added company mode

app.py

@@ -4,7 +4,8 @@ from src.content import (
     HERO_TEXT,
     ABOUT_TEXT,
     CITATION_LABEL,
-    CITATION_TEXT,
+    CITATION_TEXT_CALCULATOR,
+    CITATION_TEXT_SOFTWARE,
     LICENCE_TEXT,
     INTRO_TEXT,
     METHODOLOGY_TEXT
@@ -13,6 +14,7 @@ from src.content import (
 from src.expert import expert_mode
 from src.calculator import calculator_mode
 from src.token_estimator import token_estimator
+from src.company import company_mode
 
 st.set_page_config(
     layout="wide",
@@ -27,9 +29,10 @@ st.html(HERO_TEXT)
 
 st.markdown(INTRO_TEXT)
 
-tab_calculator, tab_expert, tab_token, tab_method, tab_about = st.tabs(
+tab_calculator, tab_company, tab_expert, tab_token, tab_method, tab_about = st.tabs(
     [
         '🧮 Calculator',
+        '👩🏻‍💻 Companies',
         '🤓 Expert Mode',
         '🪙 Tokens estimator',
         '📖 Methodology',
@@ -41,6 +44,10 @@ with tab_calculator:
 
     calculator_mode()
 
+with tab_company:
+
+    company_mode()
+
 with tab_expert:
 
     expert_mode()
@@ -59,6 +66,7 @@ with tab_about:
 
 with st.expander('📚 Citation'):
     st.html(CITATION_LABEL)
-    st.html(CITATION_TEXT)
+    st.html(CITATION_TEXT_CALCULATOR)
+    st.html(CITATION_TEXT_SOFTWARE)
 
 st.html(LICENCE_TEXT)

src/calculator.py

@@ -45,28 +45,28 @@ def calculator_mode():
         if df_filtered['warning_arch'].values[0] and df_filtered['warning_multi_modal'].values[0]:
             st.warning(WARNING_BOTH)
             
-    #try:
+    try:
 
-    impacts = llm_impacts(
-                    provider=provider_raw,
-                    model_name=model_raw,
-                    output_token_count=[x[1] for x in PROMPTS if x[0] == output_tokens][0],
-                    request_latency=100000
-                )
+        impacts = llm_impacts(
+                        provider=provider_raw,
+                        model_name=model_raw,
+                        output_token_count=[x[1] for x in PROMPTS if x[0] == output_tokens][0],
+                        request_latency=100000
+                    )
 
-    impacts, _, _ = format_impacts(impacts)
-    
-    with st.container(border=True):
+        impacts, _, _ = format_impacts(impacts)
+        
+        with st.container(border=True):
 
-        st.markdown('<h3 align = "center">Environmental impacts</h3>', unsafe_allow_html=True)
-        st.markdown('<p align = "center">To understand how the environmental impacts are computed go to the 📖 Methodology tab.</p>', unsafe_allow_html=True)
-        display_impacts(impacts, provider, location="🌎 World")
-    
-    with st.container(border=True):
+            st.markdown('<h3 align = "center">Environmental impacts</h3>', unsafe_allow_html=True)
+            st.markdown('<p align = "center">To understand how the environmental impacts are computed go to the 📖 Methodology tab.</p>', unsafe_allow_html=True)
+            display_impacts(impacts, provider, location="🌎 World")
         
-        st.markdown('<h3 align = "center">That\'s equivalent to ...</h3>', unsafe_allow_html=True)
-        st.markdown('<p align = "center">Making this request to the LLM is equivalent to the following actions :</p>', unsafe_allow_html=True)
-        display_equivalent(impacts, provider, location="🌎 World")
+        with st.container(border=True):
             
-    # except Exception as e:
-    #     st.error('Could not find the model in the repository. Please try another model.')
+            st.markdown('<h3 align = "center">That\'s equivalent to ...</h3>', unsafe_allow_html=True)
+            st.markdown('<p align = "center">Making this request to the LLM is equivalent to the following actions :</p>', unsafe_allow_html=True)
+            display_equivalent(impacts, provider, location="🌎 World")
+                
+    except Exception as e:
+        st.error('Could not find the model in the repository. Please try another model.')

src/company.py

@@ -0,0 +1,119 @@
+import streamlit as st
+
+from ecologits.tracers.utils import llm_impacts
+from src.impacts import get_impacts, display_impacts_company, display_equivalent_company
+from src.utils import format_impacts
+from src.content import WARNING_CLOSED_SOURCE, WARNING_MULTI_MODAL, WARNING_BOTH
+from src.models import load_models
+
+from src.constants import PROMPTS
+
+def company_mode():
+
+    st.markdown("### 👩🏻‍💻 Calculator for companies")
+
+    with st.container(border=True):
+        
+        df = load_models(filter_main=True)
+        
+        col1, col2, col3 = st.columns(3)
+
+        with col1:
+            provider = st.selectbox(
+                label = 'Provider',
+                options = [x for x in df['provider_clean'].unique()],
+                index = 7,
+                key = 61
+            ) 
+
+        with col2:
+            model = st.selectbox(
+                label = 'Model',
+                options = [x for x in df['name_clean'].unique() if x in df[df['provider_clean'] == provider]['name_clean'].unique()],
+                key = 62
+            )
+
+        with col3:
+            output_tokens = st.selectbox(
+                'Example prompt', 
+                [x[0] for x in PROMPTS],
+                key = 63     
+            )
+            
+        # WARNING DISPLAY
+        provider_raw = df[(df['provider_clean'] == provider) & (df['name_clean'] == model)]['provider'].values[0]
+        model_raw = df[(df['provider_clean'] == provider) & (df['name_clean'] == model)]['name'].values[0]
+
+        df_filtered = df[(df['provider_clean'] == provider) & (df['name_clean'] == model)]
+
+        if df_filtered['warning_arch'].values[0] and not df_filtered['warning_multi_modal'].values[0]:
+            st.warning(WARNING_CLOSED_SOURCE)
+        if df_filtered['warning_multi_modal'].values[0] and not df_filtered['warning_arch'].values[0]:
+            st.warning(WARNING_MULTI_MODAL)
+        if df_filtered['warning_arch'].values[0] and df_filtered['warning_multi_modal'].values[0]:
+            st.warning(WARNING_BOTH)
+            
+        col4, col5, col6 = st.columns(3)
+
+        with col4:
+            company_size = st.number_input(
+                label="Company size (in number of employees)",
+                min_value=1,
+                value=10,   # valeur par défaut
+                step=1,
+                key = 64
+            ) 
+        
+        #TODO : lire la literature pour comprendre des chiffres en moyen pour remplisser comme defaut
+        #par example, entre 400 - 800 > entreprise taille moyenne, frequence correspondant : ...
+        with col5:
+            use_percentage = st.number_input(
+                label = 'What percentage of employees use LLM daily (in %)?',
+                min_value=0,
+                max_value=100,
+                value=75,   # valeur par défaut
+                step=5,
+                key = 65
+            )
+
+        #TODO : lire la literature pour comprendre des chiffres en moyen pour remplisser comme defaut
+        #par example, entre 400 - 800 > entreprise taille moyenne, frequence correspondant : ...
+        with col6:
+            request_frequency = st.number_input(
+                label = 'How frequently do the employees use LLM (times per day)?',
+                min_value=1,
+                value=20,   # valeur par défaut
+                step=5,
+                key = 66
+            )
+
+    company_multiplier = company_size * use_percentage/100 * request_frequency
+
+    #try:
+
+    impacts = llm_impacts(
+                    provider=provider_raw,
+                    model_name=model_raw,
+                    output_token_count=[x[1] for x in PROMPTS if x[0] == output_tokens][0],
+                    request_latency=100000
+                )
+
+    impacts, _, _ = format_impacts(impacts)
+
+    #down here
+
+    
+    with st.container(border=True):
+
+        st.markdown('<h3 align = "center">Environmental impacts</h3>', unsafe_allow_html=True)
+        st.markdown('<p align = "center">To understand how the environmental impacts are computed go to the 📖 Methodology tab.</p>', unsafe_allow_html=True)
+        display_impacts_company(impacts, provider, company_multiplier, location="🌎 World")
+    
+    with st.container(border=True):
+        #TODO : corriger ça 
+        st.markdown('<h3 align = "center">That\'s equivalent to ...</h3>', unsafe_allow_html=True)
+        st.markdown('<p align = "center">On the scale of the company, making this request to the LLM over a day is equivalent to the following actions :</p>', unsafe_allow_html=True)
+        display_equivalent_company(impacts, provider, company_multiplier, location="🌎 World")
+            
+    #except Exception as e:
+    #    st.error('Could not find the model in the repository. Please try another model.')

src/content.py

@@ -258,17 +258,21 @@ an Olympic-sized swimming pool holds about 2.5 million liters of water.
 """
 
 CITATION_LABEL = "BibTeX citation for EcoLogits Calculator and the EcoLogits library:"
-CITATION_TEXT = r"""@misc{ecologits-calculator,
+CITATION_TEXT_CALCULATOR = r"""@misc{ecologits-calculator,
   author={Samuel Rincé, Adrien Banse, Valentin Defour, and Chieh Hsu},
   title={EcoLogits Calculator},
   year={2025},
   howpublished= {\url{https://huggingface.co/spaces/genai-impact/ecologits-calculator}},
 }
+"""
+
+CITATION_TEXT_SOFTWARE = r"""
 @software{ecologits,
   author = {Samuel Rincé, Adrien Banse, Vinh Nguyen, Luc Berton, and Chieh Hsu},
   publisher = {GenAI Impact},
   title = {EcoLogits: track the energy consumption and environmental footprint of using generative AI models through APIs.},
-}"""
+}
+"""
 
 LICENCE_TEXT = """<p xmlns:cc="http://creativecommons.org/ns#" >
   This work is licensed under 

src/expert.py

@@ -141,20 +141,19 @@ def expert_mode():
 
         st.markdown('The usage impacts account for the electricity consumption of the model while the embodied impacts account for resource extraction (e.g., minerals and metals), manufacturing, and transportation of the hardware.')
         
-        col_ghg_comparison, col_adpe_comparison, col_pe_comparison = st.columns(3)
+        col_ghg_comparison, col_adpe_comparison, col_pe_comparison, col_water_comparison = st.columns(4)
         
         with col_ghg_comparison:
-
             fig_gwp = px.pie(
-            values = [average_range_impacts(usage.gwp.value), average_range_impacts(embodied.gwp.value)],
-            names = ['usage', 'embodied'],
-            title = 'GHG emissions',
-            color_discrete_sequence=["#00BF63", "#0B3B36"],
-            width = 400
+                values = [average_range_impacts(usage.gwp.value), average_range_impacts(embodied.gwp.value)],
+                names = ['usage', 'embodied'],
+                title = 'GHG emissions',
+                color_discrete_sequence=["#00BF63", "#0B3B36"],   
+                width = 300
             )
             fig_gwp.update_layout(
                 showlegend=False, 
-                title_x=0.25)
+                title_x=0.1)
 
             st.plotly_chart(fig_gwp)
 
@@ -163,13 +162,18 @@ def expert_mode():
                 values = [average_range_impacts(usage.adpe.value), average_range_impacts(embodied.adpe.value)],
                 names = ['usage', 'embodied'],
                 title = 'Abiotic depletion',
-                color_discrete_sequence=["#0B3B36","#00BF63"],
-                width = 400
-                )
+                color = ['usage', 'embodied'],  # Associe chaque valeur à un label pour la couleur
+                color_discrete_map={
+                    'usage': '#00BF63',
+                    'embodied': '#0B3B36'
+                },
+                width = 300
+            )
             fig_adpe.update_layout(
                 showlegend=False,
-                title_x=0.25)
-            
+                title_x=0.05
+            )
+
             st.plotly_chart(fig_adpe)
 
         with col_pe_comparison:
@@ -178,14 +182,28 @@ def expert_mode():
                 names = ['usage', 'embodied'],
                 title = 'Primary energy',
                 color_discrete_sequence=["#00BF63", "#0B3B36"],
-                width = 400
+                width = 300
                 )
             fig_pe.update_layout(
                 showlegend=False, 
-                title_x=0.25)
+                title_x=0.1)
 
             st.plotly_chart(fig_pe)
 
+        with col_water_comparison:
+            fig_water = px.pie(
+                values = [average_range_impacts(usage.water.value), average_range_impacts(embodied.water.value)],
+                names = ['usage', 'embodied'],
+                title = 'Water',
+                color_discrete_sequence=["#00BF63", "#0B3B36"],
+                width = 300
+                )
+            fig_water.update_layout(
+                showlegend=False, 
+                title_x=0.3)
+
+            st.plotly_chart(fig_water)
+
     with st.expander('🌍️ Location impact'):
 
         st.markdown('<h4 align="center">How can location impact the footprint ?</h4>', unsafe_allow_html = True)

src/impacts.py

@@ -9,6 +9,14 @@ from src.utils import (
     format_gwp_eq_streaming,
     format_water_eq_bottled_waters,
     format_water_eq_olympic_sized_swimming_pool,
+    format_energy_eq_electricity_production_company,
+    format_energy_eq_electricity_consumption_ireland_company,
+    format_gwp_eq_airplane_paris_nyc_company,
+    format_water_eq_olympic_sized_swimming_pool_company,
+    format_energy_eq_physical_activity_company,
+    format_gwp_eq_streaming_company,
+    format_energy_eq_electric_vehicle_company,
+    format_water_eq_bottled_waters_company,
     PhysicalActivity,
     EnergyProduction,
     AI_COMPANY_TO_DATA_CENTER_PROVIDER,
@@ -67,7 +75,23 @@ def display_impacts(impacts, provider, location):
         <div style="font-size: 16px;">Abiotic Resources</div>
         </div>
         """, unsafe_allow_html = True)
-        st.latex(f'\Large {impacts.adpe.magnitude:.3g} \ \large {impacts.adpe.units}')
+        company_impact = impacts.adpe.magnitude
+        impacts_adpe_units = impacts.adpe.units
+        #errornique 
+        if company_impact <= 1 and impacts_adpe_units == "kgSbeq":
+            company_impact *= 1000
+            impacts_adpe_units = "gSbeq"
+        if company_impact <= 1 and impacts_adpe_units == "gSbeq":
+            company_impact *= 1000
+            impacts_adpe_units = "mgSbeq"
+        if company_impact <= 1 and impacts_adpe_units == "mgSbeq":
+            company_impact *= 1000
+            impacts_adpe_units = "μSbeq"
+    ################################################
+        if company_impact >= 1000 and impacts_adpe_units == "kgSbeq":
+            company_impact /= 1000
+            impacts_adpe_units = "tSbeq"
+        st.latex(f'\Large {company_impact:.3g} \ \large {impacts_adpe_units}')
         st.markdown("""
         <div style="text-align: center;"><i>Evaluates the use of metals and minerals<i>
         </div>
@@ -101,6 +125,154 @@ def display_impacts(impacts, provider, location):
         """, unsafe_allow_html = True)
 
 
+#################################################################################################
+def display_impacts_company(impacts, provider, company_multiplier, location):
+
+    st.divider()
+
+    col_energy, col_ghg, col_adpe, col_pe, col_water = st.columns(5)
+
+    with col_energy:
+        st.markdown("""
+        <div style="text-align: center;">
+        <div style="font-size: 30px;">⚡️</div>
+        <div style="font-size: 25px;">Energy</div>
+        </div>
+        """, unsafe_allow_html = True)
+        company_impact = impacts.energy.magnitude * company_multiplier
+        impacts_energy_units = impacts.energy.units
+        if company_impact >= 1000 and impacts_energy_units == "Wh":
+            company_impact /= 1000
+            impacts_energy_units = "kWh"
+        if company_impact >= 1000 and impacts_energy_units == "kWh":
+            company_impact /= 1000
+            impacts_energy_units = "MWh"
+        if company_impact >= 1000 and impacts_energy_units == "MWh":
+            company_impact /= 1000
+            impacts_energy_units = "GWh"
+        if company_impact >= 1000 and impacts_energy_units == "GWh":
+            company_impact /= 1000
+            impacts_energy_units = "TWh"
+        if company_impact >= 1000 and impacts_energy_units == "TWh":
+            company_impact /= 1000
+            impacts_energy_units = "PWh"
+        st.latex(f'\Large {company_impact:.3g} \ \large {impacts_energy_units}')
+        st.markdown("""
+        <div style="height: 10px;"></div>            
+        <div style="text-align: center;"><i>Evaluates the electricity consumption<i>
+        </div>
+        """, unsafe_allow_html = True)
+
+    with col_ghg:
+        st.markdown("""
+        <div style="text-align: center;">
+        <div style="font-size: 30px;">🌍️</div>
+        <div style="font-size: 18px;">GHG Emissions</div>
+        </div>
+        """, unsafe_allow_html = True)
+        impacts_ghg_units = impacts.gwp.units
+        company_impact = impacts.gwp.magnitude * company_multiplier
+        if company_impact >= 1000 and impacts_ghg_units == "gCO2eq":
+            company_impact /= 1000
+            impacts_ghg_units = "kgCO2eq"
+        if company_impact >= 1000 and impacts_ghg_units == "kgCO2eq":
+            company_impact /= 1000
+            impacts_ghg_units = "tCO2eq"
+        st.latex(f'\Large {company_impact:.3g} \ \large {impacts_ghg_units}')
+        st.markdown("""
+        <div style="text-align: center;"><i>Evaluates the effect on climate change<i>
+        </div>
+        """, unsafe_allow_html = True)
+
+    with col_adpe:
+        st.markdown("""
+        <div style="text-align: center;">
+        <div style="font-size: 30px;">🪨</div>
+        <div style="font-size: 16px;">Abiotic Resources</div>
+        </div>
+        """, unsafe_allow_html = True)
+        company_impact = impacts.adpe.magnitude * company_multiplier
+        impacts_adpe_units = impacts.adpe.units
+        if company_impact <= 1 and impacts_adpe_units == "kgSbeq":
+            company_impact *= 1000
+            impacts_adpe_units = "gSbeq"
+        if company_impact <= 1 and impacts_adpe_units == "gSbeq":
+            company_impact *= 1000
+            impacts_adpe_units = "mgSbeq"
+
+        ##############    
+        if company_impact <= 1 and impacts_adpe_units == "mgSbeq":
+            company_impact *= 1000
+            impacts_adpe_units = "μSbeq"
+        if company_impact >= 1000 and impacts_adpe_units == "kgSbeq":
+            company_impact /= 1000
+            impacts_adpe_units = "tSbeq"
+        st.latex(f'\Large {company_impact:.3g} \ \large {impacts_adpe_units}')
+        st.markdown("""
+        <div style="text-align: center;"><i>Evaluates the use of metals and minerals<i>
+        </div>
+        """, unsafe_allow_html = True)
+
+    with col_pe:
+        st.markdown("""
+        <div style="text-align: center;">
+        <div style="font-size: 30px;">⛽️</div>
+        <div style="font-size: 18px;">Primary Energy</div>
+        </div>
+        """, unsafe_allow_html = True)
+        company_impact = impacts.pe.magnitude * company_multiplier
+        impacts_pe_units = impacts.pe.units
+        if company_impact >= 1000 and impacts_pe_units == "kJ":
+            company_impact /= 1000
+            impacts_pe_units = "MJ"
+        if company_impact >= 1000 and impacts_pe_units == "MJ":
+            company_impact /= 1000
+            impacts_pe_units = "GJ"
+        if company_impact >= 1000 and impacts_pe_units == "GJ":
+            company_impact /= 1000
+            impacts_pe_units = "TJ"
+        if company_impact >= 1000 and impacts_pe_units == "TJ":
+            company_impact /= 1000
+            impacts_pe_units = "PJ"
+        st.latex(f'\Large {company_impact:.3g} \ \large {impacts_pe_units}')
+        st.markdown("""
+        <div style="height: 10px;"></div>
+        <div style="text-align: center;"><i>Evaluates the use of energy resources<i>
+        </div>
+        """, unsafe_allow_html = True)
+
+    with col_water: 
+        st.markdown("""
+        <div style="text-align: center;">
+        <div style="font-size: 30px;">🚰</div>
+        <div style="font-size: 25px;">Water</div>
+        </div>
+        """, unsafe_allow_html = True)
+        company_impact = impacts.water.magnitude * company_multiplier
+        impacts_water_units = impacts.water.units
+        if company_impact >= 1000 and impacts_water_units == "mL":
+            company_impact /= 1000
+            impacts_water_units = "L"
+        if company_impact >= 1000 and impacts_water_units == "L":
+            company_impact /= 1000
+            impacts_water_units = "kL"
+        if company_impact >= 1000 and impacts_water_units == "kL":
+            company_impact /= 1000
+            impacts_water_units = "ML"
+        if company_impact >= 1000 and impacts_water_units == "ML":
+            company_impact /= 1000
+            impacts_water_units = "GL"
+        if company_impact >= 1000 and impacts_water_units == "GL":
+            company_impact /= 1000
+            impacts_water_units = "TL"
+        st.latex(f'\Large {company_impact:.3g} \ \large {impacts_water_units}')
+        st.markdown("""
+        <div style="text-align: center;"><i>Evaluates the use of water<i>
+        </div>
+        """, unsafe_allow_html = True)
+
+
+
 ############################################################################################################
 
 def display_equivalent(impacts, provider, location):
@@ -182,21 +354,229 @@ def display_equivalent(impacts, provider, location):
         if electricity_production == EnergyProduction.WIND:
             emoji = "💨️ "
             name = "Wind turbines"
-        st.markdown(f'<h4 align="center">{emoji} {count.magnitude:.0f} {name} <span style="font-size: 12px">\n (yearly ⚡️ production)</span></h2></h4>', unsafe_allow_html = True)
+        st.markdown(f"""
+            <div style="text-align: center;">
+                <div style="font-size: 30px;">
+                    {emoji} 
+                </div>
+                <div style="font-size: 30px;">
+                    {count.magnitude:.3g} 
+                </div>
+                <div style="font-size: 25px;">
+                    {name}
+                </div>
+                <div style="font-size: 12px;">
+                    (yearly ⚡️ production)
+                </div>
+            </div>
+        """, unsafe_allow_html=True)
         st.markdown(f'<p align="center"><i>Based on energy consumption<i></p>', unsafe_allow_html = True)
         
     with col6:
         ireland_count = format_energy_eq_electricity_consumption_ireland(impacts.energy)
-        st.markdown(f'<h4 align="center">🇮🇪 {ireland_count.magnitude:.3f} x Irelands <span style="font-size: 12px">\n (yearly ⚡️ consumption)</span></h2></h4>', unsafe_allow_html = True)
+        st.markdown(f"""
+            <div style="text-align: center;">
+                <div style="font-size: 30px;">
+                    ☘️🇮🇪
+                </div>
+                <div style="font-size: 30px;">
+                    {ireland_count.magnitude:.3g} 
+                </div>
+                <div style="font-size: 25px;">
+                    Irelands
+                </div>
+                <div style="font-size: 12px;">
+                    (yearly ⚡️ consumption)
+                </div>
+            </div>
+        """, unsafe_allow_html=True)        
         st.markdown(f'<p align="center"><i>Based on energy consumption<i></p>', unsafe_allow_html = True)
 
     with col7:
         paris_nyc_airplane = format_gwp_eq_airplane_paris_nyc(impacts.gwp)
-        st.markdown(f'<h4 align="center">✈️ {round(paris_nyc_airplane.magnitude):,} Paris ↔ NYC</h4>', unsafe_allow_html = True)
+        st.markdown(f"""
+            <div style="text-align: center;">
+                <div style="font-size: 30px;">
+                    ✈️
+                </div>
+                <div style="font-size: 30px;">
+                    {paris_nyc_airplane.magnitude:.3g}
+                </div>
+                <div style="font-size: 25px;">
+                    Paris ↔ NYC
+                </div>
+            </div>
+        """, unsafe_allow_html=True)        
         st.markdown(f'<p align="center"><i>Based on GHG emissions<i></p>', unsafe_allow_html = True)
 
     with col8:
         olympic_swimming_pool = format_water_eq_olympic_sized_swimming_pool(impacts.water)
-        st.markdown(f'<div style="text-align: center; font-size: 20px; font-weight: bold;">🏊🏼 {round(olympic_swimming_pool.magnitude):,} Olympic-sized swimming pools</h4>', unsafe_allow_html = True)
+        st.markdown(f"""
+            <div style="text-align: center;">
+                <div style="font-size: 30px;">
+                    🏊🏼  
+                </div>
+                <div style="font-size: 30px;">
+                    {olympic_swimming_pool.magnitude:.3g}
+                </div>
+                <div style="font-size: 22px;">
+                    Olympic-sized swimming pools
+                </div>
+            </div>
+        """, unsafe_allow_html=True)
         st.markdown(f'<p align="center"><i>Based on water consumption<i></p>', unsafe_allow_html = True)
 
+#####################################################################################
+
+def display_equivalent_company(impacts, provider, company_multiplier, location):
+
+    st.divider()
+
+    ev_eq = format_energy_eq_electric_vehicle(impacts.energy)
+    
+    streaming_eq = format_gwp_eq_streaming(impacts.gwp)
+
+    col1, col2, col3, col4 = st.columns(4)
+
+    with col1:
+        physical_activity, distance = format_energy_eq_physical_activity_company(impacts.energy, company_multiplier)
+        if physical_activity == PhysicalActivity.WALKING:
+            physical_activity_emoji = "🚶 " 
+            physical_activity = physical_activity.capitalize()
+        if physical_activity == PhysicalActivity.RUNNING:
+            physical_activity_emoji = "🏃 " 
+            physical_activity = physical_activity.capitalize()
+
+        st.markdown(f"""
+        <div style="text-align: center;">
+        <div style="font-size: 30px;">{physical_activity_emoji}</div>
+        <div style="font-size: 25px;">{physical_activity}</div>
+        </div>
+        """, unsafe_allow_html = True)
+        value = round(distance.magnitude, 3)
+        st.latex(rf'\Large {value:.0g} \ \large {distance.units}')
+        st.markdown(f'<p align="center"><i>Based on energy consumption<i></p>', unsafe_allow_html = True)
+
+    with col2:
+        ev_eq = format_energy_eq_electric_vehicle_company(impacts.energy, company_multiplier)
+        st.markdown(f"""
+        <div style="text-align: center;">
+        <div style="font-size: 30px;">🔋</div>
+        <div style="font-size: 22px;">Electric Vehicle</div>
+        </div>
+        """, unsafe_allow_html = True)
+        value = round(ev_eq.magnitude, 3)
+        st.latex(rf'\Large {value:.0f} \ \large {ev_eq.units}')
+        st.markdown(f'<p align="center"><i>Based on energy consumption<i></p>', unsafe_allow_html = True)
+
+    with col3:
+        streaming_eq = format_gwp_eq_streaming_company(impacts.gwp, company_multiplier)
+        st.markdown(f"""
+        <div style="text-align: center;">
+        <div style="font-size: 30px;">⏯️</div>
+        <div style="font-size: 25px;">Streaming</div>
+        </div>
+        """, unsafe_allow_html = True)
+        value = round(streaming_eq.magnitude, 3)
+        st.latex(rf'\Large {value:.0f} \ \large {streaming_eq.units}')
+        st.markdown(f'<p align="center"><i>Based on GHG emissions<i></p>', unsafe_allow_html = True)
+    
+    with col4:
+        #water = water_impact(impacts, provider, location)
+        water_eq = format_water_eq_bottled_waters_company(impacts.water, company_multiplier)
+        st.markdown(f"""
+        <div style="text-align: center;">
+        <div style="font-size: 30px;">🚰</div>
+        <div style="font-size: 25px;">Bottled Waters</div>
+        </div>
+        """, unsafe_allow_html = True)
+        value = round(water_eq.magnitude, 3)
+        st.latex(rf'\Large {value:.0f} \ \large {"bottles"}')
+        st.markdown(f'<p align="center"><i>Based on water consumption, measured in 0.75 L bottles.<i></p>', unsafe_allow_html = True)
+
+    st.divider()
+    
+    st.markdown('<h3 align="center">What if the company does this request everyday for 251 days (number of work days per year in France in 2025) ?</h3>', unsafe_allow_html = True)
+
+    col5, col6, col7, col8 = st.columns(4)
+
+    with col5:
+
+        electricity_production, count = format_energy_eq_electricity_production_company(impacts.energy, company_multiplier)
+        if electricity_production == EnergyProduction.NUCLEAR:
+            emoji = "☢️"
+            name = "Nuclear power plants"
+        if electricity_production == EnergyProduction.WIND:
+            emoji = "💨️ "
+            name = "Wind turbines"
+        st.markdown(f"""
+            <div style="text-align: center;">
+                <div style="font-size: 30px;">
+                    {emoji} 
+                </div>
+                <div style="font-size: 30px;">
+                    {count.magnitude:.3g} 
+                </div>
+                <div style="font-size: 25px;">
+                    {name}
+                </div>
+                <div style="font-size: 12px;">
+                    (yearly ⚡️ production)
+                </div>
+            </div>
+        """, unsafe_allow_html=True)
+        st.markdown(f'<p align="center"><i>Based on energy consumption<i></p>', unsafe_allow_html = True)
+        
+    with col6:
+        ireland_count = format_energy_eq_electricity_consumption_ireland_company(impacts.energy, company_multiplier)
+        st.markdown(f"""
+            <div style="text-align: center;">
+                <div style="font-size: 30px;">
+                    ☘️🇮🇪
+                </div>
+                <div style="font-size: 30px;">
+                    {ireland_count.magnitude:.3g} 
+                </div>
+                <div style="font-size: 25px;">
+                    Irelands
+                </div>
+                <div style="font-size: 12px;">
+                    (yearly ⚡️ consumption)
+                </div>
+            </div>
+        """, unsafe_allow_html=True)
+        st.markdown(f'<p align="center"><i>Based on energy consumption<i></p>', unsafe_allow_html = True)
+
+    with col7:
+        paris_nyc_airplane = format_gwp_eq_airplane_paris_nyc_company(impacts.gwp, company_multiplier)
+        st.markdown(f"""
+            <div style="text-align: center;">
+                <div style="font-size: 30px;">
+                    ✈️
+                </div>
+                <div style="font-size: 30px;">
+                    {paris_nyc_airplane.magnitude:.3g}
+                </div>
+                <div style="font-size: 25px;">
+                    Paris ↔ NYC
+                </div>
+            </div>
+        """, unsafe_allow_html=True)
+        st.markdown(f'<p align="center"><i>Based on GHG emissions<i></p>', unsafe_allow_html = True)
+
+    with col8:
+        olympic_swimming_pool = format_water_eq_olympic_sized_swimming_pool_company(impacts.water, company_multiplier)
+        st.markdown(f"""
+            <div style="text-align: center;">
+                <div style="font-size: 30px;">
+                    🏊🏼  
+                </div>
+                <div style="font-size: 30px;">
+                    {olympic_swimming_pool.magnitude:.3g}
+                </div>
+                <div style="font-size: 22px;">
+                    Olympic-sized swimming pools
+                </div>
+            </div>
+        """, unsafe_allow_html=True)
+        st.markdown(f'<p align="center"><i>Based on water consumption<i></p>', unsafe_allow_html = True)

src/utils.py

@@ -78,7 +78,9 @@ BOTTLED_WATERS_EQ = q("0.75 L")
 # From https://ourworldindata.org/population-growth
 ONE_PERCENT_WORLD_POPULATION = 80_000_000
 
-DAYS_IN_YEAR = 365
+DAYS_IN_YEAR = 365.15
+
+WORKDAYS_IN_YEAR_FRANCE = 251
 
 # For a 900 MW nuclear plant -> 500 000 MWh / month
 # From https://www.edf.fr/groupe-edf/espaces-dedies/jeunes-enseignants/pour-les-jeunes/lenergie-de-a-a-z/produire-de-lelectricite/le-nucleaire-en-chiffres
@@ -235,6 +237,10 @@ def format_impacts_expert(impacts: Impacts, display_range: bool) -> QImpacts:
             pe=format_pe(pe),
             water=format_water(impacts.water)
         ), impacts.usage, impacts.embodied
+    
+
+
+######################################################################3
 
 #####################################################################################
 ### EQUIVALENT FORMATING
@@ -286,6 +292,7 @@ def format_energy_eq_electricity_consumption_ireland(energy: Quantity) -> Quanti
     electricity_eq = electricity_eq.to("TWh")
     return electricity_eq / YEARLY_IRELAND_ELECTRICITY_CONSUMPTION
 
+
 def format_gwp_eq_airplane_paris_nyc(gwp: Quantity) -> Quantity:
     gwp_eq = gwp * ONE_PERCENT_WORLD_POPULATION * DAYS_IN_YEAR
     gwp_eq = gwp_eq.to("kgCO2eq")
@@ -296,8 +303,64 @@ def format_water_eq_olympic_sized_swimming_pool(water: Quantity) -> Quantity:
     water_eq = water_eq.to("L")
     return water_eq / OLYMPIC_SWIMMING_POOL
 
-# def format_water_eq_olympic_sized_swimming_pool(water):
-#     water_eq = water * ONE_PERCENT_WORLD_POPULATION * DAYS_IN_YEAR
-#     return water_eq / OLYMPIC_SWIMMING_POOL
+########################################################################
+
+def format_energy_eq_physical_activity_company(energy: Quantity, company_multiplier) -> tuple[PhysicalActivity, Quantity]:
+    energy = energy.to("kJ")
+    running_eq = energy / RUNNING_ENERGY_EQ * company_multiplier
+    if running_eq > q("1 km"):
+        return PhysicalActivity.RUNNING, running_eq
+
+    walking_eq = energy / WALKING_ENERGY_EQ
+    if walking_eq < q("1 km"):
+        walking_eq = walking_eq.to("meter")
+    return PhysicalActivity.WALKING, walking_eq
+
+def format_energy_eq_electric_vehicle_company(energy: Quantity, company_multiplier) -> Quantity:
+    energy = energy.to("kWh")
+    ev_eq = energy / EV_ENERGY_EQ * company_multiplier
+    if ev_eq < q("1 km"):
+        ev_eq = ev_eq.to("meter")
+    return ev_eq
+
+def format_gwp_eq_streaming_company(gwp: Quantity, company_multiplier) -> Quantity:
+    gwp = gwp.to("kgCO2eq")
+    streaming_eq = gwp * STREAMING_GWP_EQ * company_multiplier
+    if streaming_eq < q("1 h"):
+        streaming_eq = streaming_eq.to("min")
+    if streaming_eq < q("1 min"):
+        streaming_eq = streaming_eq.to("s")
+    return streaming_eq
+
+def format_water_eq_bottled_waters_company(water: Quantity, company_multiplier) -> Quantity:
+    water = water.to("L")
+    bottled_water_eq = water / BOTTLED_WATERS_EQ * company_multiplier
+    return bottled_water_eq
+
+def format_energy_eq_electricity_production_company(energy: Quantity, company_multiplier) -> tuple[EnergyProduction, Quantity]:
+    electricity_eq = energy * company_multiplier * WORKDAYS_IN_YEAR_FRANCE
+    electricity_eq = electricity_eq.to("TWh")
+    if electricity_eq > YEARLY_NUCLEAR_ENERGY_EQ:
+        return EnergyProduction.NUCLEAR, electricity_eq / YEARLY_NUCLEAR_ENERGY_EQ
+    electricity_eq = electricity_eq.to("GWh")
+    return EnergyProduction.WIND, electricity_eq / YEARLY_WIND_ENERGY_EQ
+
+
+def format_energy_eq_electricity_consumption_ireland_company(energy: Quantity, company_multiplier) -> Quantity:
+    electricity_eq = energy * company_multiplier * WORKDAYS_IN_YEAR_FRANCE
+    electricity_eq = electricity_eq.to("TWh")
+    return electricity_eq / YEARLY_IRELAND_ELECTRICITY_CONSUMPTION
+
+
+def format_gwp_eq_airplane_paris_nyc_company(gwp: Quantity, company_multiplier) -> Quantity:
+    gwp_eq = gwp * company_multiplier * WORKDAYS_IN_YEAR_FRANCE
+    gwp_eq = gwp_eq.to("kgCO2eq")
+    return gwp_eq / AIRPLANE_PARIS_NYC_GWP_EQ
+
+def format_water_eq_olympic_sized_swimming_pool_company(water: Quantity, company_multiplier) -> Quantity:
+    water_eq = water * company_multiplier * WORKDAYS_IN_YEAR_FRANCE
+    water_eq = water_eq.to("L")
+    return water_eq / OLYMPIC_SWIMMING_POOL
+
 
 ####################################################################################### MODELS PARAMETER####################################################################################