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| import streamlit as st | |
| 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 | |
| #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 | |
| 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 | |
| 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('./About_Us_Images/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('./About_Us_Images/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('./About_Us_Images/SC.jfif', use_column_width=True) | |
| st.subheader('Sebastian Capp') | |
| st.write(""" | |
| **University of Michigan**\n | |
| *MADS (Master of Applied Data Science)*\n | |
| """) | |
| 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() |