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import streamlit as st
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from ecologits.tracers.utils import llm_impacts
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from src.impacts import get_impacts, display_impacts, display_equivalent
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from src.utils import format_impacts
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from src.content import WARNING_CLOSED_SOURCE, WARNING_MULTI_MODAL, WARNING_BOTH
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from src.models import load_models
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from src.constants import PROMPTS
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def calculator_mode():
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with st.container(border=True):
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df = load_models(filter_main=True)
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col1, col2, col3 = st.columns(3)
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with col1:
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provider = st.selectbox(
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label = 'Provider',
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options = [x for x in df['provider_clean'].unique()],
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index = 7
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)
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with col2:
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model = st.selectbox(
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label = 'Model',
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options = [x for x in df['name_clean'].unique() if x in df[df['provider_clean'] == provider]['name_clean'].unique()]
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)
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with col3:
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output_tokens = st.selectbox('Example prompt', [x[0] for x in PROMPTS])
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provider_raw = df[(df['provider_clean'] == provider) & (df['name_clean'] == model)]['provider'].values[0]
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model_raw = df[(df['provider_clean'] == provider) & (df['name_clean'] == model)]['name'].values[0]
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df_filtered = df[(df['provider_clean'] == provider) & (df['name_clean'] == model)]
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if df_filtered['warning_arch'].values[0] and not df_filtered['warning_multi_modal'].values[0]:
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st.warning(WARNING_CLOSED_SOURCE)
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if df_filtered['warning_multi_modal'].values[0] and not df_filtered['warning_arch'].values[0]:
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st.warning(WARNING_MULTI_MODAL)
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if df_filtered['warning_arch'].values[0] and df_filtered['warning_multi_modal'].values[0]:
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st.warning(WARNING_BOTH)
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try:
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impacts = llm_impacts(
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provider=provider_raw,
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model_name=model_raw,
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output_token_count=[x[1] for x in PROMPTS if x[0] == output_tokens][0],
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request_latency=100000
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)
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impacts, _, _ = format_impacts(impacts)
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with st.container(border=True):
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st.markdown('<h3 align = "center">Environmental impacts</h3>', unsafe_allow_html=True)
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st.markdown('<p align = "center">To understand how the environmental impacts are computed go to the 📖 Methodology tab.</p>', unsafe_allow_html=True)
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display_impacts(impacts, provider, location="🌎 World")
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with st.container(border=True):
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st.markdown('<h3 align = "center">That\'s equivalent to ...</h3>', unsafe_allow_html=True)
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st.markdown('<p align = "center">Making this request to the LLM is equivalent to the following actions :</p>', unsafe_allow_html=True)
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display_equivalent(impacts, provider, location="🌎 World")
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except Exception as e:
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st.error('Could not find the model in the repository. Please try another model.') |
