Lecture 14
Agenda
Recap of what we learned on Tuesday
Discussion of Chrome extensions
Filling out FINAL PROJECT GROUP SURVEY
Ideation discussion for final project
(If time) Local LLM Integration Project
What are we learning? (1)
Client/server architectures
With
Render
you deploy a
server
With local code you are creating a
client
"Standardization"
We have decided on a "standard"
Send:
{ "password": "
<password to check>
" }
Respond:
{ "valid":
true/false
, "reason": "
<human readable error reason>
" }
Importantly, the "reason" is not software readable (it would require standardizing the error strings)
This allows many servers to interact with many clients
What are we learning? (2)
Learning how to deploy from GitHub
Learning about "Infrastructure as Code" (render.yaml)
Learning about
remote deployment (https://cis3500-buggy-password-validator.onrender.com/)
local deployment (http://localhost:5324)
Learning how to make GET/POST requests
with CURL in the terminal
with
requests.get()
and
requests.post()
in Python
with RapidAPI or Postman
Learning about JSON, content-types, parsing
What are we learning? (3)
"Grokking"
"To understand something so deeply and holistically that it becomes second nature."
(Martian word from sci-fi author Robert A. Heinlein in 1961 novel
Stranger in a Strange Land
)
The kinds of problems you may encounter
Uses Python 3 but you don't have it
Uses Python 3.12 but you have Python 3.11
Documentation shows endpoint that isn't yours
Forgot to install packages
Forgot to use virtual environment (or pipenv)
Chrome Extension
Presentation
Ideation
Data Extractors
Data Extractors
Extract data from your context
That is useful to paste in ChatGPT
Create extensions that simplify this process
Ideation workshop now
Activity as a group (15 mins)
Download the LLM Use Case Sheets
Create a list of
all the data types that are necessary to create prompts
Activity as an individual (10 mins)
Come up with ideas of data extractors
Design a Chrome extension idea
Activity as group (10 mins)