Skip to content

Instantly share code, notes, and snippets.

LinkedIn Post Analysis Plugins via Semantic Kernel

Overview

The Semantic Kernel framework is a powerful tool that allows users to leverage large language models to transform, analyze, or generate content based on custom-defined prompts. It's particularly useful for domain-specific transformations, complex content analyses, or any other application where a generic predefined language model doesn't suffice.

Plugins

Plugins in the Semantic Kernel framework are essentially predefined templates or prompts that instruct the underlying language model to perform specific tasks. These can range from content translation to perception analysis, summarization, and more.

Setting up Semantic Kernel

@momr
momr / backtracking_template.py
Created February 15, 2022 23:44 — forked from RuolinZheng08/backtracking_template.py
[Algo] Backtracking Template & N-Queens Solution
def is_valid_state(state):
# check if it is a valid solution
return True
def get_candidates(state):
return []
def search(state, solutions):
if is_valid_state(state):
solutions.append(state.copy())
@momr
momr / gist:1025ccf205fd8d3642ef59e986867a6c
Created January 30, 2018 03:04 — forked from speric/gist:6096965
vimtutor Lesson Summaries
Lesson 1 SUMMARY
1. The cursor is moved using either the arrow keys or the hjkl keys.
h (left) j (down) k (up) l (right)
2. To start Vim from the shell prompt type: vim FILENAME <ENTER>
3. To exit Vim type: <ESC> :q! <ENTER> to trash all changes.
OR type: <ESC> :wq <ENTER> to save the changes.