@mastra/core/dist/chunk-XAL3MXVP.cjs.map

Mastra is a framework for building AI-powered applications and agents with a modern TypeScript stack.

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{ ToolLoopAgent } from '@internal/ai-v6';\nimport type { ToolLoopAgentSettings } from '@internal/ai-v6';\n\n/**\n * Shape of a ToolLoopAgent-like object for runtime extraction.\n * We use this looser type because TypeScript's structural typing doesn't work\n * well with private properties across different package declarations.\n */\nexport interface ToolLoopAgentLike {\n  readonly id?: string;\n  readonly version?: string;\n  // The settings property is private in ToolLoopAgent but accessible at runtime\n  // We don't declare it here since we access it via type casting\n}\n\nexport function isToolLoopAgentLike(obj: any): obj is ToolLoopAgentLike {\n  if (!obj) return false;\n  if (obj instanceof ToolLoopAgent) return true;\n  return (\n    'version' in obj &&\n    typeof obj.version === 'string' &&\n    (obj.version === 'agent-v1' || obj.version.startsWith('agent-v'))\n  );\n}\n\n/**\n * Extracts the settings from a ToolLoopAgent instance.\n * ToolLoopAgent.settings is private in TypeScript but accessible at runtime.\n */\nexport function getSettings(agent: ToolLoopAgentLike): ToolLoopAgentSettings<any, any, any> {\n  const settings = (agent as unknown as { settings: ToolLoopAgentSettings<any, any, any> }).settings;\n  if (!settings) {\n    throw new Error('Could not extract settings from ToolLoopAgent. The agent may be from an incompatible version.');\n  }\n  return settings;\n}\n","import type {\n  ToolLoopAgent,\n  AgentCallParameters,\n  ModelMessage,\n  StepResult,\n  ToolLoopAgentSettings,\n} from '@internal/ai-v6';\nimport { isSupportedLanguageModel } from '../agent';\nimport type { AgentExecutionOptions, AgentInstructions } from '../agent';\nimport { resolveModelConfig } from '../llm/model/resolve-model';\nimport type { MastraLanguageModel } from '../llm/model/shared.types';\nimport type { ProcessInputStepArgs, ProcessInputStepResult, Processor } from '../processors';\nimport { getSettings as getToolLoopAgentSettings } from './utils';\nimport type { ToolLoopAgentLike } from './utils';\n\ntype PrepareCallInput = AgentCallParameters<never> &\n  Pick<\n    ToolLoopAgentSettings<never, any, any>,\n    | 'model'\n    | 'tools'\n    | 'maxOutputTokens'\n    | 'temperature'\n    | 'topP'\n    | 'topK'\n    | 'presencePenalty'\n    | 'frequencyPenalty'\n    | 'stopSequences'\n    | 'seed'\n    | 'headers'\n    | 'instructions'\n    | 'stopWhen'\n    | 'experimental_telemetry'\n    | 'activeTools'\n    | 'providerOptions'\n    | 'experimental_context'\n    | 'experimental_download'\n  >;\n\nexport class ToolLoopAgentProcessor implements Processor<'tool-loop-agent-processor'> {\n  readonly id = 'tool-loop-agent-processor';\n  readonly name = 'ToolLoop to Mastra Agent Processor';\n\n  private agent: ToolLoopAgentLike;\n  private settings: ToolLoopAgentSettings<any, any, any>;\n  private prepareCallResult?: Awaited<ReturnType<NonNullable<ToolLoopAgentSettings<any, any, any>['prepareCall']>>>;\n\n  constructor(agent: ToolLoopAgentLike) {\n    this.agent = agent;\n    this.settings = getToolLoopAgentSettings(agent);\n  }\n\n  public getAgentConfig() {\n    const tools = 'tools' in this.agent ? (this.agent as ToolLoopAgent).tools : undefined;\n\n    // Build default options from ToolLoopAgent config params\n    const defaultOptions: Omit<AgentExecutionOptions<unknown>, 'abortSignal'> = {};\n\n    // AgentExecutionOptions\n    if (this.settings.toolChoice) {\n      defaultOptions.toolChoice = this.settings.toolChoice;\n    }\n    if (this.settings.providerOptions) {\n      defaultOptions.providerOptions = this.settings.providerOptions;\n    }\n    // AgentExecutionOptions[\"modelSettings\"]\n    if (this.settings.temperature !== undefined) {\n      defaultOptions.modelSettings = {\n        ...(defaultOptions.modelSettings ?? {}),\n        temperature: this.settings.temperature,\n      };\n    }\n    if (this.settings.topP !== undefined) {\n      defaultOptions.modelSettings = { ...(defaultOptions.modelSettings ?? {}), topP: this.settings.topP };\n    }\n    if (this.settings.topK !== undefined) {\n      defaultOptions.modelSettings = { ...(defaultOptions.modelSettings ?? {}), topK: this.settings.topK };\n    }\n    if (this.settings.seed !== undefined) {\n      defaultOptions.modelSettings = { ...(defaultOptions.modelSettings ?? {}), seed: this.settings.seed };\n    }\n    if (this.settings.maxOutputTokens !== undefined) {\n      defaultOptions.modelSettings = {\n        ...(defaultOptions.modelSettings ?? {}),\n        maxOutputTokens: this.settings.maxOutputTokens,\n      };\n    }\n    if (this.settings.presencePenalty !== undefined) {\n      defaultOptions.modelSettings = {\n        ...(defaultOptions.modelSettings ?? {}),\n        presencePenalty: this.settings.presencePenalty,\n      };\n    }\n    if (this.settings.frequencyPenalty !== undefined) {\n      defaultOptions.modelSettings = {\n        ...(defaultOptions.modelSettings ?? {}),\n        frequencyPenalty: this.settings.frequencyPenalty,\n      };\n    }\n    if (this.settings.stopSequences !== undefined) {\n      defaultOptions.modelSettings = {\n        ...(defaultOptions.modelSettings ?? {}),\n        stopSequences: this.settings.stopSequences,\n      };\n    }\n    if (this.settings.stopWhen) {\n      // TODO: The callback signatures differ (Types of parameters stepResult and event are incompatible)\n      defaultOptions.stopWhen = this.settings.stopWhen as any;\n    }\n    if (this.settings.onStepFinish) {\n      // TODO: The callback signatures differ (Types of parameters stepResult and event are incompatible)\n      defaultOptions.onStepFinish = this.settings.onStepFinish as any;\n    }\n    if (this.settings.onFinish) {\n      // TODO: The callback signatures differ (Types of parameters 'event' and 'event' are incompatible)\n      defaultOptions.onFinish = this.settings.onFinish as any;\n    }\n\n    return {\n      id: this.settings.id,\n      name: this.settings.id,\n      instructions: (this.settings.instructions as AgentInstructions) ?? '',\n      model: this.settings.model,\n      tools,\n      maxRetries: this.settings.maxRetries,\n      defaultOptions: Object.keys(defaultOptions).length > 0 ? defaultOptions : undefined,\n    };\n  }\n\n  /**\n   * Maps prepareCall or prepareStep result to ProcessInputStepResult.\n   * Both hooks return similar structures that can override model, tools, activeTools, etc.\n   */\n  private mapToProcessInputStepResult(\n    result: Awaited<ReturnType<NonNullable<ToolLoopAgentSettings<any, any, any>['prepareCall']>>> | undefined,\n  ): ProcessInputStepResult {\n    if (!result) {\n      return {};\n    }\n\n    const stepResult: ProcessInputStepResult = {};\n\n    // Map model (both prepareCall and prepareStep can return this)\n    if (result.model) {\n      stepResult.model = result.model;\n    }\n\n    // Map tools (prepareCall can return this)\n    if ('tools' in result && result.tools) {\n      stepResult.tools = result.tools as Record<string, unknown>;\n    }\n\n    // Map toolChoice (prepareStep can return this)\n    if ('toolChoice' in result && result.toolChoice !== undefined) {\n      stepResult.toolChoice = result.toolChoice as ProcessInputStepResult['toolChoice'];\n    }\n\n    // Map activeTools (both can return this)\n    if (result.activeTools) {\n      stepResult.activeTools = result.activeTools as string[];\n    }\n\n    // Map providerOptions (prepareCall can return this)\n    if ('providerOptions' in result && result.providerOptions) {\n      stepResult.providerOptions = result.providerOptions;\n    }\n\n    // Map model settings (prepareCall can return individual settings)\n    const modelSettings: ProcessInputStepResult['modelSettings'] = {};\n    if ('temperature' in result && result.temperature !== undefined) {\n      modelSettings.temperature = result.temperature;\n    }\n    if ('topP' in result && result.topP !== undefined) {\n      modelSettings.topP = result.topP;\n    }\n    if ('topK' in result && result.topK !== undefined) {\n      modelSettings.topK = result.topK;\n    }\n    if ('maxOutputTokens' in result && result.maxOutputTokens !== undefined) {\n      modelSettings.maxOutputTokens = result.maxOutputTokens;\n    }\n    if ('presencePenalty' in result && result.presencePenalty !== undefined) {\n      modelSettings.presencePenalty = result.presencePenalty;\n    }\n    if ('frequencyPenalty' in result && result.frequencyPenalty !== undefined) {\n      modelSettings.frequencyPenalty = result.frequencyPenalty;\n    }\n    if ('stopSequences' in result && result.stopSequences !== undefined) {\n      modelSettings.stopSequences = result.stopSequences;\n    }\n    if ('seed' in result && result.seed !== undefined) {\n      modelSettings.seed = result.seed;\n    }\n\n    if (Object.keys(modelSettings).length > 0) {\n      stepResult.modelSettings = modelSettings;\n    }\n\n    // Map system/instructions to systemMessages\n    // prepareCall returns 'instructions', prepareStep returns 'system'\n    const systemContent =\n      'instructions' in result ? result.instructions : 'system' in result ? result.system : undefined;\n    if (systemContent) {\n      // Convert to CoreMessageV4 format\n      if (typeof systemContent === 'string') {\n        stepResult.systemMessages = [{ role: 'system', content: systemContent }];\n      } else if (Array.isArray(systemContent)) {\n        stepResult.systemMessages = systemContent.map(msg =>\n          typeof msg === 'string' ? { role: 'system' as const, content: msg } : msg,\n        );\n      } else if (typeof systemContent === 'object' && 'role' in systemContent && 'content' in systemContent) {\n        stepResult.systemMessages = [systemContent as { role: 'system'; content: string }];\n      }\n    }\n\n    // Map messages if prepareStep returns them\n    // Convert AI SDK ModelMessage[] to MastraDBMessage[]\n    if ('messages' in result && result.messages && Array.isArray(result.messages)) {\n      // AI SDK v6 ModelMessage is compatible with MessageListInput at runtime\n      // stepResult.messages = convertMessages(result.messages as any).to('Mastra.V2');\n      stepResult.messages = result.messages as any;\n    }\n\n    return stepResult;\n  }\n\n  private async handlePrepareCall(args: ProcessInputStepArgs) {\n    if (this.settings.prepareCall) {\n      const { model, messages, activeTools, providerOptions, modelSettings, tools } = args;\n      // TODO: This should probably happen in processInput, currently calling in processInputStep if stepNumber === 0\n\n      // Build the prepareCall input object\n      // AI SDK prepareCall expects: AgentCallParameters & Pick<ToolLoopAgentSettings, ...settings>\n      const prepareCallInput: PrepareCallInput = {\n        // TODO: prepareCall expects messages in AI SDK format, we have them in Mastra format\n        messages: messages as unknown as any,\n        model,\n        tools,\n        instructions: this.settings.instructions,\n        stopWhen: this.settings.stopWhen,\n        activeTools,\n        providerOptions,\n\n        // Model settings\n        temperature: modelSettings?.temperature,\n        topP: modelSettings?.topP,\n        topK: modelSettings?.topK,\n        maxOutputTokens: modelSettings?.maxOutputTokens,\n        presencePenalty: modelSettings?.presencePenalty,\n        frequencyPenalty: modelSettings?.frequencyPenalty,\n        stopSequences: modelSettings?.stopSequences,\n        seed: modelSettings?.seed,\n\n        // Experimental options\n        // experimental_telemetry: this.settings.experimental_telemetry,\n        // experimental_context: this.settings.experimental_context,\n        // experimental_download: this.settings.experimental_download,\n      };\n\n      // Call prepareCall and apply any returned overrides\n      const prepareCallResult = await this.settings.prepareCall(prepareCallInput as any); // TODO: types\n      this.prepareCallResult = prepareCallResult;\n    }\n  }\n\n  private async handlePrepareStep(args: ProcessInputStepArgs, currentResult: ProcessInputStepResult) {\n    if (this.settings.prepareStep) {\n      const { messages, steps, stepNumber } = args;\n\n      let model = args.model;\n      if (currentResult.model) {\n        const resolvedModel = await resolveModelConfig(currentResult.model);\n        if (!isSupportedLanguageModel(resolvedModel)) {\n          throw new Error('prepareStep returned an unsupported model version');\n        }\n        model = resolvedModel;\n      }\n\n      // Use the model from currentResult if prepareCall overrode it, otherwise use args.model\n\n      // Note: We pass messages and steps in Mastra format rather than converting to AI SDK format.\n      // This is intentional - most prepareStep callbacks only return overrides and don't inspect\n      // the message content. The type casts handle the format difference at runtime.\n      const prepareStepInputArgs: {\n        /**\n         * The steps that have been executed so far.\n         */\n        steps: Array<StepResult<NoInfer<any>>>;\n        /**\n         * The number of the step that is being executed.\n         */\n        stepNumber: number;\n        /**\n         * The model instance that is being used for this step.\n         */\n        model: MastraLanguageModel;\n        /**\n         * The messages that will be sent to the model for the current step.\n         * Note: These are in Mastra format (MastraDBMessage[]), not AI SDK ModelMessage format.\n         */\n        messages: Array<ModelMessage>;\n        /**\n         * The context passed via the experimental_context setting (experimental).\n         */\n        experimental_context: unknown;\n      } = {\n        model,\n        // Messages are in Mastra format (MastraDBMessage[])\n        messages: messages as any,\n        // Steps may have minor type differences in usage properties (inputTokenDetails/outputTokenDetails)\n        steps: steps as any,\n        stepNumber,\n        experimental_context: undefined,\n      };\n\n      const prepareStepResult = await this.settings.prepareStep(prepareStepInputArgs);\n      return prepareStepResult;\n    }\n  }\n\n  async processInputStep(args: ProcessInputStepArgs): Promise<ProcessInputStepResult | undefined | void> {\n    const { stepNumber } = args;\n\n    if (stepNumber === 0 && this.settings.prepareCall) {\n      await this.handlePrepareCall(args);\n    }\n\n    let result: ProcessInputStepResult = {};\n\n    // Apply prepareCall result (only on step 0, already called above)\n    if (this.prepareCallResult) {\n      const mappedResult = this.mapToProcessInputStepResult(this.prepareCallResult);\n      if (Object.keys(mappedResult).length > 0) {\n        result = { ...result, ...mappedResult };\n      }\n    }\n\n    // Apply prepareStep result (called on every step)\n    // Pass the current result so prepareStep sees any overrides from prepareCall\n    if (this.settings.prepareStep) {\n      const prepareStepResult = await this.handlePrepareStep(args, result);\n      if (prepareStepResult) {\n        const mappedResult = this.mapToProcessInputStepResult(prepareStepResult as any);\n        // prepareStep overrides prepareCall for this step\n        result = { ...result, ...mappedResult };\n      }\n    }\n\n    return result;\n  }\n}\n","import { generateId } from '@internal/ai-sdk-v5';\nimport { Agent } from '../agent';\nimport { ToolLoopAgentProcessor } from './tool-loop-processor';\nimport type { ToolLoopAgentLike } from './utils';\nexport { type ToolLoopAgentLike, isToolLoopAgentLike, getSettings } from './utils';\n\n/**\n * Converts an AI SDK v6 ToolLoopAgent instance into a Mastra Agent.\n *\n * This enables users to create a ToolLoopAgent using AI SDK's API\n * while gaining access to Mastra features like memory, processors, scorers, and observability.\n *\n * @example\n * ```typescript\n * import { ToolLoopAgent, tool } from 'ai';\n * import { openai } from '@ai-sdk/openai';\n * import { toolLoopAgentToMastraAgent } from '@mastra/core/tool-loop-agent';\n *\n * const toolLoopAgent = new ToolLoopAgent({\n *   id: 'weather-agent',\n *   model: openai('gpt-4o'),\n *   instructions: 'You are a helpful weather assistant.',\n *   tools: { weather: weatherTool },\n *   temperature: 0.7,\n * });\n *\n * const mastraAgent = toolLoopAgentToMastraAgent(toolLoopAgent);\n *\n * const result = await mastraAgent.generate({ prompt: 'What is the weather in NYC?' });\n * ```\n *\n * @param agent - The ToolLoopAgent instance\n * @param options - Optional name fallback since Mastra Agent requires id/name but ToolLoopAgent doesn't\n * @returns A Mastra Agent instance\n */\nexport function toolLoopAgentToMastraAgent(agent: ToolLoopAgentLike, options?: { fallbackName?: string }) {\n  const processor = new ToolLoopAgentProcessor(agent);\n  const agentConfig = processor.getAgentConfig();\n  const id = agentConfig.id || options?.fallbackName || `tool-loop-agent-${generateId()}`;\n\n  return new Agent({\n    ...agentConfig,\n    id,\n    name: agentConfig.name || id,\n    inputProcessors: [processor],\n  });\n}\n"]}