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KrSharangrav
commited on
Commit
Β·
f2ddc64
1
Parent(s):
f453bef
change in UI image
Browse files
app.py
CHANGED
@@ -3,38 +3,35 @@ import pandas as pd
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from db import insert_data_if_empty, get_mongo_client
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from chatbot import chatbot_response
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# Ensure historical data is inserted into MongoDB if not already present.
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insert_data_if_empty()
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# Connect to MongoDB (optional: for additional visualizations)
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collection = get_mongo_client()
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with
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st.
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st.markdown(ai_response)
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st.write("### Sentiment Analysis:")
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st.write(f"**Sentiment Detected:** {sentiment_label} ({sentiment_confidence*100:.2f}% confidence)")
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st.write("### Category Extraction:")
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st.write(f"**Category Detected:** {topic_label} ({topic_confidence*100:.2f}% confidence)")
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else:
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st.warning("β οΈ Please enter a question or text for analysis.")
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from db import insert_data_if_empty, get_mongo_client
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from chatbot import chatbot_response
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# Sidebar: Display image and title.
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st.sidebar.image("https://huggingface.co/spaces/sharangrav24/SentimentAnalysis/resolve/main/sentiment.png", width=100)
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st.sidebar.markdown("## Group A Submission - Python")
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# Ensure historical data is inserted into MongoDB if not already present.
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insert_data_if_empty()
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# Connect to MongoDB (optional: for additional visualizations)
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collection = get_mongo_client()
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st.subheader("π¬ Chatbot with Sentiment Analysis & Category Extraction")
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# Create an expander to display example questions on separate lines.
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with st.expander("π Hi, allow me to help you with prompts:"):
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st.write("π‘ Provide analysis for data entry 1 in the dataset")
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st.write("π‘ What is the dataset summary?")
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st.write("π‘ or just ask me something of your own, I'll be happy to help π")
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# Text area for user input.
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user_prompt = st.text_area("Ask me something:")
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if st.button("Get Response"):
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ai_response, sentiment_label, sentiment_confidence, topic_label, topic_confidence = chatbot_response(user_prompt)
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if ai_response:
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st.write("### Response:")
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st.markdown(ai_response)
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st.write("### Sentiment Analysis:")
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st.write(f"**Sentiment Detected:** {sentiment_label} ({sentiment_confidence*100:.2f}% confidence)")
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st.write("### Category Extraction:")
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st.write(f"**Category Detected:** {topic_label} ({topic_confidence*100:.2f}% confidence)")
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else:
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st.warning("β οΈ Please enter a question or text for analysis.")
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