rrational
scrapping reddit.com/r/rational and analytics
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This project has data from r/rational in markdown that you can browse, see ./data/cache2/ for the data.
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This project also has an html table you can see/download at https://wassname.github.io/scrape_r_rational/
More info:
Reddit Discussion: https://old.reddit.com/r/rational/comments/1hoonrc/v2_table_which_stories_have_been_linked_most/
Table Columns
- 'Title': LLM's opinion about the title
- '⬆️': Sum of comment score for associated links
- 'Comments': number of comments with the link in that we found and assocated with this row
- '⭐Qual': LLM's opinion about the users opinion of quality of the fiction out of 10
- '⭐Rat': LLM's opinion about the users opinion of the rating of the fiction
- '⭐Writ': LLM on writing style
- '⭐Plot': LLM on plot
- '⭐Char': LLM on characters
- '⭐World': LLM on wordbuilding
- 'Tags': LLM's opinion about the tags
- 'First Link': Date of the first link
- 'Last Link': Date of the last link
- 'Links': Number of associated links
- 'URLs': List of associated links
- 'Reviews Summary': An LLM was asked to summarize user reviews
- 'Threads': Links to all the threads!!
- 'Comments': Links to all the comments!!
- 'Similar': LLM's opinion about similar fictions
- 'Description': LLM's description
- 'Recommendations': LLM on why a r/rational user would reccomend
- 'Disrecommendations': LLM
- 'Why': LLM
- 'Reviews': An LLM was asked to quote user reivews... it made some of them up
You can see the actuall prompt in <nbs/mjc_005_allm.ipynb>, search for class FictionInfo
For the Table UI I've included
- smart search https://datatables.net/reference/option/search.smart
- search builder https://datatables.net/extensions/searchbuilder/
- save states
- export to excel
- column visibility
Project plan:
- Init
- Fill out README
- Scrape r/rational
- use statistics
- Use llm to get reccomendations, sentiment, karma etc
- share
- comment md to html
- comment expand
- threads where it's mentioned
- better tittles and data cleaning
- github pages
Install requirements
This project uses poetry for requirement and is set up for torch using cuda.
poetry install
Then
cp .env.example .env
Then fill out the api keys
How to run
First run <nbs/mjc_001_download.ipynb> to update the data in <data/cache2/>
Then run <nbs/mjc_004_process.ipynb> to analyse the data and output <index.html>
use <nbs/mjc_005_allm.ipynb> to run an llm from openrouter (costs around $50) and the results are... OK
