为 Agent 构建全新的上下文基础设施

近日,通义办公正式开源全新上下文基础设施「MyContext」。

它将散落各处、格式多样的个人工作数据,加工成 Agent 更易理解的专属工作档案,让 Agent 真正读懂用户和真实的业务工作流,在决策与执行过程中实现高效的人机协作,显著优化在办公场景中的表现。

项目上线仅一周,已在 GitHub 收获超过 1,000 个 Star,人气持续攀升。

让 Agent 真正读懂用户和真实业务工作流

为何需要上下文基础设施

随着模型能力快速提升和 Agent Harness 架构的迭代,通用 Agent 的办公能力日趋成熟,显著提升了个人效率。然而,由于缺乏真实工作环境的上下文,这类 Agent 难以融入实际业务流程,限制了组织生产力的提升。MIT 发布的 NANDA 报告指出,大约 95% 的企业级生成式 AI 试点项目未能产生实际收益,核心原因正是缺少数据基础设施,导致 AI 系统无法融入现有工作流。

一份持续更新的工作档案

与传统知识库或向量数据库不同,MyContext 以本地化方式运行在用户设备上,能够自动汇聚来自即时通讯、文档、会议记录、协作平台以及线上线下多源数据,沉淀为一份持续更新的个人工作档案。该档案涵盖职责范围、协作关系、行为习惯和工作讨论结论,使 Agent 在执行任务时可快速查询并进行推理。每条数据均可追溯至原始出处,明确标注来源、时间和内容,过程透明,有助于缓解 AI 幻觉问题,大幅提升任务执行的准确率。

MyContext 背后的技术新思维

通义办公在处理时间序列数据与矛盾数据等关键任务时,采用了创新的算法与工程设计。例如,针对 IM 中前后矛盾的信息,传统方法通常采用“取最新”或“取置信度最高”,但这两种方式在 Agent 场景下容易造成信息丢失。MyContext 在检测到冲突时,会先进行语义分析,判断应合并还是覆盖;若无法自动判断,则交由用户确认。一旦经用户确认,模型便不可再覆盖,从而极大保障了数据的有效性与一致性。

企业上下文时代即将来临

MyContext 目前支持处理个人钉钉、飞书等同类 IM 系统数据。用户导入数据后,即可构建专属 Agent 助手,该助手能基于用户知识总结,以用户的语气自动回复工作消息。未来,团队还将推出企业版上下文基础设施,全面支持 Salesforce、SAP 等主流企业系统和本地工作流,推动企业上下文时代的到来,助力组织整体生产力跃升。

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