Ai solution for Luhmann's Zettelkasten
Project description
A command line utility for topic discovery and doc-linking within the Zettelkasten using AI approaches.
Installation
Install zmsai by executing the following command-
$ pip install zmsai
Test Run
Test run using dummy docs (see ./custom)
$ zmsai test
Usage
To learn n topics in your Zettelkasten at /path/to/your/zettelkasten/-
$ zmsai run -t n -p "/path/to/your/zettelkasten/"
This will create a metadata file meta.zms storing all the distributions exhibited by the documents in your Zettelkasten.
[Running the model] it may take a while. Hang tight!
[Data stored] ... kb
You can delete your metadata file by executing-
$ zmsai delete
These learnt distributions can be printed using zmsai display. You can pass an additional argument -w, the number of top most occuring words that you want to print from the distributions involing words.
To display doc-topic distribution-
$ zmsai display -d dt
To display topic-word distribution-
$ zmsai display -w n -d tw
To display doc-word distribution-
$ zmsai display -w n -d dw
To display vocabulary-
$ zmsai display -w n -d voc
To display all distributions at once-
$ zmsai display -w n -d all
or simply
$ zmsai display
This will take default value of 5 for nwords argument.
Manual
usage: zmsai [-h] [--path [PATH]] [--topics [TOPICS]] [--nwords [NWORDS]] [--distro [DISTRO]] [task]
positional arguments:
task Provide task to perform [default : 'run'] [values : 'run', 'delete', 'display', 'man', 'test']
optional arguments:
-h, --help show this help message and exit
--path [PATH], -p [PATH]
Provide directory of text files. [with : 'run'] [default : './custom']
--topics [TOPICS], -t [TOPICS]
How many topics do you expect? [with : 'run'] [default : 'number of docs']
--nwords [NWORDS], -w [NWORDS]
How many words per topic/doc do you want to display? [with : 'display'] [default : 5]
--distro [DISTRO], -d [DISTRO]
What distributions do you want to display? [with : 'display'] [default : all] [values : 'dt', 'tw', 'dw', 'voc', 'all']
Dependency Graph
attrs==20.2.0
- pytest==6.1.1 [requires: attrs>=17.4.0]
iniconfig==1.1.1
- pytest==6.1.1 [requires: iniconfig]
joblib==0.17.0
- scikit-learn==0.23.2 [requires: joblib>=0.11]
- sklearn==0.0 [requires: scikit-learn]
numpy==1.19.2
- scikit-learn==0.23.2 [requires: numpy>=1.13.3]
- sklearn==0.0 [requires: scikit-learn]
- scipy==1.5.3 [requires: numpy>=1.14.5]
- scikit-learn==0.23.2 [requires: scipy>=0.19.1]
- sklearn==0.0 [requires: scikit-learn]
pip==20.1.1
pluggy==0.13.1
- pytest==6.1.1 [requires: pluggy>=0.12,<1.0]
py==1.9.0
- pytest==6.1.1 [requires: py>=1.8.2]
pyparsing==2.4.7
- packaging==20.4 [requires: pyparsing>=2.0.2]
- pytest==6.1.1 [requires: packaging]
setuptools==46.4.0
six==1.15.0
- packaging==20.4 [requires: six]
- pytest==6.1.1 [requires: packaging]
threadpoolctl==2.1.0
- scikit-learn==0.23.2 [requires: threadpoolctl>=2.0.0]
- sklearn==0.0 [requires: scikit-learn]
toml==0.10.1
- pytest==6.1.1 [requires: toml]
wheel==0.34.2
Contribution
Are welcome.
License
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