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I tried making a bot write an omo story


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i did as the title stated but i tried to take some short cuts while writing the program and here are the fruits of my labor 
 

 

 

“She did a good point of the game but I wanna is a little too late to go back and get it and I have decided it was going on with her she said and her diaper was messed her diaper and cleaned up and cleaned it out she had to a diaper and cleaned up she had to let go of the bed she was soaked in the bathroom she had a good job and cleaned her room she had to let go of it I had her bladder started her diaper she and she had a diaper diaper and she cleaned her room she had to her diaper she was cut her legs together she had to let go of the bed she was soaked she had a good job and I didn’t want to know she had to her privates she had a good job she was going to go pick her out her clothes and then I got her diaper bag and then she grabbed the door and she looked in and her diaper bag was ready she had a bag of wet wipes she was soaked in her clothes she was bag bag bag bag bag bag bag bag bag bag bag bag bag bag bag bag bag bag bag bag bag bag bag bag bag bag bag bag“

 

as you can see i cut it off because it endlessly said bag i do not what made it do this and i don’t want to 

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Better than the Mad-Libs program I wrote.  Typical output:

This kludge generates yard-tenting tweets.
Why?   I don't Know.

Mildred seems the southern plushy bunnies.

Hazel appears a southern milkshake .

Hazel hugs bedroom for a lively kitten .

awesome Hatsu kisses intelligent Confucius .

Mildred plays over active squirts.

Aki dances dryly a big cup .

Sakura kisses winningly for a lively couch .

Mitsu and Mitsu drink slowly .

while bed time Misa sneaks truthfully about the attractive soup .

after night Mitsu applies reliably below a cottony roof .

colorful computer sings

  YardTentingTweetsSpelling.py

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This reminds me of a thread I made a few days ago, in which a Neural Net story prompt generator could be adapted to prompt omorashi stories (albeit with some effort and patience)

Yeah that one worked fairly OK, although I suppose a lot of that is that it had a dataset of around 8 million web pages to work on rather than about 30 stories, neural nets tend to be terrible no matter what you do with so little input

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