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Create app.py
Browse files
app.py
ADDED
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import streamlit as st
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import json
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urls = [
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"https://huggingface.co/spaces/awacke1/CB-GR-Chatbot-Blenderbot",
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"https://huggingface.co/spaces/awacke1/TTS-STT-Blocks",
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"https://huggingface.co/spaces/awacke1/Prompt-Refinery-Text-to-Image-Generation",
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"https://huggingface.co/spaces/awacke1/Video-Summary",
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"https://huggingface.co/spaces/awacke1/AI-MovieMaker-Comedy",
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"https://huggingface.co/spaces/awacke1/ChatGPT-Memory-Chat-Story-Generator",
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"https://huggingface.co/spaces/awacke1/CloneAnyVoice",
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"https://huggingface.co/spaces/awacke1/ChatGPT-Streamlit-2",
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"https://huggingface.co/spaces/awacke1/WikipediaUltimateAISearch",
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"https://huggingface.co/spaces/awacke1/RLHF.Cognitive.Episodic.Semantic.Memory",
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"https://huggingface.co/spaces/awacke1/Memory-Shared",
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"https://huggingface.co/spaces/awacke1/VideoSwap",
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"https://huggingface.co/spaces/awacke1/AI-Wikipedia-Search",
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"https://huggingface.co/spaces/awacke1/AutoMLUsingStreamlit-Plotly",
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"https://huggingface.co/spaces/awacke1/NLP-Lyric-Chorus-Image",
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"https://huggingface.co/spaces/awacke1/OpenAssistant-Chatbot-FTW-Open-Source",
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"https://huggingface.co/spaces/awacke1/ChatGPTStreamlit7",
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"https://huggingface.co/spaces/awacke1/MultiPDF-QA-ChatGPT-Langchain",
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"https://huggingface.co/spaces/awacke1/SOTA-Plan",
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"https://huggingface.co/spaces/awacke1/AIandSmartTools",
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"https://huggingface.co/spaces/awacke1/3DVirtualFood",
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"https://huggingface.co/spaces/awacke1/Gradio-Gallery-Health-Medical-Icon-Sets",
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"https://huggingface.co/spaces/awacke1/DatasetAnalyzer",
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"https://huggingface.co/spaces/awacke1/PrompTart",
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"https://huggingface.co/spaces/awacke1/sileod-deberta-v3-base-tasksource-nli",
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"https://huggingface.co/spaces/awacke1/File-Memory-Operations-Human-Feedback-Gradio",
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"https://huggingface.co/spaces/awacke1/Bloom.Big.Science.Continual.Generator",
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"https://huggingface.co/spaces/awacke1/Ontology-Gradio",
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"https://huggingface.co/spaces/awacke1/HTML5-Aframe-3dMap-Flight",
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"https://huggingface.co/spaces/awacke1/Bloom.Generative.Writer",
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"https://huggingface.co/spaces/awacke1/Voice-ChatGPT-Streamlit-12",
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"https://huggingface.co/spaces/awacke1/HTML5-AR-VR",
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"https://huggingface.co/spaces/awacke1/AnimationAI",
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"https://huggingface.co/spaces/awacke1/GenerativeWordsandImages",
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"https://huggingface.co/spaces/awacke1/AR-VR-IOT-Demo",
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"https://huggingface.co/spaces/awacke1/ArtStyleFoodsandNutrition",
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"https://huggingface.co/spaces/awacke1/CarePlanQnAWithContext",
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"https://huggingface.co/spaces/awacke1/VideoSummaryYoutube3",
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"https://huggingface.co/spaces/awacke1/AW-01ST-CSV-Dataset-Analyzer",
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"https://huggingface.co/spaces/awacke1/Try.Playing.Learning.Sharing.On.This",
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"https://huggingface.co/spaces/awacke1/google-flan-t5-base",
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"https://huggingface.co/spaces/awacke1/PubMed-Parrot-Paraphraser-on-T5",
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"https://huggingface.co/spaces/awacke1/Writing-Grammar-And-Paraphrase-w-Pegasus",
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"https://huggingface.co/spaces/awacke1/runwayml-stable-diffusion-v1-5",
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"https://huggingface.co/spaces/awacke1/DockerGoFlanT5",
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"https://huggingface.co/spaces/awacke1/GradioContinualGenerator",
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"https://huggingface.co/spaces/awacke1/StreamlitSuperPowerCheatSheet"
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]
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# Extract the last part of each URL (after the last '/') to serve as the name of the button
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url_names = [url.split('/')[-1] for url in urls]
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# Associate each URL with a relevant emoji based on keywords in its name
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emoji_mapping = {
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"Chatbot": "π€",
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"TTS": "π£οΈ",
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"STT": "π",
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"Video": "π₯",
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"MovieMaker": "πΏ",
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"ChatGPT": "π¬",
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"Voice": "ποΈ",
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"Wikipedia": "π",
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"Memory": "π§ ",
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"AI": "π§ ",
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"OpenAssistant": "π€",
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"3D": "πΆοΈ",
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"AR": "π",
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"VR": "πΆοΈ",
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"Animation": "ποΈ",
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"Dataset": "π",
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"Gradio": "π»",
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"HTML5": "π",
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"Writing": "βοΈ",
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"Grammar": "ποΈ",
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"Paraphrase": "π",
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"Streamlit": "π "
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}
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# Map each URL name to its most relevant emoji
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url_emojis = []
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for name in url_names:
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associated_emoji = "π" # Default emoji
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for keyword, emoji in emoji_mapping.items():
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if keyword in name:
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associated_emoji = emoji
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break
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url_emojis.append(associated_emoji)
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def get_emoji(name):
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for key, emoji in emoji_mapping.items():
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if key in name:
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return emoji
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return "π"
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def load_votes():
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try:
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with open("votes.json", "r") as f:
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return json.load(f)
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except FileNotFoundError:
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return {url: 0 for url in urls}
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def save_votes(votes):
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with open("votes.json", "w") as f:
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json.dump(votes, f)
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def main():
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st.set_page_config(layout="wide")
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if 'current_url' not in st.session_state:
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st.session_state.current_url = None
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votes = load_votes()
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# Create two columns
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col1, col2 = st.columns([1, 2])
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with col1:
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# Create sorted list of items
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items = [{"url": url, "name": url.split('/')[-1],
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"emoji": get_emoji(url.split('/')[-1]),
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"votes": votes[url]} for url in urls]
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items.sort(key=lambda x: (-x["votes"], x["name"]))
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# Display buttons in 2 columns within col1
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button_cols = st.columns(2)
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for i, item in enumerate(items):
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with button_cols[i % 2]:
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if st.button(f"{item['emoji']} {item['name']}", key=item['url']):
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votes[item['url']] += 1
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save_votes(votes)
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st.session_state.current_url = item['url']
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st.rerun()
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st.write(f"Votes: {item['votes']}")
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with col2:
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if st.session_state.current_url:
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st.components.iframe(st.session_state.current_url, height=800, scrolling=True)
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else:
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st.write("Select an app to view")
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# Display vote graph at bottom of col1
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if any(votes.values()):
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with col1:
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source = ColumnDataSource({
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'names': [i["name"] for i in items if votes[i["url"]] > 0],
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'votes': [i["votes"] for i in items if votes[i["url"]] > 0]
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})
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p = figure(x_range=source.data['names'], height=250, title="Vote Counts")
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p.vbar(x='names', top='votes', width=0.9, source=source)
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p.xaxis.major_label_orientation = 1.2
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st.bokeh_chart(p)
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if __name__ == "__main__":
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main()
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