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| import numpy as np | |
| import streamlit as st | |
| import plotly.graph_objects as go | |
| from transformers import pipeline | |
| st.set_page_config( | |
| page_title="Fill Mask", | |
| page_icon="🚀") | |
| # App Title | |
| st.title("Zero-Shot Text Classification") | |
| # Initialize the zero-shot classification pipeline | |
| zero_shot = pipeline("zero-shot-classification", model="facebook/bart-large-mnli") | |
| # Colors | |
| colors = ['rgba(24, 203, 162, 1)', 'rgba(34, 180, 20, 1)', 'rgba(231, 110, 212, 1)', 'rgba(191, 206, 164, 1)', 'rgba(100, 233, 42, 1)', | |
| 'rgba(185, 222, 92, 1)', 'rgba(27, 157, 138, 1)', 'rgba(212, 207, 155, 1)', 'rgba(172, 202, 164, 1)', 'rgba(47, 65, 177, 1)', | |
| 'rgba(26, 44, 233, 1)', 'rgba(65, 242, 9, 1)', 'rgba(171, 50, 253, 1)', 'rgba(125, 201, 227, 1)', 'rgba(135, 196, 15, 1)', | |
| 'rgba(114, 106, 242, 1)', 'rgba(176, 50, 34, 1)', 'rgba(100, 159, 247, 1)', 'rgba(246, 103, 72, 1)', 'rgba(180, 180, 5, 1)', | |
| 'rgba(64, 29, 164, 1)', 'rgba(65, 192, 5, 1)', 'rgba(149, 97, 155, 1)', 'rgba(210, 2, 107, 1)', 'rgba(70, 203, 162, 1)', | |
| 'rgba(68, 74, 64, 1)', 'rgba(164, 42, 173, 1)', 'rgba(220, 37, 239, 1)', 'rgba(76, 89, 84, 1)', 'rgba(29, 190, 84, 1)', | |
| 'rgba(180, 35, 240, 1)', 'rgba(222, 72, 217, 1)', 'rgba(203, 80, 243, 1)', 'rgba(121, 164, 68, 1)', 'rgba(107, 218, 79, 1)', | |
| 'rgba(152, 225, 65, 1)', 'rgba(57, 170, 43, 1)', 'rgba(77, 131, 61, 1)', 'rgba(145, 101, 161, 1)', 'rgba(115, 77, 3, 1)', | |
| 'rgba(29, 159, 63, 1)', 'rgba(71, 105, 200, 1)', 'rgba(98, 78, 55, 1)', 'rgba(242, 159, 60, 1)', 'rgba(175, 67, 54, 1)', | |
| 'rgba(120, 246, 81, 1)', 'rgba(216, 132, 219, 1)', 'rgba(82, 77, 251, 1)', 'rgba(213, 29, 120, 1)', 'rgba(252, 90, 31, 1)', | |
| 'rgba(194, 181, 168, 1)', 'rgba(246, 60, 189, 1)', 'rgba(22, 50, 26, 1)', 'rgba(54, 11, 134, 1)', 'rgba(27, 103, 59, 1)', | |
| 'rgba(234, 96, 187, 1)', 'rgba(167, 157, 215, 1)', 'rgba(104, 1, 252, 1)', 'rgba(76, 121, 131, 1)', 'rgba(65, 250, 218, 1)', | |
| 'rgba(219, 59, 127, 1)', 'rgba(18, 242, 194, 1)', 'rgba(14, 132, 131, 1)', 'rgba(82, 68, 61, 1)', 'rgba(109, 229, 43, 1)', | |
| 'rgba(202, 96, 66, 1)', 'rgba(216, 112, 64, 1)', 'rgba(101, 215, 114, 1)', 'rgba(85, 234, 109, 1)', 'rgba(17, 43, 113, 1)', | |
| 'rgba(104, 132, 5, 1)', 'rgba(23, 177, 214, 1)', 'rgba(112, 131, 160, 1)', 'rgba(142, 43, 188, 1)', 'rgba(189, 61, 176, 1)', | |
| 'rgba(196, 198, 61, 1)', 'rgba(253, 176, 165, 1)', 'rgba(113, 143, 126, 1)', 'rgba(122, 156, 220, 1)', 'rgba(221, 11, 29, 1)', | |
| 'rgba(233, 200, 5, 1)', 'rgba(232, 176, 217, 1)', 'rgba(199, 6, 130, 1)', 'rgba(140, 118, 154, 1)', 'rgba(177, 46, 36, 1)', | |
| 'rgba(244, 81, 66, 1)', 'rgba(94, 99, 24, 1)', 'rgba(159, 90, 50, 1)', 'rgba(67, 144, 236, 1)', 'rgba(78, 202, 143, 1)', | |
| 'rgba(13, 116, 114, 1)', 'rgba(139, 194, 124, 1)', 'rgba(174, 63, 214, 1)', 'rgba(84, 114, 130, 1)', 'rgba(143, 208, 199, 1)', | |
| 'rgba(27, 60, 225, 1)', 'rgba(69, 228, 28, 1)', 'rgba(167, 157, 10, 1)', 'rgba(61, 185, 55, 1)', 'rgba(143, 52, 233, 1)'] | |
| colors = np.array(colors) | |
| # Input Section | |
| st.write("Enter a sentence or text to classify and provide possible labels.") | |
| user_input = st.text_input("Input your text:", "Streamlit is an amazing tool for building web apps.") | |
| labels_input = st.text_input("Enter possible labels (comma-separated):", "technology, finance, health") | |
| # Process and Display Results | |
| if st.button("Classify Text"): | |
| labels = [label.strip().title() for label in labels_input.split(",") if label.strip()] | |
| if not user_input or not labels: | |
| st.error("Please provide both text and at least one label.") | |
| else: | |
| try: | |
| st.write("## Classification Results:") | |
| probabilities = [] | |
| result = zero_shot(user_input, labels) | |
| labels.clear() | |
| for label, score in zip(result['labels'], result['scores']): | |
| labels.append(label) | |
| probabilities.append(round(score, 2)) | |
| fig = go.Figure(data=[ | |
| go.Bar( | |
| x=labels, | |
| y=probabilities, | |
| marker_color=np.random.choice(colors, len(labels)).tolist(), # Colors for each category | |
| text=probabilities, # Show values on the bars | |
| textposition='auto' | |
| ) | |
| ]) | |
| # Customize layout | |
| fig.update_layout( | |
| # title="Sentiment Analysis Results", | |
| xaxis_title="Label", | |
| yaxis_title="Probability", | |
| template="seaborn", | |
| ) | |
| # Show the figure | |
| st.plotly_chart(fig, use_container_width=True, theme=None) | |
| except Exception as e: | |
| st.error(f"An error occurred: {e}") | |