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| import streamlit as st | |
| import pandas as pd | |
| from transformers import pipeline | |
| # Load the zero-shot classification model | |
| classifier = pipeline("zero-shot-classification", | |
| model="facebook/bart-large-mnli") | |
| # Sample dataset (replace this with your actual dataset) | |
| df = pd.read_csv('datasets.csv') | |
| def tag_finder(user_input): | |
| keywords = df['Keyword'].unique() | |
| result = classifier(user_input, keywords) | |
| threshold = result['scores'][0] | |
| for score in result['scores']: | |
| if score == threshold: | |
| continue | |
| if (threshold - score) >= threshold / 10: | |
| threshold = score | |
| else: | |
| break | |
| useful_tags = [result['labels'][idx] for idx, score in enumerate(result['scores']) if score >= threshold] | |
| relevant_datasets = [] | |
| for tag in useful_tags: | |
| relevant_datasets.extend(df[df['Keyword'] == tag]['Datasets'].tolist()) | |
| return useful_tags, relevant_datasets | |
| # Define the Streamlit app | |
| def main(): | |
| # Set title and description | |
| st.title("Dataset Finder") | |
| st.write("Enter short description about your ML model below and get relevant tags for your dataset.") | |
| # Get user input | |
| user_input = st.text_input("Enter the description:") | |
| if st.button("Submit"): | |
| # Find relevant tags and datasets | |
| relevant_tags, relevant_datasets = tag_finder(user_input) | |
| # Display relevant tags | |
| if relevant_tags: | |
| st.subheader("Datasets:") | |
| for dataset in relevant_datasets: | |
| tag = df[df['Datasets'] == dataset]['Keyword'].iloc[0] | |
| st.markdown(f''' | |
| <div style="border: 2px solid #555; border-radius: 10px; padding: 10px; margin-bottom: 10px; background-color: #333; color: white; display: flex; justify-content: space-between; align-items: center;"> | |
| <div>{dataset}</div> | |
| <div style="padding: 5px 10px; border: #fff 2px solid; border-radius: 5px;transition: background-color 0.3s;"><a href="https://datasetsearch.research.google.com/search?search&src=0&query={dataset}" style = "text-decoration: none; color: white;">link</a></div> | |
| <div style="border: 1px solid #666; padding: 5px; background-color: #444; border-radius: 12px;"> | |
| <img width="20" height="20" style="margin: 5px;" src="https://img.icons8.com/ios/50/ffffff/price-tag--v2.png" alt="price-tag--v2"/>{tag} | |
| </div> | |
| </div> | |
| ''', unsafe_allow_html=True) | |
| else: | |
| st.warning("No relevant tags found.") | |
| # Run the app | |
| if __name__ == "__main__": | |
| main() | |