CV Generator

A Streamlit-based application for generating tailored CVs using AI. Upload your CV, provide a job description, and get a customized CV optimized for the position.

Features

• CV Management: Edit and manage your CV data in JSON format
• CV Upload & Analysis: Upload existing CVs (PDF, DOCX, TXT) and automatically extract information
• User Story: Maintain a personal user story to provide context for CV generation
• AI-Powered CV Generation: Generate tailored CVs based on job descriptions
• Prompt Injection: Add custom HTML/CSS modifications to your generated CV
• CV Preview: View and print generated CVs directly in the browser
• History Viewer: Access and view previously generated CV versions

Requirements

• Python 3.14 or higher
• Ollama (for running local LLM models)

Installation

1. Clone the repository:

git clone <repository-url>
cd cv-generator

2. Install dependencies using uv (recommended):

uv sync

Or using pip:

pip install -r requirements.txt

3. Make sure Ollama is running with a compatible model (e.g., llama3.2)

Running the Application

Start the Streamlit application:

streamlit run streamlit_app.py

Or with uv:

uv run streamlit run streamlit_app.py

The application will open in your default web browser at http://localhost:8501

Usage

1. Upload or Edit Your CV

   • Upload an existing CV file (PDF, DOCX, or TXT) or manually edit the CV JSON
   • The system will analyze and extract relevant information

2. Add Your User Story (Optional)

   • Provide additional context about your background and career goals
   • This helps the AI generate more personalized CVs

3. Generate Tailored CV

   • Paste the job description
   • Add any additional instructions
   • Optionally add custom HTML/CSS prompt injection
   • Click "Generate" to create your tailored CV

4. View and Print

   • Preview the generated CV in the browser
   • Use the print button to export as PDF (A4 format)
   • View previously generated CVs from the history section

Project Structure

cv-generator/
├── streamlit_app.py       # Main Streamlit application
├── cv_generator.py        # CV generation logic
├── cv_analyzer.py         # CV analysis and extraction
├── cv_renderer.py         # HTML rendering using Jinja2
├── llm.py                 # LLM integration
├── models.py              # Pydantic models
├── cv.json                # Current CV data
├── user_story.txt         # User story file
├── templates/             # Jinja2 templates
│   └── cv_template.html
├── temp/                  # Generated CV files
└── text/                  # Translations
    ├── base.py
    └── en.py

Dependencies

• streamlit: Web application framework
• langchain: LLM orchestration
• langchain-ollama: Ollama integration
• pydantic: Data validation
• pypdf: PDF processing
• jinja2: Template rendering
• thefuzz: Fuzzy string matching

License

[Add your license here]