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import gradio as gr |
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from gradio_huggingfacehub_search import HuggingfaceHubSearch |
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import pandas as pd |
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def update_table(category): |
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data_dict = { |
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"Overall": { |
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"Rank": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26], |
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"Model": ["Model A", "Model B", "Model C", "Model D", "Model E", "Model F", "Model G", "Model H", "Model I", "Model J", "Model K", "Model L", "Model M", "Model N", "Model O", "Model P", "Model Q", "Model R", "Model S", "Model T", "Model U", "Model V", "Model W", "Model X", "Model Y", "Model Z"], |
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"Votes": [1250, 200, 3150, 4250, 5200, 6150, 7250, 8200, 9150, 10250, 11200, 12150, 13250, 21250, 200, 3150, 4250, 5200, 6150, 7250, 8200, 9150, 10250, 11200, 12150, 13250], |
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"Organization": ["Org A", "Org B", "Org C", "Org D", "Org E", "Org F", "Org G", "Org H", "Org I", "Org J", "Org K", "Org L", "Org M", "Org N", "Org O", "Org P", "Org Q", "Model R", "Model S", "Model T", "Model U", "Model V", "Model W", "Model X", "Model Y", "Model Z"], |
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"License": ["1MIT", "2Apache 2.0", "3GPL", "4MIT", "5Apache 2.0", "6GPL", "7MIT", "8Apache 2.0", "9GPL", "10MIT", "11Apache 2.0", "12GPL", "13MIT", "1MIT", "2Apache 2.0", "3GPL", "4MIT", "5Apache 2.0", "6GPL", "7MIT", "8Apache 2.0", "9GPL", "10MIT", "11Apache 2.0", "12GPL", "13MIT"] |
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}, |
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"Biology": { |
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"Rank": [1, 2], |
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"Model": ["GenePredict", "BioSeq"], |
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"Votes": [180, 160], |
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"Organization": ["BioTech", "Genomics Inc"], |
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"License": ["GPL", "MIT"] |
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} |
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} |
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data = data_dict.get(category, {"Rank": [], "Model": [], "Votes": [], "Organization": [], "License": []}) |
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df = pd.DataFrame(data) |
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return df |
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def submit_vote(vote): |
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return f"Vote '{vote}' submitted successfully!" |
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def submit_model(model_id): |
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if not model_id: |
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return "All fields are required!" |
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url = "https://sdk.nexa4ai.com/task" |
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data = { |
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"model_id": model_id |
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} |
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response = requests.post(url, json=data) |
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if response.status_code == 200: |
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return "Your request has been submitted successfully. We will notify you by email once processing is complete." |
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else: |
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return f"Failed to submit request: {response.text}" |
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with gr.Blocks() as app: |
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with gr.Tabs(): |
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with gr.TabItem("Table"): |
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dropdown = gr.Dropdown( |
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choices=[ |
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"Overall", "Biology", "Physics", "Business", "Chemistry", |
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"Economics", "Philosophy", "History", "Culture", "Computer Science", |
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"Math", "Health", "Law", "Engineering", "Other" |
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], |
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label="Select Category", |
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value="Overall" |
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) |
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initial_data = update_table("Overall") |
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table = gr.Dataframe( |
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headers=["Rank", "Model", "Votes", "Organization", "License"], |
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datatype=["number", "str", "number", "str", "str"], |
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value=initial_data, |
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col_count=(5, "fixed"), |
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) |
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dropdown.change(update_table, inputs=dropdown, outputs=table) |
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with gr.TabItem("Vote"): |
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vote = gr.Radio(choices=["Option 1", "Option 2", "Option 3"], label="Choose your option") |
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submit_button = gr.Button("Submit Vote") |
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submit_result = gr.Label() |
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submit_button.click(fn=submit_vote, inputs=vote, outputs=submit_result) |
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with gr.TabItem("Submit Model"): |
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model_id = HuggingfaceHubSearch( |
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label="Hub Model ID", |
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placeholder="Search for model id on Huggingface", |
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search_type="model", |
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) |
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submit_model_button = gr.Button("Submit Model") |
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submit_model_result = gr.Label() |
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submit_model_button.click(fn=submit_model, inputs=[model_id], outputs=submit_model_result) |
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app.launch() |
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