Core Viewpoint - The company has launched two core open-source products, Coze Studio and Coze Loop, as part of its AI Agent development platform, aiming to enhance developer engagement and competition in the open-source space [4][6][39]. Group 1: Product Launch and Features - The open-source products have collectively garnered 9.5K stars on GitHub, indicating significant interest in the AI agent development field [7]. - Coze Studio is a no-code development platform that allows users to create functional AI agents through a visual interface, making it accessible even for those without coding skills [10][11]. - Coze Loop serves as a comprehensive lifecycle management tool for AI agents, facilitating development, evaluation, observation, and optimization [28][34]. Group 2: Technical Architecture and Performance - The platform's backend is built on Golang, while the frontend utilizes React and TypeScript, ensuring a robust and efficient architecture [19][21]. - The microservices architecture allows for clear responsibilities and modular development, enhancing maintainability and collaboration within the open-source community [22]. - The platform supports containerized deployment, simplifying the setup process for developers [23]. Group 3: Open Source Strategy and Community Engagement - The decision to open-source these products under the Apache 2.0 license reflects the company's commitment to fostering a developer-friendly ecosystem, allowing for commercial use without licensing fees [43][45]. - By opening up its technology, the company aims to attract a larger developer community to contribute to the ecosystem, enhancing product evolution through collaborative efforts [54][55]. - The open-source initiative is seen as a strategic move to establish a new standard in the AI agent development space, positioning the company as a leader in this emerging market [44][58].

Core Viewpoint - The year 2025 is anticipated to be a breakthrough year for Agents, significantly enhancing the capabilities of large models and transforming human-computer interaction across various platforms, particularly in multi-task automation [1]. Group 1: Agent Development and Platforms - The emergence of the first general-purpose Agent product, Manus, has garnered unprecedented attention, with major internet companies and startups focusing on Agents as a key area of AI competition [2]. - At the recent Force 2025 conference, Agents were highlighted alongside the latest version of the Doubao large model series [3]. - The conference's main forum showcased a new paradigm for AI cloud-native Agent development, emphasizing how Agents can reshape productivity [4]. - The Doubao platform has evolved into a "full lifecycle platform," addressing diverse development and tuning needs for Agents in the era of large models [5]. Group 2: Doubao Platform Features - The Doubao development platform enables low-code Agent development, allowing users with no coding experience to quickly build and deploy Agents across various channels [8]. - The platform empowers Agent development through four main aspects: intelligent IDE, application IDE, a rich set of plugins and workflow templates, and enterprise-level security capabilities [9]. - The application IDE, set to launch in 2024, will allow developers to create GUI-based applications using drag-and-drop features [10]. - Pre-configured Agent templates facilitate rapid deployment of functional Agents, such as smart customer service assistants and educational assistants [12]. Group 3: Eino Framework - Eino, a Go language-based LLM application development framework, draws inspiration from open-source communities and emphasizes simplicity, scalability, reliability, and effectiveness [13]. - Eino standardizes core modules for Agent development, enabling seamless integration with both open-source and closed-source models [14]. - The framework supports flexible orchestration capabilities for complex task decomposition and multi-tool collaboration [15]. - Over 300 systems have been developed internally at ByteDance using Eino, with a GitHub star count of 4.3k, indicating growing interest among developers [16]. Group 4: Agent Lifecycle Management - The Doubao platform establishes a comprehensive Agent lifecycle system encompassing development, evaluation, online observation, and optimization [16]. - The evaluation phase includes quantifying Agent performance to ensure it meets standards, while the observation phase involves real-time data collection and analysis [19]. - Developers can analyze user queries and behavior to adjust Agent performance, identifying and addressing issues through a robust observation system [20]. - The platform supports flexible evaluation set management, allowing developers to create and manage evaluation sets easily [22]. Group 5: Doubao Space - Doubao Space, launched in April, serves as a collaborative platform for high-quality Agents, facilitating efficient task resolution through expert collaboration [25]. - Users can leverage Doubao Space for market analysis, academic guidance, and expert support, with capabilities continuously expanded through the MCP protocol [26]. - The Doubao platform is expected to become foundational infrastructure for Agent development in the era of large models [27].

| 组件名 | 组件功能 | | --- | --- | | ChatModel | 与大模型交互，输入 Message 上下文,得到模型的输出 Message | | Tool | 与世界交互，根据模型的输出，执行对应的动作 | | Retriever | 获取相关的上下文，让模型的输出基于高质量的事实 | | ChatTemplate | 接收外界输入，转化成预设格式的 prompt 交给模型 | | Document Loader | 加载指定的文本 | | Document Transformer | 按照特定规则转化指定的文本 | | Indexer | 存储文件并建立索引，供后续 Retriever 使用 | | Embedding | Retriever 和 Indexer 的共同依赖,文本转向量,捕获文本语义 | | Lambda | 用户定制 function | 二、Eino框架的三大核心优势 （一）灵活的编排能力 Eino框架的编排能力是其亮点之一。 开发者可通过简单代码将不同组件按业务逻辑编排，形成复杂业务流程。 框架提供Chain（线性编排）和Graph（图结构 编排）等工具，满足不 ...