+
+โ ๏ธ You have selected a closed-source model. Please be aware that - some providers do not fully disclose information about such models. Consequently, our - estimates have a lower precision for closed-source models. For further details, refer to - our FAQ in the About section. -
""", elem_classes="warning-box") - - with gr.Row(): - gr.Markdown(""" - ## Environmental impacts - - To understand how the environmental impacts are computed go to the ๐ Methodology tab. - """) - with gr.Row(): - with gr.Column(scale=1, min_width=220): - gr.Markdown(f""" -Evaluates the electricity consumption
Evaluates the effect on global warming
Evaluates the use of metals and minerals
Evaluates the use of energy resources
Based on energy consumption
Based on energy consumption
Based on GHG emissions
Based on electricity consumption
Based on electricity consumption
Based on GHG emissions
Evaluates the electricity consumption
Evaluates the effect on global warming
% of GWP by usage (vs embodied)
Evaluates the use of metals and minerals
% of ADPE by usage (vs embodied)
Evaluates the use of energy resources
% of PE by usage (vs embodied)
Evaluates the electricity consumption
Evaluates the effect on global warming
Evaluates the use of metals and minerals
Evaluates the use of energy resources
To understand how the environmental impacts are computed go to the ๐ Methodology tab.
', unsafe_allow_html=True) + display_impacts(impacts) + + with st.container(border=True): + + st.markdown('Making this request to the LLM is equivalent to the following actions :
', unsafe_allow_html=True) + display_equivalent(impacts) + + except Exception as e: + st.error('Could not find the model in the repository. Please try another model.') \ No newline at end of file diff --git a/constants.py b/constants.py new file mode 100755 index 0000000000000000000000000000000000000000..01f5f17177c0e02cb2539be85e25ad6f1408e0a5 --- /dev/null +++ b/constants.py @@ -0,0 +1,106 @@ +PROVIDERS = [ + ("OpenAI", "openai"), + ("Anthropic", "anthropic"), + ("Cohere", "cohere"), + ("Meta", "huggingface_hub/meta"), + ("Mistral AI", "mistralai"), +] + +OPENAI_MODELS = [ + ("GPT-4o", "gpt-4o"), + ("GPT-4-Turbo", "gpt-4-turbo"), + ("GPT-4", "gpt-4"), + ("GPT-3.5-Turbo", "gpt-3.5-turbo"), +] + +ANTHROPIC_MODELS = [ + ("Claude 3 Opus", "claude-3-opus-20240229"), + ("Claude 3 Sonnet", "claude-3-sonnet-20240229"), + ("Claude 3 Haiku", "claude-3-haiku-20240307"), + ("Claude 2.1", "claude-2.1"), + ("Claude 2.0", "claude-2.0"), + ("Claude Instant 1.2", "claude-instant-1.2"), +] + +COHERE_MODELS = [ + ("Command Light", "command-light"), + ("Command", "command"), + ("Command R", "command-r"), + ("Command R+", "command-r-plus"), +] + +META_MODELS = [ + ("Llama 3 8B", "meta-llama/Meta-Llama-3-8B"), + ("Llama 3 70B", "meta-llama/Meta-Llama-3-70B"), + ("Llama 2 7B", "meta-llama/Llama-2-7b-hf"), + ("Llama 2 13B", "meta-llama/Llama-2-13b-hf"), + ("Llama 2 70B", "meta-llama/Llama-2-70b-hf"), +] + +MISTRALAI_MODELS = [ + ("Mistral 7B", "open-mistral-7b"), + ("Mixtral 8x7B", "open-mixtral-8x7b"), + ("Mixtral 8x22B", "open-mixtral-8x22b"), + ("Tiny", "mistral-tiny-2312"), + ("Small", "mistral-small-2402"), + ("Medium", "mistral-medium-2312"), + ("Large", "mistral-large-2402"), +] + +PROMPTS = [ + ("Write a Tweet", 50), + ("Write an email", 170), + ("Write an article summary", 250), + ("Small conversation with a chatbot", 400), + ("Write a report of 5 pages", 5000), + ("Write the code for this app", 10000) +] +PROMPTS = [(s + f" ({v} output tokens)", v) for (s, v) in PROMPTS] + +CLOSED_SOURCE_MODELS = { + "openai/gpt-4o", + "openai/gpt-4-turbo", + "openai/gpt-4", + "openai/gpt-3.5-turbo", + "anthropic/claude-3-opus-20240229", + "anthropic/claude-3-sonnet-20240229", + "anthropic/claude-3-haiku-20240307", + "anthropic/claude-2.1", + "anthropic/claude-2.0", + "anthropic/claude-instant-1.2", + "mistralai/mistral-tiny-2312", + "mistralai/mistral-small-2402", + "mistralai/mistral-medium-2312", + "mistralai/mistral-large-2402", +} + +MODELS = [ + ("OpenAI / GPT-4o", "openai/gpt-4o"), + ("OpenAI / GPT-4-Turbo", "openai/gpt-4-turbo"), + ("OpenAI / GPT-4", "openai/gpt-4"), + ("OpenAI / GPT-3.5-Turbo", "openai/gpt-3.5-turbo"), + ("Anthropic / Claude 3 Opus", "anthropic/claude-3-opus-20240229"), + ("Anthropic / Claude 3 Sonnet", "anthropic/claude-3-sonnet-20240229"), + ("Anthropic / Claude 3 Haiku", "anthropic/claude-3-haiku-20240307"), + ("Anthropic / Claude 2.1", "anthropic/claude-2.1"), + ("Anthropic / Claude 2.0", "anthropic/claude-2.0"), + ("Anthropic / Claude Instant 1.2", "anthropic/claude-instant-1.2"), + ("Mistral AI / Mistral 7B", "mistralai/open-mistral-7b"), + ("Mistral AI / Mixtral 8x7B", "mistralai/open-mixtral-8x7b"), + ("Mistral AI / Mixtral 8x22B", "mistralai/open-mixtral-8x22b"), + ("Mistral AI / Tiny", "mistralai/mistral-tiny-2312"), + ("Mistral AI / Small", "mistralai/mistral-small-2402"), + ("Mistral AI / Medium", "mistralai/mistral-medium-2312"), + ("Mistral AI / Large", "mistralai/mistral-large-2402"), + ("Meta / Llama 3 8B", "huggingface_hub/meta-llama/Meta-Llama-3-8B"), + ("Meta / Llama 3 70B", "huggingface_hub/meta-llama/Meta-Llama-3-70B"), + ("Meta / Llama 2 7B", "huggingface_hub/meta-llama/Llama-2-7b-hf"), + ("Meta / Llama 2 13B", "huggingface_hub/meta-llama/Llama-2-13b-hf"), + ("Meta / Llama 2 70B", "huggingface_hub/meta-llama/Llama-2-70b-hf"), + ("Cohere / Command Light", "cohere/command-light"), + ("Cohere / Command", "cohere/command"), + ("Cohere / Command R", "cohere/command-r"), + ("Cohere / Command R+", "cohere/command-r-plus"), +] + +MODEL_REPOSITORY_URL = "https://raw.githubusercontent.com/genai-impact/ecologits/refs/heads/main/ecologits/data/models.json" \ No newline at end of file diff --git a/content.py b/content.py new file mode 100755 index 0000000000000000000000000000000000000000..e1503dc72bcbe2c3cd89a41479da761ff41996d5 --- /dev/null +++ b/content.py @@ -0,0 +1,232 @@ +HERO_TEXT = """ +
+
++ EcoLogits is a python library that tracks the energy consumption and environmental + footprint of using generative AI models through APIs. +
+
+ This work is licensed under
+
+ CC BY-SA 4.0
+
+ 
+ 
+ 
+
+ This work is licensed under
+
+ CC BY-SA 4.0
+
+
+
+
+
Evaluates the electricity consumption
', unsafe_allow_html = True) + + with col_ghg: + st.markdown('Evaluates the effect on global warming
', unsafe_allow_html = True) + + with col_adpe: + st.markdown('Evaluates the use of metals and minerals
', unsafe_allow_html = True) + + with col_pe: + st.markdown('Evaluates the use of energy resources
', unsafe_allow_html = True) + + with col_water: + st.markdown('Evaluates the use of water
', unsafe_allow_html = True) + +############################################################################################################ + +def display_equivalent(impacts): + + st.divider() + + ev_eq = format_energy_eq_electric_vehicle(impacts.energy) + + streaming_eq = format_gwp_eq_streaming(impacts.gwp) + + col1, col2, col3 = st.columns(3) + + with col1: + physical_activity, distance = format_energy_eq_physical_activity(impacts.energy) + if physical_activity == PhysicalActivity.WALKING: + physical_activity = "๐ถ " + physical_activity.capitalize() + if physical_activity == PhysicalActivity.RUNNING: + physical_activity = "๐ " + physical_activity.capitalize() + + st.markdown(f'Based on energy consumption
', unsafe_allow_html = True) + + with col2: + ev_eq = format_energy_eq_electric_vehicle(impacts.energy) + st.markdown(f'Based on energy consumption
', unsafe_allow_html = True) + + with col3: + streaming_eq = format_gwp_eq_streaming(impacts.gwp) + st.markdown(f'Based on GHG emissions
', unsafe_allow_html = True) + + st.divider() + + st.markdown('If this use case is largely deployed around the world, the equivalent impacts would be the impacts of this request x 1% of 8 billion people x 365 days in a year.
', unsafe_allow_html = True) + + col4, col5, col6 = st.columns(3) + + with col4: + + electricity_production, count = format_energy_eq_electricity_production(impacts.energy) + if electricity_production == EnergyProduction.NUCLEAR: + emoji = "โข๏ธ" + name = "Nuclear power plants" + if electricity_production == EnergyProduction.WIND: + emoji = "๐จ๏ธ " + name = "Wind turbines" + st.markdown(f'Based on energy consumption
', unsafe_allow_html = True) + + with col5: + ireland_count = format_energy_eq_electricity_consumption_ireland(impacts.energy) + st.markdown(f'Based on energy consumption
', unsafe_allow_html = True) + + with col6: + paris_nyc_airplane = format_gwp_eq_airplane_paris_nyc(impacts.gwp) + st.markdown(f'Based on GHG emissions
', unsafe_allow_html = True) \ No newline at end of file diff --git a/models.py b/models.py new file mode 100755 index 0000000000000000000000000000000000000000..956903fd3d0df69f6d8e4ec9895f25cd153a2a01 --- /dev/null +++ b/models.py @@ -0,0 +1,46 @@ +import requests +import json +import pandas as pd +from src.constants import MODEL_REPOSITORY_URL + +def clean_models_data(df): + + dict_providers = { + 'google': 'Google', + 'mistralai': 'MistralAI', + 'meta-llama': 'Meta', + 'openai': 'OpenAI', + 'anthropic': 'Anthropic', + 'cohere': 'Cohere', + 'microsoft': 'Microsoft', + 'mistral-community': 'Mistral Community', + 'databricks': 'Databricks' + } + + df.drop('type', axis=1, inplace=True) + + df.loc[df['name'].str.contains('/'), 'name_clean'] = df.loc[df['name'].str.contains('/'), 'name'].str.split('/').str[1] + df['name_clean'] = df['name_clean'].fillna(df['name']) + df['name_clean'] = df['name_clean'].replace({'-': ' '}, regex = True) + + df.loc[df['provider'] == 'huggingface_hub', 'provider_clean'] = df.loc[df['provider'] == 'huggingface_hub', 'name'].str.split('/').str[0] + df['provider_clean'] = df['provider_clean'].fillna(df['provider']) + df['provider_clean'] = df['provider_clean'].replace(dict_providers, regex = True) + + df['architecture_type'] = df['architecture'].apply(lambda x: x['type']) + df['architecture_parameters'] = df['architecture'].apply(lambda x: x['parameters']) + + df['warnings'] = df['warnings'].apply(lambda x: ', '.join(x) if x else None).fillna('none') + df['warning_arch'] = df['warnings'].apply(lambda x: 'model-arch-not-released' in x) + df['warning_multi_modal'] = df['warnings'].apply(lambda x: 'model-arch-multimodal' in x) + + return df[['provider', 'provider_clean', 'name', 'name_clean', 'architecture_type', 'architecture_parameters', 'warning_arch', 'warning_multi_modal']] + +def load_models(): + + resp = requests.get(MODEL_REPOSITORY_URL) + data = json.loads(resp.text) + df = pd.DataFrame(data['models']) + + return clean_models_data(df) + diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 0000000000000000000000000000000000000000..352b479a916e22258d23fa2667aaea313794b1b1 --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,12 @@ +[project] +name = "ecologits-calculator-streamlit" +version = "0.1.0" +description = "Add your description here" +readme = "README.md" +requires-python = ">=3.12" +dependencies = [ + "ecologits>=0.6.1", + "pint>=0.24.4", + "plotly>=6.0.0", + "streamlit>=1.43.1", +] diff --git a/requirements-dev.txt b/requirements-dev.txt deleted file mode 100644 index 34468efab8d8185af5c6e8642da82d98cbbed799..0000000000000000000000000000000000000000 --- a/requirements-dev.txt +++ /dev/null @@ -1,6 +0,0 @@ -gradio -ecologits==0.5.1 -pint -beautifulsoup4 -requests -tiktoken \ No newline at end of file diff --git a/requirements.txt b/requirements.txt old mode 100644 new mode 100755 index 9b17f99731be34eef108bf1b0eab003ce56be7b7..1af5d473909d1454aed5d2894ec06ff5ecc9b13d --- a/requirements.txt +++ b/requirements.txt @@ -1,5 +1,4 @@ -ecologits==0.5.1 +streamlit +ecologits pint -beautifulsoup4 -requests -tiktoken \ No newline at end of file +plotly \ No newline at end of file diff --git a/src/__init__.py b/src/__init__.py new file mode 100755 index 0000000000000000000000000000000000000000..e53d4650102036d98cd320bda9d8e98feba875c8 --- /dev/null +++ b/src/__init__.py @@ -0,0 +1,8 @@ +from .content import * +from .constants import * +from .expert import expert_mode +from .utils import * +from .calculator import calculator_mode +from .impacts import get_impacts, display_impacts +from .models import load_models +from .electricity_mix import * \ No newline at end of file diff --git a/src/__pycache__/__init__.cpython-312.pyc b/src/__pycache__/__init__.cpython-312.pyc new file mode 100644 index 0000000000000000000000000000000000000000..f855e5e9daf0fca729cbd4ea9e55d3cb8a6cc6c1 Binary files /dev/null and b/src/__pycache__/__init__.cpython-312.pyc differ diff --git a/src/__pycache__/calculator.cpython-312.pyc b/src/__pycache__/calculator.cpython-312.pyc new file mode 100644 index 0000000000000000000000000000000000000000..26b4cb670a13d3e2bb58f33a3055025045df682b Binary files /dev/null and b/src/__pycache__/calculator.cpython-312.pyc differ diff --git a/src/__pycache__/constants.cpython-312.pyc b/src/__pycache__/constants.cpython-312.pyc new file mode 100644 index 0000000000000000000000000000000000000000..6e31cba5eb8d5683f32f7c1f09d664e80722b516 Binary files /dev/null and b/src/__pycache__/constants.cpython-312.pyc differ diff --git a/src/__pycache__/content.cpython-312.pyc b/src/__pycache__/content.cpython-312.pyc new file mode 100644 index 0000000000000000000000000000000000000000..52787e694c0ece26f109831c384332a76c35c851 Binary files /dev/null and b/src/__pycache__/content.cpython-312.pyc differ diff --git a/src/__pycache__/electricity_mix.cpython-312.pyc b/src/__pycache__/electricity_mix.cpython-312.pyc new file mode 100644 index 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differ diff --git a/src/__pycache__/utils.cpython-312.pyc b/src/__pycache__/utils.cpython-312.pyc new file mode 100644 index 0000000000000000000000000000000000000000..285352d7406b8d71b43d2b0ee633837385eef5ca Binary files /dev/null and b/src/__pycache__/utils.cpython-312.pyc differ diff --git a/src/assets.py b/src/assets.py deleted file mode 100644 index bf148570b111a9e5dddb75a84ef7a5de03111d2a..0000000000000000000000000000000000000000 --- a/src/assets.py +++ /dev/null @@ -1,17 +0,0 @@ -custom_css = """ - -.descriptive-text span { - font-size: 16px !important; -} - - -.warning-box p { - background-color: #ff91001a; - border: 1px solid #f19637; - border-radius: 8px; - padding: 4px 8px; - margin: 4px 0px; - font-size: 14px !important; - font-weight: bold !important; -} -""" \ No newline at end of file diff --git a/src/calculator.py b/src/calculator.py new file mode 100755 index 0000000000000000000000000000000000000000..ea3a8c29c27b1f6361cb6ac9ad292b540d8355c1 --- /dev/null +++ b/src/calculator.py @@ -0,0 +1,67 @@ +import streamlit as st +import pandas as pd + +from ecologits.tracers.utils import llm_impacts +from src.impacts import get_impacts, display_impacts, display_equivalent +from src.utils import format_impacts +from src.content import WARNING_CLOSED_SOURCE, WARNING_MULTI_MODAL, WARNING_BOTH +from src.models import load_models, clean_models_data + +from src.constants import PROMPTS + +def calculator_mode(): + + with st.container(border=True): + + df = load_models() + + col1, col2, col3 = st.columns(3) + + with col1: + provider = st.selectbox(label = 'Provider', + options = [x for x in df['provider_clean'].unique()], + index = 9) + provider_raw = df[df['provider_clean'] == provider]['provider'].values[0] + + with col2: + model = st.selectbox('Model', [x for x in df['name_clean'].unique() if x in df[df['provider_clean'] == provider]['name_clean'].unique()]) + model_raw = df[(df['provider_clean'] == provider) & (df['name_clean'] == model)]['name'].values[0] + + with col3: + output_tokens = st.selectbox('Example prompt', [x[0] for x in PROMPTS]) + + # WARNING DISPLAY + + 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) + + 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) + + with st.container(border=True): + + st.markdown('To understand how the environmental impacts are computed go to the ๐ Methodology tab.
', unsafe_allow_html=True) + display_impacts(impacts) + + with st.container(border=True): + + st.markdown('Making this request to the LLM is equivalent to the following actions :
', unsafe_allow_html=True) + display_equivalent(impacts) + + except Exception as e: + st.error('Could not find the model in the repository. Please try another model.') \ No newline at end of file diff --git a/src/constants.py b/src/constants.py old mode 100644 new mode 100755 index 7d3a45e468664a7dd05aba1b00ce1a8c56d08bc5..01f5f17177c0e02cb2539be85e25ad6f1408e0a5 --- a/src/constants.py +++ b/src/constants.py @@ -1,103 +1,106 @@ -PROVIDERS = [ - ("OpenAI", "openai"), - ("Anthropic", "anthropic"), - ("Cohere", "cohere"), - ("Meta", "huggingface_hub/meta"), - ("Mistral AI", "mistralai"), -] - -OPENAI_MODELS = [ - ("GPT-4o", "gpt-4o"), - ("GPT-4-Turbo", "gpt-4-turbo"), - ("GPT-4", "gpt-4"), - ("GPT-3.5-Turbo", "gpt-3.5-turbo"), -] - -ANTHROPIC_MODELS = [ - ("Claude 3 Opus", "claude-3-opus-20240229"), - ("Claude 3 Sonnet", "claude-3-sonnet-20240229"), - ("Claude 3 Haiku", "claude-3-haiku-20240307"), - ("Claude 2.1", "claude-2.1"), - ("Claude 2.0", "claude-2.0"), - ("Claude Instant 1.2", "claude-instant-1.2"), -] - -COHERE_MODELS = [ - ("Command Light", "command-light"), - ("Command", "command"), - ("Command R", "command-r"), - ("Command R+", "command-r-plus"), -] - -META_MODELS = [ - ("Llama 3 8B", "meta-llama/Meta-Llama-3-8B"), - ("Llama 3 70B", "meta-llama/Meta-Llama-3-70B"), - ("Llama 2 7B", "meta-llama/Llama-2-7b-hf"), - ("Llama 2 13B", "meta-llama/Llama-2-13b-hf"), - ("Llama 2 70B", "meta-llama/Llama-2-70b-hf"), -] - -MISTRALAI_MODELS = [ - ("Mistral 7B", "open-mistral-7b"), - ("Mixtral 8x7B", "open-mixtral-8x7b"), - ("Mixtral 8x22B", "open-mixtral-8x22b"), - ("Tiny", "mistral-tiny-2312"), - ("Small", "mistral-small-2402"), - ("Medium", "mistral-medium-2312"), - ("Large", "mistral-large-2402"), -] - -PROMPTS = [ - ("Write a Tweet", 50), - ("Write an email", 170), - ("Write an article summary", 250), - ("Small conversation with a chatbot", 400), - ("Write a report of 5 pages", 5000), -] -PROMPTS = [(s + f" ({v} output tokens)", v) for (s, v) in PROMPTS] - -CLOSED_SOURCE_MODELS = { - "openai/gpt-4o", - "openai/gpt-4-turbo", - "openai/gpt-4", - "openai/gpt-3.5-turbo", - "anthropic/claude-3-opus-20240229", - "anthropic/claude-3-sonnet-20240229", - "anthropic/claude-3-haiku-20240307", - "anthropic/claude-2.1", - "anthropic/claude-2.0", - "anthropic/claude-instant-1.2", - "mistralai/mistral-tiny-2312", - "mistralai/mistral-small-2402", - "mistralai/mistral-medium-2312", - "mistralai/mistral-large-2402", -} - -MODELS = [ - ("OpenAI / GPT-4o", "openai/gpt-4o"), - ("OpenAI / GPT-4-Turbo", "openai/gpt-4-turbo"), - ("OpenAI / GPT-4", "openai/gpt-4"), - ("OpenAI / GPT-3.5-Turbo", "openai/gpt-3.5-turbo"), - ("Anthropic / Claude 3 Opus", "anthropic/claude-3-opus-20240229"), - ("Anthropic / Claude 3 Sonnet", "anthropic/claude-3-sonnet-20240229"), - ("Anthropic / Claude 3 Haiku", "anthropic/claude-3-haiku-20240307"), - ("Anthropic / Claude 2.1", "anthropic/claude-2.1"), - ("Anthropic / Claude 2.0", "anthropic/claude-2.0"), - ("Anthropic / Claude Instant 1.2", "anthropic/claude-instant-1.2"), - ("Mistral AI / Mistral 7B", "mistralai/open-mistral-7b"), - ("Mistral AI / Mixtral 8x7B", "mistralai/open-mixtral-8x7b"), - ("Mistral AI / Mixtral 8x22B", "mistralai/open-mixtral-8x22b"), - ("Mistral AI / Tiny", "mistralai/mistral-tiny-2312"), - ("Mistral AI / Small", "mistralai/mistral-small-2402"), - ("Mistral AI / Medium", "mistralai/mistral-medium-2312"), - ("Mistral AI / Large", "mistralai/mistral-large-2402"), - ("Meta / Llama 3 8B", "huggingface_hub/meta-llama/Meta-Llama-3-8B"), - ("Meta / Llama 3 70B", "huggingface_hub/meta-llama/Meta-Llama-3-70B"), - ("Meta / Llama 2 7B", "huggingface_hub/meta-llama/Llama-2-7b-hf"), - ("Meta / Llama 2 13B", "huggingface_hub/meta-llama/Llama-2-13b-hf"), - ("Meta / Llama 2 70B", "huggingface_hub/meta-llama/Llama-2-70b-hf"), - ("Cohere / Command Light", "cohere/command-light"), - ("Cohere / Command", "cohere/command"), - ("Cohere / Command R", "cohere/command-r"), - ("Cohere / Command R+", "cohere/command-r-plus"), -] +PROVIDERS = [ + ("OpenAI", "openai"), + ("Anthropic", "anthropic"), + ("Cohere", "cohere"), + ("Meta", "huggingface_hub/meta"), + ("Mistral AI", "mistralai"), +] + +OPENAI_MODELS = [ + ("GPT-4o", "gpt-4o"), + ("GPT-4-Turbo", "gpt-4-turbo"), + ("GPT-4", "gpt-4"), + ("GPT-3.5-Turbo", "gpt-3.5-turbo"), +] + +ANTHROPIC_MODELS = [ + ("Claude 3 Opus", "claude-3-opus-20240229"), + ("Claude 3 Sonnet", "claude-3-sonnet-20240229"), + ("Claude 3 Haiku", "claude-3-haiku-20240307"), + ("Claude 2.1", "claude-2.1"), + ("Claude 2.0", "claude-2.0"), + ("Claude Instant 1.2", "claude-instant-1.2"), +] + +COHERE_MODELS = [ + ("Command Light", "command-light"), + ("Command", "command"), + ("Command R", "command-r"), + ("Command R+", "command-r-plus"), +] + +META_MODELS = [ + ("Llama 3 8B", "meta-llama/Meta-Llama-3-8B"), + ("Llama 3 70B", "meta-llama/Meta-Llama-3-70B"), + ("Llama 2 7B", "meta-llama/Llama-2-7b-hf"), + ("Llama 2 13B", "meta-llama/Llama-2-13b-hf"), + ("Llama 2 70B", "meta-llama/Llama-2-70b-hf"), +] + +MISTRALAI_MODELS = [ + ("Mistral 7B", "open-mistral-7b"), + ("Mixtral 8x7B", "open-mixtral-8x7b"), + ("Mixtral 8x22B", "open-mixtral-8x22b"), + ("Tiny", "mistral-tiny-2312"), + ("Small", "mistral-small-2402"), + ("Medium", "mistral-medium-2312"), + ("Large", "mistral-large-2402"), +] + +PROMPTS = [ + ("Write a Tweet", 50), + ("Write an email", 170), + ("Write an article summary", 250), + ("Small conversation with a chatbot", 400), + ("Write a report of 5 pages", 5000), + ("Write the code for this app", 10000) +] +PROMPTS = [(s + f" ({v} output tokens)", v) for (s, v) in PROMPTS] + +CLOSED_SOURCE_MODELS = { + "openai/gpt-4o", + "openai/gpt-4-turbo", + "openai/gpt-4", + "openai/gpt-3.5-turbo", + "anthropic/claude-3-opus-20240229", + "anthropic/claude-3-sonnet-20240229", + "anthropic/claude-3-haiku-20240307", + "anthropic/claude-2.1", + "anthropic/claude-2.0", + "anthropic/claude-instant-1.2", + "mistralai/mistral-tiny-2312", + "mistralai/mistral-small-2402", + "mistralai/mistral-medium-2312", + "mistralai/mistral-large-2402", +} + +MODELS = [ + ("OpenAI / GPT-4o", "openai/gpt-4o"), + ("OpenAI / GPT-4-Turbo", "openai/gpt-4-turbo"), + ("OpenAI / GPT-4", "openai/gpt-4"), + ("OpenAI / GPT-3.5-Turbo", "openai/gpt-3.5-turbo"), + ("Anthropic / Claude 3 Opus", "anthropic/claude-3-opus-20240229"), + ("Anthropic / Claude 3 Sonnet", "anthropic/claude-3-sonnet-20240229"), + ("Anthropic / Claude 3 Haiku", "anthropic/claude-3-haiku-20240307"), + ("Anthropic / Claude 2.1", "anthropic/claude-2.1"), + ("Anthropic / Claude 2.0", "anthropic/claude-2.0"), + ("Anthropic / Claude Instant 1.2", "anthropic/claude-instant-1.2"), + ("Mistral AI / Mistral 7B", "mistralai/open-mistral-7b"), + ("Mistral AI / Mixtral 8x7B", "mistralai/open-mixtral-8x7b"), + ("Mistral AI / Mixtral 8x22B", "mistralai/open-mixtral-8x22b"), + ("Mistral AI / Tiny", "mistralai/mistral-tiny-2312"), + ("Mistral AI / Small", "mistralai/mistral-small-2402"), + ("Mistral AI / Medium", "mistralai/mistral-medium-2312"), + ("Mistral AI / Large", "mistralai/mistral-large-2402"), + ("Meta / Llama 3 8B", "huggingface_hub/meta-llama/Meta-Llama-3-8B"), + ("Meta / Llama 3 70B", "huggingface_hub/meta-llama/Meta-Llama-3-70B"), + ("Meta / Llama 2 7B", "huggingface_hub/meta-llama/Llama-2-7b-hf"), + ("Meta / Llama 2 13B", "huggingface_hub/meta-llama/Llama-2-13b-hf"), + ("Meta / Llama 2 70B", "huggingface_hub/meta-llama/Llama-2-70b-hf"), + ("Cohere / Command Light", "cohere/command-light"), + ("Cohere / Command", "cohere/command"), + ("Cohere / Command R", "cohere/command-r"), + ("Cohere / Command R+", "cohere/command-r-plus"), +] + +MODEL_REPOSITORY_URL = "https://raw.githubusercontent.com/genai-impact/ecologits/refs/heads/main/ecologits/data/models.json" \ No newline at end of file diff --git a/src/content.py b/src/content.py old mode 100644 new mode 100755 index 69e78816887f4e7bfd3905120599f2e284e97663..e1503dc72bcbe2c3cd89a41479da761ff41996d5 --- a/src/content.py +++ b/src/content.py @@ -1,286 +1,232 @@ - -HERO_TEXT = """ -
-
-- EcoLogits is a python library that tracks the energy consumption and environmental - footprint of using generative AI models through APIs. -
-
- This work is licensed under
-
- CC BY-SA 4.0
-
-
-
-
-
- This work is licensed under
-
- CC BY-SA 4.0
-
-
-
-
-
+
++ EcoLogits is a python library that tracks the energy consumption and environmental + footprint of using generative AI models through APIs. +
+
+ This work is licensed under
+
+ CC BY-SA 4.0
+
+
+
+
+
+ This work is licensed under
+
+ CC BY-SA 4.0
+
+
+
+
+
Evaluates the electricity consumption
', unsafe_allow_html = True) + + with col_ghg: + st.markdown('Evaluates the effect on global warming
', unsafe_allow_html = True) + + with col_adpe: + st.markdown('Evaluates the use of metals and minerals
', unsafe_allow_html = True) + + with col_pe: + st.markdown('Evaluates the use of energy resources
', unsafe_allow_html = True) + + with col_water: + st.markdown('Evaluates the use of water
', unsafe_allow_html = True) + +############################################################################################################ + +def display_equivalent(impacts): + + st.divider() + + ev_eq = format_energy_eq_electric_vehicle(impacts.energy) + + streaming_eq = format_gwp_eq_streaming(impacts.gwp) + + col1, col2, col3 = st.columns(3) + + with col1: + physical_activity, distance = format_energy_eq_physical_activity(impacts.energy) + if physical_activity == PhysicalActivity.WALKING: + physical_activity = "๐ถ " + physical_activity.capitalize() + if physical_activity == PhysicalActivity.RUNNING: + physical_activity = "๐ " + physical_activity.capitalize() + + st.markdown(f'Based on energy consumption
', unsafe_allow_html = True) + + with col2: + ev_eq = format_energy_eq_electric_vehicle(impacts.energy) + st.markdown(f'Based on energy consumption
', unsafe_allow_html = True) + + with col3: + streaming_eq = format_gwp_eq_streaming(impacts.gwp) + st.markdown(f'Based on GHG emissions
', unsafe_allow_html = True) + + st.divider() + + st.markdown('If this use case is largely deployed around the world, the equivalent impacts would be the impacts of this request x 1% of 8 billion people x 365 days in a year.
', unsafe_allow_html = True) + + col4, col5, col6 = st.columns(3) + + with col4: + + electricity_production, count = format_energy_eq_electricity_production(impacts.energy) + if electricity_production == EnergyProduction.NUCLEAR: + emoji = "โข๏ธ" + name = "Nuclear power plants" + if electricity_production == EnergyProduction.WIND: + emoji = "๐จ๏ธ " + name = "Wind turbines" + st.markdown(f'Based on energy consumption
', unsafe_allow_html = True) + + with col5: + ireland_count = format_energy_eq_electricity_consumption_ireland(impacts.energy) + st.markdown(f'Based on energy consumption
', unsafe_allow_html = True) + + with col6: + paris_nyc_airplane = format_gwp_eq_airplane_paris_nyc(impacts.gwp) + st.markdown(f'Based on GHG emissions
', unsafe_allow_html = True) \ No newline at end of file diff --git a/src/models.py b/src/models.py new file mode 100755 index 0000000000000000000000000000000000000000..956903fd3d0df69f6d8e4ec9895f25cd153a2a01 --- /dev/null +++ b/src/models.py @@ -0,0 +1,46 @@ +import requests +import json +import pandas as pd +from src.constants import MODEL_REPOSITORY_URL + +def clean_models_data(df): + + dict_providers = { + 'google': 'Google', + 'mistralai': 'MistralAI', + 'meta-llama': 'Meta', + 'openai': 'OpenAI', + 'anthropic': 'Anthropic', + 'cohere': 'Cohere', + 'microsoft': 'Microsoft', + 'mistral-community': 'Mistral Community', + 'databricks': 'Databricks' + } + + df.drop('type', axis=1, inplace=True) + + df.loc[df['name'].str.contains('/'), 'name_clean'] = df.loc[df['name'].str.contains('/'), 'name'].str.split('/').str[1] + df['name_clean'] = df['name_clean'].fillna(df['name']) + df['name_clean'] = df['name_clean'].replace({'-': ' '}, regex = True) + + df.loc[df['provider'] == 'huggingface_hub', 'provider_clean'] = df.loc[df['provider'] == 'huggingface_hub', 'name'].str.split('/').str[0] + df['provider_clean'] = df['provider_clean'].fillna(df['provider']) + df['provider_clean'] = df['provider_clean'].replace(dict_providers, regex = True) + + df['architecture_type'] = df['architecture'].apply(lambda x: x['type']) + df['architecture_parameters'] = df['architecture'].apply(lambda x: x['parameters']) + + df['warnings'] = df['warnings'].apply(lambda x: ', '.join(x) if x else None).fillna('none') + df['warning_arch'] = df['warnings'].apply(lambda x: 'model-arch-not-released' in x) + df['warning_multi_modal'] = df['warnings'].apply(lambda x: 'model-arch-multimodal' in x) + + return df[['provider', 'provider_clean', 'name', 'name_clean', 'architecture_type', 'architecture_parameters', 'warning_arch', 'warning_multi_modal']] + +def load_models(): + + resp = requests.get(MODEL_REPOSITORY_URL) + data = json.loads(resp.text) + df = pd.DataFrame(data['models']) + + return clean_models_data(df) + diff --git a/src/scrapper.py b/src/scrapper.py deleted file mode 100644 index e85b2e51d9b335dcf233b820256ad66bb0fed46e..0000000000000000000000000000000000000000 --- a/src/scrapper.py +++ /dev/null @@ -1,33 +0,0 @@ -import requests -from bs4 import BeautifulSoup -import tiktoken - -tokenizer = tiktoken.get_encoding('cl100k_base') - -def process_input(text): - - r = requests.get(text, verify=False) - - soup = BeautifulSoup(r.text, "html.parser") - print(soup) - list_text = str(soup).split('parts":["') - #print(list_text) - s = '' - for item in list_text[1:int(len(list_text)/2)]: - if list_text.index(item)%2 == 1: - s = s + item.split('"]')[0] - - amout_token = tiktoken_len(s) - - return amout_token - -def tiktoken_len(text): - tokens = tokenizer.encode( - text, - disallowed_special=() - ) - return len(tokens) - -answer = process_input('https://chatgpt.com/share/6737b9b5-56fc-8002-a212-35339f5b1d5a') - -print(answer) \ No newline at end of file diff --git a/src/utils.py b/src/utils.py old mode 100644 new mode 100755 index ee510314985d370438cba4d1073563664b3cfbc4..af4187d59db6f21451bd8b4a921a5fee808f99e6 --- a/src/utils.py +++ b/src/utils.py @@ -1,197 +1,262 @@ -from dataclasses import dataclass -from enum import Enum - -import pandas as pd - -from ecologits.impacts.modeling import Impacts, Energy, GWP, ADPe, PE -from ecologits.tracers.utils import llm_impacts, _avg -from pint import UnitRegistry, Quantity - - -u = UnitRegistry() -u.define('Wh = watt_hour') -u.define('kWh = kilowatt_hour') -u.define('MWh = megawatt_hour') -u.define('GWh = gigawatt_hour') -u.define('TWh = terawatt_hour') -u.define('gCO2eq = gram') -u.define('kgCO2eq = kilogram') -u.define('tCO2eq = metricton') -u.define('kgSbeq = kilogram') -u.define('kJ = kilojoule') -u.define('MJ = megajoule') -u.define('m = meter') -u.define('km = kilometer') -u.define('s = second') -u.define('min = minute') -u.define('h = hour') -q = u.Quantity - - -@dataclass -class QImpacts: - energy: Quantity - gwp: Quantity - adpe: Quantity - pe: Quantity - - -class PhysicalActivity(str, Enum): - RUNNING = "running" - WALKING = "walking" - - -class EnergyProduction(str, Enum): - NUCLEAR = "nuclear" - WIND = "wind" - - -COUNTRIES = [ - ("cook_islands", 38.81, 9_556), - ("tonga", 51.15, 104_490), - ("comoros", 100, 821_632), - ("samoa", 100, 821_632), -] - -def df_elec_mix_for_plot(): - return pd.DataFrame({ - 'country': ['Sweden', 'France', 'Canada', 'USA', 'China', 'Australia', 'India'], - 'electricity_mix': [46, 81, 238, 679, 1057, 1123, 1583] - }) - -# From https://www.runningtools.com/energyusage.htm -RUNNING_ENERGY_EQ = q("294 kJ / km") # running 1 km at 10 km/h with a weight of 70 kg -WALKING_ENERGY_EQ = q("196 kJ / km") # walking 1 km at 3 km/h with a weight of 70 kg - -# From https://selectra.info/energie/actualites/insolite/consommation-vehicules-electriques-france-2040 -# and https://www.tesla.com/fr_fr/support/power-consumption -EV_ENERGY_EQ = q("0.17 kWh / km") - -# From https://impactco2.fr/outils/comparateur?value=1&comparisons=streamingvideo -STREAMING_GWP_EQ = q("15.6 h / kgCO2eq") - -# From https://ourworldindata.org/population-growth -ONE_PERCENT_WORLD_POPULATION = 80_000_000 - -DAYS_IN_YEAR = 365 - -# 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 -YEARLY_NUCLEAR_ENERGY_EQ = q("6 TWh") - -# For a 2MW wind turbine -# https://www.ecologie.gouv.fr/eolien-terrestre -YEARLY_WIND_ENERGY_EQ = q("4.2 GWh") - -# Ireland yearly electricity consumption -# From https://en.wikipedia.org/wiki/List_of_countries_by_electricity_consumption -YEARLY_IRELAND_ELECTRICITY_CONSUMPTION = q("33 TWh") -IRELAND_POPULATION_MILLION = 5 - -# From https://impactco2.fr/outils/comparateur?value=1&comparisons=&equivalent=avion-pny -AIRPLANE_PARIS_NYC_GWP_EQ = q("177000 kgCO2eq") - - -def format_energy(energy: Energy) -> Quantity: - val = q(energy.value, energy.unit) - if val < q("1 kWh"): - val = val.to("Wh") - return val - - -def format_gwp(gwp: GWP) -> Quantity: - val = q(gwp.value, gwp.unit) - if val < q("1 kgCO2eq"): - val = val.to("gCO2eq") - return val - - -def format_adpe(adpe: ADPe) -> Quantity: - return q(adpe.value, adpe.unit) - - -def format_pe(pe: PE) -> Quantity: - val = q(pe.value, pe.unit) - if val < q("1 MJ"): - val = val.to("kJ") - return val - -def format_impacts(impacts: Impacts) -> QImpacts: - try: - impacts.energy.value = (impacts.energy.value.max + impacts.energy.value.min)/2 - impacts.gwp.value = (impacts.gwp.value.max + impacts.gwp.value.min)/2 - impacts.adpe.value = (impacts.adpe.value.max + impacts.adpe.value.min)/2 - impacts.pe.value = (impacts.pe.value.max + impacts.pe.value.min)/2 - return QImpacts( - energy=format_energy(impacts.energy), - gwp=format_gwp(impacts.gwp), - adpe=format_adpe(impacts.adpe), - pe=format_pe(impacts.pe) - ) - except: #when no range - return QImpacts( - energy=format_energy(impacts.energy), - gwp=format_gwp(impacts.gwp), - adpe=format_adpe(impacts.adpe), - pe=format_pe(impacts.pe) - ) - -def format_impacts_expert(impacts: Impacts) -> QImpacts: - return QImpacts( - energy=format_energy(impacts.energy), - gwp=format_gwp(impacts.gwp), - adpe=format_adpe(impacts.adpe), - pe=format_pe(impacts.pe) - - ), impacts.usage, impacts.embodied - - -def format_energy_eq_physical_activity(energy: Quantity) -> tuple[PhysicalActivity, Quantity]: - energy = energy.to("kJ") - running_eq = energy / RUNNING_ENERGY_EQ - 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(energy: Quantity) -> Quantity: - energy = energy.to("kWh") - ev_eq = energy / EV_ENERGY_EQ - if ev_eq < q("1 km"): - ev_eq = ev_eq.to("meter") - return ev_eq - - -def format_gwp_eq_streaming(gwp: Quantity) -> Quantity: - gwp = gwp.to("kgCO2eq") - streaming_eq = gwp * STREAMING_GWP_EQ - 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_energy_eq_electricity_production(energy: Quantity) -> tuple[EnergyProduction, Quantity]: - electricity_eq = energy * ONE_PERCENT_WORLD_POPULATION * DAYS_IN_YEAR - 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(energy: Quantity) -> Quantity: - electricity_eq = energy * ONE_PERCENT_WORLD_POPULATION * DAYS_IN_YEAR - 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") - return gwp_eq / AIRPLANE_PARIS_NYC_GWP_EQ +from dataclasses import dataclass +from enum import Enum + +import pandas as pd +from ecologits.model_repository import models +from ecologits.impacts.modeling import Impacts, Energy, GWP, ADPe, PE +#from ecologits.tracers.utils import llm_impacts +from pint import UnitRegistry, Quantity + +##################################################################################### +### UNITS DEFINITION +##################################################################################### + +u = UnitRegistry() +u.define('Wh = watt_hour') +u.define('kWh = kilowatt_hour') +u.define('MWh = megawatt_hour') +u.define('GWh = gigawatt_hour') +u.define('TWh = terawatt_hour') +u.define('gCO2eq = gram') +u.define('kgCO2eq = kilogram') +u.define('tCO2eq = metricton') +u.define('kgSbeq = kilogram') +u.define('kJ = kilojoule') +u.define('MJ = megajoule') +u.define('m = meter') +u.define('km = kilometer') +u.define('s = second') +u.define('min = minute') +u.define('h = hour') +q = u.Quantity + +@dataclass +class QImpacts: + energy: Quantity + gwp: Quantity + adpe: Quantity + pe: Quantity + + +class PhysicalActivity(str, Enum): + RUNNING = "running" + WALKING = "walking" + + +class EnergyProduction(str, Enum): + NUCLEAR = "nuclear" + WIND = "wind" + + +COUNTRIES = [ + ("cook_islands", 38.81, 9_556), + ("tonga", 51.15, 104_490), + ("comoros", 100, 821_632), + ("samoa", 100, 821_632), +] + +##################################################################################### +### EQUIVALENT RAW DATA +##################################################################################### + +# From https://www.runningtools.com/energyusage.htm +RUNNING_ENERGY_EQ = q("294 kJ / km") # running 1 km at 10 km/h with a weight of 70 kg +WALKING_ENERGY_EQ = q("196 kJ / km") # walking 1 km at 3 km/h with a weight of 70 kg + +# From https://selectra.info/energie/actualites/insolite/consommation-vehicules-electriques-france-2040 +# and https://www.tesla.com/fr_fr/support/power-consumption +EV_ENERGY_EQ = q("0.17 kWh / km") + +# From https://impactco2.fr/outils/comparateur?value=1&comparisons=streamingvideo +STREAMING_GWP_EQ = q("15.6 h / kgCO2eq") + +# From https://ourworldindata.org/population-growth +ONE_PERCENT_WORLD_POPULATION = 80_000_000 + +DAYS_IN_YEAR = 365 + +# 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 +YEARLY_NUCLEAR_ENERGY_EQ = q("6 TWh") + +# For a 2MW wind turbine +# https://www.ecologie.gouv.fr/eolien-terrestre +YEARLY_WIND_ENERGY_EQ = q("4.2 GWh") + +# Ireland yearly electricity consumption +# From https://en.wikipedia.org/wiki/List_of_countries_by_electricity_consumption +YEARLY_IRELAND_ELECTRICITY_CONSUMPTION = q("33 TWh") +IRELAND_POPULATION_MILLION = 5 + +# From https://impactco2.fr/outils/comparateur?value=1&comparisons=&equivalent=avion-pny +AIRPLANE_PARIS_NYC_GWP_EQ = q("177000 kgCO2eq") + +def filter_models(provider, list_models): + + model = 1 + + return model + +##################################################################################### +### IMPACTS FORMATING +##################################################################################### + +def format_energy(energy: Energy) -> Quantity: + val = q(energy.value, energy.unit) + if val < q("1 kWh"): + val = val.to("Wh") + return val + +def format_gwp(gwp: GWP) -> Quantity: + val = q(gwp.value, gwp.unit) + if val < q("1 kgCO2eq"): + val = val.to("gCO2eq") + return val + +def format_adpe(adpe: ADPe) -> Quantity: + return q(adpe.value, adpe.unit) + +def format_pe(pe: PE) -> Quantity: + val = q(pe.value, pe.unit) + if val < q("1 MJ"): + val = val.to("kJ") + return val + +def format_impacts(impacts: Impacts) -> QImpacts: + + try: + impacts.energy.value = (impacts.energy.value.max + impacts.energy.value.min)/2 + impacts.gwp.value = (impacts.gwp.value.max + impacts.gwp.value.min)/2 + impacts.adpe.value = (impacts.adpe.value.max + impacts.adpe.value.min)/2 + impacts.pe.value = (impacts.pe.value.max + impacts.pe.value.min)/2 + return QImpacts( + energy=format_energy(impacts.energy), + gwp=format_gwp(impacts.gwp), + adpe=format_adpe(impacts.adpe), + pe=format_pe(impacts.pe) + ), impacts.usage, impacts.embodied + except: #when no range + return QImpacts( + energy=format_energy(impacts.energy), + gwp=format_gwp(impacts.gwp), + adpe=format_adpe(impacts.adpe), + pe=format_pe(impacts.pe) + ), impacts.usage, impacts.embodied + +def split_impacts_u_e(impacts: Impacts) -> QImpacts: + return impacts.usage, impacts.embodied + +def average_range_impacts(RangeValue): + return (RangeValue.max + RangeValue.min)/2 + +def format_impacts_expert(impacts: Impacts, display_range: bool) -> QImpacts: + + if display_range: + return QImpacts( + energy=format_energy(impacts.energy), + gwp=format_gwp(impacts.gwp), + adpe=format_adpe(impacts.adpe), + pe=format_pe(impacts.pe) + ), impacts.usage, impacts.embodied + + else: + energy = {"value":(impacts.energy.value.max + impacts.energy.value.min)/2, "unit":impacts.energy.unit} + gwp = (impacts.gwp.value.max + impacts.gwp.value.min)/2 + adpe = (impacts.adpe.value.max + impacts.adpe.value.min)/2 + pe = (impacts.pe.value.max + impacts.pe.value.min)/2 + return QImpacts( + energy=format_energy(energy), + gwp=format_gwp(gwp), + adpe=format_adpe(adpe), + pe=format_pe(pe) + ), impacts.usage, impacts.embodied + +##################################################################################### +### EQUIVALENT FORMATING +##################################################################################### + +def format_energy_eq_physical_activity(energy: Quantity) -> tuple[PhysicalActivity, Quantity]: + energy = energy.to("kJ") + running_eq = energy / RUNNING_ENERGY_EQ + 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(energy: Quantity) -> Quantity: + energy = energy.to("kWh") + ev_eq = energy / EV_ENERGY_EQ + if ev_eq < q("1 km"): + ev_eq = ev_eq.to("meter") + return ev_eq + +def format_gwp_eq_streaming(gwp: Quantity) -> Quantity: + gwp = gwp.to("kgCO2eq") + streaming_eq = gwp * STREAMING_GWP_EQ + 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_energy_eq_electricity_production(energy: Quantity) -> tuple[EnergyProduction, Quantity]: + electricity_eq = energy * ONE_PERCENT_WORLD_POPULATION * DAYS_IN_YEAR + 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(energy: Quantity) -> Quantity: + electricity_eq = energy * ONE_PERCENT_WORLD_POPULATION * DAYS_IN_YEAR + 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") + return gwp_eq / AIRPLANE_PARIS_NYC_GWP_EQ + +##################################################################################### +### MODELS PARAMETERS +##################################################################################### + +def model_active_params_fn(provider_name: str, model_name: str, n_param: float): + if model_name == 'CUSTOM': + return n_param + else: + model = models.find_model(provider=provider_name, model_name=model_name) + + if model.architecture == 'moe': + try: + return model.architecture.parameters.active.max + except: + try: + return model.architecture.parameters.active + except: + return model.architecture.parameters + elif model.architecture == 'dense': + try: #dense with range + return model.architecture.parameters.max + except: #dense without range + return model.architecture.parameters + +def model_total_params_fn(provider_name: str, model_name: str, n_param: float): + if model_name == 'CUSTOM': + return n_param + provider, model_name = model_name.split('/', 1) + model = models.find_model(provider=provider, model_name=model_name) + try: #moe + return model.architecture.parameters.total.max + except: + try: #dense with range + return model.architecture.parameters.max + except: #dense without range + try: + return model.architecture.parameters.total + except: + return model.architecture.parameters \ No newline at end of file diff --git a/utils.py b/utils.py new file mode 100755 index 0000000000000000000000000000000000000000..af4187d59db6f21451bd8b4a921a5fee808f99e6 --- /dev/null +++ b/utils.py @@ -0,0 +1,262 @@ +from dataclasses import dataclass +from enum import Enum + +import pandas as pd +from ecologits.model_repository import models +from ecologits.impacts.modeling import Impacts, Energy, GWP, ADPe, PE +#from ecologits.tracers.utils import llm_impacts +from pint import UnitRegistry, Quantity + +##################################################################################### +### UNITS DEFINITION +##################################################################################### + +u = UnitRegistry() +u.define('Wh = watt_hour') +u.define('kWh = kilowatt_hour') +u.define('MWh = megawatt_hour') +u.define('GWh = gigawatt_hour') +u.define('TWh = terawatt_hour') +u.define('gCO2eq = gram') +u.define('kgCO2eq = kilogram') +u.define('tCO2eq = metricton') +u.define('kgSbeq = kilogram') +u.define('kJ = kilojoule') +u.define('MJ = megajoule') +u.define('m = meter') +u.define('km = kilometer') +u.define('s = second') +u.define('min = minute') +u.define('h = hour') +q = u.Quantity + +@dataclass +class QImpacts: + energy: Quantity + gwp: Quantity + adpe: Quantity + pe: Quantity + + +class PhysicalActivity(str, Enum): + RUNNING = "running" + WALKING = "walking" + + +class EnergyProduction(str, Enum): + NUCLEAR = "nuclear" + WIND = "wind" + + +COUNTRIES = [ + ("cook_islands", 38.81, 9_556), + ("tonga", 51.15, 104_490), + ("comoros", 100, 821_632), + ("samoa", 100, 821_632), +] + +##################################################################################### +### EQUIVALENT RAW DATA +##################################################################################### + +# From https://www.runningtools.com/energyusage.htm +RUNNING_ENERGY_EQ = q("294 kJ / km") # running 1 km at 10 km/h with a weight of 70 kg +WALKING_ENERGY_EQ = q("196 kJ / km") # walking 1 km at 3 km/h with a weight of 70 kg + +# From https://selectra.info/energie/actualites/insolite/consommation-vehicules-electriques-france-2040 +# and https://www.tesla.com/fr_fr/support/power-consumption +EV_ENERGY_EQ = q("0.17 kWh / km") + +# From https://impactco2.fr/outils/comparateur?value=1&comparisons=streamingvideo +STREAMING_GWP_EQ = q("15.6 h / kgCO2eq") + +# From https://ourworldindata.org/population-growth +ONE_PERCENT_WORLD_POPULATION = 80_000_000 + +DAYS_IN_YEAR = 365 + +# 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 +YEARLY_NUCLEAR_ENERGY_EQ = q("6 TWh") + +# For a 2MW wind turbine +# https://www.ecologie.gouv.fr/eolien-terrestre +YEARLY_WIND_ENERGY_EQ = q("4.2 GWh") + +# Ireland yearly electricity consumption +# From https://en.wikipedia.org/wiki/List_of_countries_by_electricity_consumption +YEARLY_IRELAND_ELECTRICITY_CONSUMPTION = q("33 TWh") +IRELAND_POPULATION_MILLION = 5 + +# From https://impactco2.fr/outils/comparateur?value=1&comparisons=&equivalent=avion-pny +AIRPLANE_PARIS_NYC_GWP_EQ = q("177000 kgCO2eq") + +def filter_models(provider, list_models): + + model = 1 + + return model + +##################################################################################### +### IMPACTS FORMATING +##################################################################################### + +def format_energy(energy: Energy) -> Quantity: + val = q(energy.value, energy.unit) + if val < q("1 kWh"): + val = val.to("Wh") + return val + +def format_gwp(gwp: GWP) -> Quantity: + val = q(gwp.value, gwp.unit) + if val < q("1 kgCO2eq"): + val = val.to("gCO2eq") + return val + +def format_adpe(adpe: ADPe) -> Quantity: + return q(adpe.value, adpe.unit) + +def format_pe(pe: PE) -> Quantity: + val = q(pe.value, pe.unit) + if val < q("1 MJ"): + val = val.to("kJ") + return val + +def format_impacts(impacts: Impacts) -> QImpacts: + + try: + impacts.energy.value = (impacts.energy.value.max + impacts.energy.value.min)/2 + impacts.gwp.value = (impacts.gwp.value.max + impacts.gwp.value.min)/2 + impacts.adpe.value = (impacts.adpe.value.max + impacts.adpe.value.min)/2 + impacts.pe.value = (impacts.pe.value.max + impacts.pe.value.min)/2 + return QImpacts( + energy=format_energy(impacts.energy), + gwp=format_gwp(impacts.gwp), + adpe=format_adpe(impacts.adpe), + pe=format_pe(impacts.pe) + ), impacts.usage, impacts.embodied + except: #when no range + return QImpacts( + energy=format_energy(impacts.energy), + gwp=format_gwp(impacts.gwp), + adpe=format_adpe(impacts.adpe), + pe=format_pe(impacts.pe) + ), impacts.usage, impacts.embodied + +def split_impacts_u_e(impacts: Impacts) -> QImpacts: + return impacts.usage, impacts.embodied + +def average_range_impacts(RangeValue): + return (RangeValue.max + RangeValue.min)/2 + +def format_impacts_expert(impacts: Impacts, display_range: bool) -> QImpacts: + + if display_range: + return QImpacts( + energy=format_energy(impacts.energy), + gwp=format_gwp(impacts.gwp), + adpe=format_adpe(impacts.adpe), + pe=format_pe(impacts.pe) + ), impacts.usage, impacts.embodied + + else: + energy = {"value":(impacts.energy.value.max + impacts.energy.value.min)/2, "unit":impacts.energy.unit} + gwp = (impacts.gwp.value.max + impacts.gwp.value.min)/2 + adpe = (impacts.adpe.value.max + impacts.adpe.value.min)/2 + pe = (impacts.pe.value.max + impacts.pe.value.min)/2 + return QImpacts( + energy=format_energy(energy), + gwp=format_gwp(gwp), + adpe=format_adpe(adpe), + pe=format_pe(pe) + ), impacts.usage, impacts.embodied + +##################################################################################### +### EQUIVALENT FORMATING +##################################################################################### + +def format_energy_eq_physical_activity(energy: Quantity) -> tuple[PhysicalActivity, Quantity]: + energy = energy.to("kJ") + running_eq = energy / RUNNING_ENERGY_EQ + 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(energy: Quantity) -> Quantity: + energy = energy.to("kWh") + ev_eq = energy / EV_ENERGY_EQ + if ev_eq < q("1 km"): + ev_eq = ev_eq.to("meter") + return ev_eq + +def format_gwp_eq_streaming(gwp: Quantity) -> Quantity: + gwp = gwp.to("kgCO2eq") + streaming_eq = gwp * STREAMING_GWP_EQ + 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_energy_eq_electricity_production(energy: Quantity) -> tuple[EnergyProduction, Quantity]: + electricity_eq = energy * ONE_PERCENT_WORLD_POPULATION * DAYS_IN_YEAR + 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(energy: Quantity) -> Quantity: + electricity_eq = energy * ONE_PERCENT_WORLD_POPULATION * DAYS_IN_YEAR + 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") + return gwp_eq / AIRPLANE_PARIS_NYC_GWP_EQ + +##################################################################################### +### MODELS PARAMETERS +##################################################################################### + +def model_active_params_fn(provider_name: str, model_name: str, n_param: float): + if model_name == 'CUSTOM': + return n_param + else: + model = models.find_model(provider=provider_name, model_name=model_name) + + if model.architecture == 'moe': + try: + return model.architecture.parameters.active.max + except: + try: + return model.architecture.parameters.active + except: + return model.architecture.parameters + elif model.architecture == 'dense': + try: #dense with range + return model.architecture.parameters.max + except: #dense without range + return model.architecture.parameters + +def model_total_params_fn(provider_name: str, model_name: str, n_param: float): + if model_name == 'CUSTOM': + return n_param + provider, model_name = model_name.split('/', 1) + 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