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---
title: CareerAI
emoji: 🚀
colorFrom: green
colorTo: blue
sdk: docker
app_port: 7860
pinned: false
---
<p align="center">
  <img src="https://i.postimg.cc/2yY6ztpG/ideogram-v3-0-Logo-minimalista-y-moderno-para-Career-AI-una-app-de-asistente-IA-para-carreras-p-0-(1.png" alt="CareerAI Logo" width="400">
</p>

<h1 align="center">CareerAI</h1>

<p align="center">
  <strong>AI-Powered Career Assistant with Hybrid RAG Pipeline</strong><br>
  <em>Upload your CV → Get personalized career advice → Land your next job</em>
</p>

<p align="center">
  <a href="https://careerai-app.hf.space">
    <img src="https://img.shields.io/badge/🚀_TRY_LIVE_DEMO-careerai--app.hf.space-00C853?style=for-the-badge&logoColor=white" alt="Live Demo">
  </a>
  &nbsp;
  <a href="https://github.com/Nicola671/CareerAI">
    <img src="https://img.shields.io/badge/⭐_Star_on_GitHub-Nicola671%2FCareerAI-181717?style=for-the-badge&logo=github&logoColor=white" alt="GitHub">
  </a>
</p>
<p align="center">
  <img src="https://img.shields.io/badge/Python-3.10+-3776AB?logo=python&logoColor=white" alt="Python">
  <img src="https://img.shields.io/badge/FastAPI-0.115+-009688?logo=fastapi&logoColor=white" alt="FastAPI">
  <img src="https://img.shields.io/badge/Groq-Llama_3_Family-F97316?logo=meta&logoColor=white" alt="Groq">
  <img src="https://img.shields.io/badge/RAG-Hybrid_Search-8B5CF6" alt="RAG">
  <img src="https://img.shields.io/badge/ChromaDB-Vector_Store-7C3AED" alt="ChromaDB">
  <img src="https://img.shields.io/badge/Docker-Deployed-2496ED?logo=docker&logoColor=white" alt="Docker">
  <img src="https://img.shields.io/github/license/Nicola671/CareerAI?color=EAB308" alt="License">
  <img src="https://img.shields.io/github/stars/Nicola671/CareerAI?style=social" alt="Stars">
</p>

<p align="center">
  <a href="#-english">🇺🇸 English</a> · <a href="#-español">🇦🇷 Español</a>
</p>

---

## 📸 Screenshots

<p align="center">
  <img src="https://i.postimg.cc/RhQtrcLs/foto-del-la-app-Career-AI.png" alt="CareerAI — Main Interface" width="800">
</p>
<p align="center"><em>Premium dark-mode interface with real-time AI streaming</em></p>

<br>

<table>
  <tr>
    <td width="50%">
      <img src="https://i.postimg.cc/yNcYr7PZ/image.png" alt="AI Conversation" width="100%">
      <p align="center"><em>💬 AI Chat — Context-aware responses from your CV</em></p>
    </td>
    <td width="50%">
      <img src="https://i.postimg.cc/6qmXpPcW/image.png" alt="Job Search" width="100%">
      <p align="center"><em>💼 Job Search — Live listings from LinkedIn, Indeed & more</em></p>
    </td>
  </tr>
  <tr>
    <td width="50%">
      <img src="https://i.postimg.cc/Sx5JvTb5/image.png" alt="Dashboard Analytics" width="100%">
      <p align="center"><em>📊 Dashboard — Skills analysis & professional insights</em></p>
    </td>
    <td width="50%">
      <img src="https://i.postimg.cc/85dcsTfz/image.png" alt="Dashboard Charts" width="100%">
      <p align="center"><em>📈 Analytics — Radar charts & career timeline</em></p>
    </td>
  </tr>
</table>
---

# 🇺🇸 English

## What is CareerAI?

**CareerAI** is a full-stack AI web application that analyzes your professional documents (CV, cover letters, certificates) using a **5-stage hybrid RAG pipeline** to deliver accurate, context-aware career guidance — with zero hallucinations.

Every response is grounded in **your actual documents**, not generic advice.

> **🚀 Try it now →** [careerai-app.hf.space](https://careerai-app.hf.space)

---

## ⚡ Quick Start (3 minutes)

```bash
# 1. Clone & setup
git clone https://github.com/Nicola671/CareerAI.git
cd CareerAI
python -m venv venv && venv\Scripts\activate
pip install -r requirements.txt
# 2. Configure (create .env file)
echo GROQ_API_KEY=your_key_here > .env
echo SECRET_KEY=your_random_secret >> .env
# 3. Run
uvicorn api:app --reload --port 8000
```

Open **http://localhost:8000** → Upload your CV → Start chatting 🚀

> 💡 Get your free Groq API key at [console.groq.com](https://console.groq.com)

---

## Key Features

### AI Models

| Model | Engine | Use Case |
|-------|--------|----------|
| 🧠 **CareerAI Pro** | Llama 3.3 70B | Deep analysis, detailed responses |
| ⚡ **CareerAI Flash** | Llama 3.1 8B | Quick answers, instant feedback |

### 5 Specialized Modes

| Mode | Description |
|------|-------------|
| 💬 **General Chat** | Open-ended career consultation |
| 🎯 **Job Match** | Compatibility analysis with job postings (% match score) |
| ✉️ **Cover Letter** | Auto-generated cover letters based on your actual CV data |
| 📈 **Skills Gap** | Identifies missing skills + improvement roadmap |
| 🎤 **Mock Interview** | Simulated interviews with STAR method and technical questions |

### Platform Capabilities

| Category | Features |
|----------|----------|
| **Document Processing** | PDF, DOCX, TXT, JPG, PNG, WebP — including scanned documents via Vision AI |
| **Real-time Streaming** | Token-by-token response generation with live markdown rendering |
| **Export Engine** | Professional PDF, DOCX, HTML, TXT with smart filename generation |
| **Analytics Dashboard** | Skills radar chart, professional timeline, AI-powered insights |
| **Authentication** | JWT + BCrypt + Google OAuth + password recovery |
| **Job Search** | Live job listings from LinkedIn, Indeed, Glassdoor via JSearch API |
| **Responsive Design** | Premium dark-mode UI optimized for desktop, tablet, and mobile |
| **Cloud Persistence** | Conversations synced per user, guest sessions isolated |

---

## RAG Pipeline Architecture

```
📝 User Query
     │
     ├── 1. Vector Search (Semantic)
     │     └── ChromaDB + BGE-M3 Embeddings (100+ languages)
     │
     ├── 2. Keyword Search (Lexical)
     │     └── BM25 with tokenized index
     │
     ├── 3. Reciprocal Rank Fusion (RRF)
     │     └── Merges and normalizes both result sets
     │
     ├── 4. Cross-Encoder Reranking
     │     └── BGE-Reranker-v2-m3 (fine-grained relevance scoring)
     │
     └── 5. LLM Generation
           └── Groq API + Llama 3.3 70B (streaming)
```

### Embedding Models

| Model | Languages | Size |
|-------|-----------|------|
| 🌍 **BGE-M3** (default) | 100+ | ~2.3 GB |
| 🚀 **GTE Multilingual** | 70+ | ~580 MB |
| 📐 **Multilingual E5** | 100+ | ~1.1 GB |
| ⚡ **MiniLM v2** | English | ~90 MB |

---

## Tech Stack

| Layer | Technology |
|-------|------------|
| **Backend** | FastAPI + Uvicorn |
| **Frontend** | Vanilla HTML5 / CSS3 / JavaScript |
| **LLM** | Groq API (Llama 3.3 70B / Llama 3.1 8B) |
| **RAG** | ChromaDB + BM25 + BGE-M3 + Reranker + RRF |
| **Database** | SQLite + SQLAlchemy |
| **Auth** | JWT + BCrypt + Google OAuth 2.0 |
| **Vision AI** | Groq + Llama 4 Scout (scanned document OCR) |
| **Embeddings** | HuggingFace Sentence-Transformers |
| **Export** | FPDF2, python-docx |
| **Job Search** | JSearch API (RapidAPI) |
| **Deployment** | Docker + HuggingFace Spaces |

---

## Deployment

### HuggingFace Spaces (recommended — free)

```bash
git remote add hf https://huggingface.co/spaces/CareerAI/app
git push hf main --force
```

Set these as **Secrets** in HF Space → Settings:

| Variable | Required | Description |
|----------|----------|-------------|
| `GROQ_API_KEY` | ✅ | LLM API key ([console.groq.com](https://console.groq.com)) |
| `SECRET_KEY` | ✅ | JWT signing key (random string) |
| `EMBEDDING_MODEL` | ❌ | Override embedding model (default: `bge-m3`) |
| `ENABLE_RERANKING` | ❌ | Enable/disable reranker (default: `true`) |
| `JSEARCH_API_KEY` | ❌ | Job search API |
| `MAIL_USERNAME` | ❌ | Gmail SMTP username |
| `MAIL_PASSWORD` | ❌ | Gmail app password |
| `MAIL_FROM` | ❌ | Sender email address |

### Docker (any platform)

```bash
docker build -t careerai .
docker run -p 7860:7860 --env-file .env careerai
```

---

## Project Structure

```
CareerAI/
├── api.py                     # FastAPI application (22 endpoints)
├── Dockerfile                 # Production Docker image
├── requirements.txt           # Python dependencies
├── .env                       # Environment variables (git-ignored)
│
├── frontend/                  # Client-side application
│   ├── index.html             # HTML structure
│   ├── app.js                 # Application logic (1,842 lines)
│   ├── styles.css             # Design system (1,695 lines)
│   └── *.png                  # Icons and favicon
│
├── src/                       # Core modules
│   ├── rag_engine.py          # Hybrid RAG — Vector + BM25 + RRF + Reranking
│   ├── career_assistant.py    # LLM orchestration — 5 specialized modes
│   ├── document_processor.py  # Multi-format extraction + Vision AI
│   ├── profile_extractor.py   # Profile analysis engine for dashboard
│   ├── exporter.py            # PDF / DOCX / HTML / TXT export engine
│   ├── auth.py                # JWT + Google OAuth + email recovery
│   └── models.py              # SQLAlchemy ORM (User, Conversation)
│
└── data/                      # Runtime data (git-ignored)
    ├── uploads/               # User documents
    └── vectordb/              # ChromaDB vector persistence
```

---

## API Reference

**22 endpoints** — interactive documentation at [`/docs`](https://careerai-app.hf.space/docs)

| Group | Method | Endpoint | Description |
|-------|--------|----------|-------------|
| Status | `GET` | `/api/status` | Health check + system info |
| Config | `POST` | `/api/config` | Configure API key and model |
| Config | `POST` | `/api/config/rag` | Configure RAG pipeline settings |
| Chat | `POST` | `/api/chat` | Single-response chat |
| Chat | `POST` | `/api/chat/stream` | SSE streaming chat |
| Documents | `POST` | `/api/documents/upload` | Upload & index document |
| Documents | `GET` | `/api/documents` | List indexed documents |
| Documents | `DELETE` | `/api/documents/{file}` | Remove document from index |
| Export | `POST` | `/api/export` | Export message to PDF/DOCX/HTML/TXT |
| Export | `POST` | `/api/export/conversation` | Export full conversation |
| Jobs | `GET` | `/api/jobs` | Search live job listings |
| Dashboard | `GET` | `/api/dashboard` | AI-powered profile analysis |
| Auth | `POST` | `/api/auth/register` | User registration |
| Auth | `POST` | `/api/auth/login` | User login (JWT) |
| Auth | `GET` | `/api/auth/me` | Get current user profile |
| Auth | `POST` | `/api/auth/me` | Update user profile |
| Auth | `POST` | `/api/auth/forgot-password` | Request password reset code |
| Auth | `POST` | `/api/auth/reset-password` | Reset password with code |
| Auth | `POST` | `/api/auth/google` | Google OAuth login |
| Conversations | `GET` | `/api/conversations` | List saved conversations |
| Conversations | `POST` | `/api/conversations` | Save conversation |
| Conversations | `DELETE` | `/api/conversations/{id}` | Delete conversation |

---

## Metrics

| Metric | Value |
|--------|-------|
| Total lines of code | **8,400+** |
| API endpoints | **22** |
| Frontend functions | **80+** |
| Backend modules | **7** |
| Assistant modes | **5** |
| Export formats | **4** |
| Supported upload types | **7** |
| Embedding models | **4** |

---

## 🗺️ Roadmap

- [x] Hybrid RAG pipeline (Vector + BM25 + RRF + Reranking)
- [x] Real-time SSE streaming
- [x] Multi-format document processing with Vision AI
- [x] Premium export engine (PDF, DOCX, HTML, TXT)
- [x] Full authentication system (JWT + Google OAuth)
- [x] AI-powered dashboard with analytics
- [x] Job search integration (JSearch API)
- [x] Docker deployment on HuggingFace Spaces
- [ ] Multi-language UI (EN / ES / PT)
- [ ] Resume builder with AI suggestions
- [ ] Interview recording with real-time feedback
- [ ] LinkedIn profile import
- [ ] Custom domain support

---

## 💰 Cost

| Component | Cost |
|-----------|------|
| Groq API (Llama 3.3 70B) | ✅ Free |
| BGE-M3 Embeddings | ✅ Free (runs locally) |
| BGE-Reranker-v2-m3 | ✅ Free (runs locally) |
| ChromaDB + BM25 | ✅ Free (runs locally) |
| HuggingFace Spaces | ✅ Free (16 GB RAM) |
| **Total** | **$0** |

---

## 🤝 Contributing

Contributions are welcome! Whether it's bug fixes, new features, or documentation improvements.

1. **Fork** the repository
2. **Create** a branch: `git checkout -b feature/your-feature`
3. **Commit** your changes: `git commit -m "Add your feature"`
4. **Push** to the branch: `git push origin feature/your-feature`
5. **Open** a Pull Request

---

## 📄 License

This project is licensed under the **MIT License** — free to use, modify, and distribute.

---

---

# 🇦🇷 Español

## ¿Qué es CareerAI?

**CareerAI** es una aplicación web full-stack que analiza tus documentos profesionales (CV, cartas de presentación, certificados) usando un **pipeline RAG híbrido de 5 etapas** para darte asesoramiento preciso y personalizado — sin alucinaciones.

Cada respuesta está basada en **tus documentos reales**, no en consejos genéricos.

> **🚀 Probalo ahora →** [careerai-app.hf.space](https://careerai-app.hf.space)

---

## ⚡ Inicio Rápido (3 minutos)

```bash
# 1. Clonar y configurar
git clone https://github.com/Nicola671/CareerAI.git
cd CareerAI
python -m venv venv && venv\Scripts\activate
pip install -r requirements.txt
# 2. Configurar (.env)
echo GROQ_API_KEY=tu_key_aqui > .env
echo SECRET_KEY=tu_secret_random >> .env
# 3. Ejecutar
uvicorn api:app --reload --port 8000
```

Abrí **http://localhost:8000** → Subí tu CV → Empezá a chatear 🚀

> 💡 Obtené tu API key gratis en [console.groq.com](https://console.groq.com)

---

## Funcionalidades

### Modelos de IA

| Modelo | Motor | Uso |
|--------|-------|-----|
| 🧠 **CareerAI Pro** | Llama 3.3 70B | Análisis profundo, respuestas detalladas |
| ⚡ **CareerAI Flash** | Llama 3.1 8B | Respuestas rápidas, feedback instantáneo |

### 5 Modos Especializados

| Modo | Descripción |
|------|-------------|
| 💬 **Chat General** | Consulta abierta sobre tu carrera profesional |
| 🎯 **Job Match** | Análisis de compatibilidad con ofertas laborales (% de match) |
| ✉️ **Cover Letter** | Cartas de presentación generadas desde tu CV real |
| 📈 **Skills Gap** | Identifica habilidades faltantes + roadmap de mejora |
| 🎤 **Entrevista** | Simulación con preguntas técnicas y método STAR |

### Capacidades de la Plataforma

| Categoría | Características |
|-----------|----------------|
| **Procesamiento de Documentos** | PDF, DOCX, TXT, JPG, PNG, WebP — incluyendo documentos escaneados con Vision AI |
| **Streaming en Tiempo Real** | Generación token-por-token con rendering markdown en vivo |
| **Motor de Exportación** | PDF, DOCX, HTML, TXT profesional con nombres de archivo inteligentes |
| **Dashboard Analítico** | Gráfico radar de skills, timeline profesional, insights generados con IA |
| **Autenticación Completa** | JWT + BCrypt + Google OAuth + recuperación de contraseña |
| **Búsqueda de Empleo** | Ofertas en tiempo real de LinkedIn, Indeed, Glassdoor vía JSearch API |
| **Diseño Responsive** | UI premium dark-mode optimizada para desktop, tablet y móvil |
| **Persistencia en la Nube** | Conversaciones sincronizadas por usuario, sesiones guest aisladas |

---

## Arquitectura del Pipeline RAG

CareerAI implementa un **pipeline de retrieval híbrido de 5 etapas** que combina comprensión semántica con precisión léxica:

```
📝 Query del usuario
     │
     ├── 1. Búsqueda Vectorial (Semántica)
     │     └── ChromaDB + BGE-M3 Embeddings (100+ idiomas)
     │
     ├── 2. Búsqueda por Keywords (Léxica)
     │     └── BM25 con índice tokenizado
     │
     ├── 3. Reciprocal Rank Fusion (RRF)
     │     └── Combina y normaliza ambos conjuntos de resultados
     │
     ├── 4. Reranking con Cross-Encoder
     │     └── BGE-Reranker-v2-m3 (scoring fino de relevancia)
     │
     └── 5. Generación LLM
           └── Groq API + Llama 3.3 70B (streaming)
```

### Modelos de Embeddings

| Modelo | Idiomas | Tamaño |
|--------|---------|--------|
| 🌍 **BGE-M3** (default) | 100+ | ~2.3 GB |
| 🚀 **GTE Multilingual** | 70+ | ~580 MB |
| 📐 **Multilingual E5** | 100+ | ~1.1 GB |
| ⚡ **MiniLM v2** | Inglés | ~90 MB |

---

## Stack Tecnológico

| Capa | Tecnología |
|------|------------|
| **Backend** | FastAPI + Uvicorn |
| **Frontend** | HTML5 / CSS3 / JavaScript (vanilla) |
| **LLM** | Groq API (Llama 3.3 70B / Llama 3.1 8B) |
| **RAG** | ChromaDB + BM25 + BGE-M3 + Reranker + RRF |
| **Base de Datos** | SQLite + SQLAlchemy |
| **Autenticación** | JWT + BCrypt + Google OAuth 2.0 |
| **Vision AI** | Groq + Llama 4 Scout (OCR de documentos escaneados) |
| **Embeddings** | HuggingFace Sentence-Transformers |
| **Exportación** | FPDF2, python-docx |
| **Búsqueda de Empleo** | JSearch API (RapidAPI) |
| **Deployment** | Docker + HuggingFace Spaces |

---

## Deployment

### HuggingFace Spaces (recomendado — gratis)

```bash
git remote add hf https://huggingface.co/spaces/CareerAI/app
git push hf main --force
```

Configurá estos **Secrets** en HF Space → Settings:

| Variable | Requerida | Descripción |
|----------|-----------|-------------|
| `GROQ_API_KEY` | ✅ | API key del LLM ([console.groq.com](https://console.groq.com)) |
| `SECRET_KEY` | ✅ | Clave de firma JWT (string aleatorio) |
| `EMBEDDING_MODEL` | ❌ | Sobreescribir modelo de embedding (default: `bge-m3`) |
| `ENABLE_RERANKING` | ❌ | Activar/desactivar reranker (default: `true`) |
| `JSEARCH_API_KEY` | ❌ | API de búsqueda de empleo |
| `MAIL_USERNAME` | ❌ | Usuario SMTP de Gmail |
| `MAIL_PASSWORD` | ❌ | App password de Gmail |
| `MAIL_FROM` | ❌ | Dirección de email del remitente |

### Docker (cualquier plataforma)

```bash
docker build -t careerai .
docker run -p 7860:7860 --env-file .env careerai
```

---

## Estructura del Proyecto

```
CareerAI/
├── api.py                     # Aplicación FastAPI (22 endpoints)
├── Dockerfile                 # Imagen Docker para producción
├── requirements.txt           # Dependencias Python
├── .env                       # Variables de entorno (ignorado por git)
│
├── frontend/                  # Aplicación cliente
│   ├── index.html             # Estructura HTML
│   ├── app.js                 # Lógica de la app (1,842 líneas)
│   ├── styles.css             # Sistema de diseño (1,695 líneas)
│   └── *.png                  # Iconos y favicon
│
├── src/                       # Módulos core
│   ├── rag_engine.py          # RAG Híbrido — Vector + BM25 + RRF + Reranking
│   ├── career_assistant.py    # Orquestación LLM — 5 modos especializados
│   ├── document_processor.py  # Extracción multi-formato + Vision AI
│   ├── profile_extractor.py   # Motor de análisis de perfil para dashboard
│   ├── exporter.py            # Motor de exportación PDF / DOCX / HTML / TXT
│   ├── auth.py                # JWT + Google OAuth + recuperación por email
│   └── models.py              # ORM SQLAlchemy (User, Conversation)
│
└── data/                      # Datos en runtime (ignorado por git)
    ├── uploads/               # Documentos del usuario
    └── vectordb/              # Persistencia de vectores ChromaDB
```

---

## Referencia de API

**22 endpoints** — documentación interactiva en [`/docs`](https://careerai-app.hf.space/docs)

| Grupo | Método | Endpoint | Descripción |
|-------|--------|----------|-------------|
| Estado | `GET` | `/api/status` | Health check + info del sistema |
| Config | `POST` | `/api/config` | Configurar API key y modelo |
| Config | `POST` | `/api/config/rag` | Configurar pipeline RAG |
| Chat | `POST` | `/api/chat` | Chat con respuesta única |
| Chat | `POST` | `/api/chat/stream` | Chat con streaming SSE |
| Documentos | `POST` | `/api/documents/upload` | Subir e indexar documento |
| Documentos | `GET` | `/api/documents` | Listar documentos indexados |
| Documentos | `DELETE` | `/api/documents/{file}` | Eliminar documento del índice |
| Exportar | `POST` | `/api/export` | Exportar mensaje a PDF/DOCX/HTML/TXT |
| Exportar | `POST` | `/api/export/conversation` | Exportar conversación completa |
| Empleos | `GET` | `/api/jobs` | Buscar ofertas laborales |
| Dashboard | `GET` | `/api/dashboard` | Análisis de perfil con IA |
| Auth | `POST` | `/api/auth/register` | Registro de usuario |
| Auth | `POST` | `/api/auth/login` | Login (JWT) |
| Auth | `GET` | `/api/auth/me` | Obtener perfil actual |
| Auth | `POST` | `/api/auth/me` | Actualizar perfil |
| Auth | `POST` | `/api/auth/forgot-password` | Solicitar código de reset |
| Auth | `POST` | `/api/auth/reset-password` | Resetear contraseña con código |
| Auth | `POST` | `/api/auth/google` | Login con Google OAuth |
| Conversaciones | `GET` | `/api/conversations` | Listar conversaciones guardadas |
| Conversaciones | `POST` | `/api/conversations` | Guardar conversación |
| Conversaciones | `DELETE` | `/api/conversations/{id}` | Eliminar conversación |

---

## Métricas del Proyecto

| Métrica | Valor |
|---------|-------|
| Líneas de código totales | **8,400+** |
| Endpoints de API | **22** |
| Funciones del frontend | **80+** |
| Módulos del backend | **7** |
| Modos del asistente | **5** |
| Formatos de exportación | **4** |
| Tipos de archivo soportados | **7** |
| Modelos de embeddings | **4** |

---

## 🗺️ Roadmap

- [x] Pipeline RAG híbrido (Vector + BM25 + RRF + Reranking)
- [x] Streaming en tiempo real con SSE
- [x] Procesamiento multi-formato con Vision AI
- [x] Motor de exportación premium (PDF, DOCX, HTML, TXT)
- [x] Sistema de autenticación completo (JWT + Google OAuth)
- [x] Dashboard analítico con IA
- [x] Integración de búsqueda de empleo (JSearch API)
- [x] Deployment con Docker en HuggingFace Spaces
- [ ] UI multi-idioma (EN / ES / PT)
- [ ] Constructor de CV con sugerencias de IA
- [ ] Grabación de entrevistas con feedback en tiempo real
- [ ] Importación de perfil de LinkedIn
- [ ] Soporte de dominio personalizado

---

## 💰 Costo

| Componente | Costo |
|-----------|-------|
| Groq API (Llama 3.3 70B) | ✅ Gratis |
| BGE-M3 Embeddings | ✅ Gratis (corre local) |
| BGE-Reranker-v2-m3 | ✅ Gratis (corre local) |
| ChromaDB + BM25 | ✅ Gratis (corre local) |
| HuggingFace Spaces | ✅ Gratis (16 GB RAM) |
| **Total** | **$0** |

---

## 🤝 Contribuir

¡Las contribuciones son bienvenidas! Ya sea corrección de bugs, nuevas features o mejoras en la documentación.

1. **Fork** el repositorio
2. **Creá** una branch: `git checkout -b feature/tu-feature`
3. **Commit** tus cambios: `git commit -m "Agregar tu feature"`
4. **Push** a la branch: `git push origin feature/tu-feature`
5. **Abrí** un Pull Request

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## 📄 Licencia

Este proyecto está bajo la **Licencia MIT** — libre para usar, modificar y distribuir.

---

<p align="center">
  <strong>Nicolás Medina</strong>
</p>

<p align="center">
  <a href="https://github.com/Nicola671">
    <img src="https://img.shields.io/badge/GitHub-Nicola671-181717?logo=github&logoColor=white&style=for-the-badge" alt="GitHub">
  </a>
  &nbsp;
  <a href="https://www.linkedin.com/in/nicolás-medina-33663237a">
    <img src="https://img.shields.io/badge/LinkedIn-Nicolás_Medina-0A66C2?logo=linkedin&logoColor=white&style=for-the-badge" alt="LinkedIn">
  </a>
  &nbsp;
  <a href="mailto:nicolasmedinae06@gmail.com">
    <img src="https://img.shields.io/badge/Email-Contact-EA4335?logo=gmail&logoColor=white&style=for-the-badge" alt="Email">
  </a>
</p>
<br>

<p align="center">
  <em>If this project helped you, consider giving it a ⭐ on GitHub!</em><br>
  <em>Si te sirvió, ¡dejale una ⭐ en GitHub!</em>
</p>

<br>

<p align="center">
  <strong>CareerAI v2.0</strong> — Full-Stack AI Career Assistant<br>
  <em>Made with ❤️ in Argentina 🇦🇷</em>
</p>