import streamlit as st import base64 import boto3 st.set_page_config(page_title='Auto-BG: The Game Concept Generator', layout='wide') tab1, tab2, tab3, tab4 = st.tabs(['App', 'Blog', 'Feedback', '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 import base64 #S3 Bucket session = boto3.Session(aws_access_key_id=st.secrets.accesskey, aws_secret_access_key=st.secrets.secretaccesskey) #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']} s3=session.client('s3') reportedjson = s3.get_object(Bucket='auto-bg', Key='reported.json') r_d = pd.read_json(reportedjson.get("Body")) r_df = pd.DataFrame(data, index=[len(r_d)+1]) w_p = pd.concat([r_df, r_d]) w_p = w_p.drop_duplicates().reset_index(drop=True) s3.put_object(Body=w_p.to_json() ,Bucket='auto-bg', Key='reported.json') ###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(): from pathlib import Path st.write('### Auto-BG: The Board Game Concept Generator') st.write("#### Abstract") st.write("*This application augments one step in the board game design process by generating potential full game concepts from a collection of descriptive tags.\ 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 concepts support general users and designers-to-be as alternatives to current concepts, seeds for future concepts, or an entertaining thought experiment.*") # Code adapted from "Display and Download PDF in Streamlit: A Blog Use Case" by My Data Talk, https://towardsdatascience.com/display-and-download-pdf-in-streamlit-a-blog-use-case-5fc1ac87d4b1 path = Path(__file__).parent / 'Auto_BG_Blog.pdf' with open(path, "rb") as blog_file: blog_pdf = base64.b64encode(blog_file.read()).decode('utf-8') blog_display = f'
' st.markdown(blog_display, unsafe_allow_html=True) def about_us(): """ About us page describing creators of Auto-BG """ st.write('### Creators of Auto-BG') st.write('*With a shared love of data science and board games, we came together and created Auto-BG as a Capstone project\ in the "Master of Applied Data Science" program at the University of Michigan.\ We hope you enjoy!*') st.write("\n") # Columns containing information on each of the creators col1, col2, col3 = st.columns([1,1,1]) with col1: st.image('./About_Us_Images/NC.jfif', use_column_width=True) st.subheader('Nick Canu') st.write(""" **University of Michigan**\n ***Master of Applied Data Science, Class of 2023***\n N. Canu trained, evaluated, & implemented pipeline classes text and title generator models for Auto-BG.\n Their current board game obsession is Obsession by Kayenta Games. """) with col2: st.image('./About_Us_Images/TD.jfif', use_column_width=True) st.subheader('Taylor Druhot') st.write(""" **University of Michigan**\n ***Master of Applied Data Science, Class of 2023***\n T. Druhot scoped and designed the Streamlit application. He also built the UI front end & title generator final module, and integrated modules into live application.\n Avid Magic the Gathering Limited player and deck/engine building board games. """) with col3: st.image('./About_Us_Images/SC.jfif', use_column_width=True) st.subheader('Sebastian Capp') st.write(""" **University of Michigan**\n ***Master of Applied Data Science, Class of 2023***\n S. Capp contributed research, text generator prototyping, streamlit application modules, and visualizations.\n Immense fan of Catan, Coup, and any deduction games. """) def feedback(): import pandas as pd from pathlib import Path session = boto3.Session(aws_access_key_id=st.secrets.accesskey, aws_secret_access_key=st.secrets.secretaccesskey) st.subheader('Leave comments below') with st.form('feed',clear_on_submit=True): f = st.text_area('Feedback') sub = st.form_submit_button('Submit') if sub: s3=session.client('s3') feedbackcsv = s3.get_object(Bucket='auto-bg', Key='Feedback.csv') f_f = pd.read_csv(feedbackcsv.get("Body")) f_s = pd.DataFrame({'feedback':f}, index=[0]) f_f = pd.concat([f_f, f_s]) s3.put_object(Body=f_f.to_csv() ,Bucket='auto-bg', Key='Feedback.csv') with tab1: application() with tab2: blog() with tab3: feedback() with tab4: about_us()