diff --git a/README.en.md b/README.en.md index d89345d3..4eb670e2 100644 --- a/README.en.md +++ b/README.en.md @@ -1,23 +1,43 @@ -# OfferPilot — Open-source AI Job Application Tracker +# OfferPilot — An Open-source, Local-first Job-search Agent [简体中文](README.md) | [English](README.en.md) -OfferPilot by offercontext is a local-first workspace for individual -job seekers. Keep applications, resumes, interviews and offers together, -with optional AI assistance for preparation and review. +**Prepare for your next interview—and explore how an agent gets things done.** -## Features +OfferPilot by offercontext brings applications, resumes, interviews and offers into one workspace. +Its built-in Pilot agent uses your saved job-search materials to find information, draft content and call tools. +Changes to important job-search records require your confirmation by default. It does not automatically apply for jobs or contact recruiters. -| Feature | Purpose | -| --- | --- | -| Application tracking | Organize companies, roles, application stages and interview schedules | -| Resume management | Maintain resume versions and review job-specific material suggestions | -| Mock interviews | Practice with your resume and job description, then review feedback | -| Interview reviews | Record lessons and select priorities for further practice | -| Offer comparison | Compare compensation, benefits and response deadlines | -| Salary negotiation preparation | Prepare questions and communication drafts | +For AI builders, the same project offers illustrated scenarios, small experiments and source walkthroughs +covering tool use, context, write approval and execution control. + +[Windows unsigned test build](https://github.com/offercontext/offerPilot/releases/tag/v0.1.0-desktop.1) · [Docker / source setup](#getting-started) · [Explore the agent](#use-it-and-learn-how-it-works) · [User guide (Chinese)](docs/product-manual/产品说明书.md) + +The Windows installer is an experimental prerelease; read the [test-build limitations](#getting-started) before installing. +Basic application tracking does not need AI. AI features use your configured model service and may send relevant data off-device and incur provider fees. +This English README does not imply that every product screen or tutorial is available in English. + +## Watch an interview become a saved record + +These screenshots come from a real operation captured on October 8, 2026, using a real model and isolated fictional data +at source revision `c0a447bb`. They are not a full acceptance test of the current Windows release. +The company, role and date are demonstration data, not a pending task. -New to AI agents? Start with [how an interview gets recorded](docs/learn/01-record-an-interview.md), or browse the [learning path](docs/learn/README.md). These tutorials are in Chinese and require no coding or installation to read. +The request was to add an online, 60-minute interview for the fictional Yunlan Data test-development role, +starting at 15:00 Beijing time (UTC+8) on October 15, 2026. + +**Find the application → propose the details → you review and confirm → save → verify the calendar record.** + +1. Pilot uses a tool to find the application and proposes an interview using the returned information. +2. The confirmation card shows what would be saved. No interview has been added yet. +3. After approval, the program saves the interview. The calendar lets you check the company, role and time. No notification was sent to a recruiter. + +![Actual confirmation card for the fictional interview: October 15, 15:00, online, 60 minutes; interface in Chinese](docs/learn/images/runtime-20261008/05-interview-pending.jpg) + +![Actual calendar record after confirmation: the same fictional interview, 15:00–16:00; interface in Chinese](docs/learn/images/runtime-20261008/08-calendar-verified.jpg) + +“Done” is not enough: check the saved record. +Read the [full walkthrough](docs/learn/01-record-an-interview.md) and [capture conditions and verification scope](docs/learn/images/runtime-20261008/README.md) (Chinese). ## Getting started @@ -43,15 +63,54 @@ and [user guide in Chinese](docs/product-manual/产品说明书.md). Basic application tracking does not require AI configuration. -## Privacy and limitations +## How it helps during your job search -Workspace data is stored locally. AI features send relevant materials -to your configured model service and may incur provider fees. +| Feature | Purpose | +| --- | --- | +| Pilot agent | Query saved information, draft content and use tools, with confirmation before important record changes | +| Application tracking | Organize companies, roles, stages and interview schedules | +| Resume and material preparation | Maintain resume versions and review job-specific suggestions | +| Mock interviews | Practice with your resume and job description, then review feedback | +| Interview reviews | Record lessons and choose priorities for further practice | +| Offer comparison and negotiation preparation | Compare known terms and deadlines, then prepare questions and drafts | + +See the [real interface screenshots](README.md#真实界面) and [user guide](docs/product-manual/产品说明书.md) (Chinese). +This repository describes the locally deployed edition. [offerContext Hub](https://hub.offercontext.cn) is a separate online service; +its features and data handling follow its own disclosures, and should not be assumed identical or connected. + +## Haru and Pilot + +Pilot is the built-in agent. Haru is an optional character entry point on wide desktop layouts. +You can hide Haru and keep using Pilot. Haru is an official Live2D sample character, not an original OfferPilot character; +see the [third-party notices](README.md#第三方角色与运行时). + +## Use it, and learn how it works + +You do not need to study agent engineering to use the workspace. AI builders can start with one concrete question: +**why should confirming the same interview twice still create only one record?** + +- **Understand:** follow [one interview being recorded](docs/learn/01-record-an-interview.md), then the [four-article short route](docs/learn/README.md). No installation or coding is required to read it. +- **Experiment:** try the [Python standard-library experiment](docs/learn/examples/README.md): zero records before confirmation, one after approval, still one after repeated confirmation. It uses a simulated model, needs no model key and does not evaluate real model quality. +- **Read the implementation:** explore the [Harness source walkthroughs](docs/learn/advanced/README.md), including the agent loop, context, approval, cancellation, recovery and validation. + +These learning materials are in Chinese and state their source revision and verification limits. +Reader trials have not yet been conducted; this is a reading and experimentation route, not a guarantee of mastering a complete system. + +## Contribute + +[Report an issue](https://github.com/offercontext/offerPilot/issues) or read the [contribution guide](CONTRIBUTING.md) +before proposing a change. Describe the goal, scope and checks you actually ran. + +## Privacy and limitations -OfferPilot does not automatically submit applications or message recruiters. -Review generated content before using it. +- Workspace data is stored locally. AI features send relevant materials to your configured model service and may incur provider fees. Local-first does not mean all AI processing stays on your device. +- Changes to important job-search records require confirmation by default. Review the confirmation card before proceeding. +- OfferPilot does not automatically submit applications or message recruiters. Review generated content, dates, numbers and commitments before using them. +- Interview recordings remain in the current page and are not uploaded or persisted. The optional offline Whisper model downloads to the browser cache only after you request it. +- AI can make mistakes. Decisions about applications, offers and negotiation remain yours. ## License -See [LICENSE](LICENSE) and the +[AGPLv3](LICENSE) covers the project, not the Live2D character, model data or runtime. +Haru and Cubism Core belong to Live2D Inc.; their separate terms and the offline speech-model notices are in the [third-party notices](README.md#许可证). diff --git a/README.md b/README.md index c1d004e3..8af9443b 100644 --- a/README.md +++ b/README.md @@ -1,75 +1,40 @@ -# OfferPilot — 开源、本地优先的 AI 求职与投递管理工具 +# OfferPilot — 开源、本地优先的求职 Agent [简体中文](README.md) | [English](README.en.md) -**集中管理投递进度、简历、面试与 Offer，让每一轮准备都有记录可查。** +**帮你准备下一场面试，也让你看懂 Agent 怎样把事情做成。** -OfferPilot 由 offercontext 维护，是面向个人求职者的开源 AI 求职工作台。 -你可以在本地管理不同公司和岗位的投递记录，整理简历与岗位描述， -进行模拟面试、保存复盘，并比较收到的 Offer。 +OfferPilot 由 offercontext 维护，把投递、简历、面试与 Offer 放进同一个工作台。 +内置 Pilot 结合你保存的求职资料查询信息、起草内容、调用工具，并在你确认后更新关键求职记录。 +它不会自动投递，也不会替你联系招聘方。 -**English:** OfferPilot by offercontext is an open-source, local-first -AI job application tracker for individual job seekers. It supports resume -management, interview preparation, mock interviews, interview reviews, -offer comparison and salary negotiation preparation. +想研究 Agent 的 AI builder，也可以从同一个求职场景出发，沿着图解、小实验与源码， +理解工具调用、上下文、写入确认和执行控制。 -提供 Windows x64 未签名桌面测试版，也支持 Docker 或源码方式在本机部署。基础投递记录无需先配置 AI； -使用 AI 辅助功能时，再连接自己的模型服务。 +[Windows 未签名测试版下载](https://github.com/offercontext/offerPilot/releases/tag/v0.1.0-desktop.1)｜[Docker / 源码启动](#快速开始)｜[看懂 Agent](#不仅能用也可以拆开学)｜[用户指南](docs/product-manual/产品说明书.md) -[Windows 测试版下载](https://github.com/offercontext/offerPilot/releases/tag/v0.1.0-desktop.1)｜[快速开始](#快速开始)｜[用户指南](docs/product-manual/产品说明书.md)｜[常见问题](#常见问题) +Windows 安装包为实验性预发行版，请先阅读下方[测试版边界](#快速开始)。基础投递记录无需配置 AI； +使用 AI 时需连接自己的模型服务，相关资料可能离开设备并产生服务商费用。 -第一次接触 Agent？先看[一场面试是怎么记下来的](docs/learn/01-record-an-interview.md)，无需写代码或安装项目。其他主题见[完整学习路线](docs/learn/README.md)。 +## 先看它怎样记下一场面试 -## 主要功能 +下面复用一次真实操作的素材：2026-10-08，在固定源码基线 `c0a447bb` 上使用隔离的虚构数据与真实模型采集， +不代表当前 Windows 测试版的完整验收。公司、岗位与日期均为演示案例，不是你的待办。 -| 功能 | 具体用途 | -| --- | --- | -| 投递管理 | 按公司、岗位和阶段跟进求职进度，关联岗位描述与面试安排 | -| 简历与材料准备 | 管理简历版本，结合岗位要求生成并审阅材料建议 | -| 面试准备与模拟 | 根据简历和岗位描述练习问答，查看 AI 追问与反馈 | -| 面试复盘 | 保存面试记录，选择并确认需要继续练习的重点 | -| Offer 对比与谈薪 | 比较已填写的薪酬、福利和答复期限，准备谈薪沟通 | -| Pilot AI 助手 | 结合求职资料查询、分析、起草内容或提出修改建议 | - -Pilot 是内置 AI 助手，Haru 是可选角色入口；隐藏 Haru 不影响使用 Pilot。 - -本仓库介绍本地部署版本。在线服务可访问 -[offerContext Hub](https://hub.offercontext.cn)； -其功能与数据处理方式以站内说明为准，不默认与本地版本一致或互通。 - -## 真实界面 - -以下为本地部署开发版的实际界面，截图更新于 2026 年 9 月。不同版本的功能与界面可能存在差异，截图对应版本见[用户指南](docs/product-manual/产品说明书.md)。 - -### 1. 跟进每个岗位的投递进度 - -在同一看板中查看公司、岗位与当前阶段，按待投递、已投递、笔试、面试、Offer 和结束整理进展。 - -![投递看板：按公司、岗位和阶段跟进](docs/product-manual/screenshots/R03-05-page-create-saved.png) - -### 2. 为目标岗位准备投递材料 +> 请为云岚数据的测试开发岗位新增面试日程：2026 年 10 月 15 日，北京时间下午 3 点（UTC+8），线上，时长 60 分钟。 -在投递详情中选择简历和本次使用的岗位描述（JD），进入材料工作区生成并审阅建议。确认后创建岗位简历版本，保留基础简历。 - -![投递准备：对照岗位与简历审阅 AI 生成的优化建议草稿](docs/product-manual/screenshots/04-03-material-generated.png) - -### 3. 结合求职资料使用 AI 助手 - -在同一个会话中查询投递进展、整理岗位资料或起草下一步计划，并对照右侧参考资料核对建议。 - -![完整 Pilot 页面：左侧会话列表、中间对话与新建投递确认卡、右侧参考资料及底部输入区](docs/product-manual/screenshots/R03-02-pilot-create-confirm.png) - -### 4. 面试前练习，面试后整理经验 - -从已安排的面试进入练习，或直接使用“快速模拟”，选择并核对本次岗位资料与简历后开始问答。独立练习不要求先创建真实投递或日程。 +**查询已有投递 → 提出保存建议 → 你核对并确认 → 程序保存 → 在日历核对结果。** -![新版文字模拟面试：沿用筱哲与远帆科技案例，查看中文提问依据并回答 AI 追问](docs/product-manual/screenshots/R08-studio-evidence.png) +1. Pilot 借助工具查找对应投递，结合返回资料提出面试安排。 +2. 确认卡展示准备保存的内容；此时尚未新增日程。 +3. 确认后，程序保存同一场面试，再到日历核对公司、岗位和时间。此次操作没有向招聘方发送通知。 -### 5. 比较 Offer 条件，准备谈薪 +![实际待确认卡：云岚数据测试开发、10 月 15 日 15:00、线上、60 分钟](docs/learn/images/runtime-20261008/05-interview-pending.jpg) -录入 Offer 后可以比较已知薪酬条件、补充自定义比较维度，并进入谈薪准备或谈薪教练，整理下一次沟通的重点。 +![实际保存后的日历：同一场云岚数据测试开发面试，15:00–16:00](docs/learn/images/runtime-20261008/08-calendar-verified.jpg) -![Offer 横向对比：查看等宽摘要卡片、年薪与回复时间差，并逐项核对薪酬、福利和截止日](docs/product-manual/screenshots/R08-offer-comparison-polished.png) +AI 说“记好了”还不够，记录要真正保存，内容也要核对正确。 +[查看完整过程](docs/learn/01-record-an-interview.md)与[素材、版本及验证范围](docs/learn/images/runtime-20261008/README.md)。 ## 快速开始 @@ -159,6 +124,77 @@ macOS Keychain 或 Linux Secret Service；仅安装 Python 包不等于系统安 需要 AI 辅助时，再到“设置 → AI 与模型 → 配置 AI”填写模型服务信息，测试连接、应用到 Provider 列表，最后点击页面顶部“保存”。完整步骤见[第一次使用指南](docs/product-manual/产品说明书.md#start)。 +## 求职过程中，可以怎样使用它 + +| 功能 | 具体用途 | +| --- | --- | +| 投递管理 | 按公司、岗位和阶段跟进求职进度，关联岗位描述与面试安排 | +| 简历与材料准备 | 管理简历版本，结合岗位要求生成并审阅材料建议 | +| 面试准备与模拟 | 根据简历和岗位描述练习问答，查看 AI 追问与反馈 | +| 面试复盘 | 保存面试记录，选择并确认需要继续练习的重点 | +| Offer 对比与谈薪 | 比较已填写的薪酬、福利和答复期限，准备谈薪沟通 | +| Pilot 求职 Agent | 结合资料查询、分析和起草内容，调用工具，并在确认后更新关键记录 | + +本仓库介绍本地部署版本。在线服务可访问 +[offerContext Hub](https://hub.offercontext.cn)； +其功能与数据处理方式以站内说明为准，不默认与本地版本一致或互通。 + +## 真实界面 + +以下为本地部署开发版的实际界面，截图更新于 2026 年 9 月。不同版本的功能与界面可能存在差异，截图对应版本见[用户指南](docs/product-manual/产品说明书.md)。 + +### 1. 跟进每个岗位的投递进度 + +在同一看板中查看公司、岗位与当前阶段，按待投递、已投递、笔试、面试、Offer 和结束整理进展。 + +![投递看板：按公司、岗位和阶段跟进](docs/product-manual/screenshots/R03-05-page-create-saved.png) + +### 2. 为目标岗位准备投递材料 + +在投递详情中选择简历和本次使用的岗位描述（JD），进入材料工作区生成并审阅建议。确认后创建岗位简历版本，保留基础简历。 + +![投递准备：对照岗位与简历审阅 AI 生成的优化建议草稿](docs/product-manual/screenshots/04-03-material-generated.png) + +### 3. 结合求职资料使用 AI 助手 + +在同一个会话中查询投递进展、整理岗位资料或起草下一步计划，并对照右侧参考资料核对建议。 + +![完整 Pilot 页面：左侧会话列表、中间对话与新建投递确认卡、右侧参考资料及底部输入区](docs/product-manual/screenshots/R03-02-pilot-create-confirm.png) + +### 4. 面试前练习，面试后整理经验 + +从已安排的面试进入练习，或直接使用“快速模拟”，选择并核对本次岗位资料与简历后开始问答。独立练习不要求先创建真实投递或日程。 + +![新版文字模拟面试：沿用筱哲与远帆科技案例，查看中文提问依据并回答 AI 追问](docs/product-manual/screenshots/R08-studio-evidence.png) + +### 5. 比较 Offer 条件，准备谈薪 + +录入 Offer 后可以比较已知薪酬条件、补充自定义比较维度，并进入谈薪准备或谈薪教练，整理下一次沟通的重点。 + +![Offer 横向对比：查看等宽摘要卡片、年薪与回复时间差，并逐项核对薪酬、福利和截止日](docs/product-manual/screenshots/R08-offer-comparison-polished.png) + +## Haru 与 Pilot + +Pilot 是负责对话与任务协作的内置 Agent；Haru 是桌面宽屏上的可选角色入口。 +喜欢角色交互，可以从 Haru 进入；喜欢清爽界面，也可以隐藏它，继续使用 Pilot。 +Haru 采用 Live2D 官方样例角色，并非 OfferPilot 原创角色，归属与使用条件见[许可证](#许可证)。 + +## 不仅能用，也可以拆开学 + +求职者可以直接使用工作台，不需要先学习 Harness。AI builder 也可以只研究一个具体问题： +**为什么同一条面试安排，重复确认也不该保存两遍？** + +- **先看懂**：从[一场面试怎样被记录](docs/learn/01-record-an-interview.md)开始，再按[四篇短路线](docs/learn/README.md)看清资料、模型、工具与人的分工。无需安装项目或写代码。 +- **动手试**：运行[只用 Python 标准库的小实验](docs/learn/examples/README.md)，观察“确认前 0 条 → 确认后 1 条 → 重复确认仍为 1 条”。实验使用模拟模型，不需要模型密钥，不是模型能力评测。 +- **拆开实现**：按兴趣阅读[Harness 源码导读](docs/learn/advanced/README.md)，追踪 Agent Loop、上下文、写入确认、取消与恢复、运行记录和验证。 + +学习材料以具体源码基线与验证记录为依据，尚未开展读者试读；它是一条实战阅读与实验路线，不保证读完就能独立实现完整系统。 + +## 参与项目 + +发现问题或有改进建议，欢迎[提交 Issue](https://github.com/offercontext/offerPilot/issues)。 +想贡献改动，请先阅读[贡献指南](CONTRIBUTING.md)，说明目标、修改范围与实际验证结果。 + ## 隐私、费用与使用限制 - 本地部署将业务数据保存在你的设备上。使用 AI 功能时，相关资料会发送给你配置的模型服务；本地存储不代表所有 AI 处理都在本地完成。模型调用可能产生服务商费用。