cv

cv is a FastAPI application for managing professional resumes. It includes:

• A JSON API with SQLite persistence
• A desktop-focused web client (single-page experience) built with templates, HTMX, Web Components, and Pico CSS
• JSON export validated against JSON Schema

Features

• Resume CRUD with nested sections:
  • Contact info
  • Optional summary
  • Education
  • Experience
• Reusable highlight bullets that can be attached to experiences
• Resume export endpoint validated using JSON Schema
• Styled HTML/PDF document rendering for saved resumes
• Browser UI with:
  • Resume list view
  • Dynamic create-resume composer
  • Reuse of existing contact, education, experience, and highlight data
  • Document page describing the formatted/PDF rendering flow

Quickstart

1. Create a virtual environment and install dependencies:

python -m venv .venv
source .venv/bin/activate
pip install -e ".[dev]"

2. Run the API:

uvicorn app.main:app --reload

3. Open the web client:

http://127.0.0.1:8000/

4. API docs:

http://127.0.0.1:8000/docs

Key Endpoints

• POST /highlights create or reuse a highlight
• GET /highlights list highlights
• POST /resumes create a resume
• GET /resumes list resumes
• GET /resumes/{resume_id} fetch a resume
• PUT /resumes/{resume_id} replace a resume
• DELETE /resumes/{resume_id} delete a resume
• POST /summaries/generate generate a resume summary from the current draft resume payload
• GET /resumes/{resume_id}/export get schema-validated JSON export
• GET /resumes/{resume_id}/document get the styled HTML document for a resume
• GET /resumes/{resume_id}/pdf render a resume as PDF
• GET /schemas/resume-export get the JSON schema used for exports

Web UI Routes

• GET / main SPA shell (resume list + create workflow)
• GET /ui/resumes HTMX partial for resume list
• GET /ui/resume/new HTMX partial for dynamic resume composer
• POST /ui/resumes HTMX form submit for creating a resume
• GET /document placeholder for future formatted/PDF document rendering

PDF Rendering Dependencies

The PDF renderer uses WeasyPrint, which converts HTML/CSS into PDF output. On macOS, install the native libraries it depends on with Homebrew:

brew install cairo pango harfbuzz fribidi glib

Then install the project dependencies in your virtual environment:

pip install -e ".[dev]"

AI Summary Generation

The resume composer supports AI-generated summaries. The frontend sends the current draft resume payload to POST /summaries/generate, the backend summarizes the experience section, and the returned text is saved into Resume.summary when the user submits the full resume form.

For local development, this feature is Ollama-first. Start Ollama, then pull a lighter model such as gemma3:4b:

ollama serve
ollama pull gemma

Configuration is controlled with environment variables:

• CV_SUMMARY_PROVIDER defaults to ollama
• CV_OLLAMA_URL defaults to http://127.0.0.1:11434
• CV_OLLAMA_MODEL defaults to gemma

Example: Create Resume

curl -X POST http://127.0.0.1:8000/resumes \
  -H "Content-Type: application/json" \
  -d '{
    "title": "Senior Backend Engineer",
    "contact_info": {
      "name": "Jordan Candidate",
      "email": "jordan@example.com",
      "phone": "555-0100",
      "location": "Remote"
    },
    "summary": "Backend engineer with strong API design experience.",
    "education": [],
    "experiences": [
      {
        "job_title": "Senior Engineer",
        "employer": "Acme Corp",
        "is_current": true,
        "highlights": [
          {"text": "Improved deployment speed by 40%."}
        ]
      }
    ]
  }'