offercontext/offerPilot
开源、本地优先的求职 Agent:管理投递、准备面试与整理 Offer;附 Agent Loop、Harness 源码导读和动手实验。
What it solves
求职过程往往分散在多个工具和平台中,投递、简历、面试和Offer信息难以统一管理。OfferPilot将这一切整合到一个本地优先的工作台中,并借助AI Agent辅助查询信息、起草内容、提醒事项,同时要求关键修改必须经过用户确认,避免AI擅自改动重要记录。它不自动投递简历或联系招聘方,把决策权始终留在用户手中。
How it works
- 用户先记录公司、岗位、阶段等投递信息,AI为可选功能,基础记录无需配置模型。
- 配置自己的模型服务后,内置Pilot Agent可以结合已保存的求职资料,通过工具调用查询投递情况、生成面试安排或起草材料,并生成确认卡供用户核对。用户确认后,程序才真正写入数据,随后还会在日历等模块中验证是否保存正确。
- 提供投递看板、简历管理、模拟面试、Offer对比等模块,以及实验性的求职邮件助手(需用户手动启用和输入授权码)。
- 本地优先:业务数据保存在本地(Windows桌面版为%APPDATA%\OfferPilot Desktop\data,源码版为~/.offerpilot,Docker使用数据卷)。使用AI时,相关资料会发送到用户配置的模型服务,可能产生服务商费用。
- 同时附带学习材料,包括图解、小实验和源码导读,展示Agent如何实现工具调用、上下文管理、写入确认和取消恢复。
Who it's for
- 求职者:希望集中管理投递、准备面试、对比Offer,并愿意使用AI辅助但保留最终控制权的人。
- AI builder:想研究Agent如何结合工具调用和人工确认机制的人,项目提供了从概念到源码的完整学习路径。
Highlights
- 本地优先,数据保存在用户设备,不乱发消息或自动投递。
- 关键求职记录的修改默认需要用户确认,有明确的确认卡机制。
- Pilot Agent结合资料查询、起草和工具调用,并支持取消、恢复和运行记录。
- 实验性的邮件助手需要手动启用,授权码仅存于系统凭据库。
- 附有学习路线和实验,可拆解Agent实现细节。
- AGPLv3开源,Live2D角色和离线Whisper组件遵循各自的许可证。
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