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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 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=[
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x
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for x in df["name_clean"].unique()
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if x in df[df["provider_clean"] == provider]["name_clean"].unique()
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],
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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[
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(df["provider_clean"] == provider) & (df["name_clean"] == model)
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]["provider"].values[0]
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model_raw = df[
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(df["provider_clean"] == provider) & (df["name_clean"] == model)
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]["name"].values[0]
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df_filtered = df[
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(df["provider_clean"] == provider) & (df["name_clean"] == model)
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]
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if (
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df_filtered["warning_arch"].values[0]
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and not df_filtered["warning_multi_modal"].values[0]
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):
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st.warning(WARNING_CLOSED_SOURCE)
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if (
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df_filtered["warning_multi_modal"].values[0]
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and not df_filtered["warning_arch"].values[0]
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):
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st.warning(WARNING_MULTI_MODAL)
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if (
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df_filtered["warning_arch"].values[0]
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and df_filtered["warning_multi_modal"].values[0]
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):
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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(
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'<h3 align = "center">Environmental impacts</h3>',
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unsafe_allow_html=True,
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)
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st.markdown(
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'<p align = "center">To understand how the environmental impacts are computed go to the 📖 Methodology tab.</p>',
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unsafe_allow_html=True,
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)
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display_impacts(impacts)
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with st.container(border=True):
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st.markdown(
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'<h3 align = "center">That\'s equivalent to ...</h3>',
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unsafe_allow_html=True,
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)
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st.markdown(
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'<p align = "center">Making this request to the LLM is equivalent to the following actions :</p>',
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unsafe_allow_html=True,
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)
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display_equivalent(impacts)
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except Exception:
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st.error(
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"Could not find the model in the repository. Please try another model."
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)
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