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I Built HirePilot: An Open-Source AI Career Copilot That Runs Locally 🚀

Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle Submission 💸 This is a submission for the Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle What I Built What if preparing for a job interview didn’t mean juggling five different tools? Meet HirePilot AI 🚀 — an open-source, local-first AI career copilot that helps candidates go from a job description to an interview preparation plan.

Hacktoberfest 开源 AI 挑战赛第 2 周：副业项目提交 💸 这是 Hacktoberfest 开源 AI 挑战赛第 2 周的副业项目提交。我构建了什么？如果准备面试不需要同时使用五种不同的工具会怎样？来认识一下 HirePilot AI 🚀——这是一个开源的、本地优先的 AI 职业副驾驶，旨在帮助求职者从职位描述出发，制定出一份完整的面试准备计划。

Here’s the workflow: 📄 Upload your resume + paste the job description. HirePilot analyzes your existing experience, identifies relevant skills, and highlights gaps against the role. 💬 Answer a few questions. When important details are missing, it asks contextual follow-up questions to improve your resume without inventing experience or achievements. ✍️ Generate an ATS-friendly resume. Get a role-tailored, editable resume with relevant keywords, plus PDF and DOCX exports.

工作流程如下：📄 上传简历并粘贴职位描述。HirePilot 会分析你现有的经验，识别相关技能，并指出与职位要求之间的差距。💬 回答几个问题。当缺少重要细节时，它会提出情境化的后续问题来完善你的简历，而不会捏造经验或成就。✍️ 生成 ATS 友好型简历。获取一份针对职位定制、可编辑的简历，包含相关关键词，并支持 PDF 和 DOCX 导出。

🔎 Research the company. Enter a company name to discover relevant company information and publicly reported interview questions, with source links. 🧠 Prepare for the interview. Get role-specific technical and behavioral questions, suggested answers, and a personalized list of topics to revise. ✅ Track your readiness. Work through a prioritized preparation checklist and watch your progress move from 0% to 100%.

🔎 研究公司。输入公司名称即可发现相关的公司信息和公开的面试题，并附带来源链接。🧠 准备面试。获取针对职位的技术和行为面试题、建议答案以及个性化的复习主题列表。✅ 跟踪准备进度。通过优先级的准备清单进行学习，并观察你的进度从 0% 提升到 100%。

The idea is simple: one job description → one tailored resume → a complete interview preparation roadmap. Who would pay for it? Students, fresh graduates, job seekers, and professionals applying to multiple roles could use HirePilot to reduce repetitive preparation work. A potential business model is a free local version with premium resume templates and additional career workflows. The goal is to make useful career preparation accessible without requiring a paid LLM subscription.

这个想法很简单：一份职位描述 → 一份定制简历 → 一份完整的面试准备路线图。谁会为此付费？学生、应届毕业生、求职者以及申请多个职位的专业人士都可以使用 HirePilot 来减少重复的准备工作。一个潜在的商业模式是提供免费的本地版本，并辅以高级简历模板和额外的职业工作流。其目标是让实用的职业准备工作变得触手可及，而无需订阅付费的大语言模型服务。

Code The code is open source, and you’re welcome to explore, fork, and build on it! Yaser-123 / hirepilot-ai HirePilot AI — Private, Grounded AI Career Preparation Platform Created and Open-Sourced by Alliet Software Labs An open-source, zero-fabrication career preparation platform powered by 100% on-device local AI.

代码：该代码是开源的，欢迎探索、分叉并在此基础上进行构建！Yaser-123 / hirepilot-ai HirePilot AI — 由 Alliet Software Labs 创建并开源的私有化、基于事实的 AI 职业准备平台。这是一个由 100% 设备端本地 AI 驱动的开源、零捏造职业准备平台。

Transform any job description and resume into a role-targeted ATS resume, mathematical gap audit, verified company research, situational interview answers, and an actionable 0–100% readiness checklist—without sending your confidential career history to cloud servers. 🌐 Website: https://alliet.company/ ✉️ Contact: contact@alliet.company 💡 Emblem & Brand: Official Open-Source Project by Alliet Software Labs

将任何职位描述和简历转化为针对职位的 ATS 简历、数学化的差距审计、经过验证的公司研究、情境化面试答案以及可操作的 0–100% 准备清单——无需将你的机密职业履历发送到云端服务器。🌐 网站：https://alliet.company/ ✉️ 联系方式：contact@alliet.company 💡 标志与品牌：Alliet Software Labs 的官方开源项目。

Table of Contents Why HirePilot AI? Key Capabilities & Architecture Zero-Telemetry Privacy Architecture Technology Stack Prerequisites Quick Start Guide Step-by-Step Workflow Project Structure Contributing Guidelines FAQ & Troubleshooting License & Credits

目录：为什么选择 HirePilot AI？关键功能与架构、零遥测隐私架构、技术栈、先决条件、快速入门指南、分步工作流程、项目结构、贡献指南、常见问题与故障排除、许可证与致谢。

1. Why HirePilot AI? Most AI resume tools act as generic chat wrappers: they hallucinate skills you don’t have, flatten rich career history into tiny one-bullet summaries, and send your sensitive contact and employment history to proprietary third-party clouds. HirePilot… View on GitHub

2. 为什么选择 HirePilot AI？大多数 AI 简历工具只是通用的聊天包装器：它们会捏造你并不具备的技能，将丰富的职业履历压缩成简短的单行摘要，并将你敏感的联系方式和就业历史发送到专有的第三方云端。HirePilot……在 GitHub 上查看。

What’s under the hood? 🧠 Gemma 3 4B + Ollama — local inference for resume analysis, tailoring, and interview preparation. ⚛️ React 19 + TypeScript + Vite — the frontend. ⚡ FastAPI + Python — the backend. 🔍 DuckDuckGo Search + optional Tavily — company research and sourced interview insights. 📋 Local progress tracking — persistent application sessions, resume edits, and preparation checklists. The project is released under the MIT License.

其核心技术是什么？🧠 Gemma 3 4B + Ollama — 用于简历分析、定制和面试准备的本地推理。⚛️ React 19 + TypeScript + Vite — 前端。⚡ FastAPI + Python — 后端。🔍 DuckDuckGo 搜索 + 可选的 Tavily — 公司研究和来源可靠的面试见解。📋 本地进度跟踪 — 持久化的应用程序会话、简历编辑和准备清单。该项目基于 MIT 许可证发布。

How I Built It The central idea behind HirePilot is that your career data shouldn’t need to leave your computer just to help you prepare for a job. I built the application around Google’s Gemma 3 4B model, running locally through Ollama. Instead of relying on a proprietary cloud LLM API, HirePilot performs its core AI tasks using local inference.

我是如何构建它的：HirePilot 背后的核心理念是，你的职业数据不应该为了准备工作而离开你的电脑。我围绕 Google 的 Gemma 3 4B 模型构建了该应用程序，并通过 Ollama 在本地运行。HirePilot 不依赖专有的云端 LLM API，而是通过本地推理执行其核心 AI 任务。

The stack: AI: Gemma 3 4B through Ollama. Frontend: React 19, TypeScript, Vite, Tailwind CSS, and Lucide React. Backend: Python, FastAPI, Pydantic, and HTTPX. Resume processing: pypdf and python-docx. Company research: ddgs for DuckDuckGo search, with optional Tavily integration. Persistence: Browser localStorage for application sessions, edits, and preparation progress.

技术栈：AI：通过 Ollama 运行的 Gemma 3 4B。前端：React 19、TypeScript、Vite、Tailwind CSS 和 Lucide React。后端：Python、FastAPI、Pydantic 和 HTTPX。简历处理：pypdf 和 python-docx。公司研究：用于 DuckDuckGo 搜索的 ddgs，以及可选的 Tavily 集成。持久化：用于应用程序会话、编辑和准备进度的浏览器 localStorage。

I separated the workflow into focused stages: resume and JD analysis, contextual clarification, resume generation, company research, interview preparation, and checklist generation. The resume matching score is calculated from matching skills, requirement gaps, and keyword coverage. It is an estimate of alignment with the JD, not a guarantee of passing an ATS. The application also distinguishes candidate-confirmed information from missing skills, so the AI doesn’t need to fabricate experience to make a resume appear stronger.

我将工作流程分为几个重点阶段：简历与职位描述分析、情境澄清、简历生成、公司研究、面试准备和清单生成。简历匹配分数是根据匹配的技能、需求差距和关键词覆盖率计算得出的。这只是对职位匹配度的估计，并不能保证通过 ATS 系统。该应用程序还将候选人确认的信息与缺失的技能区分开来，因此 AI 不需要捏造经验来使简历看起来更出色。

Why Does Open Innovation Matter? For HirePilot, open innovation is what makes a privacy-focused, affordable career tool practical. 🔒 Privacy by design Resumes contain personal information and employment history. Running inference locally means candidates can use AI without sending their resume to a commercial LLM provider. Company research is handled separately. Search queries contain relevant company and role information, not the candidate’s resume or personal contact details.

为什么开放创新很重要？对于 HirePilot 而言，开放创新是使这款注重隐私且经济实惠的职业工具变得切实可行的关键。🔒 隐私设计：简历包含个人信息和就业历史。在本地运行推理意味着候选人可以在不将简历发送给商业 LLM 提供商的情况下使用 AI。公司研究是单独处理的。搜索查询仅包含相关的公司和职位信息，而不包含候选人的简历或个人联系方式。

💸 No mandatory per-request LLM fees Once Ollama and the model are installed, the core AI workflow can run on the user’s hardware without paying a commercial LLM API for each request. There is still a hardware requirement, and web research needs an internet connection. 🔄 Freedom to experiment Ollama makes it straightforward to experiment with different locally installed models. Developers can adjust prompts, generation settings, and model choices without tying the application to one proprietary API.

💸 无需按请求支付 LLM 费用：一旦安装了 Ollama 和模型，核心 AI 工作流就可以在用户的硬件上运行，而无需为每次请求支付商业 LLM API 费用。当然，这仍然有硬件要求，且网络研究需要互联网连接。🔄 实验自由：Ollama 使得尝试不同的本地安装模型变得非常简单。开发人员可以调整提示词、生成设置和模型选择，而无需将应用程序绑定到某个专有的 API 上。

🌱 Accessible career preparation A paid AI subscription shouldn’t be a prerequisite for building a better resume or preparing for an interview. Local inference makes the core workflow more accessible while giving users greater control over their data.

🌱 可及的职业准备：付费的 AI 订阅不应成为制作更好简历或准备面试的先决条件。本地推理使核心工作流更易于获取，同时让用户对自己的数据拥有更大的控制权。