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    Type Alias WorkflowExecutorEmbedOptions

    WorkflowExecutorEmbedOptions: Omit<WorkflowExecutorTuningOptions, "loggerLevel"> & {
        agentUrl?: string;
        ai?: { apiKey: string; model: string; provider: "anthropic" | "openai" };
        database?: { uri?: string; [option: string]: unknown };
        encryptionKey?: string;
        inMemory?: boolean;
        port?: number;
    }

    Options for an embedded workflow executor, started in the same process as the agent through agent.addWorkflowExecutor().

    Type Declaration

    • OptionalagentUrl?: string

      URL the executor uses to reach this agent's data layer. Auto-derived when the agent runs on its own server (mountOnStandaloneServer). Required when the agent is mounted on an external framework (Express/Fastify/NestJS), since the agent cannot know the host application's address.

    • Optionalai?: { apiKey: string; model: string; provider: "anthropic" | "openai" }

      Bring your own AI provider instead of Forest's AI server. All three fields are required together; omit ai entirely to keep using Forest's server.

    • Optionaldatabase?: { uri?: string; [option: string]: unknown }

      Database connection used to persist workflow run state. Accepts a connection URI or a Sequelize options object. The agent throws at startup if it is omitted (unless inMemory is set).

    • OptionalencryptionKey?: string

      HKDF secret encrypting OAuth-protected MCP connector credentials at rest. Only needed if you use OAuth-protected MCP connectors; without it their credential deposits return 503. Embed-time equivalent of the standalone FOREST_EXECUTOR_ENCRYPTION_KEY env var.

    • OptionalinMemory?: boolean

      Use an in-memory run store instead of a database. No database is required, but runs are lost when the process restarts, so it is not meant for production. Mutually exclusive with database.

    • Optionalport?: number

      Loopback port the embedded executor listens on; the agent proxies to it internally. Defaults to 3400.