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Update frontend.py
Browse files- frontend.py +3 -2
frontend.py
CHANGED
@@ -57,7 +57,8 @@ with st.sidebar:
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backend_url = st.text_input("π Backend URL", value="http://localhost:8000")
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sentiment_model = st.selectbox("π Sentiment Model", [
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"Auto-detect",
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"nlptown/bert-base-multilingual-uncased-sentiment"
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])
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industry = st.selectbox("π Industry", ["Auto-detect", "Generic", "E-commerce", "Healthcare", "Education"])
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@@ -132,7 +133,7 @@ with tab1:
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if data:
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st.subheader("π Summary")
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st.info(data["summary"])
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st.caption(
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st.markdown(f"**Context:** `{data['industry']}` | `{data['product_category']}` | `Web`")
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st.metric("π Sentiment", data["sentiment"]["label"], delta=f"{data['sentiment']['score']:.2%}")
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backend_url = st.text_input("π Backend URL", value="http://localhost:8000")
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sentiment_model = st.selectbox("π Sentiment Model", [
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"Auto-detect",
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"distilbert-base-uncased-finetuned-sst-2-english",
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"nlptown/bert-base-multilingual-uncased-sentiment"
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])
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industry = st.selectbox("π Industry", ["Auto-detect", "Generic", "E-commerce", "Healthcare", "Education"])
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if data:
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st.subheader("π Summary")
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st.info(data["summary"])
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st.caption("π§ Summary Model: facebook/bart-large-cnn | " + verbosity + " response")
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st.markdown(f"**Context:** `{data['industry']}` | `{data['product_category']}` | `Web`")
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st.metric("π Sentiment", data["sentiment"]["label"], delta=f"{data['sentiment']['score']:.2%}")
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