georgelarson.me (terminal theme)

Static, no-build personal site for George Larson.

Structure

• index.html - intro and navigation hub
• resume.html - renders resume.txt and shows AI-assisted lens summaries
• resume.txt - plain text source for search, printing, and lens generation
• data/resume_lenses.json - cached lens summaries (regen via script below)
• schedule.html - Cal.com embed for booking sessions
• ask.html - local, private search over the resume text (supports ?q= links)
• style.css - shared terminal aesthetic
• scripts/generate_lenses.py - optional helper to regenerate lens summaries with Hugging Face or Venice.ai
• functions/api/lens-summary.ts - Cloudflare Pages Function that proxies Hugging Face Inference for on-demand lens summaries

Deploy on Cloudflare Pages

1. Create a GitHub repo and push these files to main.
2. In Cloudflare Pages choose Create project and connect the repo.
   • Build command: (leave blank)
   • Output directory: /
3. Add your custom domain and follow the DNS instructions.

Deploy on GitHub Pages

1. Repo settings -> Pages.
2. Source: main branch, directory / (root).

Notes

• ask.html intentionally keeps everything client side. It is a placeholder for a future RAG or on-device LLM workflow while remaining private today.
• The resume lens feature can be generated live (via /api/lens-summary) or by using the cached JSON. The Cloudflare Pages function uses HF_TOKEN so your secret never reaches the browser.

Generate lens summaries (Hugging Face)

1. Create a Hugging Face access token with Inference API permissions and set it in your shell:
   • macOS/Linux: export HF_API_TOKEN=hf_yourtoken
   • Windows PowerShell: $Env:HF_API_TOKEN = "hf_yourtoken"
   • Cloudflare Pages build settings: add an environment variable named HF_TOKEN (script accepts either name).
2. (Optional) Override the model by setting HF_MODEL (defaults to mistralai/Mistral-7B-Instruct-v0.3).
3. Run python scripts/generate_lenses.py.
   • The script writes data/resume_lenses.json. Commit the change to publish new summaries.
4. If the API returns errors, the script will surface the response body so you can adjust rate limits or prompts.

Live lens endpoint

• Path: POST /api/lens-summary
• Body: {"lens": "How does George handle manufacturing ops?", "model": "mistralai/Mistral-7B-Instruct-v0.3"}
• Response: JSON containing summary, key_points, model, generated_at
• The function reads resume.txt at request time, so updates deploy instantly without new scripts.