: `number` }[] ; `created?`: `number` ; `id`: `string` ; `model`: `string` ; `object?`: `string` }>>> ; `stream`: `boolean` = true }	Returns an async iterable over the text deltas (only the tex different of the first choice).
`textDeltaIterable.handler`	(`__namedParameters`: { `response`: `Response` }) => `Promise`<`AsyncIterable`<`Delta`<{ `choices`: { `delta`: { `content?`: `null` \| `string` ; `role?`: `null` \| `"user"` \| `"assistant"` } ; `finish_reason?`: `null` \| `"length"` \| `"stop"` \| `"model_length"` ; `index`: `number` }[] ; `created?`: `number` ; `id`: `string` ; `model`: `string` ; `object?`: `string` }>>>	-
`textDeltaIterable.stream`	`boolean`	-

Defined in

packages/modelfusion/src/model-provider/mistral/MistralChatModel.ts:298

OPENAI_CHAT_MESSAGE_BASE_TOKEN_COUNT

• Const OPENAI_CHAT_MESSAGE_BASE_TOKEN_COUNT: 5

Prompt tokens that are included automatically for every message that is sent to OpenAI.

Defined in

packages/modelfusion/src/model-provider/openai/countOpenAIChatMessageTokens.ts:19

OPENAI_CHAT_PROMPT_BASE_TOKEN_COUNT

• Const OPENAI_CHAT_PROMPT_BASE_TOKEN_COUNT: 2

Prompt tokens that are included automatically for every full chat prompt (several messages) that is sent to OpenAI.

Defined in

packages/modelfusion/src/model-provider/openai/countOpenAIChatMessageTokens.ts:13

OPENAI_TEXT_EMBEDDING_MODELS

• Const OPENAI_TEXT_EMBEDDING_MODELS: Object

Type declaration

Name	Type
`text-embedding-3-large`	{ `contextWindowSize`: `number` = 8192; `dimensions`: `number` = 3072 }
`text-embedding-3-large.contextWindowSize`	`number`
`text-embedding-3-large.dimensions`	`number`
`text-embedding-3-small`	{ `contextWindowSize`: `number` = 8192; `dimensions`: `number` = 1536 }
`text-embedding-3-small.contextWindowSize`	`number`
`text-embedding-3-small.dimensions`	`number`
`text-embedding-ada-002`	{ `contextWindowSize`: `number` = 8192; `dimensions`: `number` = 1536 }
`text-embedding-ada-002.contextWindowSize`	`number`
`text-embedding-ada-002.dimensions`	`number`

Defined in

packages/modelfusion/src/model-provider/openai/OpenAITextEmbeddingModel.ts:10

OPENAI_TEXT_GENERATION_MODELS

• Const OPENAI_TEXT_GENERATION_MODELS: Object

See

Type declaration

Name	Type
`gpt-3.5-turbo-instruct`	{ `contextWindowSize`: `number` = 4097 }
`gpt-3.5-turbo-instruct.contextWindowSize`	`number`

Defined in

packages/modelfusion/src/model-provider/openai/OpenAICompletionModel.ts:23

OllamaChatResponseFormat

• Const OllamaChatResponseFormat: Object

Type declaration

Name	Type	Description
`deltaIterable`	{ `handler`: (`__namedParameters`: { `response`: `Response` }) => `Promise`<`AsyncIterable`<`Delta`<{ `created_at`: `string` ; `done`: `false` ; `message`: { `content`: `string` ; `role`: `string` } ; `model`: `string` } \| { `created_at`: `string` ; `done`: `true` ; `eval_count`: `number` ; `eval_duration`: `number` ; `load_duration?`: `number` ; `model`: `string` ; `prompt_eval_count?`: `number` ; `prompt_eval_duration?`: `number` ; `total_duration`: `number` }>>> ; `stream`: `boolean` = true }	Returns an async iterable over the full deltas (all choices, including full current state at time of event) of the response stream.
`deltaIterable.handler`	(`__namedParameters`: { `response`: `Response` }) => `Promise`<`AsyncIterable`<`Delta`<{ `created_at`: `string` ; `done`: `false` ; `message`: { `content`: `string` ; `role`: `string` } ; `model`: `string` } \| { `created_at`: `string` ; `done`: `true` ; `eval_count`: `number` ; `eval_duration`: `number` ; `load_duration?`: `number` ; `model`: `string` ; `prompt_eval_count?`: `number` ; `prompt_eval_duration?`: `number` ; `total_duration`: `number` }>>>	-
`deltaIterable.stream`	`boolean`	-
`json`	{ `handler`: (`__namedParameters`: { `requestBodyValues`: `unknown` ; `response`: `Response` ; `url`: `string` }) => `Promise`<{ `created_at`: `string` ; `done`: `true` ; `eval_count`: `number` ; `eval_duration`: `number` ; `load_duration?`: `number` ; `message`: { `content`: `string` ; `role`: `string` } ; `model`: `string` ; `prompt_eval_count?`: `number` ; `prompt_eval_duration?`: `number` ; `total_duration`: `number` }> ; `stream`: `false` = false }	Returns the response as a JSON object.
`json.handler`	(`__namedParameters`: { `requestBodyValues`: `unknown` ; `response`: `Response` ; `url`: `string` }) => `Promise`<{ `created_at`: `string` ; `done`: `true` ; `eval_count`: `number` ; `eval_duration`: `number` ; `load_duration?`: `number` ; `message`: { `content`: `string` ; `role`: `string` } ; `model`: `string` ; `prompt_eval_count?`: `number` ; `prompt_eval_duration?`: `number` ; `total_duration`: `number` }>	-
`json.stream`	`false`	-

Defined in

packages/modelfusion/src/model-provider/ollama/OllamaChatModel.ts:318

OllamaCompletionResponseFormat

• Const OllamaCompletionResponseFormat: Object

Type declaration

Name	Type	Description
`deltaIterable`	{ `handler`: (`__namedParameters`: { `response`: `Response` }) => `Promise`<`AsyncIterable`<`Delta`<{ `created_at`: `string` ; `done`: `false` ; `model`: `string` ; `response`: `string` } \| { `context?`: `number`[] ; `created_at`: `string` ; `done`: `true` ; `eval_count`: `number` ; `eval_duration`: `number` ; `load_duration?`: `number` ; `model`: `string` ; `prompt_eval_count?`: `number` ; `prompt_eval_duration?`: `number` ; `sample_count?`: `number` ; `sample_duration?`: `number` ; `total_duration`: `number` }>>> ; `stream`: `boolean` = true }	Returns an async iterable over the full deltas (all choices, including full current state at time of event) of the response stream.
`deltaIterable.handler`	(`__namedParameters`: { `response`: `Response` }) => `Promise`<`AsyncIterable`<`Delta`<{ `created_at`: `string` ; `done`: `false` ; `model`: `string` ; `response`: `string` } \| { `context?`: `number`[] ; `created_at`: `string` ; `done`: `true` ; `eval_count`: `number` ; `eval_duration`: `number` ; `load_duration?`: `number` ; `model`: `string` ; `prompt_eval_count?`: `number` ; `prompt_eval_duration?`: `number` ; `sample_count?`: `number` ; `sample_duration?`: `number` ; `total_duration`: `number` }>>>	-
`deltaIterable.stream`	`boolean`	-
`json`	{ `handler`: (`__namedParameters`: { `requestBodyValues`: `unknown` ; `response`: `Response` ; `url`: `string` }) => `Promise`<{ `context?`: `number`[] ; `created_at`: `string` ; `done`: `true` ; `eval_count`: `number` ; `eval_duration`: `number` ; `load_duration?`: `number` ; `model`: `string` ; `prompt_eval_count?`: `number` ; `prompt_eval_duration?`: `number` ; `response`: `string` ; `total_duration`: `number` }> ; `stream`: `false` = false }	Returns the response as a JSON object.
`json.handler`	(`__namedParameters`: { `requestBodyValues`: `unknown` ; `response`: `Response` ; `url`: `string` }) => `Promise`<{ `context?`: `number`[] ; `created_at`: `string` ; `done`: `true` ; `eval_count`: `number` ; `eval_duration`: `number` ; `load_duration?`: `number` ; `model`: `string` ; `prompt_eval_count?`: `number` ; `prompt_eval_duration?`: `number` ; `response`: `string` ; `total_duration`: `number` }>	-
`json.stream`	`false`	-

Defined in

packages/modelfusion/src/model-provider/ollama/OllamaCompletionModel.ts:397

OpenAIChatResponseFormat

• Const OpenAIChatResponseFormat: Object

Type declaration

Name	Type	Description
`deltaIterable`	{ `handler`: (`__namedParameters`: { `response`: `Response` }) => `Promise`<`AsyncIterable`<`Delta`<{ `choices`: { `delta`: { `content?`: `null` \| `string` ; `function_call?`: { `arguments?`: `string` ; `name?`: `string` } ; `role?`: `"user"` \| `"assistant"` ; `tool_calls?`: { `function`: { `arguments`: `string` ; `name`: `string` } ; `id`: `string` ; `type`: `"function"` }[] } ; `finish_reason?`: `null` \| `"length"` \| `"stop"` \| `"function_call"` \| `"tool_calls"` \| `"content_filter"` ; `index`: `number` }[] ; `created`: `number` ; `id`: `string` ; `model?`: `string` ; `object`: `string` ; `system_fingerprint?`: `null` \| `string` }>>> ; `stream`: `boolean` = true }	Returns an async iterable over the text deltas (only the tex different of the first choice).
`deltaIterable.handler`	(`__namedParameters`: { `response`: `Response` }) => `Promise`<`AsyncIterable`<`Delta`<{ `choices`: { `delta`: { `content?`: `null` \| `string` ; `function_call?`: { `arguments?`: `string` ; `name?`: `string` } ; `role?`: `"user"` \| `"assistant"` ; `tool_calls?`: { `function`: { `arguments`: `string` ; `name`: `string` } ; `id`: `string` ; `type`: `"function"` }[] } ; `finish_reason?`: `null` \| `"length"` \| `"stop"` \| `"function_call"` \| `"tool_calls"` \| `"content_filter"` ; `index`: `number` }[] ; `created`: `number` ; `id`: `string` ; `model?`: `string` ; `object`: `string` ; `system_fingerprint?`: `null` \| `string` }>>>	-
`deltaIterable.stream`	`boolean`	-
`json`	{ `handler`: `ResponseHandler`<{ `choices`: { `finish_reason?`: `null` \| `"length"` \| `"stop"` \| `"function_call"` \| `"tool_calls"` \| `"content_filter"` ; `index?`: `number` ; `logprobs?`: `any` ; `message`: { `content`: `null` \| `string` ; `function_call?`: { `arguments`: `string` ; `name`: `string` } ; `role`: `"assistant"` ; `tool_calls?`: { `function`: { `arguments`: `string` ; `name`: `string` } ; `id`: `string` ; `type`: `"function"` }[] } }[] ; `created`: `number` ; `id`: `string` ; `model`: `string` ; `object`: `"chat.completion"` ; `system_fingerprint?`: `null` \| `string` ; `usage`: { `completion_tokens`: `number` ; `prompt_tokens`: `number` ; `total_tokens`: `number` } }> ; `stream`: `boolean` = false }	Returns the response as a JSON object.
`json.handler`	`ResponseHandler`<{ `choices`: { `finish_reason?`: `null` \| `"length"` \| `"stop"` \| `"function_call"` \| `"tool_calls"` \| `"content_filter"` ; `index?`: `number` ; `logprobs?`: `any` ; `message`: { `content`: `null` \| `string` ; `function_call?`: { `arguments`: `string` ; `name`: `string` } ; `role`: `"assistant"` ; `tool_calls?`: { `function`: { `arguments`: `string` ; `name`: `string` } ; `id`: `string` ; `type`: `"function"` }[] } }[] ; `created`: `number` ; `id`: `string` ; `model`: `string` ; `object`: `"chat.completion"` ; `system_fingerprint?`: `null` \| `string` ; `usage`: { `completion_tokens`: `number` ; `prompt_tokens`: `number` ; `total_tokens`: `number` } }>	-
`json.stream`	`boolean`	-

Defined in

packages/modelfusion/src/model-provider/openai/AbstractOpenAIChatModel.ts:449

OpenAIImageGenerationResponseFormat

• Const OpenAIImageGenerationResponseFormat: Object

Type declaration

Name	Type
`base64Json`	{ `handler`: `ResponseHandler`<{ `created`: `number` ; `data`: { `b64_json`: `string` }[] }> ; `type`: `"b64_json"` }
`base64Json.handler`	`ResponseHandler`<{ `created`: `number` ; `data`: { `b64_json`: `string` }[] }>
`base64Json.type`	`"b64_json"`
`url`	{ `handler`: `ResponseHandler`<{ `created`: `number` ; `data`: { `url`: `string` }[] }> ; `type`: `"url"` }
`url.handler`	`ResponseHandler`<{ `created`: `number` ; `data`: { `url`: `string` }[] }>
`url.type`	`"url"`

Defined in

packages/modelfusion/src/model-provider/openai/OpenAIImageGenerationModel.ts:174

OpenAITextResponseFormat

• Const OpenAITextResponseFormat: Object

Type declaration

Name	Type	Description
`deltaIterable`	{ `handler`: (`__namedParameters`: { `response`: `Response` }) => `Promise`<`AsyncIterable`<`Delta`<{ `choices`: { `finish_reason?`: `null` \| `"length"` \| `"stop"` \| `"content_filter"` ; `index`: `number` ; `text`: `string` }[] ; `created`: `number` ; `id`: `string` ; `model`: `string` ; `object`: `"text_completion"` ; `system_fingerprint?`: `string` }>>> ; `stream`: `boolean` = true }	Returns an async iterable over the full deltas (all choices, including full current state at time of event) of the response stream.
`deltaIterable.handler`	(`__namedParameters`: { `response`: `Response` }) => `Promise`<`AsyncIterable`<`Delta`<{ `choices`: { `finish_reason?`: `null` \| `"length"` \| `"stop"` \| `"content_filter"` ; `index`: `number` ; `text`: `string` }[] ; `created`: `number` ; `id`: `string` ; `model`: `string` ; `object`: `"text_completion"` ; `system_fingerprint?`: `string` }>>>	-
`deltaIterable.stream`	`boolean`	-
`json`	{ `handler`: `ResponseHandler`<{ `choices`: { `finish_reason?`: `null` \| `"length"` \| `"stop"` \| `"content_filter"` ; `index`: `number` ; `logprobs?`: `any` ; `text`: `string` }[] ; `created`: `number` ; `id`: `string` ; `model`: `string` ; `object`: `"text_completion"` ; `system_fingerprint?`: `string` ; `usage`: { `completion_tokens`: `number` ; `prompt_tokens`: `number` ; `total_tokens`: `number` } }> ; `stream`: `boolean` = false }	Returns the response as a JSON object.
`json.handler`	`ResponseHandler`<{ `choices`: { `finish_reason?`: `null` \| `"length"` \| `"stop"` \| `"content_filter"` ; `index`: `number` ; `logprobs?`: `any` ; `text`: `string` }[] ; `created`: `number` ; `id`: `string` ; `model`: `string` ; `object`: `"text_completion"` ; `system_fingerprint?`: `string` ; `usage`: { `completion_tokens`: `number` ; `prompt_tokens`: `number` ; `total_tokens`: `number` } }>	-
`json.stream`	`boolean`	-

Defined in

packages/modelfusion/src/model-provider/openai/AbstractOpenAICompletionModel.ts:238

OpenAITranscriptionResponseFormat

• Const OpenAITranscriptionResponseFormat: Object

Type declaration

Name	Type
`json`	{ `handler`: `ResponseHandler`<{ `text`: `string` }> ; `type`: `"json"` }
`json.handler`	`ResponseHandler`<{ `text`: `string` }>
`json.type`	`"json"`
`srt`	{ `handler`: `ResponseHandler`<`string`> ; `type`: `"srt"` }
`srt.handler`	`ResponseHandler`<`string`>
`srt.type`	`"srt"`
`text`	{ `handler`: `ResponseHandler`<`string`> ; `type`: `"text"` }
`text.handler`	`ResponseHandler`<`string`>
`text.type`	`"text"`
`verboseJson`	{ `handler`: `ResponseHandler`<{ `duration`: `number` ; `language`: `string` ; `segments`: { `avg_logprob`: `number` ; `compression_ratio`: `number` ; `end`: `number` ; `id`: `number` ; `no_speech_prob`: `number` ; `seek`: `number` ; `start`: `number` ; `temperature`: `number` ; `text`: `string` ; `tokens`: `number`[] ; `transient?`: `boolean` }[] ; `task`: `"transcribe"` ; `text`: `string` }> ; `type`: `"verbose_json"` }
`verboseJson.handler`	`ResponseHandler`<{ `duration`: `number` ; `language`: `string` ; `segments`: { `avg_logprob`: `number` ; `compression_ratio`: `number` ; `end`: `number` ; `id`: `number` ; `no_speech_prob`: `number` ; `seek`: `number` ; `start`: `number` ; `temperature`: `number` ; `text`: `string` ; `tokens`: `number`[] ; `transient?`: `boolean` }[] ; `task`: `"transcribe"` ; `text`: `string` }>
`verboseJson.type`	`"verbose_json"`
`vtt`	{ `handler`: `ResponseHandler`<`string`> ; `type`: `"vtt"` }
`vtt.handler`	`ResponseHandler`<`string`>
`vtt.type`	`"vtt"`

Defined in

packages/modelfusion/src/model-provider/openai/OpenAITranscriptionModel.ts:228

jsonObjectPrompt

• Const jsonObjectPrompt: Object

Type declaration

Name	Type
`custom`	<SOURCE_PROMPT, TARGET_PROMPT>(`createPrompt`: (`prompt`: `SOURCE_PROMPT`, `schema`: `Schema`<`unknown`> & `JsonSchemaProducer`) => `TARGET_PROMPT`) => `ObjectFromTextPromptTemplate`<`SOURCE_PROMPT`, `TARGET_PROMPT`>
`instruction`	(`__namedParameters`: { `schemaPrefix?`: `string` ; `schemaSuffix?`: `string` }) => `FlexibleObjectFromTextPromptTemplate`<`InstructionPrompt`, `InstructionPrompt`>
`text`	(`__namedParameters`: { `schemaPrefix?`: `string` ; `schemaSuffix?`: `string` }) => `FlexibleObjectFromTextPromptTemplate`<`string`, `InstructionPrompt`>

Defined in

packages/modelfusion/src/model-function/generate-object/jsonObjectPrompt.ts:14

jsonToolCallPrompt

• Const jsonToolCallPrompt: Object

Type declaration

Name	Type
`instruction`	(`__namedParameters`: { `toolPrompt?`: (`tool`: `ToolDefinition`<`string`, `unknown`>) => `string` }) => `ToolCallPromptTemplate`<`InstructionPrompt`, `InstructionPrompt`>
`text`	(`__namedParameters`: { `toolPrompt?`: (`tool`: `ToolDefinition`<`string`, `unknown`>) => `string` }) => `ToolCallPromptTemplate`<`string`, `InstructionPrompt`>

Defined in

packages/modelfusion/src/tool/generate-tool-call/jsonToolCallPrompt.ts:22

openAITextEmbeddingResponseSchema

• Const openAITextEmbeddingResponseSchema: ZodObject<{ data: ZodArray<ZodObject<{ embedding: ZodArray<ZodNumber, "many"> ; index: ZodNumber ; object: ZodLiteral<"embedding"> }, "strip", ZodTypeAny, { embedding: number[] ; index: number ; object: "embedding" }, { embedding: number[] ; index: number ; object: "embedding" }>, "many"> ; model: ZodString ; object: ZodLiteral<"list"> ; usage: ZodOptional<ZodObject<{ prompt_tokens: ZodNumber ; total_tokens: ZodNumber }, "strip", ZodTypeAny, { prompt_tokens: number ; total_tokens: number }, { prompt_tokens: number ; total_tokens: number }>> }, "strip", ZodTypeAny, { data: { embedding: number[] ; index: number ; object: "embedding" }[] ; model: string ; object: "list" ; usage?: { prompt_tokens: number ; total_tokens: number } }, { data: { embedding: number[] ; index: number ; object: "embedding" }[] ; model: string ; object: "list" ; usage?: { prompt_tokens: number ; total_tokens: number } }>

Defined in

packages/modelfusion/src/model-provider/openai/OpenAITextEmbeddingModel.ts:34

textGenerationModelProperties

• Const textGenerationModelProperties: readonly ["maxGenerationTokens", "stopSequences", "numberOfGenerations", "trimWhitespace"]

Defined in

packages/modelfusion/src/model-function/generate-text/TextGenerationModel.ts:12

References

MistralChatMessage

Renames and re-exports ChatMessage

MistralChatPrompt

Renames and re-exports ChatPrompt

OllamaChatMessage

Renames and re-exports ChatMessage

OllamaChatPrompt

Renames and re-exports ChatPrompt

OpenAIChatMessage

Renames and re-exports ChatMessage

OpenAIChatPrompt

Renames and re-exports ChatPrompt

retryNever

Re-exports retryNever

Type Aliases

AssistantContent

Ƭ AssistantContent: string | (TextPart | ToolCallPart)[]

Defined in

packages/modelfusion/src/model-function/generate-text/prompt-template/ChatPrompt.ts:41

AudioMimeType

Defined in

packages/modelfusion/src/util/audio/AudioMimeType.ts:1

Automatic1111ErrorData

Ƭ Automatic1111ErrorData: Object

Type declaration

Name	Type
`body`	`string`
`detail`	`string`
`error`	`string`
`errors`	`string`

Defined in

packages/modelfusion/src/model-provider/automatic1111/Automatic1111Error.ts:16

Automatic1111ImageGenerationPrompt

Ƭ Automatic1111ImageGenerationPrompt: Object

Type declaration

Name	Type
`negativePrompt?`	`string`
`prompt`	`string`

Defined in

packages/modelfusion/src/model-provider/automatic1111/Automatic1111ImageGenerationPrompt.ts:3

Automatic1111ImageGenerationResponse

Ƭ Automatic1111ImageGenerationResponse: Object

Type declaration

Name	Type
`images`	`string`[]
`info`	`string`
`parameters`

Defined in

packages/modelfusion/src/model-provider/automatic1111/Automatic1111ImageGenerationModel.ts:184

AzureOpenAIApiConfigurationOptions

Ƭ AzureOpenAIApiConfigurationOptions: Object

Type declaration

Name	Type
`apiKey?`	`string`
`apiVersion`	`string`
`deploymentId`	`string`
`resourceName`	`string`
`retry?`	`RetryFunction`
`throttle?`	`ThrottleFunction`

Defined in

packages/modelfusion/src/model-provider/openai/AzureOpenAIApiConfiguration.ts:6

BaseFunctionFinishedEventResult

Ƭ BaseFunctionFinishedEventResult: { status: "success" ; value: unknown } | { error: unknown ; status: "error" } | { status: "abort" }

Defined in

packages/modelfusion/src/core/FunctionEvent.ts:93

BaseModelCallFinishedEventResult

Ƭ BaseModelCallFinishedEventResult: { rawResponse: unknown ; status: "success" ; usage?: unknown ; value: unknown } | { error: unknown ; status: "error" } | { status: "abort" }

Defined in

packages/modelfusion/src/model-function/ModelCallEvent.ts:65

BaseUrlPartsApiConfigurationOptions

Ƭ BaseUrlPartsApiConfigurationOptions: Object

Type declaration

Name	Type
`baseUrl`	`string` \| `UrlParts`
`customCallHeaders?`	`CustomHeaderProvider`
`headers?`	`Record`<`string`, `string`>
`retry?`	`RetryFunction`
`throttle?`	`ThrottleFunction`

Defined in

packages/modelfusion/src/core/api/BaseUrlApiConfiguration.ts:13

ChatMessage

Ƭ ChatMessage: { content: UserContent ; role: "user" } | { content: AssistantContent ; role: "assistant" } | { content: ToolContent ; role: "tool" }

A message in a chat prompt.

See

ChatPrompt

Defined in

packages/modelfusion/src/model-function/generate-text/prompt-template/ChatPrompt.ts:49

packages/modelfusion/src/model-function/generate-text/prompt-template/ChatPrompt.ts:54

ClassifyFinishedEventResult

Ƭ ClassifyFinishedEventResult: { rawResponse: unknown ; status: "success" ; value: unknown } | { error: unknown ; status: "error" } | { status: "abort" }

Defined in

packages/modelfusion/src/model-function/classify/ClassifyEvent.ts:11

CohereDetokenizationResponse

Ƭ CohereDetokenizationResponse: Object

Type declaration

Name	Type
`meta`	{ `api_version`: { `version`: `string` } }
`meta.api_version`	{ `version`: `string` }
`meta.api_version.version`	`string`
`text`	`string`

Defined in

packages/modelfusion/src/model-provider/cohere/CohereTokenizer.ts:141

CohereErrorData

Ƭ CohereErrorData: Object

Type declaration

Name	Type
`message`	`string`

Defined in

packages/modelfusion/src/model-provider/cohere/CohereError.ts:9

CohereTextEmbeddingModelType

Ƭ CohereTextEmbeddingModelType: keyof typeof COHERE_TEXT_EMBEDDING_MODELS

Defined in

packages/modelfusion/src/model-provider/cohere/CohereTextEmbeddingModel.ts:51

CohereTextEmbeddingResponse

Ƭ CohereTextEmbeddingResponse: Object

Type declaration

Name	Type
`embeddings`	`number`[][]
`id`	`string`
`meta`	{ `api_version`: { `version`: `string` } }
`meta.api_version`	{ `version`: `string` }
`meta.api_version.version`	`string`
`texts`	`string`[]

Defined in

packages/modelfusion/src/model-provider/cohere/CohereTextEmbeddingModel.ts:196

CohereTextGenerationModelType

Ƭ CohereTextGenerationModelType: keyof typeof COHERE_TEXT_GENERATION_MODELS

Defined in

packages/modelfusion/src/model-provider/cohere/CohereTextGenerationModel.ts:41

CohereTextGenerationResponse

Ƭ CohereTextGenerationResponse: Object

Type declaration

Name	Type
`generations`	{ `finish_reason?`: `string` ; `id`: `string` ; `text`: `string` }[]
`id`	`string`
`meta?`	{ `api_version`: { `version`: `string` } }
`meta.api_version`	{ `version`: `string` }
`meta.api_version.version`	`string`
`prompt`	`string`

Defined in

packages/modelfusion/src/model-provider/cohere/CohereTextGenerationModel.ts:292

CohereTextGenerationResponseFormatType

Ƭ CohereTextGenerationResponseFormatType<T>: Object

Type parameters

Name
`T`

Type declaration

Name	Type
`handler`	`ResponseHandler`<`T`>
`stream`	`boolean`

Defined in

packages/modelfusion/src/model-provider/cohere/CohereTextGenerationModel.ts:310

CohereTextStreamChunk

Ƭ CohereTextStreamChunk: { is_finished: false ; text: string } | { finish_reason: string ; is_finished: true ; response: { generations: { finish_reason?: string ; id: string ; text: string }[] ; id: string ; meta?: { api_version: { version: string } } ; prompt: string } = cohereTextGenerationResponseSchema }

Defined in

packages/modelfusion/src/model-provider/cohere/CohereTextGenerationModel.ts:308

CohereTokenizationResponse

Ƭ CohereTokenizationResponse: Object

Type declaration

Name	Type
`meta`	{ `api_version`: { `version`: `string` } }
`meta.api_version`	{ `version`: `string` }
`meta.api_version.version`	`string`
`token_strings`	`string`[]
`tokens`	`number`[]

Defined in

packages/modelfusion/src/model-provider/cohere/CohereTokenizer.ts:155

CohereTokenizerModelType

Ƭ CohereTokenizerModelType: CohereTextGenerationModelType | CohereTextEmbeddingModelType

Defined in

packages/modelfusion/src/model-provider/cohere/CohereTokenizer.ts:16

CustomHeaderProvider

Ƭ CustomHeaderProvider: (headerParameters: HeaderParameters) => Record<string, string | undefined>

Type declaration

▸ (headerParameters): Record<string, string | undefined>

Parameters

Name	Type
`headerParameters`	`HeaderParameters`

Returns

Record<string, string | undefined>

Defined in

packages/modelfusion/src/core/api/CustomHeaderProvider.ts:3

DataContent

Ƭ DataContent: string | Uint8Array | ArrayBuffer | Buffer

Data content. Can either be a base64-encoded string, a Uint8Array, an ArrayBuffer, or a Buffer.

Defined in

packages/modelfusion/src/util/format/DataContent.ts:6

Delta

Ƭ Delta<T>: { deltaValue: T ; type: "delta" } | { error: unknown ; type: "error" }

Type parameters

Name
`T`

Defined in

packages/modelfusion/src/model-function/Delta.ts:1

EmbeddingFinishedEventResult

Ƭ EmbeddingFinishedEventResult: { rawResponse: unknown ; status: "success" ; value: Vector | Vector[] } | { error: unknown ; status: "error" } | { status: "abort" }

Defined in

packages/modelfusion/src/model-function/embed/EmbeddingEvent.ts:12

ExecuteToolMetadata

Ƭ ExecuteToolMetadata: Object

Type declaration

Name	Type
`callId`	`string`
`durationInMs`	`number`
`finishTimestamp`	`Date`
`functionId?`	`string`
`runId?`	`string`
`sessionId?`	`string`
`startTimestamp`	`Date`
`userId?`	`string`

Defined in

packages/modelfusion/src/tool/execute-tool/executeTool.ts:16

FlexibleObjectFromTextPromptTemplate

Ƭ FlexibleObjectFromTextPromptTemplate<SOURCE_PROMPT, INTERMEDIATE_PROMPT>: Object

Type parameters

Name
`SOURCE_PROMPT`
`INTERMEDIATE_PROMPT`

Type declaration

Name	Type
`adaptModel`	(`model`: `TextStreamingModel`<`never`> & { `withChatPrompt`: () => `TextStreamingModel`<`ChatPrompt`, `TextGenerationModelSettings`> ; `withInstructionPrompt`: () => `TextStreamingModel`<`InstructionPrompt`, `TextGenerationModelSettings`> ; `withTextPrompt`: () => `TextStreamingModel`<`string`, `TextGenerationModelSettings`> }) => `TextStreamingModel`<`INTERMEDIATE_PROMPT`>
`createPrompt`	(`prompt`: `SOURCE_PROMPT`, `schema`: `Schema`<`unknown`> & `JsonSchemaProducer`) => `INTERMEDIATE_PROMPT`
`extractObject`	(`response`: `string`) => `unknown`
`withJsonOutput?`	(`__namedParameters`: { `model`: { `withJsonOutput`: (`schema`: `Schema`<`unknown`> & `JsonSchemaProducer`) => { `withJsonOutput`: (`schema`: `Schema`<`unknown`> & `JsonSchemaProducer`) => { withJsonOutput(schema: Schema<unknown> & JsonSchemaProducer): ...; } } } ; `schema`: `Schema`<`unknown`> & `JsonSchemaProducer` }) => { `withJsonOutput`: (`schema`: `Schema`<`unknown`> & `JsonSchemaProducer`) => { withJsonOutput(schema: Schema<unknown> & JsonSchemaProducer): ...; } }

Defined in

packages/modelfusion/src/model-function/generate-object/ObjectFromTextPromptTemplate.ts:28

FunctionCallOptions

Ƭ FunctionCallOptions: Omit<FunctionOptions, "callId"> & { callId: string ; functionType: string }

Extended options that are passed to models when functions are called. They are passed into e.g. API providers to create custom headers.

Defined in

packages/modelfusion/src/core/FunctionOptions.ts:53

FunctionEvent

Defined in

packages/modelfusion/src/core/FunctionEvent.ts:125

FunctionOptions

Ƭ FunctionOptions: Object

Additional settings for ModelFusion functions.

Type declaration

Name	Type	Description
`cache?`	`Cache`	Optional cache that can be used by the function to store and retrieve cached values. Not supported by all functions.
`callId?`	`string`	Unique identifier of the call id of the parent function. Used in events and logging. It has the same name as the `callId` in `FunctionCallOptions` to allow for easy propagation of the call id. However, in the `FunctionOptions`, it is the call ID for the parent call, and it is optional.
`functionId?`	`string`	Optional function identifier. Used in events and logging.
`logging?`	`LogFormat`	Optional logging to use for the function. Logs are sent to the console. Overrides the global function logging setting.
`observers?`	`FunctionObserver`[]	Optional observers that are called when the function is invoked.
`run?`	`Run`	Optional run as part of which this function is called. Used in events and logging. Run callbacks are invoked when it is provided.

Defined in

packages/modelfusion/src/core/FunctionOptions.ts:9

HeaderParameters

Ƭ HeaderParameters: Object

Type declaration

Name	Type
`callId`	`string`
`functionId?`	`string`
`functionType`	`string`
`run?`	`Run`

Defined in

packages/modelfusion/src/core/api/ApiConfiguration.ts:5

HuggingFaceErrorData

Ƭ HuggingFaceErrorData: Object

Type declaration

Name	Type
`error`	`string` \| `string`[] & `undefined` \| `string` \| `string`[]

Defined in

packages/modelfusion/src/model-provider/huggingface/HuggingFaceError.ts:9

HuggingFaceTextEmbeddingResponse

Ƭ HuggingFaceTextEmbeddingResponse: number[][]

Defined in

packages/modelfusion/src/model-provider/huggingface/HuggingFaceTextEmbeddingModel.ts:148

HuggingFaceTextGenerationResponse

Ƭ HuggingFaceTextGenerationResponse: { generated_text: string }[]

Defined in

packages/modelfusion/src/model-provider/huggingface/HuggingFaceTextGenerationModel.ts:194

ImageGenerationFinishedEventResult

Ƭ ImageGenerationFinishedEventResult: { rawResponse: unknown ; status: "success" ; value: string } | { error: unknown ; status: "error" } | { status: "abort" }

Defined in

packages/modelfusion/src/model-function/generate-image/ImageGenerationEvent.ts:10

InstructionContent

Ƭ InstructionContent: string | (TextPart | ImagePart)[]

Defined in

packages/modelfusion/src/model-function/generate-text/prompt-template/InstructionPrompt.ts:40

LlamaCppCompletionResponseFormatType

Ƭ LlamaCppCompletionResponseFormatType<T>: Object

Type parameters

Name
`T`

Type declaration

Name	Type
`handler`	`ResponseHandler`<`T`>
`stream`	`boolean`

Defined in

packages/modelfusion/src/model-provider/llamacpp/LlamaCppCompletionModel.ts:588

LlamaCppErrorData

Ƭ LlamaCppErrorData: Object

Type declaration

Name	Type
`error`	`string`

Defined in

packages/modelfusion/src/model-provider/llamacpp/LlamaCppError.ts:9

LlamaCppTextEmbeddingResponse

Ƭ LlamaCppTextEmbeddingResponse: Object

Type declaration

Name	Type
`embedding`	`number`[]

Defined in

packages/modelfusion/src/model-provider/llamacpp/LlamaCppTextEmbeddingModel.ts:120

LlamaCppTextGenerationResponse

Ƭ LlamaCppTextGenerationResponse: Object

Type declaration

Name	Type
`content`	`string`
`generation_settings`	{ `frequency_penalty`: `number` ; `ignore_eos`: `boolean` ; `logit_bias`: `number`[] ; `mirostat`: `number` ; `mirostat_eta`: `number` ; `mirostat_tau`: `number` ; `model`: `string` ; `n_ctx`: `number` ; `n_keep`: `number` ; `n_predict`: `number` ; `n_probs`: `number` ; `penalize_nl`: `boolean` ; `presence_penalty`: `number` ; `repeat_last_n`: `number` ; `repeat_penalty`: `number` ; `seed`: `number` ; `stop`: `string`[] ; `stream`: `boolean` ; `temperature?`: `number` ; `tfs_z`: `number` ; `top_k`: `number` ; `top_p`: `number` ; `typical_p`: `number` }
`generation_settings.frequency_penalty`	`number`
`generation_settings.ignore_eos`	`boolean`
`generation_settings.logit_bias`	`number`[]
`generation_settings.mirostat`	`number`
`generation_settings.mirostat_eta`	`number`
`generation_settings.mirostat_tau`	`number`
`generation_settings.model`	`string`
`generation_settings.n_ctx`	`number`
`generation_settings.n_keep`	`number`
`generation_settings.n_predict`	`number`
`generation_settings.n_probs`	`number`
`generation_settings.penalize_nl`	`boolean`
`generation_settings.presence_penalty`	`number`
`generation_settings.repeat_last_n`	`number`
`generation_settings.repeat_penalty`	`number`
`generation_settings.seed`	`number`
`generation_settings.stop`	`string`[]
`generation_settings.stream`	`boolean`
`generation_settings.temperature?`	`number`
`generation_settings.tfs_z`	`number`
`generation_settings.top_k`	`number`
`generation_settings.top_p`	`number`
`generation_settings.typical_p`	`number`
`model`	`string`
`prompt`	`string`
`stop`	`true`
`stopped_eos`	`boolean`
`stopped_limit`	`boolean`
`stopped_word`	`boolean`
`stopping_word`	`string`
`timings`	{ `predicted_ms`: `number` ; `predicted_n`: `number` ; `predicted_per_second`: `null` \| `number` ; `predicted_per_token_ms`: `null` \| `number` ; `prompt_ms?`: `null` \| `number` ; `prompt_n`: `number` ; `prompt_per_second`: `null` \| `number` ; `prompt_per_token_ms`: `null` \| `number` }
`timings.predicted_ms`	`number`
`timings.predicted_n`	`number`
`timings.predicted_per_second`	`null` \| `number`
`timings.predicted_per_token_ms`	`null` \| `number`
`timings.prompt_ms?`	`null` \| `number`
`timings.prompt_n`	`number`
`timings.prompt_per_second`	`null` \| `number`
`timings.prompt_per_token_ms`	`null` \| `number`
`tokens_cached`	`number`
`tokens_evaluated`	`number`
`tokens_predicted`	`number`
`truncated`	`boolean`

Defined in

packages/modelfusion/src/model-provider/llamacpp/LlamaCppCompletionModel.ts:536

LlamaCppTextStreamChunk

Ƭ LlamaCppTextStreamChunk: { content: string ; generation_settings: { frequency_penalty: number ; ignore_eos: boolean ; logit_bias: number[] ; mirostat: number ; mirostat_eta: number ; mirostat_tau: number ; model: string ; n_ctx: number ; n_keep: number ; n_predict: number ; n_probs: number ; penalize_nl: boolean ; presence_penalty: number ; repeat_last_n: number ; repeat_penalty: number ; seed: number ; stop: string[] ; stream: boolean ; temperature?: number ; tfs_z: number ; top_k: number ; top_p: number ; typical_p: number } ; model: string ; prompt: string ; stop: true ; stopped_eos: boolean ; stopped_limit: boolean ; stopped_word: boolean ; stopping_word: string ; timings: { predicted_ms: number ; predicted_n: number ; predicted_per_second: null | number ; predicted_per_token_ms: null | number ; prompt_ms?: null | number ; prompt_n: number ; prompt_per_second: null | number ; prompt_per_token_ms: null | number } ; tokens_cached: number ; tokens_evaluated: number ; tokens_predicted: number ; truncated: boolean } | { content: string ; stop: false }

Defined in

packages/modelfusion/src/model-provider/llamacpp/LlamaCppCompletionModel.ts:548

LlamaCppTokenizationResponse

Ƭ LlamaCppTokenizationResponse: Object

Type declaration

Name	Type
`tokens`	`number`[]

Defined in

packages/modelfusion/src/model-provider/llamacpp/LlamaCppTokenizer.ts:75

LmntSpeechResponse

Ƭ LmntSpeechResponse: Object

Type declaration

Name	Type
`audio`	`string`
`durations`	{ `duration`: `number` ; `start`: `number` ; `text`: `string` }[]
`seed`	`number`

Defined in

packages/modelfusion/src/model-provider/lmnt/LmntSpeechModel.ts:151

LogFormat

Ƭ LogFormat: undefined | "off" | "basic-text" | "detailed-object" | "detailed-json"

The logging output format to use, e.g. for functions. Logs are sent to the console.

off or undefined: No logging.
basic-text: Log the timestamp and the type of event as a single line of text.
detailed-object: Log everything except the original response as an object to the console.
detailed-json: Log everything except the original response as a JSON string to the console.

Defined in

packages/modelfusion/src/core/LogFormat.ts:10

MistralChatResponse

Ƭ MistralChatResponse: Object

Type declaration

Name	Type
`choices`	{ `finish_reason`: `"length"` \| `"stop"` \| `"model_length"` ; `index`: `number` ; `message`: { `content`: `string` ; `role`: `"user"` \| `"assistant"` } }[]
`created`	`number`
`id`	`string`
`model`	`string`
`object`	`string`
`usage`	{ `completion_tokens`: `number` ; `prompt_tokens`: `number` ; `total_tokens`: `number` }
`usage.completion_tokens`	`number`
`usage.prompt_tokens`	`number`
`usage.total_tokens`	`number`

Defined in

packages/modelfusion/src/model-provider/mistral/MistralChatModel.ts:267

MistralChatResponseFormatType

Ƭ MistralChatResponseFormatType<T>: Object

Type parameters

Name
`T`

Type declaration

Name	Type
`handler`	`ResponseHandler`<`T`>
`stream`	`boolean`

Defined in

packages/modelfusion/src/model-provider/mistral/MistralChatModel.ts:293

MistralChatStreamChunk

Ƭ MistralChatStreamChunk: Object

Type declaration

Name	Type
`choices`	{ `delta`: { `content?`: `null` \| `string` ; `role?`: `null` \| `"user"` \| `"assistant"` } ; `finish_reason?`: `null` \| `"length"` \| `"stop"` \| `"model_length"` ; `index`: `number` }[]
`created?`	`number`
`id`	`string`
`model`	`string`
`object?`	`string`

Defined in

packages/modelfusion/src/model-provider/mistral/MistralChatModel.ts:289

MistralErrorData

Ƭ MistralErrorData: Object

Type declaration

Name	Type
`code`	`string`
`message`	`string`
`object`	`"error"`
`param`	`null` \| `string`
`type`	`string`

Defined in

packages/modelfusion/src/model-provider/mistral/MistralError.ts:17

MistralTextEmbeddingResponse

Ƭ MistralTextEmbeddingResponse: Object

Type declaration

Name	Type
`data`	{ `embedding`: `number`[] ; `index`: `number` ; `object`: `string` }[]
`id`	`string`
`model`	`string`
`object`	`string`
`usage`	{ `prompt_tokens`: `number` ; `total_tokens`: `number` }
`usage.prompt_tokens`	`number`
`usage.total_tokens`	`number`

Defined in

packages/modelfusion/src/model-provider/mistral/MistralTextEmbeddingModel.ts:138

ModelCallFinishedEvent

Defined in

packages/modelfusion/src/model-function/ModelCallEvent.ts:117

ModelCallMetadata

Ƭ ModelCallMetadata: Object

Type declaration

Name	Type
`callId`	`string`
`durationInMs`	`number`
`finishTimestamp`	`Date`
`functionId?`	`string`
`model`	`ModelInformation`
`runId?`	`string`
`sessionId?`	`string`
`startTimestamp`	`Date`
`usage?`	`unknown`
`userId?`	`string`

Defined in

packages/modelfusion/src/model-function/ModelCallMetadata.ts:3

ModelCallStartedEvent

Defined in

packages/modelfusion/src/model-function/ModelCallEvent.ts:103

ModelInformation

Ƭ ModelInformation: Object

Type declaration

Name	Type
`modelName`	`string` \| `null`
`provider`	`string`

Defined in

packages/modelfusion/src/model-function/ModelInformation.ts:1

ObjectFromTextPromptTemplate

Ƭ ObjectFromTextPromptTemplate<SOURCE_PROMPT, TARGET_PROMPT>: Object

Type parameters

Name
`SOURCE_PROMPT`
`TARGET_PROMPT`

Type declaration

Name	Type
`createPrompt`	(`prompt`: `SOURCE_PROMPT`, `schema`: `Schema`<`unknown`> & `JsonSchemaProducer`) => `TARGET_PROMPT`
`extractObject`	(`response`: `string`) => `unknown`
`withJsonOutput?`	(`__namedParameters`: { `model`: { `withJsonOutput`: (`schema`: `Schema`<`unknown`> & `JsonSchemaProducer`) => { `withJsonOutput`: (`schema`: `Schema`<`unknown`> & `JsonSchemaProducer`) => { withJsonOutput(schema: Schema<unknown> & JsonSchemaProducer): ...; } } } ; `schema`: `Schema`<`unknown`> & `JsonSchemaProducer` }) => { `withJsonOutput`: (`schema`: `Schema`<`unknown`> & `JsonSchemaProducer`) => { withJsonOutput(schema: Schema<unknown> & JsonSchemaProducer): ...; } }

Defined in

packages/modelfusion/src/model-function/generate-object/ObjectFromTextPromptTemplate.ts:7

ObjectGenerationFinishedEvent

Ƭ ObjectGenerationFinishedEvent: BaseModelCallFinishedEvent & { functionType: "generate-object" ; result: ObjectGenerationFinishedEventResult }

Defined in

packages/modelfusion/src/model-function/generate-object/ObjectGenerationEvent.ts:26

ObjectGenerationFinishedEventResult

Ƭ ObjectGenerationFinishedEventResult: { rawResponse: unknown ; status: "success" ; usage?: { completionTokens: number ; promptTokens: number ; totalTokens: number } ; value: unknown } | { error: unknown ; status: "error" } | { status: "abort" }

Defined in

packages/modelfusion/src/model-function/generate-object/ObjectGenerationEvent.ts:11

ObjectStream

Ƭ ObjectStream<OBJECT>: AsyncIterable<{ partialObject: PartialDeep<OBJECT, { recurseIntoArrays: true }> ; partialText: string ; textDelta: string }>

Type parameters

Name
`OBJECT`

Defined in

packages/modelfusion/src/model-function/generate-object/ObjectStream.ts:5

OllamaChatResponse

Ƭ OllamaChatResponse: Object

Type declaration

Name	Type
`created_at`	`string`
`done`	`true`
`eval_count`	`number`
`eval_duration`	`number`
`load_duration?`	`number`
`message`	{ `content`: `string` ; `role`: `string` }
`message.content`	`string`
`message.role`	`string`
`model`	`string`
`prompt_eval_count?`	`number`
`prompt_eval_duration?`	`number`
`total_duration`	`number`

Defined in

packages/modelfusion/src/model-provider/ollama/OllamaChatModel.ts:286

OllamaChatResponseFormatType

Ƭ OllamaChatResponseFormatType<T>: Object

Type parameters

Name
`T`

Type declaration

Name	Type
`handler`	`ResponseHandler`<`T`>
`stream`	`boolean`

Defined in

packages/modelfusion/src/model-provider/ollama/OllamaChatModel.ts:313

OllamaChatStreamChunk

Ƭ OllamaChatStreamChunk: { created_at: string ; done: false ; message: { content: string ; role: string } ; model: string } | { created_at: string ; done: true ; eval_count: number ; eval_duration: number ; load_duration?: number ; model: string ; prompt_eval_count?: number ; prompt_eval_duration?: number ; total_duration: number }

Defined in

packages/modelfusion/src/model-provider/ollama/OllamaChatModel.ts:311

OllamaCompletionResponse

Ƭ OllamaCompletionResponse: Object

Type declaration

Name	Type
`context?`	`number`[]
`created_at`	`string`
`done`	`true`
`eval_count`	`number`
`eval_duration`	`number`
`load_duration?`	`number`
`model`	`string`
`prompt_eval_count?`	`number`
`prompt_eval_duration?`	`number`
`response`	`string`
`total_duration`	`number`

Defined in

packages/modelfusion/src/model-provider/ollama/OllamaCompletionModel.ts:361

OllamaCompletionResponseFormatType

Ƭ OllamaCompletionResponseFormatType<T>: Object

Type parameters

Name
`T`

Type declaration

Name	Type
`handler`	`ResponseHandler`<`T`>
`stream`	`boolean`

Defined in

packages/modelfusion/src/model-provider/ollama/OllamaCompletionModel.ts:392

OllamaCompletionStreamChunk

Ƭ OllamaCompletionStreamChunk: { created_at: string ; done: false ; model: string ; response: string } | { context?: number[] ; created_at: string ; done: true ; eval_count: number ; eval_duration: number ; load_duration?: number ; model: string ; prompt_eval_count?: number ; prompt_eval_duration?: number ; sample_count?: number ; sample_duration?: number ; total_duration: number }

Defined in

packages/modelfusion/src/model-provider/ollama/OllamaCompletionModel.ts:388

OllamaErrorData

Ƭ OllamaErrorData: Object

Type declaration

Name	Type
`error`	`string`

Defined in

packages/modelfusion/src/model-provider/ollama/OllamaError.ts:13

OllamaTextEmbeddingResponse

Ƭ OllamaTextEmbeddingResponse: Object

Type declaration

Name	Type
`embedding`	`number`[]

Defined in

packages/modelfusion/src/model-provider/ollama/OllamaTextEmbeddingModel.ts:112

OpenAIChatBaseModelType

Ƭ OpenAIChatBaseModelType: keyof typeof CHAT_MODEL_CONTEXT_WINDOW_SIZES

Defined in

packages/modelfusion/src/model-provider/openai/OpenAIChatModel.ts:94

OpenAIChatChunk

Ƭ OpenAIChatChunk: Object

Type declaration

Name	Type
`choices`	{ `delta`: { `content?`: `null` \| `string` ; `function_call?`: { `arguments?`: `string` ; `name?`: `string` } ; `role?`: `"user"` \| `"assistant"` ; `tool_calls?`: { `function`: { `arguments`: `string` ; `name`: `string` } ; `id`: `string` ; `type`: `"function"` }[] } ; `finish_reason?`: `null` \| `"length"` \| `"stop"` \| `"function_call"` \| `"tool_calls"` \| `"content_filter"` ; `index`: `number` }[]
`created`	`number`
`id`	`string`
`model?`	`string`
`object`	`string`
`system_fingerprint?`	`null` \| `string`

Defined in

packages/modelfusion/src/model-provider/openai/AbstractOpenAIChatModel.ts:442

OpenAIChatModelType

Ƭ OpenAIChatModelType: OpenAIChatBaseModelType | FineTunedOpenAIChatModelType

Defined in

packages/modelfusion/src/model-provider/openai/OpenAIChatModel.ts:97

OpenAIChatResponse

Ƭ OpenAIChatResponse: Object

Type declaration

Name	Type
`choices`	{ `finish_reason?`: `null` \| `"length"` \| `"stop"` \| `"function_call"` \| `"tool_calls"` \| `"content_filter"` ; `index?`: `number` ; `logprobs?`: `any` ; `message`: { `content`: `null` \| `string` ; `function_call?`: { `arguments`: `string` ; `name`: `string` } ; `role`: `"assistant"` ; `tool_calls?`: { `function`: { `arguments`: `string` ; `name`: `string` } ; `id`: `string` ; `type`: `"function"` }[] } }[]
`created`	`number`
`id`	`string`
`model`	`string`
`object`	`"chat.completion"`
`system_fingerprint?`	`null` \| `string`
`usage`	{ `completion_tokens`: `number` ; `prompt_tokens`: `number` ; `total_tokens`: `number` }
`usage.completion_tokens`	`number`
`usage.prompt_tokens`	`number`
`usage.total_tokens`	`number`

Defined in

packages/modelfusion/src/model-provider/openai/AbstractOpenAIChatModel.ts:395

OpenAIChatResponseFormatType

Ƭ OpenAIChatResponseFormatType<T>: Object

Type parameters

Name
`T`

Type declaration

Name	Type
`handler`	`ResponseHandler`<`T`>
`stream`	`boolean`

Defined in

packages/modelfusion/src/model-provider/openai/AbstractOpenAIChatModel.ts:444

OpenAICompatibleProviderName

Ƭ OpenAICompatibleProviderName: "openaicompatible" | `openaicompatible-${string}`

Defined in

packages/modelfusion/src/model-provider/openai-compatible/OpenAICompatibleApiConfiguration.ts:3

OpenAICompletionModelType

Ƭ OpenAICompletionModelType: keyof typeof OPENAI_TEXT_GENERATION_MODELS

Defined in

packages/modelfusion/src/model-provider/openai/OpenAICompletionModel.ts:37

OpenAICompletionResponse

Ƭ OpenAICompletionResponse: Object

Type declaration

Name	Type
`choices`	{ `finish_reason?`: `null` \| `"length"` \| `"stop"` \| `"content_filter"` ; `index`: `number` ; `logprobs?`: `any` ; `text`: `string` }[]
`created`	`number`
`id`	`string`
`model`	`string`
`object`	`"text_completion"`
`system_fingerprint?`	`string`
`usage`	{ `completion_tokens`: `number` ; `prompt_tokens`: `number` ; `total_tokens`: `number` }
`usage.completion_tokens`	`number`
`usage.prompt_tokens`	`number`
`usage.total_tokens`	`number`

Defined in

packages/modelfusion/src/model-provider/openai/AbstractOpenAICompletionModel.ts:207

OpenAIErrorData

Ƭ OpenAIErrorData: Object

Type declaration

Name	Type
`error`	{ `code`: `null` \| `string` ; `message`: `string` ; `param?`: `any` ; `type`: `string` }
`error.code`	`null` \| `string`
`error.message`	`string`
`error.param?`	`any`
`error.type`	`string`

Defined in

packages/modelfusion/src/model-provider/openai/OpenAIError.ts:14

OpenAIImageGenerationBase64JsonResponse

Ƭ OpenAIImageGenerationBase64JsonResponse: Object

Type declaration

Name	Type
`created`	`number`
`data`	{ `b64_json`: `string` }[]

Defined in

packages/modelfusion/src/model-provider/openai/OpenAIImageGenerationModel.ts:170

OpenAIImageGenerationResponseFormatType

Ƭ OpenAIImageGenerationResponseFormatType<T>: Object

Type parameters

Name
`T`

Type declaration

Name	Type
`handler`	`ResponseHandler`<`T`>
`type`	`"b64_json"` \| `"url"`

Defined in

packages/modelfusion/src/model-provider/openai/OpenAIImageGenerationModel.ts:143

OpenAIImageGenerationUrlResponse

Ƭ OpenAIImageGenerationUrlResponse: Object

Type declaration

Name	Type
`created`	`number`
`data`	{ `url`: `string` }[]

Defined in

packages/modelfusion/src/model-provider/openai/OpenAIImageGenerationModel.ts:157

OpenAISpeechModelType

Ƭ OpenAISpeechModelType: "tts-1" | "tts-1-hd"

Defined in

packages/modelfusion/src/model-provider/openai/OpenAISpeechModel.ts:25

OpenAISpeechVoice

Defined in

packages/modelfusion/src/model-provider/openai/OpenAISpeechModel.ts:16

OpenAITextEmbeddingModelType

Ƭ OpenAITextEmbeddingModelType: keyof typeof OPENAI_TEXT_EMBEDDING_MODELS

Defined in

packages/modelfusion/src/model-provider/openai/OpenAITextEmbeddingModel.ts:26

OpenAITextEmbeddingResponse

Ƭ OpenAITextEmbeddingResponse: Object

Type declaration

Name	Type
`data`	{ `embedding`: `number`[] ; `index`: `number` ; `object`: `"embedding"` }[]
`model`	`string`
`object`	`"list"`
`usage?`	{ `prompt_tokens`: `number` ; `total_tokens`: `number` }
`usage.prompt_tokens`	`number`
`usage.total_tokens`	`number`

Defined in

packages/modelfusion/src/model-provider/openai/AbstractOpenAITextEmbeddingModel.ts:114

OpenAITextResponseFormatType

Ƭ OpenAITextResponseFormatType<T>: Object

Type parameters

Name
`T`

Type declaration

Name	Type
`handler`	`ResponseHandler`<`T`>
`stream`	`boolean`

Defined in

packages/modelfusion/src/model-provider/openai/AbstractOpenAICompletionModel.ts:233

OpenAITranscriptionJsonResponse

Ƭ OpenAITranscriptionJsonResponse: Object

Type declaration

Name	Type
`text`	`string`

Defined in

packages/modelfusion/src/model-provider/openai/OpenAITranscriptionModel.ts:193

OpenAITranscriptionResponseFormatType

Ƭ OpenAITranscriptionResponseFormatType<T>: Object

Type parameters

Name
`T`

Type declaration

Name	Type
`handler`	`ResponseHandler`<`T`>
`type`	`"json"` \| `"text"` \| `"srt"` \| `"verbose_json"` \| `"vtt"`

Defined in

packages/modelfusion/src/model-provider/openai/OpenAITranscriptionModel.ts:223

OpenAITranscriptionVerboseJsonResponse

Ƭ OpenAITranscriptionVerboseJsonResponse: Object

Type declaration

Name	Type
`duration`	`number`
`language`	`string`
`segments`	{ `avg_logprob`: `number` ; `compression_ratio`: `number` ; `end`: `number` ; `id`: `number` ; `no_speech_prob`: `number` ; `seek`: `number` ; `start`: `number` ; `temperature`: `number` ; `text`: `string` ; `tokens`: `number`[] ; `transient?`: `boolean` }[]
`task`	`"transcribe"`
`text`	`string`

Defined in

packages/modelfusion/src/model-provider/openai/OpenAITranscriptionModel.ts:219

PartialBaseUrlPartsApiConfigurationOptions

Ƭ PartialBaseUrlPartsApiConfigurationOptions: Omit<BaseUrlPartsApiConfigurationOptions, "baseUrl"> & { baseUrl?: string | Partial<UrlParts> }

Defined in

packages/modelfusion/src/core/api/BaseUrlApiConfiguration.ts:64

PromptFunction

Ƭ PromptFunction<INPUT, PROMPT>: () => PromiseLike<{ input: INPUT ; prompt: PROMPT }> & { [promptFunctionMarker]: true }

Type parameters

Name
`INPUT`
`PROMPT`

Defined in

packages/modelfusion/src/core/PromptFunction.ts:1

RetryErrorReason

Ƭ RetryErrorReason: "maxTriesExceeded" | "errorNotRetryable" | "abort"

Defined in

packages/modelfusion/src/core/api/RetryError.ts:1

RetryFunction

Ƭ RetryFunction: <OUTPUT>(fn: () => PromiseLike<OUTPUT>) => PromiseLike<OUTPUT>

Type declaration

▸ <OUTPUT>(fn): PromiseLike<OUTPUT>

Type parameters

Name
`OUTPUT`

Parameters

Name	Type
`fn`	() => `PromiseLike`<`OUTPUT`>

Returns

PromiseLike<OUTPUT>

Defined in

packages/modelfusion/src/core/api/RetryFunction.ts:1

SpeechGenerationFinishedEventResult

Ƭ SpeechGenerationFinishedEventResult: { rawResponse: unknown ; status: "success" ; value: Uint8Array } | { error: unknown ; status: "error" } | { status: "abort" }

Defined in

packages/modelfusion/src/model-function/generate-speech/SpeechGenerationEvent.ts:12

SplitFunction

Ƭ SplitFunction: (input: { text: string }, options?: FunctionOptions) => PromiseLike<string[]>

Type declaration

▸ (input, options?): PromiseLike<string[]>

Parameters

Name	Type
`input`	`Object`
`input.text`	`string`
`options?`	`FunctionOptions`

Returns

PromiseLike<string[]>

Defined in

packages/modelfusion/src/text-chunk/split/SplitFunction.ts:3

StabilityClipGuidancePreset

Defined in

packages/modelfusion/src/model-provider/stability/StabilityImageGenerationModel.ts:67

StabilityErrorData

Ƭ StabilityErrorData: Object

Type declaration

Name	Type
`message`	`string`

Defined in

packages/modelfusion/src/model-provider/stability/StabilityError.ts:13

StabilityImageGenerationModelType

Ƭ StabilityImageGenerationModelType: typeof stabilityImageGenerationModels[number] | string &

Defined in

packages/modelfusion/src/model-provider/stability/StabilityImageGenerationModel.ts:29

StabilityImageGenerationPrompt

Ƭ StabilityImageGenerationPrompt: { text: string ; weight?: number }[]

Defined in

packages/modelfusion/src/model-provider/stability/StabilityImageGenerationPrompt.ts:3

StabilityImageGenerationResponse

Ƭ StabilityImageGenerationResponse: Object

Type declaration

Name	Type
`artifacts`	{ `base64`: `string` ; `finishReason`: `"ERROR"` \| `"SUCCESS"` \| `"CONTENT_FILTERED"` ; `seed`: `number` }[]

Defined in

packages/modelfusion/src/model-provider/stability/StabilityImageGenerationModel.ts:256

StabilityImageGenerationSampler

Defined in

packages/modelfusion/src/model-provider/stability/StabilityImageGenerationModel.ts:55

StabilityImageGenerationStylePreset

Defined in

packages/modelfusion/src/model-provider/stability/StabilityImageGenerationModel.ts:36

TextChunk

Ƭ TextChunk: Object

Type declaration

Name	Type
`text`	`string`

Defined in

packages/modelfusion/src/text-chunk/TextChunk.ts:1

TextGenerationFinishReason

Defined in

packages/modelfusion/src/model-function/generate-text/TextGenerationResult.ts:13

TextGenerationFinishedEventResult

Ƭ TextGenerationFinishedEventResult: { rawResponse: unknown ; status: "success" ; usage?: { completionTokens: number ; promptTokens: number ; totalTokens: number } ; value: string } | { error: unknown ; status: "error" } | { status: "abort" }

Defined in

packages/modelfusion/src/model-function/generate-text/TextGenerationEvent.ts:10

TextGenerationResult

Ƭ TextGenerationResult: Object

Type declaration

Name	Type	Description
`finishReason`	`TextGenerationFinishReason`	The reason why the generation stopped.
`text`	`string`	The generated text.

Defined in

packages/modelfusion/src/model-function/generate-text/TextGenerationResult.ts:1

ThrottleFunction

Ƭ ThrottleFunction: <OUTPUT>(fn: () => PromiseLike<OUTPUT>) => PromiseLike<OUTPUT>

Type declaration

▸ <OUTPUT>(fn): PromiseLike<OUTPUT>

Type parameters

Name
`OUTPUT`

Parameters

Name	Type
`fn`	() => `PromiseLike`<`OUTPUT`>

Returns

PromiseLike<OUTPUT>

Defined in

packages/modelfusion/src/core/api/ThrottleFunction.ts:1

TikTokenTokenizerSettings

Ƭ TikTokenTokenizerSettings: Object

Type declaration

Name	Type
`model`	`OpenAIChatBaseModelType` \| `OpenAICompletionModelType` \| `OpenAITextEmbeddingModelType`

Defined in

packages/modelfusion/src/model-provider/openai/TikTokenTokenizer.ts:9

ToolCallGenerationFinishedEvent

Ƭ ToolCallGenerationFinishedEvent: BaseModelCallFinishedEvent & { functionType: "generate-tool-call" ; result: ToolCallGenerationFinishedEventResult }

Defined in

packages/modelfusion/src/tool/generate-tool-call/ToolCallGenerationEvent.ts:26

ToolCallGenerationFinishedEventResult

Ƭ ToolCallGenerationFinishedEventResult: { rawResponse: unknown ; status: "success" ; usage?: { completionTokens: number ; promptTokens: number ; totalTokens: number } ; value: unknown } | { error: unknown ; status: "error" } | { status: "abort" }

Defined in

packages/modelfusion/src/tool/generate-tool-call/ToolCallGenerationEvent.ts:11

ToolCallResult

Ƭ ToolCallResult<NAME, PARAMETERS, RETURN_TYPE>: { args: PARAMETERS ; tool: NAME ; toolCall: ToolCall<NAME, PARAMETERS> } & { ok: true ; result: RETURN_TYPE } | { ok: false ; result: ToolCallError }

Type parameters

Name	Type
`NAME`	extends `string`
`PARAMETERS`	`PARAMETERS`
`RETURN_TYPE`	`RETURN_TYPE`

Defined in

packages/modelfusion/src/tool/ToolCallResult.ts:4

ToolCallsGenerationFinishedEvent

Ƭ ToolCallsGenerationFinishedEvent: BaseModelCallFinishedEvent & { functionType: "generate-tool-calls" ; result: ToolCallsGenerationFinishedEventResult }

Defined in

packages/modelfusion/src/tool/generate-tool-calls/ToolCallsGenerationEvent.ts:26

ToolCallsGenerationFinishedEventResult

Ƭ ToolCallsGenerationFinishedEventResult: { rawResponse: unknown ; status: "success" ; usage?: { completionTokens: number ; promptTokens: number ; totalTokens: number } ; value: unknown } | { error: unknown ; status: "error" } | { status: "abort" }

Defined in

packages/modelfusion/src/tool/generate-tool-calls/ToolCallsGenerationEvent.ts:11

ToolContent

Ƭ ToolContent: ToolResponsePart[]

Defined in

packages/modelfusion/src/model-function/generate-text/prompt-template/ChatPrompt.ts:42

TranscriptionFinishedEventResult

Ƭ TranscriptionFinishedEventResult: { rawResponse: unknown ; status: "success" ; value: string } | { error: unknown ; status: "error" } | { status: "abort" }

Defined in

packages/modelfusion/src/model-function/generate-transcription/TranscriptionEvent.ts:10

UrlParts

Ƭ UrlParts: Object

Type declaration

Name	Type
`host`	`string`
`path`	`string`
`port`	`string`
`protocol`	`string`

Defined in

packages/modelfusion/src/core/api/BaseUrlApiConfiguration.ts:6

UserContent

Ƭ UserContent: string | (TextPart | ImagePart)[]

Defined in

packages/modelfusion/src/model-function/generate-text/prompt-template/ChatPrompt.ts:40

Vector

Ƭ Vector: number[]

A vector is an array of numbers. It is e.g. used to represent a text as a vector of word embeddings.

Defined in

packages/modelfusion/src/core/Vector.ts:5

WebSearchToolInput

Ƭ WebSearchToolInput: Object

Type declaration

Name	Type
`query`	`string`

Defined in

packages/modelfusion/src/tool/WebSearchTool.ts:27

WebSearchToolOutput

Ƭ WebSearchToolOutput: Object

Type declaration

Name	Type
`results`	{ `link`: `string` ; `snippet`: `string` ; `title`: `string` }[]

Defined in

packages/modelfusion/src/tool/WebSearchTool.ts:31

Classes​

Interfaces​

Namespaces​

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ObjectStreamFromResponse​

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classify​

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convertDataContentToBase64String​

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convertDataContentToUint8Array​

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cosineSimilarity​

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countOpenAIChatMessageTokens​

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countOpenAIChatPromptTokens​

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countTokens​

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createChatPrompt​

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createEventSourceStream​

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createInstructionPrompt​

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createTextPrompt​

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delay​

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embed​

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Classes

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classify

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convertDataContentToBase64String

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convertDataContentToUint8Array

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cosineSimilarity

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countOpenAIChatMessageTokens

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countOpenAIChatPromptTokens

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countTokens

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createChatPrompt

Type parameters

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createEventSourceStream

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createInstructionPrompt

Type parameters

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createTextPrompt

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delay

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embed

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