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ReferenceAgents.generate()

Agent.generate()

The .generate() method is used to interact with an agent to produce text or structured responses. This method accepts messages and optional generation options.

Usage example

await agent.generate("message for agent");

Parameters

messages:

string | string[] | CoreMessage[] | AiMessageType[] | UIMessageWithMetadata[]
The messages to send to the agent. Can be a single string, array of strings, or structured message objects with multimodal content (text, images, etc.).

options?:

AgentGenerateOptions
Optional configuration for the generation process.

Options parameters

abortSignal?:

AbortSignal
Signal object that allows you to abort the agent's execution. When the signal is aborted, all ongoing operations will be terminated.

context?:

CoreMessage[]
Additional context messages to provide to the agent.

experimental_output?:

Zod schema | JsonSchema7
Enables structured output generation alongside text generation and tool calls. The model will generate responses that conform to the provided schema.

instructions?:

string
Custom instructions that override the agent's default instructions for this specific generation. Useful for dynamically modifying agent behavior without creating a new agent instance.

output?:

Zod schema | JsonSchema7
Defines the expected structure of the output. Can be a JSON Schema object or a Zod schema.

memory?:

object
Configuration for memory. This is the preferred way to manage memory.

thread:

string | { id: string; metadata?: Record<string, any>, title?: string }
The conversation thread, as a string ID or an object with an `id` and optional `metadata`.

resource:

string
Identifier for the user or resource associated with the thread.

options?:

MemoryConfig
Configuration for memory behavior, like message history and semantic recall. See `MemoryConfig` below.

maxSteps?:

number
= 5
Maximum number of execution steps allowed.

maxRetries?:

number
= 2
Maximum number of retries. Set to 0 to disable retries.

onStepFinish?:

GenerateTextOnStepFinishCallback<any> | never
Callback function called after each execution step. Receives step details as a JSON string. Unavailable for structured output

runId?:

string
Unique ID for this generation run. Useful for tracking and debugging purposes.

telemetry?:

TelemetrySettings
Settings for telemetry collection during generation.

isEnabled?:

boolean
Enable or disable telemetry. Disabled by default while experimental.

recordInputs?:

boolean
Enable or disable input recording. Enabled by default. You might want to disable input recording to avoid recording sensitive information.

recordOutputs?:

boolean
Enable or disable output recording. Enabled by default. You might want to disable output recording to avoid recording sensitive information.

functionId?:

string
Identifier for this function. Used to group telemetry data by function.

temperature?:

number
Controls randomness in the model's output. Higher values (e.g., 0.8) make the output more random, lower values (e.g., 0.2) make it more focused and deterministic.

toolChoice?:

'auto' | 'none' | 'required' | { type: 'tool'; toolName: string }
= 'auto'
Controls how the agent uses tools during generation.

'auto':

string
Let the model decide whether to use tools (default).

'none':

string
Do not use any tools.

'required':

string
Require the model to use at least one tool.

{ type: 'tool'; toolName: string }:

object
Require the model to use a specific tool by name.

toolsets?:

ToolsetsInput
Additional toolsets to make available to the agent during generation.

clientTools?:

ToolsInput
Tools that are executed on the 'client' side of the request. These tools do not have execute functions in the definition.

savePerStep?:

boolean
Save messages incrementally after each stream step completes (default: false).

providerOptions?:

Record<string, Record<string, JSONValue>>
Additional provider-specific options that are passed through to the underlying LLM provider. The structure is `{ providerName: { optionKey: value } }`. Since Mastra extends AI SDK, see the [AI SDK documentation](https://sdk.vercel.ai/docs/providers/ai-sdk-providers) for complete provider options.

openai?:

Record<string, JSONValue>
OpenAI-specific options. Example: `{ reasoningEffort: 'high' }`

anthropic?:

Record<string, JSONValue>
Anthropic-specific options. Example: `{ maxTokens: 1000 }`

google?:

Record<string, JSONValue>
Google-specific options. Example: `{ safetySettings: [...] }`

[providerName]?:

Record<string, JSONValue>
Other provider-specific options. The key is the provider name and the value is a record of provider-specific options.

runtimeContext?:

RuntimeContext
Runtime context for dependency injection and contextual information.

maxTokens?:

number
Maximum number of tokens to generate.

topP?:

number
Nucleus sampling. This is a number between 0 and 1. It is recommended to set either `temperature` or `topP`, but not both.

topK?:

number
Only sample from the top K options for each subsequent token. Used to remove 'long tail' low probability responses.

presencePenalty?:

number
Presence penalty setting. It affects the likelihood of the model to repeat information that is already in the prompt. A number between -1 (increase repetition) and 1 (maximum penalty, decrease repetition).

frequencyPenalty?:

number
Frequency penalty setting. It affects the likelihood of the model to repeatedly use the same words or phrases. A number between -1 (increase repetition) and 1 (maximum penalty, decrease repetition).

stopSequences?:

string[]
Stop sequences. If set, the model will stop generating text when one of the stop sequences is generated.

seed?:

number
The seed (integer) to use for random sampling. If set and supported by the model, calls will generate deterministic results.

headers?:

Record<string, string | undefined>
Additional HTTP headers to be sent with the request. Only applicable for HTTP-based providers.

Returns

text?:

string
The generated text response. Present when output is 'text' (no schema provided).

object?:

object
The generated structured response. Present when a schema is provided via `output` or `experimental_output`.

toolCalls?:

Array<ToolCall>
The tool calls made during the generation process. Present in both text and object modes.

toolName:

string
The name of the tool invoked.

args:

any
The arguments passed to the tool.

Extended usage example

await agent.generate(
  [
    { role: "user", content: "message for agent" },
    {
      role: "user",
      content: [
        {
          type: "text",
          text: "message for agent"
        },
        {
          type: "image",
          imageUrl: "https://example.com/image.jpg",
          mimeType: "image/jpeg"
        }
      ]
    }
  ],
  {
    temperature: 0.7,
    maxSteps: 3,
    memory: {
      thread: "user-123",
      resource: "test-app"
    },
    toolChoice: "auto",
    providerOptions: {
      openai: {
        reasoningEffort: "high"
      }
    }
  }
);
.getAgent().stream()