Practical guide to moving beyond simple LLM completions and building robust, production-ready Al agents. Notes for engineers who want to build agents (not just smart bots) that survive contact with real users.
Reading material to know more: Antonio Gulli's (Sr. Distinguished Er, CTO Office, Google) public reference notes.
| <a-waves> | |
| <canvas class="js-canvas"></canvas> | |
| </a-waves><!-- .a-waves -->x |
A Pen by Victor Vergara on CodePen.
| <header> | |
| <h1 class="fluid">you deserve<br />more.</h1> | |
| </header> | |
| <main> | |
| <section class="content fluid"> | |
| <h2><span aria-hidden="true">you can </span> | |
| <span class="sr-only">you can ship things.</span> | |
| </h2> | |
| <ul aria-hidden="true" style="--count: 22"> | |
| <li style="--i: 0">optimize.</li> |
| import multiprocessing #:) | |
| def do_this(number): | |
| print number | |
| return number*2 | |
| # Create a list to iterate over. | |
| # (Note: Multiprocessing only accepts one item at a time) | |
| some_list = range(0,10) |
| """ | |
| Usage: | |
| Make sure that redis is running on localhost (or adjust the url) | |
| Install uvicorn or some other asgi server https://asgi.readthedocs.io/en/latest/implementations.html | |
| pip install -u uvicorn | |
| Install dependencies |