Spaces:
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Ashmi Banerjee
commited on
Commit
·
9075b46
1
Parent(s):
88f694a
removed test.py
Browse files- .gitignore +2 -1
- test.py +0 -138
.gitignore
CHANGED
@@ -165,4 +165,5 @@ notebooks/.ipynb_checkpoints
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db/empty.json
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.config/user-evaluations-firebase-creds.json
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user-evaluations-default-rtdb-export.json
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data/
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db/empty.json
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.config/user-evaluations-firebase-creds.json
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user-evaluations-default-rtdb-export.json
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data/
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test.py
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test.py
DELETED
@@ -1,138 +0,0 @@
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import streamlit as st
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import pandas as pd
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# Sample Data (Replace with your actual data loading)
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data = {
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'query_v': {
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'gemini': 'Cheap European city break in February.',
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'llama': 'Affordable European trip in February.',
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},
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'query_p0': {
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'gemini': 'European city break in February, less crowded destinations.',
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'llama': 'February European city break, away from the crowds.',
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},
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'query_p1': {
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'gemini': 'Best European cities for intense physical training and recovery with easy access to ice rinks?',
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'llama': 'Top European cities for intense training and recovery with ice rinks?',
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},
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}
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# Sample rating data (Replace this with your actual data)
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rating_data = {
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'gemini': {
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'query_v': {'relevance': 'Not Relevant', 'clarity': 'Not Clear'},
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'query_p0': {'relevance': 'Not Relevant', 'clarity': 'Not Clear', 'persona_alignment': 'N/A'},
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'query_p1': {'relevance': 'N/A', 'clarity': 'N/A', 'persona_alignment': 'N/A'},
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},
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'llama': {
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'query_v': {'relevance': 'Somewhat Relevant', 'clarity': 'Somewhat Clear'},
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'query_p0': {'relevance': 'Somewhat Relevant', 'clarity': 'Somewhat Clear', 'persona_alignment': 'Partially Aligned'},
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'query_p1': {'relevance': 'Not Relevant', 'clarity': 'Not Clear', 'persona_alignment': 'Not Aligned'},
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}
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}
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df = pd.DataFrame.from_dict(data)
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# Function to display query, rating, and controls for one query
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def display_query_section(query_type, query_text_gemini, query_text_llama, relevance_gemini, clarity_gemini, relevance_llama, clarity_llama, persona_alignment_gemini=None, persona_alignment_llama=None):
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st.subheader(f"{query_type}")
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col1, col2 = st.columns(2)
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with col1:
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st.markdown("Gemini")
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st.write(query_text_gemini)
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st.markdown("Relevance")
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relevance_options = ['N/A', 'Not Relevant', 'Somewhat Relevant', 'Relevant', 'Unclear']
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selected_relevance_gemini = st.radio("Relevance", options = relevance_options, key=f"relevance_{query_type}_gemini", index=relevance_options.index(relevance_gemini), horizontal=True)
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st.markdown("Clarity")
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clarity_options = ['N/A', 'Not Clear', 'Somewhat Clear', 'Very Clear']
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selected_clarity_gemini = st.radio("Clarity", options = clarity_options, key=f"clarity_{query_type}_gemini", index=clarity_options.index(clarity_gemini), horizontal=True)
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if persona_alignment_gemini:
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st.markdown("Persona Alignment")
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persona_options = ['N/A', 'Not Aligned', 'Partially Aligned', 'Aligned', 'Unclear']
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selected_persona_alignment_gemini = st.radio("Persona Alignment", options = persona_options, key=f"persona_{query_type}_gemini", index=persona_options.index(persona_alignment_gemini), horizontal=True)
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with col2:
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st.markdown("Llama")
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st.write(query_text_llama)
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st.markdown("Relevance")
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relevance_options_llama = ['N/A', 'Not Relevant', 'Somewhat Relevant', 'Relevant', 'Unclear']
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selected_relevance_llama = st.radio("Relevance", options = relevance_options_llama, key=f"relevance_{query_type}_llama", index=relevance_options_llama.index(relevance_llama), horizontal=True)
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st.markdown("Clarity")
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clarity_options_llama = ['N/A', 'Not Clear', 'Somewhat Clear', 'Very Clear']
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selected_clarity_llama = st.radio("Clarity", options = clarity_options_llama, key=f"clarity_{query_type}_llama", index=clarity_options_llama.index(clarity_llama), horizontal=True)
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if persona_alignment_llama:
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st.markdown("Persona Alignment")
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persona_options_llama = ['N/A', 'Not Aligned', 'Partially Aligned', 'Aligned', 'Unclear']
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selected_persona_alignment_llama = st.radio("Persona Alignment", options = persona_options_llama, key=f"persona_{query_type}_llama", index=persona_options_llama.index(persona_alignment_llama), horizontal=True)
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# Main Streamlit App
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st.set_page_config(layout="wide")
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# Context Information
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st.title("Question 1 of 5")
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st.subheader("Config ID: c_p_0_pop_low_easy")
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st.markdown("### Context Information")
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with st.expander("Persona", expanded=True):
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st.write("A top-scoring player in the local league who is also eyeing a professional career in the NHL")
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with st.expander("Filters & Cities", expanded=True):
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st.write("Filters: {'popularity': 'low', 'month': 'February'}")
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st.write("Cities: ['Adana', 'Adiyaman', 'Agri', 'Arad', 'Arkhangelsk', 'Bacau', 'Baia Mare', 'Balikesir', 'Brest',\
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'Burgas', 'Canakkale', 'Craiova', 'Debrecen', 'Denizli', 'Diyarbakir', 'Elazig', 'Erzincan', 'Eskisehir',\
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'Gaziantep', 'lasi', 'Ioannina', 'Isparta', 'Jonkoping', 'Kahramanmaras', 'Kars', 'Kayseri', 'Konya', 'Kosice',\
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'Linkoping', 'Malatya', 'Miskolc', 'Mykolaiv', 'Nalchik', 'Nevsehir', 'Nis', 'Orebro', 'Orleans', 'Rivne',\
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'Rzeszow', 'Samsun', 'Sanliurfa', 'Sevilla', 'Siirt', 'Sivas', 'Syktyvkar', 'Targu-Mures', 'Tekirdag',\
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'Thessaloniki', 'Trabzon', 'Uzhhorod', 'Valladolid', 'Van', 'Vasteras', 'Vinnytsia', 'Vitoria-Gasteiz',\
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'Vladikavkaz', 'Zaporizhzhia', 'Zielona Gora', 'Batman', 'Erzurum']")
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# Display Query Sections
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display_query_section(
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query_type="Query_v",
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query_text_gemini=df.loc['gemini','query_v'],
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query_text_llama=df.loc['llama','query_v'],
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relevance_gemini=rating_data['gemini']['query_v']['relevance'],
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clarity_gemini=rating_data['gemini']['query_v']['clarity'],
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relevance_llama=rating_data['llama']['query_v']['relevance'],
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clarity_llama=rating_data['llama']['query_v']['clarity'],
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)
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display_query_section(
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query_type="Query_p0",
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query_text_gemini=df.loc['gemini','query_p0'],
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query_text_llama=df.loc['llama','query_p0'],
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relevance_gemini=rating_data['gemini']['query_p0']['relevance'],
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clarity_gemini=rating_data['gemini']['query_p0']['clarity'],
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persona_alignment_gemini=rating_data['gemini']['query_p0']['persona_alignment'],
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relevance_llama=rating_data['llama']['query_p0']['relevance'],
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clarity_llama=rating_data['llama']['query_p0']['clarity'],
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persona_alignment_llama=rating_data['llama']['query_p0']['persona_alignment'],
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)
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display_query_section(
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query_type="Query_p1",
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query_text_gemini=df.loc['gemini','query_p1'],
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query_text_llama=df.loc['llama','query_p1'],
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relevance_gemini=rating_data['gemini']['query_p1']['relevance'],
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clarity_gemini=rating_data['gemini']['query_p1']['clarity'],
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persona_alignment_gemini=rating_data['gemini']['query_p1']['persona_alignment'],
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relevance_llama=rating_data['llama']['query_p1']['relevance'],
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clarity_llama=rating_data['llama']['query_p1']['clarity'],
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persona_alignment_llama=rating_data['llama']['query_p1']['persona_alignment'],
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)
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# Additional Comments
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st.markdown("Additional Comments (Optional):")
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st.text_area("", key="additional_comments")
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# Navigation Buttons
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col1, col2, col3 = st.columns([1,1,1])
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with col1:
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st.button("Back")
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with col2:
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st.button("Next")
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with col3:
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st.button("Exit & Resume Later")
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# Bottom message
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st.markdown("Please provide a rating before proceeding.")
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