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import streamlit as st |
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from llmware_module import ( |
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classify_sentiment, |
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detect_emotions, |
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generate_tags, |
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identify_topics, |
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perform_intent, |
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get_ratings, |
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get_category, |
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perform_ner, |
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perform_nli, |
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) |
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st.title("Perform NLP Tasks on CPU") |
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text = st.text_area("Enter text here:") |
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analysis_tools = st.multiselect( |
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"Select the analysis tools to use:", |
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["Sentiment Analysis", "Emotion Detection", "Generate Tags", "Identify Topics", |
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"Perform Intent", "Get Ratings", "Get Category", |
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"Perform NER", "Perform NLI"], |
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["Sentiment Analysis"] |
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) |
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if st.button("Analyze"): |
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results = {} |
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if "Sentiment Analysis" in analysis_tools: |
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results["Sentiment Analysis"] = classify_sentiment(text) |
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if "Emotion Detection" in analysis_tools: |
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results["Emotion Detection"] = detect_emotions(text) |
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if "Generate Tags" in analysis_tools: |
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results["Generate Tags"] = generate_tags(text) |
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if "Identify Topics" in analysis_tools: |
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results["Identify Topics"] = identify_topics(text) |
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if "Perform Intent" in analysis_tools: |
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results["Perform Intent"] = perform_intent(text) |
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if "Get Ratings" in analysis_tools: |
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results["Get Ratings"] = get_ratings(text) |
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if "Get Category" in analysis_tools: |
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results["Get Category"] = get_category(text) |
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if "Perform NER" in analysis_tools: |
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results["Perform NER"] = perform_ner(text) |
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if "Perform NLI" in analysis_tools: |
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results["Perform NLI"] = perform_nli(text) |
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for tool, response in results.items(): |
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st.subheader(tool) |
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st.json(response) |