--- title: streamText description: API Reference for streamText. --- # `streamText()` Streams text generations from a language model. You can use the streamText function for interactive use cases such as chat bots and other real-time applications. You can also generate UI components with tools. ```ts import { openai } from '@ai-sdk/openai'; import { streamText } from 'ai'; const { textStream } = streamText({ model: 'anthropic/claude-sonnet-4.5', prompt: 'Invent a new holiday and describe its traditions.', }); for await (const textPart of textStream) { process.stdout.write(textPart); } ``` To see `streamText` in action, check out [these examples](#examples). ## Import ## API Signature ### Parameters ', description: 'The input prompt to generate the text from.', }, { name: 'messages', type: 'Array', description: 'A list of messages that represent a conversation. Automatically converts UI messages from the useChat hook.', properties: [ { type: 'SystemModelMessage', parameters: [ { name: 'role', type: "'system'", description: 'The role for the system message.', }, { name: 'content', type: 'string', description: 'The content of the message.', }, ], }, { type: 'UserModelMessage', parameters: [ { name: 'role', type: "'user'", description: 'The role for the user message.', }, { name: 'content', type: 'string | Array', description: 'The content of the message.', properties: [ { type: 'TextPart', parameters: [ { name: 'type', type: "'text'", description: 'The type of the message part.', }, { name: 'text', type: 'string', description: 'The text content of the message part.', }, ], }, { type: 'ImagePart', parameters: [ { name: 'type', type: "'image'", description: 'The type of the message part.', }, { name: 'image', type: 'string | Uint8Array | Buffer | ArrayBuffer | URL', description: 'The image content of the message part. String are either base64 encoded content, base64 data URLs, or http(s) URLs.', }, { name: 'mediaType', type: 'string', isOptional: true, description: 'The IANA media type of the image.', }, ], }, { type: 'FilePart', parameters: [ { name: 'type', type: "'file'", description: 'The type of the message part.', }, { name: 'data', type: 'string | Uint8Array | Buffer | ArrayBuffer | URL', description: 'The file content of the message part. String are either base64 encoded content, base64 data URLs, or http(s) URLs.', }, { name: 'mediaType', type: 'string', description: 'The IANA media type of the file.', }, ], }, ], }, ], }, { type: 'AssistantModelMessage', parameters: [ { name: 'role', type: "'assistant'", description: 'The role for the assistant message.', }, { name: 'content', type: 'string | Array', description: 'The content of the message.', properties: [ { type: 'TextPart', parameters: [ { name: 'type', type: "'text'", description: 'The type of the message part.', }, { name: 'text', type: 'string', description: 'The text content of the message part.', }, ], }, { type: 'ReasoningPart', parameters: [ { name: 'type', type: "'reasoning'", description: 'The type of the reasoning part.', }, { name: 'text', type: 'string', description: 'The reasoning text.', }, ], }, { type: 'FilePart', parameters: [ { name: 'type', type: "'file'", description: 'The type of the message part.', }, { name: 'data', type: 'string | Uint8Array | Buffer | ArrayBuffer | URL', description: 'The file content of the message part. String are either base64 encoded content, base64 data URLs, or http(s) URLs.', }, { name: 'mediaType', type: 'string', description: 'The IANA media type of the file.', }, { name: 'filename', type: 'string', description: 'The name of the file.', isOptional: true, }, ], }, { type: 'ToolCallPart', parameters: [ { name: 'type', type: "'tool-call'", description: 'The type of the message part.', }, { name: 'toolCallId', type: 'string', description: 'The id of the tool call.', }, { name: 'toolName', type: 'string', description: 'The name of the tool, which typically would be the name of the function.', }, { name: 'input', type: 'object based on zod schema', description: 'Parameters generated by the model to be used by the tool.', }, ], }, ], }, ], }, { type: 'ToolModelMessage', parameters: [ { name: 'role', type: "'tool'", description: 'The role for the assistant message.', }, { name: 'content', type: 'Array', description: 'The content of the message.', properties: [ { type: 'ToolResultPart', parameters: [ { name: 'type', type: "'tool-result'", description: 'The type of the message part.', }, { name: 'toolCallId', type: 'string', description: 'The id of the tool call the result corresponds to.', }, { name: 'toolName', type: 'string', description: 'The name of the tool the result corresponds to.', }, { name: 'result', type: 'unknown', description: 'The result returned by the tool after execution.', }, { name: 'isError', type: 'boolean', isOptional: true, description: 'Whether the result is an error or an error message.', }, ], }, ], }, ], }, ], }, { name: 'tools', type: 'ToolSet', description: 'Tools that are accessible to and can be called by the model. The model needs to support calling tools.', properties: [ { type: 'Tool', parameters: [ { name: 'description', isOptional: true, type: 'string', description: 'Information about the purpose of the tool including details on how and when it can be used by the model.', }, { name: 'inputSchema', type: 'Zod Schema | JSON Schema', description: 'The schema of the input that the tool expects. The language model will use this to generate the input. It is also used to validate the output of the language model. Use descriptions to make the input understandable for the language model. You can either pass in a Zod schema or a JSON schema (using the `jsonSchema` function).', }, { name: 'execute', isOptional: true, type: 'async (parameters: T, options: ToolExecutionOptions) => RESULT', description: 'An async function that is called with the arguments from the tool call and produces a result. If not provided, the tool will not be executed automatically.', properties: [ { type: 'ToolExecutionOptions', parameters: [ { name: 'toolCallId', type: 'string', description: 'The ID of the tool call. You can use it e.g. when sending tool-call related information with stream data.', }, { name: 'messages', type: 'ModelMessage[]', description: 'Messages that were sent to the language model to initiate the response that contained the tool call. The messages do not include the system prompt nor the assistant response that contained the tool call.', }, { name: 'abortSignal', type: 'AbortSignal', description: 'An optional abort signal that indicates that the overall operation should be aborted.', }, ], }, ], }, ], }, ], }, { name: 'toolChoice', isOptional: true, type: '"auto" | "none" | "required" | { "type": "tool", "toolName": string }', description: 'The tool choice setting. It specifies how tools are selected for execution. The default is "auto". "none" disables tool execution. "required" requires tools to be executed. { "type": "tool", "toolName": string } specifies a specific tool to execute.', }, { name: 'maxOutputTokens', type: 'number', isOptional: true, description: 'Maximum number of tokens to generate.', }, { name: 'temperature', type: 'number', isOptional: true, description: 'Temperature setting. The value is passed through to the provider. The range depends on the provider and model. It is recommended to set either `temperature` or `topP`, but not both.', }, { name: 'topP', type: 'number', isOptional: true, description: 'Nucleus sampling. The value is passed through to the provider. The range depends on the provider and model. It is recommended to set either `temperature` or `topP`, but not both.', }, { name: 'topK', type: 'number', isOptional: true, description: 'Only sample from the top K options for each subsequent token. Used to remove "long tail" low probability responses. Recommended for advanced use cases only. You usually only need to use temperature.', }, { name: 'presencePenalty', type: 'number', isOptional: true, description: 'Presence penalty setting. It affects the likelihood of the model to repeat information that is already in the prompt. The value is passed through to the provider. The range depends on the provider and model.', }, { name: 'frequencyPenalty', type: 'number', isOptional: true, description: 'Frequency penalty setting. It affects the likelihood of the model to repeatedly use the same words or phrases. The value is passed through to the provider. The range depends on the provider and model.', }, { name: 'stopSequences', type: 'string[]', isOptional: true, description: 'Sequences that will stop the generation of the text. If the model generates any of these sequences, it will stop generating further text.', }, { name: 'seed', type: 'number', isOptional: true, description: 'The seed (integer) to use for random sampling. If set and supported by the model, calls will generate deterministic results.', }, { name: 'maxRetries', type: 'number', isOptional: true, description: 'Maximum number of retries. Set to 0 to disable retries. Default: 2.', }, { name: 'abortSignal', type: 'AbortSignal', isOptional: true, description: 'An optional abort signal that can be used to cancel the call.', }, { name: 'headers', type: 'Record', isOptional: true, description: 'Additional HTTP headers to be sent with the request. Only applicable for HTTP-based providers.', }, { name: 'experimental_generateMessageId', type: '() => string', isOptional: true, description: 'Function used to generate a unique ID for each message. This is an experimental feature.', }, { name: 'experimental_telemetry', type: 'TelemetrySettings', isOptional: true, description: 'Telemetry configuration. Experimental feature.', properties: [ { type: 'TelemetrySettings', parameters: [ { name: 'isEnabled', type: 'boolean', isOptional: true, description: 'Enable or disable telemetry. Disabled by default while experimental.', }, { name: 'recordInputs', type: 'boolean', isOptional: true, description: 'Enable or disable input recording. Enabled by default.', }, { name: 'recordOutputs', type: 'boolean', isOptional: true, description: 'Enable or disable output recording. Enabled by default.', }, { name: 'functionId', type: 'string', isOptional: true, description: 'Identifier for this function. Used to group telemetry data by function.', }, { name: 'metadata', isOptional: true, type: 'Record | Array | Array>', description: 'Additional information to include in the telemetry data.', }, ], }, ], }, { name: 'experimental_transform', type: 'StreamTextTransform | Array', isOptional: true, description: 'Optional stream transformations. They are applied in the order they are provided. The stream transformations must maintain the stream structure for streamText to work correctly.', properties: [ { type: 'StreamTextTransform', parameters: [ { name: 'transform', type: '(options: TransformOptions) => TransformStream, TextStreamPart>', description: 'A transformation that is applied to the stream.', properties: [ { type: 'TransformOptions', parameters: [ { name: 'stopStream', type: '() => void', description: 'A function that stops the stream.', }, { name: 'tools', type: 'TOOLS', description: 'The tools that are available.', }, ], }, ], }, ], }, ], }, { name: 'includeRawChunks', type: 'boolean', isOptional: true, description: 'Whether to include raw chunks from the provider in the stream. When enabled, you will receive raw chunks with type "raw" that contain the unprocessed data from the provider. This allows access to cutting-edge provider features not yet wrapped by the AI SDK. Defaults to false.', }, { name: 'providerOptions', type: 'Record | undefined', isOptional: true, description: 'Provider-specific options. The outer key is the provider name. The inner values are the metadata. Details depend on the provider.', }, { name: 'activeTools', type: 'Array | undefined', isOptional: true, description: 'The tools that are currently active. All tools are active by default.', }, { name: 'stopWhen', type: 'StopCondition | Array>', isOptional: true, description: 'Condition for stopping the generation when there are tool results in the last step. When the condition is an array, any of the conditions can be met to stop the generation. Default: stepCountIs(1).', }, { name: 'prepareStep', type: '(options: PrepareStepOptions) => PrepareStepResult | Promise>', isOptional: true, description: 'Optional function that you can use to provide different settings for a step. You can modify the model, tool choices, active tools, system prompt, and input messages for each step.', properties: [ { type: 'PrepareStepFunction', parameters: [ { name: 'options', type: 'object', description: 'The options for the step.', properties: [ { type: 'PrepareStepOptions', parameters: [ { name: 'steps', type: 'Array>', description: 'The steps that have been executed so far.', }, { name: 'stepNumber', type: 'number', description: 'The number of the step that is being executed.', }, { name: 'model', type: 'LanguageModel', description: 'The model that is being used.', }, { name: 'messages', type: 'Array', description: 'The messages that will be sent to the model for the current step.', }, ], }, ], }, ], }, { type: 'PrepareStepResult', description: 'Return value that can modify settings for the current step.', parameters: [ { name: 'model', type: 'LanguageModel', isOptional: true, description: 'Change the model for this step.', }, { name: 'toolChoice', type: 'ToolChoice', isOptional: true, description: 'Change the tool choice strategy for this step.', }, { name: 'activeTools', type: 'Array', isOptional: true, description: 'Change which tools are active for this step.', }, { name: 'system', type: 'string | SystemModelMessage', isOptional: true, description: 'Change the system prompt for this step.', }, { name: 'messages', type: 'Array', isOptional: true, description: 'Modify the input messages for this step.', }, ], }, ], }, { name: 'experimental_context', type: 'unknown', isOptional: true, description: 'Context that is passed into tool execution. Experimental (can break in patch releases).', }, { name: 'experimental_download', type: '(requestedDownloads: Array<{ url: URL; isUrlSupportedByModel: boolean }>) => Promise>', isOptional: true, description: 'Custom download function to control how URLs are fetched when they appear in prompts. By default, files are downloaded if the model does not support the URL for the given media type. Experimental feature. Return null to pass the URL directly to the model (when supported), or return downloaded content with data and media type.', }, { name: 'experimental_repairToolCall', type: '(options: ToolCallRepairOptions) => Promise', isOptional: true, description: 'A function that attempts to repair a tool call that failed to parse. Return either a repaired tool call or null if the tool call cannot be repaired.', properties: [ { type: 'ToolCallRepairOptions', parameters: [ { name: 'system', type: 'string | SystemModelMessage | undefined', description: 'The system prompt.', }, { name: 'messages', type: 'ModelMessage[]', description: 'The messages in the current generation step.', }, { name: 'toolCall', type: 'LanguageModelV3ToolCall', description: 'The tool call that failed to parse.', }, { name: 'tools', type: 'TOOLS', description: 'The tools that are available.', }, { name: 'parameterSchema', type: '(options: { toolName: string }) => JSONSchema7', description: 'A function that returns the JSON Schema for a tool.', }, { name: 'error', type: 'NoSuchToolError | InvalidToolInputError', description: 'The error that occurred while parsing the tool call.', }, ], }, ], }, { name: 'onChunk', type: '(event: OnChunkResult) => Promise |void', isOptional: true, description: 'Callback that is called for each chunk of the stream. The stream processing will pause until the callback promise is resolved.', properties: [ { type: 'OnChunkResult', parameters: [ { name: 'chunk', type: 'TextStreamPart', description: 'The chunk of the stream.', properties: [ { type: 'TextStreamPart', parameters: [ { name: 'type', type: "'text'", description: 'The type to identify the object as text delta.', }, { name: 'text', type: 'string', description: 'The text delta.', }, ], }, { type: 'TextStreamPart', parameters: [ { name: 'type', type: "'reasoning'", description: 'The type to identify the object as reasoning.', }, { name: 'text', type: 'string', description: 'The reasoning text delta.', }, ], }, { type: 'TextStreamPart', parameters: [ { name: 'type', type: "'source'", description: 'The type to identify the object as source.', }, { name: 'source', type: 'Source', description: 'The source.', }, ], }, { type: 'TextStreamPart', parameters: [ { name: 'type', type: "'tool-call'", description: 'The type to identify the object as tool call.', }, { name: 'toolCallId', type: 'string', description: 'The id of the tool call.', }, { name: 'toolName', type: 'string', description: 'The name of the tool, which typically would be the name of the function.', }, { name: 'input', type: 'object based on zod schema', description: 'Parameters generated by the model to be used by the tool.', }, ], }, { type: 'TextStreamPart', parameters: [ { name: 'type', type: "'tool-call-streaming-start'", description: 'Indicates the start of a tool call streaming. Only available when streaming tool calls.', }, { name: 'toolCallId', type: 'string', description: 'The id of the tool call.', }, { name: 'toolName', type: 'string', description: 'The name of the tool, which typically would be the name of the function.', }, ], }, { type: 'TextStreamPart', parameters: [ { name: 'type', type: "'tool-call-delta'", description: 'The type to identify the object as tool call delta. Only available when streaming tool calls.', }, { name: 'toolCallId', type: 'string', description: 'The id of the tool call.', }, { name: 'toolName', type: 'string', description: 'The name of the tool, which typically would be the name of the function.', }, { name: 'argsTextDelta', type: 'string', description: 'The text delta of the tool call arguments.', }, ], }, { type: 'TextStreamPart', description: 'The result of a tool call execution.', parameters: [ { name: 'type', type: "'tool-result'", description: 'The type to identify the object as tool result.', }, { name: 'toolCallId', type: 'string', description: 'The id of the tool call.', }, { name: 'toolName', type: 'string', description: 'The name of the tool, which typically would be the name of the function.', }, { name: 'input', type: 'object based on zod schema', description: 'Parameters generated by the model to be used by the tool.', }, { name: 'output', type: 'any', description: 'The result returned by the tool after execution has completed.', }, ], }, ], }, ], }, ], }, { name: 'onError', type: '(event: OnErrorResult) => Promise |void', isOptional: true, description: 'Callback that is called when an error occurs during streaming. You can use it to log errors.', properties: [ { type: 'OnErrorResult', parameters: [ { name: 'error', type: 'unknown', description: 'The error that occurred.', }, ], }, ], }, { name: 'output', type: 'Output', isOptional: true, description: 'Specification for parsing structured outputs from the LLM response.', properties: [ { type: 'Output', parameters: [ { name: 'Output.text()', type: 'Output', description: 'Output specification for text generation (default).', }, { name: 'Output.object()', type: 'Output', description: 'Output specification for typed object generation using schemas. When the model generates a text response, it will return an object that matches the schema.', properties: [ { type: 'Options', parameters: [ { name: 'schema', type: 'Schema