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import streamlit as st
st.set_page_config(page_title='Auto-BG: The Game Concept Generator', layout='wide')
tab1, tab2, tab3 = st.tabs(['App', 'Blog', 'About Us'])
def application():
###Imports
import pandas as pd
import numpy as np
import re
import urllib
import pickle
import spacy
from spacy.tokens import DocBin
from title_generator import Title_Generator
import gzip
import io
from datetime import date
from description_generator import input_manager, model_control
from pathlib import Path
#UI Session Variables
if 'desc_iter' not in st.session_state:
st.session_state.desc_iter = 0
if 'title_iter' not in st.session_state:
st.session_state.title_iter = 0
if 'output_dict' not in st.session_state:
st.session_state.output_dict = {}
if 'inputs' not in st.session_state:
st.session_state.inputs = []
if 'cur_pair' not in st.session_state:
st.session_state.cur_pair = ("","Run me!")
if 'f_d' not in st.session_state:
st.session_state.f_d = None
if 'g_d' not in st.session_state:
st.session_state.g_d = None
if 'm_d' not in st.session_state:
st.session_state.m_d = None
if 'c_d' not in st.session_state:
st.session_state.c_d = None
if 'coop_d' not in st.session_state:
st.session_state.coop_d = 0
#helper functions
#reader code extended from https://gist.github.com/thearn/5424244 for alternate load format
def reader(path):
f = gzip.GzipFile(filename=path)
data = f.read()
obj = pickle.loads(data)
f.close()
return obj
def token_expand(path):
nlp = spacy.blank("en")
f = gzip.GzipFile(filename=path)
data = f.read()
obj = pickle.loads(data)
f.close()
doc_bin = DocBin().from_bytes(obj)
docs = list(doc_bin.get_docs(nlp.vocab))
return (docs[1:9],docs[9:192],docs[192:276],docs[276:3901])
def revert_cats(gt, mec, cat, fam, coop):
gt = ["game_type_" + x for x in gt]
mec = ["mechanic_" + x for x in mec]
cat = ["category_" + x for x in cat]
fam = ["family_" + x for x in fam if x != "Game: [redacted]"]
if coop == 1:
co = ["cooperative", "mechanic_Cooperative Game"]
else:
co = []
final_list = [gt,mec,cat,fam, co]
return [item for sublist in final_list for item in sublist]
def builder(ip):
ks = iman.input_parser(iman.set_input(ip))
mctrl.prompt_formatter(ks)
descs = []
for status in np.arange(0,3):
desc = mctrl.call_api(status=status)
clean_desc = mctrl.resp_cleanup(desc)
inter_pair = Tgen.candidate_generator(clean_desc)
out = Tgen.candidate_score(inter_pair,ex_check)
descs.append(out)
results.success("Prompt " +str(status+1)+ "/3 Generated!")
st.session_state.output_dict = {0:descs[0],1:descs[1],2:descs[2]}
def title_check(next=0):
if next==1:
if st.session_state.title_iter == (len(st.session_state.output_dict[st.session_state.desc_iter]['titles'])-1):
st.session_state.title_iter = 0
else:
st.session_state.title_iter +=1
elif next==-1:
if st.session_state.title_iter == 0:
st.session_state.title_iter = (len(st.session_state.output_dict[st.session_state.desc_iter]['titles'])-1)
else:
st.session_state.title_iter -=1
else:
st.session_state.title_iter = 0
cur_title = st.session_state.output_dict[st.session_state.desc_iter]['titles'][st.session_state.title_iter][0]
desc = re.sub(re.compile("__"),cur_title,st.session_state.output_dict[st.session_state.desc_iter]['text'])
return (cur_title, desc.lstrip())
def show_title(val):
out = title_check(next=val)
st.session_state.cur_pair = out
def PT_button_clicked():
show_title(-1)
def NT_button_clicked():
show_title(1)
def PD_button_clicked():
if st.session_state.desc_iter == 0:
st.session_state.desc_iter = 2
st.session_state.title_iter = 0
else:
st.session_state.desc_iter -= 1
st.session_state.title_iter = 0
show_title(0)
def ND_button_clicked():
if st.session_state.desc_iter == 2:
st.session_state.desc_iter = 0
st.session_state.title_iter = 0
else:
st.session_state.desc_iter += 1
st.session_state.title_iter = 0
show_title(0)
def report():
inputs = '|'.join(str(x) for x in st.session_state.inputs)
data = {'rprtd': date.today(),'inpts': inputs, 'title': st.session_state.output_dict[st.session_state.desc_iter]['titles'][st.session_state.title_iter][0], 'desc':st.session_state.output_dict[st.session_state.desc_iter]['text']}
try:
r_df = pd.DataFrame(data, index=[0])
r_p = pd.read_pickle(Path(__file__).parent / "Persistent_Data/reported_df.PICKLE")
w_p = pd.concat([r_df, r_p])
w_p = w_p.drop_duplicates()
print('try')
print(w_p)
w_p.to_pickle(Path(__file__).parent / "Persistent_Data/reported_df.PICKLE")
except:
print('except')
print(r_df)
r_df.to_pickle(Path(__file__).parent / "Persistent_Data/reported_df.PICKLE")
###Variables
###Data
@st.cache_data
def fetch_data():
#path load solution from https://stackoverflow.com/questions/69768380/share-streamlit-cant-find-pkl-file
slim_df = pd.read_parquet(Path(__file__).parent / "Persistent_Data/slim_df.parquet.gzip")
search_tokens = token_expand(Path(__file__).parent / "Persistent_Data/token_search.gz")
vector_df = pd.read_parquet(Path(__file__).parent / 'Persistent_Data/vector_df.parquet.gzip')
category_keys = reader(Path(__file__).parent / "Persistent_Data/current_keys.gz")
return slim_df, search_tokens, vector_df, category_keys
slim_df, search_tokens, vector_df, category_keys = fetch_data()
ex_check = ["[Ee]verquest","[Cc]ivilization [Ii][IiVv]","[Cc]ivilization(?=:)","[Cc]ivilization [Ii][Ii]",
"[Cc]ivilization [Ii][Ii][Ii]","[Cc]ivilization V","[Aa]ge [Oo]f [Ee]mpires [Ii][Ii2]([Ii]|\b)", "[Rr]avenloft|[Cc]astle [Rr]avenloft",
"[Ss]cythe(?=:|\b)","[Dd]ungeons [&Aa][ n][Dd ][ Ddr][Ddra][rg][oa][gn][os](ns|\b)",
"[Aa]ge [Oo]f [Ee]mpires [Ii][Ii]: [Tt]he [Aa]ge [Oo]f [Kk]ings","[Aa]ge [Oo]f [Ee]mpires 2: [Tt]he [Aa]ge [Oo]f [Kk]ings",
"[Aa]ge [Oo]f [Ee]mpires","Doctor Who"]
###Models
@st.cache_resource
def setup_models():
spacy.cli.download("en_core_web_md")
return Title_Generator('./t5_model', slim_df), input_manager(vector_df, slim_df, search_tokens), model_control(apikey=st.secrets.key,model_id=st.secrets.model)
Tgen, iman, mctrl = setup_models()
#UI
#Application
###Intro
st.title("""Auto-BG: The Game Concept Generator""")
with st.expander("How to use", expanded=True):
st.write(
"""
Discover the concept for your next favorite game!
How do you use Auto-BG?
Pick any set of tags from four selectors below: Family, Game, Mechanic, and Category.
If you are looking to lose together - activate the cooperative toggle.
See ? icons for detailed information on each type of tag.
Select any pre-configured demo below to see how Auto-BG works on the tag set for a popular board game.
"""
)
results = st.empty()
###Demo
with st.expander('Demos'):
st.write("""These buttons run Auto-BG on the tag set for real games you might be familiar with,
choose a button and the corresponding tags automatically fill the selectors below.
Press run and see how Auto-BG creates an alternate concept for these hit titles!
""")
b1, b2, b3 = st.columns(3)
with b1:
SoC = st.button('Catan', use_container_width=True)
if SoC:
st.session_state.f_d = [
'Animals: Sheep',
'Components: Hexagonal Tiles',
'Components: Wooden pieces & boards'
]
st.session_state.g_d = ['Family Game', 'Strategy Game']
st.session_state.m_d = [
'Hexagon Grid',
'Network and Route Building',
'Random Production',
'Trading',
'Variable Set-up'
]
st.session_state.c_d = [
'Economic',
'Negotiation'
]
st.session_state.coop_d = 0
with b2:
TtR = st.button('Ticket to Ride', use_container_width=True)
if TtR:
st.session_state.f_d = [
'Components: Map (Continental / National scale)',
'Continents: North America',
'Country: USA'
]
st.session_state.g_d = ['Family Game']
st.session_state.m_d = [
'Contracts',
'End Game Bonuses',
'Network and Route Building',
'Push Your Luck',
'Set Collection'
]
st.session_state.c_d = [
'Trains'
]
st.session_state.coop_d = 0
with b3:
P = st.button('Pandemic', use_container_width=True)
if P:
st.session_state.f_d = [
'Components: Map (Global Scale)',
'Components: Multi-Use Cards',
'Medical: Diseases',
'Region: The World',
'Theme: Science'
]
st.session_state.g_d = ['Family Game', 'Strategy Game']
st.session_state.m_d = [
'Action Points',
'Point to Point Movement',
'Trading',
'Variable Player Powers'
]
st.session_state.c_d = [
'Medical'
]
st.session_state.coop_d = 1
###Form
with st.expander("Auto-BG", expanded=True):
col1, col2 = st.columns(2)
with col1:
Family_v = st.multiselect("Family", options=pd.Series(category_keys[4][8:]), key='Family', default=st.session_state.f_d, max_selections=6, help='Descriptive niches for groupings of games.\n Maximum of six choices.')
with col2:
Game_v = st.multiselect("Game", options=pd.Series(category_keys[1]), key='Game', default=st.session_state.g_d, max_selections=2, help='Top level genres - Family, Strategy, etc.\n Maximum of two choices.')
col3, col4 = st.columns(2)
with col3:
Category_v = st.multiselect("Category", options=pd.Series(category_keys[3]), key='Category', default=st.session_state.c_d, max_selections=3, help='Expanded genre tags.\n Maximum of three choices.')
with col4:
Mechanics_v = st.multiselect("Mechanics", options=pd.Series([x for x in category_keys[2] if x != "Cooperative Game"]), key='Mechanic', default=st.session_state.m_d, max_selections=5, help='Game rules!\n Maximum of five choices.')
Cooperative_v = st.checkbox('Cooperative?', value=st.session_state.coop_d, key='CoopCheck')
run = st.button("Run Model", use_container_width=True)
if run:
if st.session_state.inputs == revert_cats(Game_v, Mechanics_v, Category_v, Family_v, Cooperative_v):
st.write('Inputs did not change, results currently loaded.')
else:
st.session_state.desc_iter = 0
st.session_state.title_iter = 0
st.session_state.output_dict = {}
if Cooperative_v == True:
Mechanics_v.append('Cooperative Game')
st.session_state.inputs = revert_cats(Game_v, Mechanics_v, Category_v, Family_v, Cooperative_v)
builder(st.session_state.inputs)
st.session_state.cur_pair = title_check()
if st.session_state.output_dict == {}:
results.empty()
else:
with results.expander('Results', expanded=True):
st.write(
"""
#### Title:
""")
st.write(st.session_state.cur_pair[0])
t_col1, t_col2 = st.columns(2)
with t_col1:
st.button("See Previous Title", on_click=PT_button_clicked, use_container_width=True)
with t_col2:
st.button("See Next Title", on_click=NT_button_clicked, use_container_width=True)
st.write(
"""
#### Description:
""")
st.write(st.session_state.cur_pair[1].replace('$','\$'))
d_col1, d_col2 = st.columns(2)
with d_col1:
st.button("See Previous Description", on_click=PD_button_clicked, use_container_width=True)
with d_col2:
st.button("See Next Description", on_click=ND_button_clicked, use_container_width=True)
st.button('Report', on_click=report, use_container_width=True)
def blog():
"""
Blog describing the Auto-BG project
"""
with open("BGG Blog MD.md", 'r') as blog_md:
blog_text = blog_md.read()
st.markdown(blog_text)
st.sidebar.subheader('Auto-BG: The Board Game Concept Generator')
st.sidebar.write("*This application attempts to augment one step, early in that journey, when the seeds of an idea combine and sprout into a holistic concept.\
By interpreting disparate mechanical and descriptive tags to identify a game concept, Auto-BG uses a custom pipeline of GPT3 and T5 models to create a new description and proposed titles for a game that doesn't exist today.\
These descriptions support designers-to-be as alternatives to current concepts, seeds for future concepts, or any user as, hopefully, an entertaining thought experiment.*")
def about_us():
"""
About us page describing creators of Auto-BG
"""
st.title("About Us")
st.sidebar.subheader('Creators of Auto-BG')
st.sidebar.write('*With a shared love of data science and board games, we came together and created Auto-BG as part of our Capstone project\
for our "Master of Applied Data Science" program at the University of Michigan.\
We hope you enjoy!*')
# Columns containing information on each of the creators
col1, col2, col3 = st.columns([1,1,1])
with col1:
st.image('./NC.jfif', use_column_width=True)
st.subheader('Nick Canu')
st.write("""
**University of Michigan**\n
*MADS (Master of Applied Data Science)*\n
""")
with col2:
st.image('./TD.jfif', use_column_width=True)
st.subheader('Taylor Druhot')
st.write("""
**University of Michigan**\n
*MADS (Master of Applied Data Science)*\n
""")
with col3:
st.image('./SC.jfif', use_column_width=True)
st.subheader('Sebastian Capp')
st.write("""
**University of Michigan**\n
*MADS (Master of Applied Data Science)*\n
""")
with tab1:
application()
with tab2:
blog()
with tab3:
about_us()
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