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    Interface IAutoBeRpcService

    Interface representing the WebSocket RPC service provided by the vibe coding server to client applications.

    This interface defines the remote procedure call functions that client applications can invoke on the vibe coding server through WebSocket connections. The service enables interactive conversation-driven development where users can communicate requirements through multiple modalities and receive comprehensive development artifacts as responses.

    In TGrid's RPC paradigm, this service acts as the Provider that the server exposes to clients, allowing remote function calls that drive the entire vibe coding pipeline from requirements gathering through final implementation. Client applications obtain a Driver<IAutoBeRpcService> instance to call these functions remotely while receiving real-time progress events through the IAutoBeRpcListener.

    Samchon

    interface IAutoBeRpcService {
        conversate(
            content: string | AutoBeUserMessageContent | AutoBeUserMessageContent[],
        ): Promise<AutoBeHistory[]>;
        getFiles(
            options?: Partial<IAutoBeGetFilesOptions>,
        ): Promise<Record<string, string>>;
        getHistories(): Promise<AutoBeHistory[]>;
        getTokenUsage(): Promise<IAutoBeTokenUsageJson>;
    }

    Implemented by

    Index

    Methods

    conversate getFiles getHistories getTokenUsage

    Methods

    • Initiates or continues conversation with the vibe coding AI assistant.

      Accepts user input in various formats including simple text, single content items, or arrays of multimodal content (text, images, files, audio). The conversation drives the entire vibe coding process, with the AI assistant analyzing requirements, making decisions about which development phases to execute, and coordinating the automated development pipeline.

      This function returns the complete history of events generated during the conversation turn, allowing clients to access both the conversation flow and any development artifacts produced. Real-time progress events are delivered separately through the IAutoBeRpcListener interface for responsive user experience.

      Parameters

      Returns Promise<AutoBeHistory[]>

      Promise resolving to array of history records representing all events and artifacts generated during this conversation turn

    • Retrieves all generated files from the current development session.

      Transforms the complete conversation-driven development process into a comprehensive collection of deployable artifacts, including requirements documentation, database schemas, API specifications, NestJS implementation code, and test suites. The generated files represent a fully functional backend application ready for immediate deployment or further customization.

      The method produces a meticulously organized project structure that reflects professional software development standards. Requirements analysis documents capture and formalize your conversational input into structured technical specifications, providing clear traceability from user intent to final implementation. Database artifacts include Prisma schemas with precise type definitions, relationships, and constraints, along with migration files for proper database initialization and evolution.

      The API layer emerges through comprehensive OpenAPI specifications documenting every endpoint, request format, response structure, and error condition. Generated NestJS controllers, DTOs, and service classes implement these specifications with TypeScript's strong typing system providing compile-time safety. Quality assurance is embedded throughout with complete test suites covering both unit and end-to-end scenarios.

      The database configuration specified through the dbms option fundamentally shapes the entire generated codebase. PostgreSQL configuration produces production-ready code with robust connection pooling and enterprise-grade optimizations, while SQLite generates lightweight code perfect for local development and rapid prototyping without external dependencies.

      All artifacts maintain perfect consistency across the chosen database system, from Prisma configurations and connection strings to Docker compose files and environment templates. This deep integration ensures immediate deployment compatibility without manual configuration adjustments.

      Parameters

      • Optionaloptions: Partial<IAutoBeGetFilesOptions>

        Configuration specifying the target database management system and other code generation preferences that influence the structure and characteristics of the generated project files

      Returns Promise<Record<string, string>>

      Promise resolving to key-value pairs mapping logical file paths to complete file contents for all generated development artifacts, ready for immediate file system operations, build integration, or deployment workflows

    • Retrieves the complete conversation and development history.

      Returns the full chronological record of all events that occurred during the vibe coding session including user messages, assistant responses, development phase activities, and completion events. This comprehensive history enables conversation replay, progress analysis, and understanding of the development decision-making process.

      The history includes both message-level interactions and development-level events, providing complete transparency into how user requirements were transformed into working software through the vibe coding pipeline.

      Returns Promise<AutoBeHistory[]>

      Promise resolving to chronologically ordered array of all history records from the current session

    • Retrieves comprehensive token usage statistics for the current session.

      Returns detailed breakdown of AI token consumption across all agents and processing phases, enabling cost monitoring, performance analysis, and optimization of AI resource utilization. The statistics include both aggregate totals and component-specific breakdowns with input/output categorization and caching analysis.

      Token usage data is essential for understanding the computational costs of the vibe coding process and optimizing AI efficiency while maintaining high-quality output across requirements analysis, database design, API specification, testing, and implementation phases.

      Returns Promise<IAutoBeTokenUsageJson>

      Promise resolving to comprehensive token usage statistics with detailed breakdowns by agent, operation type, and usage category

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