MastraModelOutput
The MastraModelOutput class is returned by .stream() and provides both streaming and promise-based access to model outputs. It supports structured output generation, tool calls, reasoning, and comprehensive usage tracking.
// MastraModelOutput is returned by agent.stream()
const stream = await agent.stream("Hello world");For setup and basic usage, see the .stream() method documentation.
Streaming Properties
These properties provide real-time access to model outputs as they’re generated:
fullStream:
ReadableStream<ChunkType<OUTPUT>>
Complete stream of all chunk types including text, tool calls, reasoning, metadata, and control chunks. Provides granular access to every aspect of the model's response.
ReadableStream
ChunkType:
ChunkType<OUTPUT>
All possible chunk types that can be emitted during streaming
textStream:
ReadableStream<string>
Stream of incremental text content only. Filters out all metadata, tool calls, and control chunks to provide just the text being generated.
objectStream:
ReadableStream<PartialSchemaOutput<OUTPUT>>
Stream of progressive structured object updates when using output schemas. Emits partial objects as they're built up, allowing real-time visualization of structured data generation.
ReadableStream
PartialSchemaOutput:
PartialSchemaOutput<OUTPUT>
Partially completed object matching the defined schema
elementStream:
ReadableStream<InferSchemaOutput<OUTPUT> extends (infer T)[] ? T : never>
Stream of individual array elements when the output schema defines an array type. Each element is emitted as it's completed rather than waiting for the entire array.
Promise-based Properties
These properties resolve to final values after the stream completes:
text:
Promise<string>
The complete concatenated text response from the model. Resolves when text generation is finished.
object:
Promise<InferSchemaOutput<OUTPUT>>
The complete structured object response when using output schemas. Validated against the schema before resolving. Rejects if validation fails.
Promise
InferSchemaOutput:
InferSchemaOutput<OUTPUT>
Fully typed object matching the exact schema definition
reasoning:
Promise<string>
Complete reasoning text for models that support reasoning (like OpenAI's o1 series). Returns empty string for models without reasoning capability.
reasoningText:
Promise<string | undefined>
Alternative access to reasoning content. May be undefined for models that don't support reasoning, while 'reasoning' returns empty string.
toolCalls:
Promise<ToolCallChunk[]>
Array of all tool call chunks made during execution. Each chunk contains tool metadata and execution details.
ToolCallChunk
type:
'tool-call'
Chunk type identifier
runId:
string
Execution run identifier
from:
ChunkFrom
Source of the chunk (AGENT, WORKFLOW, etc.)
payload:
ToolCallPayload
Tool call data including toolCallId, toolName, args, and execution details
toolResults:
Promise<ToolResultChunk[]>
Array of all tool result chunks corresponding to the tool calls. Contains execution results and error information.
ToolResultChunk
type:
'tool-result'
Chunk type identifier
runId:
string
Execution run identifier
from:
ChunkFrom
Source of the chunk (AGENT, WORKFLOW, etc.)
payload:
ToolResultPayload
Tool result data including toolCallId, toolName, result, and error status
usage:
Promise<LanguageModelUsage>
Token usage statistics including input tokens, output tokens, total tokens, and reasoning tokens (for reasoning models).
Record
inputTokens:
number
Tokens consumed by the input prompt
outputTokens:
number
Tokens generated in the response
totalTokens:
number
Sum of input and output tokens
reasoningTokens?:
number
Hidden reasoning tokens (for reasoning models)
cachedInputTokens?:
number
Number of input tokens that were a cache hit
finishReason:
Promise<string | undefined>
Reason why generation stopped (e.g., 'stop', 'length', 'tool_calls', 'content_filter'). Undefined if the stream hasn't finished.
enum
stop:
'stop'
Model finished naturally
length:
'length'
Hit maximum token limit
tool_calls:
'tool_calls'
Model called tools
content_filter:
'content_filter'
Content was filtered
Error Properties
error:
string | Error | { message: string; stack: string; } | undefined
Error information if the stream encountered an error. Undefined if no errors occurred. Can be a string message, Error object, or serialized error with stack trace.
Methods
getFullOutput:
() => Promise<FullOutput>
Returns a comprehensive output object containing all results: text, structured object, tool calls, usage statistics, reasoning, and metadata. Convenient single method to access all stream results.
FullOutput
text:
string
Complete text response
object?:
InferSchemaOutput<OUTPUT>
Structured output if schema was provided
toolCalls:
ToolCallChunk[]
All tool call chunks made
toolResults:
ToolResultChunk[]
All tool result chunks
usage:
Record<string, number>
Token usage statistics
reasoning?:
string
Reasoning text if available
finishReason?:
string
Why generation finished
consumeStream:
(options?: ConsumeStreamOptions) => Promise<void>
Manually consume the entire stream without processing chunks. Useful when you only need the final promise-based results and want to trigger stream consumption.
ConsumeStreamOptions
onError?:
(error: Error) => void
Callback for handling stream errors
Usage Examples
Basic Text Streaming
const stream = await agent.stream("Write a haiku");
// Stream text as it's generated
for await (const text of stream.textStream) {
process.stdout.write(text);
}
// Or get the complete text
const fullText = await stream.text;
console.log(fullText);Structured Output Streaming
const stream = await agent.stream("Generate user data", {
output: z.object({
name: z.string(),
age: z.number(),
email: z.string()
})
});
// Stream partial objects
for await (const partial of stream.objectStream) {
console.log("Progress:", partial); // { name: "John" }, { name: "John", age: 30 }, ...
}
// Get final validated object
const user = await stream.object;
console.log("Final:", user); // { name: "John", age: 30, email: "john@example.com" }Tool Calls and Results
const stream = await agent.stream("What's the weather in NYC?", {
tools: { weather: weatherTool }
});
// Monitor tool calls
const toolCalls = await stream.toolCalls;
const toolResults = await stream.toolResults;
console.log("Tools called:", toolCalls);
console.log("Results:", toolResults);Complete Output Access
const stream = await agent.stream("Analyze this data");
const output = await stream.getFullOutput();
console.log({
text: output.text,
usage: output.usage,
reasoning: output.reasoning,
finishReason: output.finishReason
});Full Stream Processing
const stream = await agent.stream("Complex task");
for await (const chunk of stream.fullStream) {
switch (chunk.type) {
case 'text-delta':
process.stdout.write(chunk.payload.text);
break;
case 'tool-call':
console.log(`Calling ${chunk.payload.toolName}...`);
break;
case 'reasoning-delta':
console.log(`Reasoning: ${chunk.payload.text}`);
break;
case 'finish':
console.log(`Done! Reason: ${chunk.payload.stepResult.reason}`);
break;
}
}Error Handling
const stream = await agent.stream("Analyze this data");
try {
// Option 1: Handle errors in consumeStream
await stream.consumeStream({
onError: (error) => {
console.error("Stream error:", error);
}
});
const result = await stream.text;
} catch (error) {
console.error("Failed to get result:", error);
}
// Option 2: Check error property
const result = await stream.getFullOutput();
if (stream.error) {
console.error("Stream had errors:", stream.error);
}