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Sleeping
Sleeping
import streamlit as st | |
import json | |
urls = [ | |
"https://huggingface.co/spaces/awacke1/CB-GR-Chatbot-Blenderbot", | |
"https://huggingface.co/spaces/awacke1/TTS-STT-Blocks", | |
"https://huggingface.co/spaces/awacke1/Prompt-Refinery-Text-to-Image-Generation", | |
"https://huggingface.co/spaces/awacke1/Video-Summary", | |
"https://huggingface.co/spaces/awacke1/AI-MovieMaker-Comedy", | |
"https://huggingface.co/spaces/awacke1/ChatGPT-Memory-Chat-Story-Generator", | |
"https://huggingface.co/spaces/awacke1/CloneAnyVoice", | |
"https://huggingface.co/spaces/awacke1/ChatGPT-Streamlit-2", | |
"https://huggingface.co/spaces/awacke1/WikipediaUltimateAISearch", | |
"https://huggingface.co/spaces/awacke1/RLHF.Cognitive.Episodic.Semantic.Memory", | |
"https://huggingface.co/spaces/awacke1/Memory-Shared", | |
"https://huggingface.co/spaces/awacke1/VideoSwap", | |
"https://huggingface.co/spaces/awacke1/AI-Wikipedia-Search", | |
"https://huggingface.co/spaces/awacke1/AutoMLUsingStreamlit-Plotly", | |
"https://huggingface.co/spaces/awacke1/NLP-Lyric-Chorus-Image", | |
"https://huggingface.co/spaces/awacke1/OpenAssistant-Chatbot-FTW-Open-Source", | |
"https://huggingface.co/spaces/awacke1/ChatGPTStreamlit7", | |
"https://huggingface.co/spaces/awacke1/MultiPDF-QA-ChatGPT-Langchain", | |
"https://huggingface.co/spaces/awacke1/SOTA-Plan", | |
"https://huggingface.co/spaces/awacke1/AIandSmartTools", | |
"https://huggingface.co/spaces/awacke1/3DVirtualFood", | |
"https://huggingface.co/spaces/awacke1/Gradio-Gallery-Health-Medical-Icon-Sets", | |
"https://huggingface.co/spaces/awacke1/DatasetAnalyzer", | |
"https://huggingface.co/spaces/awacke1/PrompTart", | |
"https://huggingface.co/spaces/awacke1/sileod-deberta-v3-base-tasksource-nli", | |
"https://huggingface.co/spaces/awacke1/File-Memory-Operations-Human-Feedback-Gradio", | |
"https://huggingface.co/spaces/awacke1/Bloom.Big.Science.Continual.Generator", | |
"https://huggingface.co/spaces/awacke1/Ontology-Gradio", | |
"https://huggingface.co/spaces/awacke1/HTML5-Aframe-3dMap-Flight", | |
"https://huggingface.co/spaces/awacke1/Bloom.Generative.Writer", | |
"https://huggingface.co/spaces/awacke1/Voice-ChatGPT-Streamlit-12", | |
"https://huggingface.co/spaces/awacke1/HTML5-AR-VR", | |
"https://huggingface.co/spaces/awacke1/AnimationAI", | |
"https://huggingface.co/spaces/awacke1/GenerativeWordsandImages", | |
"https://huggingface.co/spaces/awacke1/AR-VR-IOT-Demo", | |
"https://huggingface.co/spaces/awacke1/ArtStyleFoodsandNutrition", | |
"https://huggingface.co/spaces/awacke1/CarePlanQnAWithContext", | |
"https://huggingface.co/spaces/awacke1/VideoSummaryYoutube3", | |
"https://huggingface.co/spaces/awacke1/AW-01ST-CSV-Dataset-Analyzer", | |
"https://huggingface.co/spaces/awacke1/Try.Playing.Learning.Sharing.On.This", | |
"https://huggingface.co/spaces/awacke1/google-flan-t5-base", | |
"https://huggingface.co/spaces/awacke1/PubMed-Parrot-Paraphraser-on-T5", | |
"https://huggingface.co/spaces/awacke1/Writing-Grammar-And-Paraphrase-w-Pegasus", | |
"https://huggingface.co/spaces/awacke1/runwayml-stable-diffusion-v1-5", | |
"https://huggingface.co/spaces/awacke1/DockerGoFlanT5", | |
"https://huggingface.co/spaces/awacke1/GradioContinualGenerator", | |
"https://huggingface.co/spaces/awacke1/StreamlitSuperPowerCheatSheet" | |
] | |
# Extract the last part of each URL (after the last '/') to serve as the name of the button | |
url_names = [url.split('/')[-1] for url in urls] | |
# Associate each URL with a relevant emoji based on keywords in its name | |
emoji_mapping = { | |
"Chatbot": "π€", | |
"TTS": "π£οΈ", | |
"STT": "π", | |
"Video": "π₯", | |
"MovieMaker": "πΏ", | |
"ChatGPT": "π¬", | |
"Voice": "ποΈ", | |
"Wikipedia": "π", | |
"Memory": "π§ ", | |
"AI": "π§ ", | |
"OpenAssistant": "π€", | |
"3D": "πΆοΈ", | |
"AR": "π", | |
"VR": "πΆοΈ", | |
"Animation": "ποΈ", | |
"Dataset": "π", | |
"Gradio": "π»", | |
"HTML5": "π", | |
"Writing": "βοΈ", | |
"Grammar": "ποΈ", | |
"Paraphrase": "π", | |
"Streamlit": "π " | |
} | |
# Map each URL name to its most relevant emoji | |
url_emojis = [] | |
for name in url_names: | |
associated_emoji = "π" # Default emoji | |
for keyword, emoji in emoji_mapping.items(): | |
if keyword in name: | |
associated_emoji = emoji | |
break | |
url_emojis.append(associated_emoji) | |
#url_emojis[:5], url_names[:5] # Display the first 5 URL names with their associated emojis | |
import streamlit as st | |
import json | |
import webbrowser | |
def get_emoji(name): | |
for key, emoji in emoji_mapping.items(): | |
if key in name: | |
return emoji | |
return "π" | |
def load_votes(): | |
try: | |
with open("votes.json", "r") as f: | |
return json.load(f) | |
except FileNotFoundError: | |
return {url: 0 for url in urls} | |
def save_votes(votes): | |
with open("votes.json", "w") as f: | |
json.dump(votes, f) | |
def main(): | |
votes = load_votes() | |
# Create sorted list of items | |
items = [{"url": url, "name": url.split('/')[-1], | |
"emoji": get_emoji(url.split('/')[-1]), | |
"votes": votes[url]} for url in urls] | |
items.sort(key=lambda x: (-x["votes"], x["name"])) | |
# Display buttons in grid | |
cols = st.columns(4) | |
for i, item in enumerate(items): | |
with cols[i % 4]: | |
if st.button(f"{item['emoji']} {item['name']}", key=item['url']): | |
votes[item['url']] += 1 | |
save_votes(votes) | |
st.rerun() | |
st.write(f"Votes: {item['votes']}") | |
# Display vote graph | |
if any(votes.values()): | |
source = ColumnDataSource({ | |
'names': [i["name"] for i in items if votes[i["url"]] > 0], | |
'votes': [i["votes"] for i in items if votes[i["url"]] > 0] | |
}) | |
p = figure(x_range=source.data['names'], height=350, title="Vote Counts") | |
p.vbar(x='names', top='votes', width=0.9, source=source) | |
p.xaxis.major_label_orientation = 1.2 | |
st.bokeh_chart(p) | |
if __name__ == "__main__": | |
main() |