You are an AI assistant tasked with creating well-structured planning specification documents for feature requests, bug reports, or improvement ideas. Your goal is to turn the provided feature description into a comprehensive specification document that follows best practices and project conventions.
Here is the feature description for you to create the specification document for: <feature_description> #$ARGUMENTS </feature_description>
Here are the steps you need to take to produce the specification document: FOLLOW ALL STEPS. Make a todo list and ultrathink:
| # Summarizes text using using importance of words occuring in sentences | |
| # if a paragraph has 10 sentences this will pick the sentence which has words with maximum tfidf cumulative | |
| from nltk.corpus import movie_reviews | |
| reviews = [movie_reviews.raw(filename) for filename in movie_reviews.fileids()] | |
| # create document-term matrix | |
| tfidf = TfidfVectorizer(stop_words='english') | |
| dtm = tfidf.fit_transform(reviews) | |
| features = tfidf.get_feature_names() |
| You are Lyra, a master-level AI prompt optimization specialist. Your mission: transform any user input into | |
| precision-crafted prompts that unlock Al's full potential across all platforms. | |
| ## THE 4-D METHODOLOGY | |
| ### 1. DECONSTRUCT | |
| - Extract core intent, key entities, and context | |
| - Identify output requirements and constraints | |
| - Map what's provided vs. what's missing |
(Based on info from Peter Downs' gitub but with modified behavior to open a new terminal window for each invocation instead of reusing an already open window.)
The following three ways to launch an iTerm2 window from Finder have been tested on iTerm2 version 3+ running on macOS Mojave+.
pdanford - April 2020
Since we're dealing with simpler AV1 encoding, that does mean we'll be eskewing aomenc-av1, since it requires 2-pass encoding to be able to take advantage of it, and I use it externally since I have access to a special build.
Now, let's get on with the simple guide.
You'll first need to be reasonably competent with command line builds or use a recent up to date ffmpeg GUI with support for SVT-AV1.
As such, I would recommend getting a master git ffmpeg build for the operating system of your choice right here:
Using GPU-PV, you can create a partition of your GPU and assign it to a Windows virtual machine
Make sure your GPU is visible.
