app.py

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": "🤖",
    "TTS": "🗣️",
    "STT": "👂",
    "Video": "🎥",
    "MovieMaker": "🍿",
    "ChatGPT": "💬",
    "Voice": "🎙️",
    "Wikipedia": "📖",
    "Memory": "🧠",
    "AI": "🧠",
    "OpenAssistant": "🤝",
    "3D": "🕶️",
    "AR": "👓",
    "VR": "🕶️",
    "Animation": "🖌️",
    "Dataset": "📊",
    "Gradio": "📻",
    "HTML5": "🌐",
    "Writing": "✍️",
    "Grammar": "🖋️",
    "Paraphrase": "🔄",
    "Streamlit": "🌠"
}

# Map each URL name to its most relevant emoji
url_emojis = []
for name in url_names:
    associated_emoji = "🔗"  # Default emoji
    for keyword, emoji in emoji_mapping.items():
        if keyword in name:
            associated_emoji = emoji
            break
    url_emojis.append(associated_emoji)


def get_emoji(name):
    for key, emoji in emoji_mapping.items():
        if key in name:
            return emoji
    return "🔗"

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():
    st.set_page_config(layout="wide")
    
    if 'current_url' not in st.session_state:
        st.session_state.current_url = None
    
    votes = load_votes()
    
    # Create two columns
    col1, col2 = st.columns([1, 2])
    
    with col1:
        # 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 2 columns within col1
        button_cols = st.columns(2)
        for i, item in enumerate(items):
            with button_cols[i % 2]:
                if st.button(f"{item['emoji']} {item['name']}", key=item['url']):
                    votes[item['url']] += 1
                    save_votes(votes)
                    st.session_state.current_url = item['url']
                    st.rerun()
                st.write(f"Votes: {item['votes']}")

    with col2:
        if st.session_state.current_url:
            st.components.iframe(st.session_state.current_url, height=800, scrolling=True)
        else:
            st.write("Select an app to view")

    # Display vote graph at bottom of col1
    if any(votes.values()):
        with col1:
            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=250, 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()