A nutritional label for food for thought.

Related tags

Deep Learning lexiscore
Overview

Lexiscore

As a first effort in tackling the theme of information overload in content consumption, I've been working on the lexiscore: a nutritional label for food for thought designed to help you narrow in on resources which personally bring you the most value. The open source companion software can automatically label raw text originating from RSS feeds, bookmarked pages, PDFs, EPUBs, and more. In the scope of this project, I'm considering valuable resources to be those from which you learn a lot, those which are packed with ideas you find surprising.

Read more...

Installation

Note: This tool requires a running instance of the conceptarium as a proxy for your knowledge.

The lexiscore labeler can either be deployed from source or using Docker.

Docker

To deploy the lexiscore labeler using Docker, first make sure to have Docker installed, then simply run the following.

docker run -p 8501:8501 paulbricman/lexiscore

The tool should be available at localhost:8501.

From Source

To set up the lexiscore labeler, clone the repository and run the following:

python3 -m pip install -r requirements.txt
streamlit run main.py

The tool should be available at localhost:8501.

Screenshots

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Comments
  • RSS OPML only pulls last article

    RSS OPML only pulls last article

    Summary

    Adding RSS from OPML only pulls the last article.

    Details

    After setting up lexiscore, I take my blog's RSS (https://ivans.io/rss/) and convert it to OPML using https://opml-gen.ovh/. This yields the following file:

    <opml version="2.0">
	<body>
		<outline text="Subscriptions" title="Subscriptions">
			<outline xmlUrl='https://ivans.io/rss/' />
	
		</outline>
	</body>
</opml>

    After adding this to lexiscore, only the most recent article appears in the reading list. I've checked the RSS feed, and all articles are fully present.

    Desired Behavior

    RSS feeds should pull all articles.

    opened by issmirnov 4
  • NLTK downloader problem when deploying with docker.

    NLTK downloader problem when deploying with docker.

    I have deployed the docker image to my personal server. After importing the RSS from my blog (https://ivans.io/rss/) as an OPML file, I click on "start labelling". This causes a stack trace:

    LookupError: ********************************************************************** 
Resource punkt not found. Please use the NLTK Downloader to obtain the resource: 
[31m>>> import nltk >>> nltk.download('punkt') 
[0m For more information see: https://www.nltk.org/data.html Attempted to load tokenizers/punkt/PY3/english.pickle
[0m Searched in: - '/root/nltk_data' - '/usr/local/nltk_data' - '/usr/local/share/nltk_data' - '/usr/local/lib/nltk_data' - '/usr/share/nltk_data' - '/usr/local/share/nltk_data' - '/usr/lib/nltk_data' - '/usr/local/lib/nltk_data' - '' **********************************************************************
Traceback:
File "/usr/local/lib/python3.8/site-packages/streamlit/script_runner.py", line 354, in _run_script
    exec(code, module.__dict__)
File "/app/main.py", line 30, in <module>
    cart_section(col2)
File "/app/components.py", line 110, in cart_section
    content_paragraphs = get_paragraphs(row['text'])
File "/app/processing.py", line 19, in get_paragraphs
    sents = sent_tokenize(line)
File "/usr/local/lib/python3.8/site-packages/nltk/tokenize/__init__.py", line 107, in sent_tokenize
    tokenizer = load("tokenizers/punkt/{0}.pickle".format(language))
File "/usr/local/lib/python3.8/site-packages/nltk/data.py", line 750, in load
    opened_resource = _open(resource_url)
File "/usr/local/lib/python3.8/site-packages/nltk/data.py", line 875, in _open
    return find(path_, path + [""]).open()
File "/usr/local/lib/python3.8/site-packages/nltk/data.py", line 583, in find
    raise LookupError(resource_not_found)
    opened by issmirnov 3
  • Add aggregator page as input source

    Add aggregator page as input source

    Imagine adding this as input sources of type "Aggregator": https://metaphor.so/search?q=The%20coolest%20essay%20on%20human-machine%20collaboration%2C%20cognitive%20augmentation%2C%20and%20tools%20for%20thought%20is

    The labeling software would sift through and add a nutritional value filter on top of a cool "search" approach

    enhancement 
    opened by paulbricman 0
  • Save concptarium URL with local cookie

    Save concptarium URL with local cookie

    Currently, I have this deployed via docker on a personal server. On every page refresh, I am asked for the url of the conceptarium. It would be useful to have this URL saved in local cookie storage.

    enhancement 
    opened by issmirnov 1
Releases(v1.0.0)
Owner
Paul Bricman
Building tools which augment the mind.
Paul Bricman
GitHub https://paulbricman.com/thoughtware/lexiscore
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