Merge pull request #4 from genai-impact/feat/upgrade-ecologits-0.9

app.py

@@ -6,7 +6,6 @@ from src.content import (
     CITATION_LABEL,
     CITATION_TEXT,
     LICENCE_TEXT,
-    INTRO_TEXT,
     METHODOLOGY_TEXT,
     SUPPORT_TEXT,
 )
@@ -15,15 +14,13 @@ from src.expert import expert_mode
 from src.calculator import calculator_mode
 from src.token_estimator import token_estimator
 
-st.set_page_config(layout="wide", page_title="ECOLOGITS", page_icon="💬")
+st.set_page_config(layout="wide", page_title="EcoLogits Calculator", page_icon="🧮")
 
 with open("src/style.css") as css:
     st.markdown(f"<style>{css.read()}</style>", unsafe_allow_html=True)
 
 st.html(HERO_TEXT)
 
-st.success(INTRO_TEXT, icon="🌱")
-
 tab_calculator, tab_expert, tab_token, tab_method, tab_about, tab_support = st.tabs(
     [
         "🧮 Calculator",

data/electricity_mix.csv

@@ -1,4 +0,0 @@
-name,unit,source,WOR,EEE,ZWE,ZMB,ZAF,YEM,VNM,VEN,UZB,URY,USA,UKR,TZA,TWN,TTO,TUR,TUN,TKM,TJK,THA,TGO,SYR,SLV,SEN,SVK,SVN,SGP,SWE,SDN,SAU,RUS,SCG,ROU,QAT,PRY,PRT,POL,PAK,PHL,PER,PAN,OMN,NZL,NPL,NOR,NLD,NIC,NGA,NAM,MOZ,MYS,MEX,MLT,MNG,MMR,MKD,MDA,MAR,LBY,LVA,LUX,LTU,LKA,LBN,KAZ,KWT,KOR,PRK,KHM,KGZ,KEN,JPN,JOR,JAM,ITA,ISL,IRN,IRQ,IND,ISR,IRL,IDN,HUN,HTI,HRV,HND,HKG,GTM,GRC,GIB,GHA,GEO,GBR,GAB,FRA,FIN,ETH,ESP,ERI,EGY,EST,ECU,DZA,DOM,DNK,DEU,CZE,CYP,CUB,CRI,COL,CHN,CMR,CHL,CIV,CHE,COG,COD,CAN,BLR,BWA,BRA,BOL,BRN,BEN,BHR,BGR,BEL,BGD,BIH,AZE,AUS,AUT,ARG,AGO,ANT,ARM,ALB,ARE
-adpe,kg éq. Sb,ADEME Base IMPACTS ®,0.0000000737708,0.0000000642317,0.000000109502,0.000000162193,0.0000000862445,0.0000000163908,0.0000000945573,0.000000112811,0.000000103681,0.000000104586,0.0000000985548,0.0000000647907,0.000000132261,0.0000000578088,0.000000064552,0.0000000749765,0.0000000177021,0.000000131822,0.000000152621,0.0000000569593,0.000000134255,0.0000000268396,0.0000000472135,0.0000000470662,0.0000000606109,0.0000000992283,0.0000000198459,0.0000000777062,0.0000000955701,0.0000000134206,0.0000000960312,0.000000132772,0.0000000981761,0.00000001324,0.000000149181,0.0000000341863,0.000000101946,0.0000000842952,0.0000000595304,0.0000000952688,0.0000000790553,0.0000000374073,0.0000000720474,0.000000238273,0.000000127486,0.0000000329318,0.0000000414983,0.0000000621,0.000000128285,0.000000148382,0.000000044938,0.0000000578358,0.000000049475,0.000000176361,0.000000152699,0.000000119873,0.000000110674,0.0000000641089,0.0000000206592,0.000000153757,0.000000105692,0.0000000294596,0.0000000986932,0.0000000182134,0.000000135386,0.0000000141168,0.0000000518017,0.000000117457,0.0000000319202,0.000000181827,0.0000000958533,0.0000000596578,0.0000000147031,0.0000000196047,0.00000005439,0.0000000781905,0.0000000220304,0.0000000404306,0.000000100099,0.0000000610194,0.0000000219257,0.0000000610451,0.0000000644587,0.0000000937057,0.000000153989,0.0000000649373,0.0000000816213,0.0000000803251,0.0000000691645,0.0000000286211,0.000000156003,0.000000137999,0.0000000370973,0.000000113843,0.0000000485798,0.0000000805114,0.000000174161,0.0000000518326,0.0000000512406,0.000000033925,0.0000000990171,0.000000127168,0.0000000216438,0.0000000429285,0.0000000157411,0.0000000878733,0.0000000817565,0.0000000448771,0.0000000299542,0.0000000863908,0.000000122031,0.0000000851552,0.000000146313,0.000000105851,0.0000000949004,0.000000100467,0.000000265575,0.000000174647,0.0000000993179,0.0000000840478,0.0000000866014,0.00000010962,0.0000000969793,0.0000000185641,0.0000000239702,0.0000000135014,0.0000000823611,0.0000000337201,0.0000000394158,0.000000148007,0.000000092567,0.0000000790846,0.000000141124,0.0000000768612,0.000000124074,0.0000000449103,0.0000000854245,0.000000229556,0.0000000141548
-pe,MJ,ADPf / (1-%renewable_energy),9.988,12.873,16.122,1.798,11.732,16.250,11.238,15.163,17.367,107.570,11.358,12.936,9.305,11.439,14.289,16.150,12.902,23.300,19.165,10.414,21.978,16.989,13.012,14.516,11.680,12.146,10.477,11.026,29.629,14.058,13.200,14.242,15.585,11.916,0.020,14.153,13.178,16.175,11.120,8.211,16.364,22.306,24.731,0.396,4.952,8.511,24.696,11.279,468.150,0.206,12.268,11.775,19.374,15.114,14.132,19.120,18.429,11.702,19.116,8.249,10.128,21.043,12.116,12.341,13.260,12.753,10.199,32.793,34.655,15.380,68.996,10.718,13.677,14.799,12.656,0.013,15.022,20.372,20.363,10.023,10.706,11.603,11.784,20.167,18.548,15.762,,14.340,14.487,,10.097,10.425,13.579,28.341,11.289,11.275,36.133,12.090,13.289,10.195,16.334,20.908,16.376,12.412,16.824,16.260,12.517,13.118,17.317,45.996,7.312,14.119,10.807,11.348,14.783,11.782,34.147,0.097,11.987,13.194,19.642,9.031,11.587,15.689,14.337,14.036,14.375,10.776,12.935,21.705,12.831,16.908,11.036,10.049,16.972,,13.380,0.201,19.032
-gwp,kg éq. CO2,ADEME Base IMPACTS ®,0.590478,0.509427,0.842811,0.0141304,1.17562,1.06777,0.555572,0.497373,0.81178,0.296953,0.67978,0.646745,0.475635,0.845351,0.933059,0.706988,0.80722,1.38296,0.0426743,0.646174,0.545455,1.08778,0.473128,1.1195,0.309341,0.498523,0.655825,0.0464664,1.12472,0.913677,0.66131,1.07808,0.664245,0.722125,0.241601,0.571172,1.15075,0.748727,0.761317,0.284364,0.53403,1.41292,0.293397,0.0841323,0.023754,0.544803,0.941626,0.693123,0.357253,0.00880732,0.832206,0.739214,1.31149,1.47192,0.48193,1.24074,1.04213,0.933694,1.35361,0.234273,0.490016,0.154229,0.709185,0.883627,1.128,0.885084,0.599585,0.797361,1.41054,0.156039,0.589603,0.540891,0.781372,1.07345,0.621329,0.0194609,0.930385,1.48728,1.58299,0.901842,0.648118,0.875394,0.541558,1.3858,0.535759,0.692837,0.95888,0.645801,1.13127,0.977477,0.540126,0.132046,0.602137,0.732511,0.0813225,0.322068,0.251299,0.467803,1.13153,0.587775,1.51492,0.627714,1.02318,0.909252,0.633534,0.657374,0.799077,0.978041,1.28325,0.224471,0.214014,1.05738,0.456622,0.574415,0.928583,0.0448568,0.904053,0.0613102,0.238191,0.795697,2.12572,0.278647,0.585131,0.997577,1.19128,0.804567,0.827087,0.256537,0.795168,1.56025,0.726126,1.12326,0.245573,0.476811,0.412014,1.13161,0.252002,0.0207635,1.09088

pyproject.toml

@@ -5,9 +5,17 @@ description = "Add your description here"
 readme = "README.md"
 requires-python = ">=3.11"
 dependencies = [
-    "ecologits>=0.7.3,<0.8.0",
+    "ecologits>=0.9.0,<0.10.0",
     "pint>=0.24.4",
     "plotly>=6.2.0",
     "streamlit>=1.47.1",
     "tiktoken>=0.9.0",
 ]
+
+[tool.uv.sources]
+ecologits = { git = "https://github.com/genai-impact/ecologits" }
+
+[dependency-groups]
+dev = [
+    "watchdog>=6.0.0",
+]

src/__init__.py

@@ -4,6 +4,6 @@ from .expert import expert_mode
 from .token_estimator import token_estimator
 from .utils import *
 from .calculator import calculator_mode
-from .impacts import get_impacts, display_impacts
+from .impacts import display_impacts
 from .models import load_models
 from .electricity_mix import *

src/calculator.py

@@ -1,99 +1,111 @@
-import streamlit as st
-
-from ecologits.tracers.utils import llm_impacts
-from src.impacts import get_impacts, display_impacts, display_equivalent_ghg, display_equivalent_energy
-from src.utils import format_impacts
-from src.content import WARNING_CLOSED_SOURCE, WARNING_MULTI_MODAL, WARNING_BOTH, HOW_TO_TEXT
-from src.models import load_models
-
-from src.constants import PROMPTS
-
-
-def calculator_mode():
-
-    st.expander("How to use this calculator?", expanded = False).markdown(HOW_TO_TEXT)
-
-    with st.container(border=True):
-        df = load_models(filter_main=True)
-
-        col1, col2, col3 = st.columns(3)
-
-        with col1:
-            providers_clean = [x for x in df["provider_clean"].unique()]
-            provider = st.selectbox(
-                label="Provider",
-                options=providers_clean,
-                index=providers_clean.index("OpenAI"),
-            )
-
-        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()
-                ],
-            )
-
-        with col3:
-            output_tokens = st.selectbox("Example prompt", [x[0] for x in PROMPTS])
-
-        # 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, icon="⚠️")
-        if (
-            df_filtered["warning_multi_modal"].values[0]
-            and not df_filtered["warning_arch"].values[0]
-        ):
-            st.warning(WARNING_MULTI_MODAL, icon="⚠️")
-        if (
-            df_filtered["warning_arch"].values[0]
-            and df_filtered["warning_multi_modal"].values[0]
-        ):
-            st.warning(WARNING_BOTH, icon="⚠️")
-
-    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('<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)                 
-        
-        with st.container(border=False):
-            st.markdown('<h3 align = "center">Equivalences</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)
-            page = st.radio(' ', ['Energy' , 'GHG'], horizontal=True)
-        
-        with st.container(border=True):                                            
-             if page == 'Energy' :
-                display_equivalent_energy(impacts)
-             else :  
-                display_equivalent_ghg(impacts)
-        
-            
-    except Exception as e:
-        st.error('Could not find the model in the repository. Please try another model.')
+import math
+import streamlit as st
+
+from ecologits.tracers.utils import llm_impacts
+from src.impacts import display_impacts, display_equivalent_ghg, display_equivalent_energy
+from src.latency_estimator import latency_estimator
+from src.utils import format_impacts
+from src.content import WARNING_CLOSED_SOURCE, WARNING_MULTI_MODAL, WARNING_BOTH, HOW_TO_TEXT
+from src.models import load_models
+
+from src.constants import PROMPTS
+
+
+def calculator_mode():
+
+    st.expander("How to use this calculator?", expanded = False).markdown(HOW_TO_TEXT)
+
+    with st.container(border=True):
+        df = load_models(filter_main=True)
+
+        col1, col2, col3 = st.columns(3)
+
+        with col1:
+            providers_clean = [x for x in df["provider_clean"].unique()]
+            provider = st.selectbox(
+                label="Provider",
+                options=providers_clean,
+                index=providers_clean.index("OpenAI"),
+            )
+
+        with col2:
+            models_clean = [
+                x
+                for x in df["name_clean"].unique()
+                if x in df[df["provider_clean"] == provider]["name_clean"].unique()
+            ]
+            model = st.selectbox(
+                label="Model",
+                options=models_clean,
+            )
+
+        with col3:
+            output_tokens = st.selectbox(
+                label="Example prompt",
+                options=[x[0] for x in PROMPTS],
+                index=2
+            )
+
+        # 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, icon="⚠️")
+        if (
+            df_filtered["warning_multi_modal"].values[0]
+            and not df_filtered["warning_arch"].values[0]
+        ):
+            st.warning(WARNING_MULTI_MODAL, icon="⚠️")
+        if (
+            df_filtered["warning_arch"].values[0]
+            and df_filtered["warning_multi_modal"].values[0]
+        ):
+            st.warning(WARNING_BOTH, icon="⚠️")
+
+    try:
+        output_tokens_count = [x[1] for x in PROMPTS if x[0] == output_tokens][0]
+        estimated_latency = latency_estimator.estimate(provider=provider_raw,
+                                                       model_name=model_raw,
+                                                       output_tokens=output_tokens_count)
+        impacts = llm_impacts(
+            provider=provider_raw,
+            model_name=model_raw,
+            output_token_count=output_tokens_count,
+            request_latency=estimated_latency
+        )
+
+        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)                 
+        
+        with st.container(border=False):
+            st.markdown('<h3 align = "center">Equivalences</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)
+            page = st.radio(' ', ['Energy' , 'GHG'], horizontal=True)
+        
+        with st.container(border=True):                                            
+             if page == 'Energy' :
+                display_equivalent_energy(impacts)
+             else :  
+                display_equivalent_ghg(impacts)
+        
+            
+    except Exception as e:
+        st.error('Could not find the model in the repository. Please try another model.')
+        raise e

src/constants.py

@@ -11,7 +11,6 @@ PROMPTS = [(s + f" ({v} output tokens)", v) for (s, v) in PROMPTS]
 MODEL_REPOSITORY_URL = "https://raw.githubusercontent.com/genai-impact/ecologits/refs/heads/main/ecologits/data/models.json"
 
 main_models_openai = [
-    "chatgpt-4o-latest",
     "gpt-3.5-turbo",
     "gpt-4",
     "gpt-4-turbo",
@@ -19,93 +18,65 @@ main_models_openai = [
     "gpt-4o-mini",
     "o1",
     "o1-mini",
-]
-
-main_models_meta = [
-    "meta-llama/Meta-Llama-3.1-8B",
-    "meta-llama/Meta-Llama-3.1-70B",
-    "meta-llama/Meta-Llama-3.1-405B",
-    "meta-llama/Meta-Llama-3-8B",
-    "meta-llama/Meta-Llama-3-70B",
-    "meta-llama/Meta-Llama-3-70B",
-    "meta-llama/Llama-2-7b",
-    "meta-llama/Llama-2-13b",
-    "meta-llama/Llama-2-70b",
-    "meta-llama/CodeLlama-7b-hf",
-    "meta-llama/CodeLlama-13b-hf",
-    "meta-llama/CodeLlama-34b-hf",
-    "meta-llama/CodeLlama-70b-hf",
-]
-
-main_models_msft = [
-    "microsoft/phi-1",
-    "microsoft/phi-1_5",
-    "microsoft/Phi-3-mini-128k-instruct",
-    "microsoft/Phi-3-small-128k-instruct",
-    "microsoft/Phi-3-medium-128k-instruct",
+    "o3-mini",
+    "gpt-4.1-nano",
+    "gpt-4.1-mini",
+    "gpt-4.1",
+    "o4-mini",
+    "gpt-5-nano",
+    "gpt-5-mini",
+    "gpt-5",
 ]
 
 main_models_anthropic = [
-    "claude-2.0",
-    "claude-2.1",
     "claude-3-5-haiku-latest",
     "claude-3-5-sonnet-latest",
     "claude-3-7-sonnet-latest",
-    "claude-3-haiku-20240307",
-    "claude-3-opus-latest",
-    "claude-3-sonnet-20240229",
+    "claude-opus-4-0",
+    "claude-opus-4-1",
+    "claude-sonnet-4-0",
+    "claude-sonnet-4-5",
+    "claude-haiku-4-5"
 ]
 
 main_models_cohere = [
-    "c4ai-aya-expanse-8b",
-    "c4ai-aya-expanse-32b",
-    "command",
-    "command-light",
+    "command-a-03-2025",
     "command-r",
-    "command-r-plus",
+    "command-r-08-2024",
+    "command-r-plus-08-2024",
+    "command-r7b-12-2024"
 ]
 
 main_models_google = [
-    "google/gemma-2-2b",
-    "google/gemma-2-9b",
-    "google/gemma-2-27b",
-    "google/codegemma-2b",
-    "google/codegemma-7b",
-    "gemini-1.0-pro",
-    "gemini-1.5-pro",
-    "gemini-1.5-flash",
+    "gemini-2.0-flash-lite",
     "gemini-2.0-flash",
-]
-
-main_models_databricks = [
-    "databricks/dolly-v1-6b",
-    "databricks/dolly-v2-12b",
-    "databricks/dolly-v2-7b",
-    "databricks/dolly-v2-3b",
-    "databricks/dbrx-base",
+    "gemini-2.5-flash-lite",
+    "gemini-2.5-flash",
+    "gemini-2.5-pro"
 ]
 
 main_models_mistral = [
-    "mistralai/Mistral-7B-v0.3",
-    "mistralai/Mixtral-8x7B-v0.1",
-    "mistralai/Mixtral-8x22B-v0.1",
-    "mistralai/Codestral-22B-v0.1",
-    "mistralai/Mathstral-7B-v0.1",
+    "codestral-latest",
+    "devstral-medium-latest",
+    "devstral-small-latest",
+    "magistral-medium-latest",
+    "magistral-small-latest",
     "ministral-3b-latest",
     "ministral-8b-latest",
-    "mistral-tiny",
-    "mistral-small",
-    "mistral-medium",
     "mistral-large-latest",
+    "mistral-medium-latest",
+    "mistral-small-latest",
+    "mistral-tiny-latest",
+    "open-mistral-7b",
+    "open-mistral-nemo",
+    "open-mixtral-8x22b",
+    "open-mixtral-8x7b"
 ]
 
 MAIN_MODELS = (
-    main_models_meta
-    + main_models_openai
+    main_models_openai
     + main_models_anthropic
     + main_models_cohere
-    + main_models_msft
     + main_models_mistral
-    + main_models_databricks
     + main_models_google
 )

src/content.py

@@ -1,26 +1,20 @@
 HERO_TEXT = """
-<div align="center">
+<div align="center" class="hero">
   <a href="https://ecologits.ai/">
-    <img style="max-height: 200px" alt="EcoLogits" src="https://raw.githubusercontent.com/genai-impact/ecologits/main/docs/assets/logo_calculator.png">
+    <img style="max-height: 200px" alt="EcoLogits" src="https://raw.githubusercontent.com/genai-impact/ecologits-calculator/main/assets/logo.png">
   </a>
 </div>
 <div align="center">
   <p style="max-width: 850px; text-align: left">
-    <b>EcoLogits</b> is a python library that tracks the <b>energy consumption</b> and <b>environmental 
-    footprint</b> of using <b>generative AI</b> models through APIs.
-  <br>
-    This Calculator allows a broader access to <b>EcoLogits</b> estimates through a visual application.</i>
- 
+    <b><a href="https://ecologits.ai/" target="_blank">EcoLogits</a></b> is an <b>open source</b> tool for estimating the <b>energy consumption</b> and <b>environmental footprint</b> when using <b>generative AI models</b>. It is developed by the <b><a href="https://genai-impact.org/">GenAI Impact</a></b> non-profit.
+    <br><br>
+    This page is the official calculator made for everyone to explore the impact evaluation methodology and raise awareness on sustainable AI.
   </p>
 
 </div>
 <br>
 """
 
-INTRO_TEXT = """
-EcoLogits Calculator is developed and maintained by [GenAI Impact](https://genai-impact.org/) non-profit. To learn more about EcoLogits documentation visit [ecologits.ai](https://ecologits.ai).
-"""
-
 HOW_TO_TEXT = """
 Chose a provider, a model and an example of usage (prompts). 
 
@@ -74,7 +68,7 @@ When you're writing or interacting with an LLM, being aware of token count can h
 """
 
 ABOUT_TEXT = r"""
-## 🎯 Our goal
+### 🎯 Our goal
 
 **The main goal of the EcoLogits Calculator is to raise awareness on the environmental impacts of LLM inference.**
 
@@ -83,7 +77,7 @@ The rapid evolution of generative AI is reshaping numerous industries and aspect
 At **[GenAI Impact](https://genai-impact.org/) we are dedicated to understanding and mitigating the environmental impacts of generative AI** through rigorous research, innovative tools, and community engagement. Especially, in early 2024 we have launched an new open-source tool called [EcoLogits](https://github.com/genai-impact/ecologits) that tracks the energy consumption and environmental footprint of using generative AI models through APIs.
 
 
-## 🙋 FAQ 
+### 🙋 FAQ 
 
 **How we assess the impacts of closed-source models?**
 
@@ -115,88 +109,84 @@ To see the full list of **generative AI providers** currently supported by EcoLo
 EcoLogits is focused on estimating the environmental impacts of generative AI (only LLMs for now) used **through API providers (such as OpenAI, Anthropic, Cloud APIs...)** whereas  CodeCarbon is more general tool to measure energy consumption and estimate GHG emissions measurement. If you deploy LLMs locally we encourage you to use CodeCarbon to get real numbers of your energy consumption.
 
 
-## 🤗 Contributing 
+### 🤗 Contributing 
 
 We are eager to get feedback from the community, don't hesitate to engage the discussion with us on this [GitHub thread](https://github.com/genai-impact/ecologits/discussions/45) or message us on [LinkedIn](https://www.linkedin.com/company/genai-impact/).
 
 We also welcome any open-source contributions on 🌱 **[EcoLogits](https://github.com/genai-impact/ecologits)** or on 🧮 **EcoLogits Calculator**.
 
 
-## ⚖️ License
+### ⚖️ License
 
 <p xmlns:cc="http://creativecommons.org/ns#" >
   This work is licensed under 
   <a href="https://creativecommons.org/licenses/by-sa/4.0/?ref=chooser-v1" target="_blank" rel="license noopener noreferrer" style="display:inline-block;">
     CC BY-SA 4.0
   </a>
-  <br>
-  <br>
-  <img style="display:inline-block;height:5px!important;margin-left:3px;vertical-align:text-bottom;" src="https://mirrors.creativecommons.org/presskit/icons/cc.svg?ref=chooser-v1" height="30" width="30" alt="">
-  <img style="display:inline-block;height:5px!important;margin-left:3px;vertical-align:text-bottom;" src="https://mirrors.creativecommons.org/presskit/icons/by.svg?ref=chooser-v1" height="30" width="30" alt="">
-  <img style="display:inline-block;height:5px!important;margin-left:3px;vertical-align:text-bottom;" src="https://mirrors.creativecommons.org/presskit/icons/sa.svg?ref=chooser-v1" height="30" width="30" alt="">
 </p>
 
-## 🙌 Acknowledgement
+### 🙌 Acknowledgement
 
 We thank [Data For Good](https://dataforgood.fr/) and [Boavizta](https://boavizta.org/en) for supporting the development of this project. Their contributions of tools, best practices, and expertise in environmental impact assessment have been invaluable. 
 
-We also extend our gratitude to the open-source contributions of 🤗 [Hugging Face](huggingface.com) on the LLM-Perf Leaderboard.
 
-
-## 🤝 Contact
+### 🤝 Contact
 
 For general question on the project, please use the [GitHub thread](https://github.com/genai-impact/ecologits/discussions/45). 
 Otherwise use our contact form on [genai-impact.org/contact](https://genai-impact.org/contact/).
 """
 
 SUPPORT_TEXT = r"""
-## How to support 
+### How to support us
 
 At GenAI Impact, our projects are powered by the passion and dedication of our team. 
-Since its first release in June 2024, this calculator has been **developped and maintained entirely on a volunteer basis by our members**.
-We aim to keep this tool available as a free and open-source ressource for the common good. We need your support to reach this goal, this is how you can help.
+Since its first release in June 2024, this calculator has been **developed and maintained entirely on a volunteer basis by our members**.
+We aim to keep this tool available as a free and open-source resource for the common good. We need your support to reach this goal, this is how you can help.
+
+#### If you have 1 second
 
-### If you have 1 second
-3 easy ways to help this project  :
+3 easy ways to help this project:
 - Give a ❤️ like to this space
-- Give a ⭐ to the EcoLogits repo on [GitHub](https://github.com/genai-impact/ecologits)
+- Give a ⭐ to the EcoLogits repository on [GitHub](https://github.com/genai-impact/ecologits)
 - Follow us on [LinkedIn](https://fr.linkedin.com/company/genai-impact)
 
-### If you have 5 minutes
+#### If you have 5 minutes
+
 Share your feedback, ask questions, help other members of the community !
 
-Engage the discussion with us :
+Engage the discussion with us:
 - Start a new discussion on this space or on this 
 [GitHub thread](https://github.com/genai-impact/ecologits/discussions/45) 
 - Use the contact form on [GenAI Impact website](https://genai-impact.org/contact/)
 - message us on [LinkedIn](https://www.linkedin.com/company/genai-impact/).
 
-### If you have more to give
+#### If you have more to give
+
+###### As an individual
 
-##### As an individual
 We welcome any open source contribution ! You can :
 - Contribute on **[EcoLogits](https://github.com/genai-impact/ecologits)** or on 
 **EcoLogits Calculator**.
 - Become a an active member of [GenAI Impact ](https://genai-impact.org/contact/) non profit. Get involved in our broader mission !
 
 
-##### As an organization
+###### As an organization
+
 If EcoLogits Calculator brings value to your organization, customers or communities you can help finance this project.
 - Become a **sponsor**
 - Become a **benefactor member** if you are a public sector or non-profit organization or a university.
 
-Contact us on [GenAI Impact ](https://genai-impact.org/contact/)
-
+Contact us on [GenAI Impact](https://genai-impact.org/contact/)
 """
 
 METHODOLOGY_TEXT = r"""
-## 📖 Methodology
+### 📖 Methodology
 
 We have developed a methodology to **estimate the energy consumption and environmental impacts for an LLM inference** based on request parameters and hypotheses on the data center location, the hardware used, the model architecture and more.
 
 In this section we will only cover the principles of the methodology related to the 🧮 **EcoLogits Calculator**. If you wish to learn more on the environmental impacts modeling of an LLM request checkout the 🌱 [EcoLogits documentation page](https://ecologits.ai/methodology/).
 
-### Modeling impacts of an LLM request
+#### Modeling impacts of an LLM request
 
 The environmental impacts of an LLM inference are split into the **usage impacts** $I_{request}^u$ to account for electricity consumption and the **embodied impacts** $I_{request}^e$ that relates to resource extraction, hardware manufacturing and transportation. In general terms it can be expressed as follow:
 
@@ -216,8 +206,10 @@ Additionally, to ⚡️ **direct energy consumption** the environmental impacts
 * 🌍 **Global Warming Potential** (GWP): Potential impact on global warming in kgCO2eq (commonly known as GHG/carbon emissions).
 * 🪨 **Abiotic Depletion Potential for Elements** (ADPe): Impact on the depletion of non-living resources such as minerals or metals in kgSbeq.
 * ⛽️ **Primary Energy** (PE): Total energy consumed from primary sources in MJ.
+* ⛽️ **Water Consumption Footprint** (WCF): Water consumed by data centers and electricity generation power plants.
+
+#### Principles, Data and Hypotheses
 
-### Principles, Data and Hypotheses
 We use a **bottom-up methodology** to model impacts, meaning that we will estimate the impacts of low-level physical components to then estimate the impacts at software level (in that case an LLM inference). We also rely on **Life Cycle Approach (LCA) proxies and approach** to model both usage and embodied phases with multi-criteria impacts. If you are interested in this approach we recommend you to read the following [Boavizta](https://boavizta.org/) resources.
 
 * [Digital & environment: How to evaluate server manufacturing footprint, beyond greenhouse gas emissions?](https://boavizta.org/en/blog/empreinte-de-la-fabrication-d-un-serveur) 
@@ -225,26 +217,27 @@ We use a **bottom-up methodology** to model impacts, meaning that we will estima
 * [Boavizta API documentation](https://doc.api.boavizta.org/)
 
 We leverage **open data to estimate the environmental impacts**, here is an exhaustive list of our data providers.
-* [LLM-Perf Leaderboard](https://huggingface.co/spaces/optimum/llm-perf-leaderboard) to estimate GPU energy consumption and latency based on the model architecture and number of output tokens.
+
+* [ML.ENERGY Leaderboard](https://ml.energy/leaderboard/) to estimate GPU energy consumption and latency based on the model architecture and number of output tokens.
 * [Boavizta API](https://github.com/Boavizta/boaviztapi) to estimate server embodied impacts and base energy consumption.
-* [ADEME Base Empreinte®](https://base-empreinte.ademe.fr/) for electricity mix impacts per country.
+* [Our World in Data](https://ourworldindata.org/), [ADEME Base Empreinte®](https://base-empreinte.ademe.fr/) and [World Resource Institute](https://www.wri.org/) for electricity mix impacts per country.
 
 Finally here are the **main hypotheses** we have made to compute the impacts.
 
 * ⚠️ **We *"guesstimate"* the model architecture of proprietary LLMs when not disclosed by the provider.** 
-* Production setup: quantized models running on data center grade servers and GPUs such as A100.
-* Electricity mix does not depend on time (help us enhance EcoLogits and work on this [issue](https://github.com/genai-impact/ecologits/issues/42))
+* Production setup: quantized models running on data center grade servers and GPUs such as H100.
+* Electricity mixes are yearly averages.
 * Ignore the following impacts: unused cloud resources, data center building, network and end-user devices... (for now)
 
-## Equivalents
+### Equivalents
 
 We have integrated impact equivalents to help people better understand the impacts and have reference points for standard use cases and everyday activities.
 
-### Request impacts
+#### Request impacts
 
 These equivalents are computed based on the request impacts only.
 
-#### 🚶‍♂️‍➡️ Walking or 🏃‍♂️‍➡️ running distance
+##### 🚶‍♂️‍➡️ Walking or 🏃‍♂️‍➡️ running distance
 
 We compare the ⚡️ direct energy consumption with the energy consumption of someone 🚶‍♂️‍➡️ walking or 🏃‍♂️‍➡️ running. From [runningtools.com](https://www.runningtools.com/energyusage.htm) we consider the following energy values per physical activity (for someone weighing 70kg):
 
@@ -253,18 +246,19 @@ We compare the ⚡️ direct energy consumption with the energy consumption of s
 
 We divide the request energy consumption by these values to compute the distance traveled. 
 
-#### 🔋 Electric Vehicle distance
+##### 🔋 Electric Vehicle distance
+
 We compare the ⚡️ direct energy consumption with the energy consumer by a EV car. From [selectra.info](https://selectra.info/energie/actualites/insolite/consommation-vehicules-electriques-france-2040) or [tesla.com](https://www.tesla.com/fr_fr/support/power-consumption) we consider an average value of energy consumed per kilometer of: $ 0.17\ kWh/km $.
 
 We divide the request energy consumption by this value to compute the distance driven by an EV. 
 
-#### ⏯️ Streaming time
+##### ⏯️ Streaming time
 
 We compare the 🌍 GHG emissions of the request and of streaming a video. From [impactco2.fr](https://impactco2.fr/outils/comparateur?value=1&comparisons=streamingvideo), we consider that $ 1\ kgCO2eq $ is equivalent to $ 15.6\ h $ of streaming.
 
 We multiply that value by the GHG emissions of the request to get an equivalent in hours of video streaming.
 
-### Scaled impacts
+#### Scaled impacts
 
 These equivalents are computed based on the request impacts scaled to a worldwide adoption use case. We imply that the same request is done 1% of the planet everyday for 1 year, and then compute impact equivalents.
 
@@ -272,25 +266,25 @@ $$
 I_{scaled} = I_{request} * [1 \% \ \text{of}\ 8B\ \text{people on earth}] * 365\ \text{days}
 $$
 
-#### Number of 💨 wind turbines or ☢️ nuclear plants
+##### Number of 💨 wind turbines or ☢️ nuclear plants
 
 We compare the ⚡️ direct energy consumption (scaled) by the energy production of wind turbines and nuclear power plants. From [ecologie.gouv.fr](https://www.ecologie.gouv.fr/eolien-terrestre) we consider that a $ 2\ MW $ wind turbine produces $ 4.2\ GWh $ a year. And from [edf.fr](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) we learn that a $ 900\ MW $ nuclear power plant produces $ 6\ TWh $ a year.
 
 We divide the scaled energy consumption by these values to get the number of wind turbines or nuclear power plants needed.
 
-#### Multiplier of 🇮🇪 Ireland electricity consumption
+##### Multiplier of 🇮🇪 Ireland electricity consumption
 
 We compare the ⚡️ direct energy consumption (scaled) by the electricity consumption of Ireland per year. From [wikipedia.org](https://en.wikipedia.org/wiki/List_of_countries_by_electricity_consumption) we consider the Ireland electricity consumption to be $ 33\ TWh $ a year for a population of 5M.
 
 We divide the scaled energy consumption by this value to get the equivalent number of "Ireland countries".
 
-#### Number of ✈️ Paris ↔ New York City flights
+##### Number of ✈️ Paris ↔ New York City flights
 
 We compare the 🌍 GHG emissions (scaled) of the request and of a return flight Paris ↔ New York City. From [impactco2.fr](https://impactco2.fr/outils/comparateur?value=1&comparisons=&equivalent=avion-pny) we consider that a return flight Paris → New York City → Paris for one passenger emits $ 1,770\ kgCO2eq $ and we consider an overall average load of 100 passengers per flight.
 
 We divide the scaled GHG emissions by this value to get the equivalent number of return flights.
 
-#### If you are motivated to help us test and enhance this methodology [contact us](https://genai-impact.org/contact/)! 💪
+##### If you are motivated to help us test and enhance this methodology [contact us](https://genai-impact.org/contact/)! 💪
 """
 
 CITATION_LABEL = "BibTeX citation for EcoLogits Calculator and the EcoLogits library:"

src/data/electricity_mix.csv

@@ -1,4 +0,0 @@
-name,unit,source,WOR,EEE,ZWE,ZMB,ZAF,YEM,VNM,VEN,UZB,URY,USA,UKR,TZA,TWN,TTO,TUR,TUN,TKM,TJK,THA,TGO,SYR,SLV,SEN,SVK,SVN,SGP,SWE,SDN,SAU,RUS,SCG,ROU,QAT,PRY,PRT,POL,PAK,PHL,PER,PAN,OMN,NZL,NPL,NOR,NLD,NIC,NGA,NAM,MOZ,MYS,MEX,MLT,MNG,MMR,MKD,MDA,MAR,LBY,LVA,LUX,LTU,LKA,LBN,KAZ,KWT,KOR,PRK,KHM,KGZ,KEN,JPN,JOR,JAM,ITA,ISL,IRN,IRQ,IND,ISR,IRL,IDN,HUN,HTI,HRV,HND,HKG,GTM,GRC,GIB,GHA,GEO,GBR,GAB,FRA,FIN,ETH,ESP,ERI,EGY,EST,ECU,DZA,DOM,DNK,DEU,CZE,CYP,CUB,CRI,COL,CHN,CMR,CHL,CIV,CHE,COG,COD,CAN,BLR,BWA,BRA,BOL,BRN,BEN,BHR,BGR,BEL,BGD,BIH,AZE,AUS,AUT,ARG,AGO,ANT,ARM,ALB,ARE
-adpe,kg éq. Sb,ADEME Base IMPACTS ®,0.0000000737708,0.0000000642317,0.000000109502,0.000000162193,0.0000000862445,0.0000000163908,0.0000000945573,0.000000112811,0.000000103681,0.000000104586,0.0000000985548,0.0000000647907,0.000000132261,0.0000000578088,0.000000064552,0.0000000749765,0.0000000177021,0.000000131822,0.000000152621,0.0000000569593,0.000000134255,0.0000000268396,0.0000000472135,0.0000000470662,0.0000000606109,0.0000000992283,0.0000000198459,0.0000000777062,0.0000000955701,0.0000000134206,0.0000000960312,0.000000132772,0.0000000981761,0.00000001324,0.000000149181,0.0000000341863,0.000000101946,0.0000000842952,0.0000000595304,0.0000000952688,0.0000000790553,0.0000000374073,0.0000000720474,0.000000238273,0.000000127486,0.0000000329318,0.0000000414983,0.0000000621,0.000000128285,0.000000148382,0.000000044938,0.0000000578358,0.000000049475,0.000000176361,0.000000152699,0.000000119873,0.000000110674,0.0000000641089,0.0000000206592,0.000000153757,0.000000105692,0.0000000294596,0.0000000986932,0.0000000182134,0.000000135386,0.0000000141168,0.0000000518017,0.000000117457,0.0000000319202,0.000000181827,0.0000000958533,0.0000000596578,0.0000000147031,0.0000000196047,0.00000005439,0.0000000781905,0.0000000220304,0.0000000404306,0.000000100099,0.0000000610194,0.0000000219257,0.0000000610451,0.0000000644587,0.0000000937057,0.000000153989,0.0000000649373,0.0000000816213,0.0000000803251,0.0000000691645,0.0000000286211,0.000000156003,0.000000137999,0.0000000370973,0.000000113843,0.0000000485798,0.0000000805114,0.000000174161,0.0000000518326,0.0000000512406,0.000000033925,0.0000000990171,0.000000127168,0.0000000216438,0.0000000429285,0.0000000157411,0.0000000878733,0.0000000817565,0.0000000448771,0.0000000299542,0.0000000863908,0.000000122031,0.0000000851552,0.000000146313,0.000000105851,0.0000000949004,0.000000100467,0.000000265575,0.000000174647,0.0000000993179,0.0000000840478,0.0000000866014,0.00000010962,0.0000000969793,0.0000000185641,0.0000000239702,0.0000000135014,0.0000000823611,0.0000000337201,0.0000000394158,0.000000148007,0.000000092567,0.0000000790846,0.000000141124,0.0000000768612,0.000000124074,0.0000000449103,0.0000000854245,0.000000229556,0.0000000141548
-pe,MJ,ADPf / (1-%renewable_energy),9.988,12.873,16.122,1.798,11.732,16.250,11.238,15.163,17.367,107.570,11.358,12.936,9.305,11.439,14.289,16.150,12.902,23.300,19.165,10.414,21.978,16.989,13.012,14.516,11.680,12.146,10.477,11.026,29.629,14.058,13.200,14.242,15.585,11.916,0.020,14.153,13.178,16.175,11.120,8.211,16.364,22.306,24.731,0.396,4.952,8.511,24.696,11.279,468.150,0.206,12.268,11.775,19.374,15.114,14.132,19.120,18.429,11.702,19.116,8.249,10.128,21.043,12.116,12.341,13.260,12.753,10.199,32.793,34.655,15.380,68.996,10.718,13.677,14.799,12.656,0.013,15.022,20.372,20.363,10.023,10.706,11.603,11.784,20.167,18.548,15.762,,14.340,14.487,,10.097,10.425,13.579,28.341,11.289,11.275,36.133,12.090,13.289,10.195,16.334,20.908,16.376,12.412,16.824,16.260,12.517,13.118,17.317,45.996,7.312,14.119,10.807,11.348,14.783,11.782,34.147,0.097,11.987,13.194,19.642,9.031,11.587,15.689,14.337,14.036,14.375,10.776,12.935,21.705,12.831,16.908,11.036,10.049,16.972,,13.380,0.201,19.032
-gwp,kg éq. CO2,ADEME Base IMPACTS ®,0.590478,0.509427,0.842811,0.0141304,1.17562,1.06777,0.555572,0.497373,0.81178,0.296953,0.67978,0.646745,0.475635,0.845351,0.933059,0.706988,0.80722,1.38296,0.0426743,0.646174,0.545455,1.08778,0.473128,1.1195,0.309341,0.498523,0.655825,0.0464664,1.12472,0.913677,0.66131,1.07808,0.664245,0.722125,0.241601,0.571172,1.15075,0.748727,0.761317,0.284364,0.53403,1.41292,0.293397,0.0841323,0.023754,0.544803,0.941626,0.693123,0.357253,0.00880732,0.832206,0.739214,1.31149,1.47192,0.48193,1.24074,1.04213,0.933694,1.35361,0.234273,0.490016,0.154229,0.709185,0.883627,1.128,0.885084,0.599585,0.797361,1.41054,0.156039,0.589603,0.540891,0.781372,1.07345,0.621329,0.0194609,0.930385,1.48728,1.58299,0.901842,0.648118,0.875394,0.541558,1.3858,0.535759,0.692837,0.95888,0.645801,1.13127,0.977477,0.540126,0.132046,0.602137,0.732511,0.0813225,0.322068,0.251299,0.467803,1.13153,0.587775,1.51492,0.627714,1.02318,0.909252,0.633534,0.657374,0.799077,0.978041,1.28325,0.224471,0.214014,1.05738,0.456622,0.574415,0.928583,0.0448568,0.904053,0.0613102,0.238191,0.795697,2.12572,0.278647,0.585131,0.997577,1.19128,0.804567,0.827087,0.256537,0.795168,1.56025,0.726126,1.12326,0.245573,0.476811,0.412014,1.13161,0.252002,0.0207635,1.09088

src/data/throughputs.json

@@ -0,0 +1,244 @@
+{
+    "models": [
+        {
+            "provider": "openai",
+            "name": "gpt-3.5-turbo",
+            "throughput": 144.6
+        },
+        {
+            "provider": "openai",
+            "name": "gpt-4",
+            "throughput": 33.0
+        },
+        {
+            "provider": "openai",
+            "name": "gpt-4-turbo",
+            "throughput": 46.5
+        },
+        {
+            "provider": "openai",
+            "name": "gpt-4o",
+            "throughput": 68.4
+        },
+        {
+            "provider": "openai",
+            "name": "gpt-4o-mini",
+            "throughput": 59.5
+        },
+        {
+            "provider": "openai",
+            "name": "o1",
+            "throughput": 442.9
+        },
+        {
+            "provider": "openai",
+            "name": "o1-mini",
+            "throughput": 173.2
+        },
+        {
+            "provider": "openai",
+            "name": "o3-mini",
+            "throughput": 597.4
+        },
+        {
+            "provider": "openai",
+            "name": "gpt-4.1-nano",
+            "throughput": 91.9
+        },
+        {
+            "provider": "openai",
+            "name": "gpt-4.1-mini",
+            "throughput": 68.7
+        },
+        {
+            "provider": "openai",
+            "name": "gpt-4.1",
+            "throughput": 61.0
+        },
+        {
+            "provider": "openai",
+            "name": "o4-mini",
+            "throughput": 64.7
+        },
+        {
+            "provider": "openai",
+            "name": "gpt-5-nano",
+            "throughput": 82.4
+        },
+        {
+            "provider": "openai",
+            "name": "gpt-5-mini",
+            "throughput": 47.1
+        },
+        {
+            "provider": "openai",
+            "name": "gpt-5",
+            "throughput": 41.3
+        },
+        {
+            "provider": "anthropic",
+            "name": "claude-3-5-haiku-latest",
+            "throughput": 59.6
+        },
+        {
+            "provider": "anthropic",
+            "name": "claude-3-5-sonnet-latest",
+            "throughput": 52.7
+        },
+        {
+            "provider": "anthropic",
+            "name": "claude-3-7-sonnet-latest",
+            "throughput": 51.9
+        },
+        {
+            "provider": "anthropic",
+            "name": "claude-opus-4-0",
+            "throughput": 37.0
+        },
+        {
+            "provider": "anthropic",
+            "name": "claude-opus-4-1",
+            "throughput": 38.1
+        },
+        {
+            "provider": "anthropic",
+            "name": "claude-sonnet-4-0",
+            "throughput": 60.2
+        },
+        {
+            "provider": "anthropic",
+            "name": "claude-sonnet-4-5",
+            "throughput": 61.4
+        },
+        {
+            "provider": "anthropic",
+            "name": "claude-haiku-4-5",
+            "throughput": 119.8
+        },
+        {
+            "provider": "mistralai",
+            "name": "codestral-latest",
+            "throughput": 272.8
+        },
+        {
+            "provider": "mistralai",
+            "name": "devstral-medium-latest",
+            "throughput": 106.7
+        },
+        {
+            "provider": "mistralai",
+            "name": "devstral-small-latest",
+            "throughput": 187.8
+        },
+        {
+            "provider": "mistralai",
+            "name": "magistral-medium-latest",
+            "throughput": 106.7
+        },
+        {
+            "provider": "mistralai",
+            "name": "magistral-small-latest",
+            "throughput": 187.8
+        },
+        {
+            "provider": "mistralai",
+            "name": "ministral-3b-latest",
+            "throughput": 309.6
+        },
+        {
+            "provider": "mistralai",
+            "name": "ministral-8b-latest",
+            "throughput": 213.7
+        },
+        {
+            "provider": "mistralai",
+            "name": "mistral-large-latest",
+            "throughput": 48.6
+        },
+        {
+            "provider": "mistralai",
+            "name": "mistral-medium-latest",
+            "throughput": 54.6
+        },
+        {
+            "provider": "mistralai",
+            "name": "mistral-small-latest",
+            "throughput": 158.0
+        },
+        {
+            "provider": "mistralai",
+            "name": "mistral-tiny-latest",
+            "throughput": 92.8
+        },
+        {
+            "provider": "mistralai",
+            "name": "open-mistral-7b",
+            "throughput": 121.5
+        },
+        {
+            "provider": "mistralai",
+            "name": "open-mistral-nemo",
+            "throughput": 153.2
+        },
+        {
+            "provider": "mistralai",
+            "name": "open-mixtral-8x22b",
+            "throughput": 85.7
+        },
+        {
+            "provider": "mistralai",
+            "name": "open-mixtral-8x7b",
+            "throughput": 80
+        },
+        {
+            "provider": "google_genai",
+            "name": "gemini-2.0-flash-lite",
+            "throughput": 74.1
+        },
+        {
+            "provider": "google_genai",
+            "name": "gemini-2.0-flash",
+            "throughput": 151.4
+        },
+        {
+            "provider": "google_genai",
+            "name": "gemini-2.5-flash-lite",
+            "throughput": 74.1
+        },
+        {
+            "provider": "google_genai",
+            "name": "gemini-2.5-flash",
+            "throughput": 93.2
+        },
+        {
+            "provider": "google_genai",
+            "name": "gemini-2.5-pro",
+            "throughput": 86.6
+        },
+        {
+            "provider": "cohere",
+            "name": "command-a-03-2025",
+            "throughput": 77.4
+        },
+        {
+            "provider": "cohere",
+            "name": "command-r",
+            "throughput": 125.1
+        },
+        {
+            "provider": "cohere",
+            "name": "command-r-08-2024",
+            "throughput": 67.2
+        },
+        {
+            "provider": "cohere",
+            "name": "command-r-plus-08-2024",
+            "throughput": 26.9
+        },
+        {
+            "provider": "cohere",
+            "name": "command-r7b-12-2024",
+            "throughput": 125.1
+        }
+    ]
+}

src/electricity_mix.py

@@ -1,174 +1,74 @@
-from csv import DictReader
-import pandas as pd
+from __future__ import annotations
 
-PATH = "src/data/electricity_mix.csv"
 
+PATH = "src/data/electricity_mix.csv"
 COUNTRY_CODES = [
     ("🌎 World", "WOR"),
-    ("🇪🇺 Europe", "EEE"),
-    ("🇿🇼 Zimbabwe", "ZWE"),
-    ("🇿🇲 Zambia", "ZMB"),
-    ("🇿🇦 South Africa", "ZAF"),
-    ("🇾🇪 Yemen", "YEM"),
-    ("🇻🇳 Vietnam", "VNM"),
-    ("🇻🇪 Venezuela", "VEN"),
-    ("🇺🇿 Uzbekistan", "UZB"),
-    ("🇺🇾 Uruguay", "URY"),
-    ("🇺🇸 United States", "USA"),
-    ("🇺🇦 Ukraine", "UKR"),
-    ("🇹🇿 Tanzania", "TZA"),
-    ("🇹🇼 Taiwan", "TWN"),
-    ("🇹🇹 Trinidad and Tobago", "TTO"),
-    ("🇹🇷 Turkey", "TUR"),
-    ("🇹🇳 Tunisia", "TUN"),
-    ("🇹🇲 Turkmenistan", "TKM"),
-    ("🇹🇯 Tajikistan", "TJK"),
-    ("🇹🇭 Thailand", "THA"),
-    ("🇹🇬 Togo", "TGO"),
-    ("🇸🇾 Syrian Arab Republic", "SYR"),
-    ("🇸🇻 El Salvador", "SLV"),
-    ("🇸🇳 Senegal", "SEN"),
-    ("🇸🇰 Slovak Republic", "SVK"),
-    ("🇸🇮 Slovenia", "SVN"),
-    ("🇸🇬 Singapore", "SGP"),
-    ("🇸🇪 Sweden", "SWE"),
-    ("🇸🇩 Sudan", "SDN"),
-    ("🇸🇦 Saudi Arabia", "SAU"),
-    ("🇷🇺 Russian Federation", "RUS"),
-    ("🇷🇸 Serbia and Montenegro", "SCG"),
-    ("🇷🇴 Romania", "ROU"),
-    ("🇶🇦 Qatar", "QAT"),
-    ("🇵🇾 Paraguay", "PRY"),
-    ("🇵🇹 Portugal", "PRT"),
-    ("🇵🇱 Poland", "POL"),
-    ("🇵🇰 Pakistan", "PAK"),
-    ("🇵🇭 Philippines", "PHL"),
-    ("🇵🇪 Peru", "PER"),
-    ("🇵🇦 Panama", "PAN"),
-    ("🇴🇲 Oman", "OMN"),
-    ("🇳🇿 New Zealand", "NZL"),
-    ("🇳🇵 Nepal", "NPL"),
-    ("🇳🇴 Norway", "NOR"),
-    ("🇳🇱 Netherlands", "NLD"),
-    ("🇳🇮 Nicaragua", "NIC"),
-    ("🇳🇬 Nigeria", "NGA"),
-    ("🇳🇦 Namibia", "NAM"),
-    ("🇲🇿 Mozambique", "MOZ"),
-    ("🇲🇾 Malaysia", "MYS"),
-    ("🇲🇽 Mexico", "MEX"),
-    ("🇲🇹 Malta", "MLT"),
-    ("🇲🇳 Mongolia", "MNG"),
-    ("🇲🇲 Myanmar", "MMR"),
-    ("🇲🇰 North Macedonia", "MKD"),
-    ("🇲🇩 Moldova", "MDA"),
-    ("🇲🇦 Morocco", "MAR"),
-    ("🇱🇾 Libya", "LBY"),
-    ("🇱🇻 Latvia", "LVA"),
-    ("🇱🇺 Luxembourg", "LUX"),
-    ("🇱🇹 Lithuania", "LTU"),
-    ("🇱🇰 Sri Lanka", "LKA"),
-    ("🇱🇧 Lebanon", "LBN"),
-    ("🇰🇿 Kazakhstan", "KAZ"),
-    ("🇰🇼 Kuwait", "KWT"),
-    ("🇰🇷 South Korea", "KOR"),
-    ("🇰🇵 North Korea", "PRK"),
-    ("🇰🇭 Cambodia", "KHM"),
-    ("🇰🇬 Kyrgyz Republic", "KGZ"),
-    ("🇰🇪 Kenya", "KEN"),
-    ("🇯🇵 Japan", "JPN"),
-    ("🇯🇴 Jordan", "JOR"),
-    ("🇯🇲 Jamaica", "JAM"),
-    ("🇮🇹 Italy", "ITA"),
-    ("🇮🇸 Iceland", "ISL"),
-    ("🇮🇷 Iran", "IRN"),
-    ("🇮🇶 Iraq", "IRQ"),
-    ("🇮🇳 India", "IND"),
-    ("🇮🇱 Israel", "ISR"),
-    ("🇮🇪 Ireland", "IRL"),
-    ("🇮🇩 Indonesia", "IDN"),
-    ("🇭🇺 Hungary", "HUN"),
-    ("🇭🇹 Haiti", "HTI"),
-    ("🇭🇷 Croatia", "HRV"),
-    ("🇭🇳 Honduras", "HND"),
-    ("🇭🇰 Hong Kong", "HKG"),
-    ("🇬🇹 Guatemala", "GTM"),
-    ("🇬🇷 Greece", "GRC"),
-    ("🇬🇮 Gibraltar", "GIB"),
-    ("🇬🇭 Ghana", "GHA"),
-    ("🇬🇪 Georgia", "GEO"),
-    ("🇬🇧 United Kingdom", "GBR"),
-    ("🇬🇦 Gabon", "GAB"),
-    ("🇫🇷 France", "FRA"),
-    ("🇫🇮 Finland", "FIN"),
-    ("🇪🇹 Ethiopia", "ETH"),
-    ("🇪🇸 Spain", "ESP"),
-    ("🇪🇷 Eritrea", "ERI"),
-    ("🇪🇬 Egypt", "EGY"),
-    ("🇪🇪 Estonia", "EST"),
-    ("🇪🇨 Ecuador", "ECU"),
-    ("🇩🇿 Algeria", "DZA"),
-    ("🇩🇴 Dominican Republic", "DOM"),
-    ("🇩🇰 Denmark", "DNK"),
-    ("🇩🇪 Germany", "DEU"),
-    ("🇨🇿 Czech Republic", "CZE"),
-    ("🇨🇾 Cyprus", "CYP"),
-    ("🇨🇺 Cuba", "CUB"),
-    ("🇨🇷 Costa Rica", "CRI"),
-    ("🇨🇴 Colombia", "COL"),
-    ("🇨🇳 China", "CHN"),
-    ("🇨🇲 Cameroon", "CMR"),
-    ("🇨🇱 Chile", "CHL"),
-    ("🇨🇮 Cote d'Ivoire", "CIV"),
-    ("🇨🇭 Switzerland", "CHE"),
-    ("🇨🇬 Congo", "COG"),
-    ("🇨🇩 Democratic Republic of the Congo", "COD"),
-    ("🇨🇦 Canada", "CAN"),
-    ("🇧🇾 Belarus", "BLR"),
-    ("🇧🇼 Botswana", "BWA"),
-    ("🇧🇷 Brazil", "BRA"),
-    ("🇧🇴 Bolivia", "BOL"),
-    ("🇧🇳 Brunei", "BRN"),
-    ("🇧🇯 Benin", "BEN"),
-    ("🇧🇭 Bahrain", "BHR"),
-    ("🇧🇬 Bulgaria", "BGR"),
-    ("🇧🇪 Belgium", "BEL"),
-    ("🇧🇩 Bangladesh", "BGD"),
-    ("🇧🇦 Bosnia and Herzegovina", "BIH"),
-    ("🇦🇿 Azerbaijan", "AZE"),
     ("🇦🇺 Australia", "AUS"),
     ("🇦🇹 Austria", "AUT"),
     ("🇦🇷 Argentina", "ARG"),
-    ("🇦🇴 Angola", "AGO"),
-    ("���� Netherlands Antilles", "ANT"),
-    ("🇦🇲 Armenia", "ARM"),
-    ("🇦🇱 Albania", "ALB"),
-    ("🇦🇪 United Arab Emirates", "ARE"),
+    ("🇧🇪 Belgium", "BEL"),
+    ("🇧🇬 Bulgaria", "BGR"),
+    ("🇧🇷 Brazil", "BRA"),
+    ("🇨🇦 Canada", "CAN"),
+    ("🇨🇭 Switzerland", "CHE"),
+    ("🇨🇱 Chile", "CHL"),
+    ("🇨🇳 China", "CHN"),
+    ("🇨🇾 Cyprus", "CYP"),
+    ("🇨🇿 Czech Republic", "CZE"),
+    ("🇩🇪 Germany", "DEU"),
+    ("🇩🇰 Denmark", "DNK"),
+    ("🇪🇸 Spain", "ESP"),
+    ("🇪🇪 Estonia", "EST"),
+    ("🇫🇮 Finland", "FIN"),
+    ("🇫🇷 France", "FRA"),
+    ("🇬🇧 United Kingdom", "GBR"),
+    ("🇬🇷 Greece", "GRC"),
+    ("🇭🇺 Hungary", "HUN"),
+    ("🇮🇩 Indonesia", "IDN"),
+    ("🇮🇳 India", "IND"),
+    ("🇮🇪 Ireland", "IRL"),
+    ("🇮🇸 Iceland", "ISL"),
+    ("🇮🇹 Italy", "ITA"),
+    ("🇯🇵 Japan", "JPN"),
+    ("🇰🇷 South Korea", "KOR"),
+    ("🇱🇹 Lithuania", "LTU"),
+    ("🇱🇺 Luxembourg", "LUX"),
+    ("🇱🇻 Latvia", "LVA"),
+    ("🇲🇽 Mexico", "MEX"),
+    ("🇲🇹 Malta", "MLT"),
+    ("🇲🇾 Malaysia", "MYS"),
+    ("🇳🇱 Netherlands", "NLD"),
+    ("🇳🇴 Norway", "NOR"),
+    ("🇳🇿 New Zealand", "NZL"),
+    ("🇵🇱 Poland", "POL"),
+    ("🇵🇹 Portugal", "PRT"),
+    ("🇷🇴 Romania", "ROU"),
+    ("🇷🇺 Russian Federation", "RUS"),
+    ("🇸🇰 Slovak Republic", "SVK"),
+    ("🇸🇮 Slovenia", "SVN"),
+    ("🇸🇪 Sweden", "SWE"),
+    ("🇺🇦 Ukraine", "UKR"),
+    ("🇹🇭 Thailand", "THA"),
+    ("🇹🇷 Turkey", "TUR"),
+    ("🇹🇼 Taiwan", "TWN"),
+    ("🇺🇸 United States", "USA")
 ]
 
+CRITERIA = {
+    "gwp": "GHG Emission (kg CO2 eq)",
+    "adpe": "Abiotic Resources (kg Sb eq)",
+    "pe": "Primary Energy (MJ)",
+    "wue": "Water Usage Effectiveness (L/kWh)"
+}
 
-def find_electricity_mix(code: str):
-    # TODO: Maybe more optimal to construct database at the beginning of the app
-    #       in the same fashion as find_model
-    res = []
-    with open(PATH) as fd:
-        csv = DictReader(fd)
-        for row in csv:
-            res += [float(row[code])]
-    return res
-
-
-def dataframe_electricity_mix(countries: list):
-    df = pd.read_csv("src/data/electricity_mix.csv")
-    df["name_unit"] = df["name"] + " (" + df["unit"] + ")"
-    df = df[["name_unit"] + [x[1] for x in COUNTRY_CODES if x[0] in countries]]
 
-    df_melted = df.melt(
-        id_vars=["name_unit"],
-        value_vars=[x[1] for x in COUNTRY_CODES if x[0] in countries],
-        var_name="country",
-        value_name="value",
-    )
+def format_country_name(code: str) -> str | None:
+    for country_name, country_code in COUNTRY_CODES:
+        if country_code == code:
+            return country_name
+    return None
 
-    df = df_melted.pivot(columns="name_unit", index="country", values="value")
 
-    return df
+def format_electricity_mix_criterion(criterion: str) -> str | None:
+    return CRITERIA.get(criterion)

src/expert.py

@@ -1,58 +1,52 @@
+import pandas as pd
 import streamlit as st
+from ecologits.electricity_mix_repository import electricity_mixes
 from ecologits.impacts.llm import compute_llm_impacts
 
-from src.utils import format_impacts, average_range_impacts
+from src.latency_estimator import latency_estimator
+from src.utils import format_impacts
 from src.impacts import display_impacts
-from src.electricity_mix import (
-    COUNTRY_CODES,
-    find_electricity_mix,
-    dataframe_electricity_mix,
-)
+from src.electricity_mix import COUNTRY_CODES, format_electricity_mix_criterion, format_country_name
 from src.models import load_models
 from src.constants import PROMPTS
+from src.constants import PROMPTS
 
 import plotly.express as px
 
 
-def reset_model():
-    model = "CUSTOM"
-
-
 def expert_mode():
     st.markdown("### 🤓 Expert mode")
 
     with st.container(border=True):
+        st.markdown("###### Configure the model")
+
         ########## Model info ##########
 
-        col1, col2, col3 = st.columns(3)
+        provider_col, model_col = st.columns(2)
 
         df = load_models(filter_main=True)
 
-        with col1:
+        with provider_col:
+            providers_clean = [x for x in df["provider_clean"].unique()]
             provider_exp = st.selectbox(
                 label="Provider",
-                options=[x for x in df["provider_clean"].unique()],
-                index=7,
+                options=providers_clean,
+                index=providers_clean.index("OpenAI"),
                 key=1,
             )
 
-        with col2:
+        with model_col:
+            models_clean = [
+                x
+                for x in df["name_clean"].unique()
+                if x in df[df["provider_clean"] == provider_exp]["name_clean"].unique()
+            ]
             model_exp = st.selectbox(
                 label="Model",
-                options=[
-                    x
-                    for x in df["name_clean"].unique()
-                    if x
-                    in df[df["provider_clean"] == provider_exp]["name_clean"].unique()
-                ],
+                options=models_clean,
                 key=2,
             )
 
-        with col3:
-            output_tokens_exp = st.selectbox(
-                label="Example prompt", options=[x[0] for x in PROMPTS], key=3
-            )
-
         df_filtered = df[
             (df["provider_clean"] == provider_exp) & (df["name_clean"] == model_exp)
         ]
@@ -79,67 +73,111 @@ def expert_mode():
                 / 2
             )
 
+        provider_raw = df_filtered["provider"].values[0]
+        model_name_raw = df_filtered["name"].values[0]
+        tps_raw = latency_estimator.get_throughput(provider_raw, model_name_raw)
+
         ########## Model parameters ##########
 
-        col11, col22, col33 = st.columns(3)
+        active_params_col, total_params_col, throughput_col = st.columns(3)
 
-        with col11:
-            active_params = st.number_input(
-                "Active parameters (B)", 0, None, active_params
-            )
+        with active_params_col:
+            active_params = st.number_input("Active parameters (B)", 0, None, active_params)
+
+        with total_params_col:
+            total_params = st.number_input("Total parameters (B)", 0, None, total_params)
 
-        with col22:
-            total_params = st.number_input(
-                "Total parameters (B)", 0, None, total_params
+        with throughput_col:
+            throughput = st.number_input("Average TPS", 1.0, None, tps_raw)
+
+
+    with st.container(border=True):
+        st.markdown("###### Configure the prompt")
+
+        prompt_col, token_col = st.columns(2)
+
+        with prompt_col:
+            output_tokens_exp = st.selectbox(
+                label="Example prompt", options=[x[0] for x in PROMPTS], key=3
             )
 
-        with col33:
+        with token_col:
             output_tokens = st.number_input(
                 label="Output completion tokens",
                 min_value=0,
                 value=[x[1] for x in PROMPTS if x[0] == output_tokens_exp][0],
             )
 
-        ########## Electricity mix ##########
 
-        location = st.selectbox("Location", [x[0] for x in COUNTRY_CODES])
-
-        col4, col5, col6 = st.columns(3)
+    with st.container(border=True):
+        st.markdown("###### Configure the data center")
+
+        dc_pue_col, dc_wue_col, dc_location_col = st.columns(3)
+        with dc_pue_col:
+            datacenter_pue = st.number_input(
+                label="Data center PUE",
+                value=1.2,
+                min_value=1.0
+            )
+        with dc_wue_col:
+            datacenter_wue = st.number_input(
+                label="Data center WUE [L / kWh]",
+                value=0.6,
+                min_value=0.
+            )
+        with dc_location_col:
+            dc_location = st.selectbox(
+                label="Data center location",
+                options=[c[1] for c in COUNTRY_CODES],
+                format_func=format_country_name,
+                index=0
+            )
 
-        with col4:
-            mix_gwp = st.number_input(
-                "Electricity mix - GHG emissions [kgCO2eq / kWh]",
-                find_electricity_mix(
-                    [x[1] for x in COUNTRY_CODES if x[0] == location][0]
-                )[2],
+        em_gwp_col, em_adpe_col, em_pe_col, em_wue_col = st.columns(4)
+        electricity_mix = electricity_mixes.find_electricity_mix(dc_location)
+        with em_gwp_col:
+            em_gwp = st.number_input(
+                label="GHG emissions [kgCO2eq / kWh]",
+                value=electricity_mix.gwp,
                 format="%0.6f",
             )
-            # disp_ranges = st.toggle('Display impact ranges', False)
-        with col5:
-            mix_adpe = st.number_input(
-                "Electricity mix - Abiotic resources [kgSbeq / kWh]",
-                find_electricity_mix(
-                    [x[1] for x in COUNTRY_CODES if x[0] == location][0]
-                )[0],
+        with em_adpe_col:
+            em_adpe = st.number_input(
+                label="Abiotic resources [kgSbeq / kWh]",
+                value=electricity_mix.adpe,
                 format="%0.13f",
             )
-        with col6:
-            mix_pe = st.number_input(
-                "Electricity mix - Primary energy [MJ / kWh]",
-                find_electricity_mix(
-                    [x[1] for x in COUNTRY_CODES if x[0] == location][0]
-                )[1],
+        with em_pe_col:
+            em_pe = st.number_input(
+                label="Primary energy [MJ / kWh]",
+                value=electricity_mix.pe,
+                format="%0.3f",
+            )
+        with em_wue_col:
+            em_wue = st.number_input(
+                label="Water consumption [L / kWh]",
+                value=electricity_mix.wue,
                 format="%0.3f",
             )
 
+    estimated_latency = latency_estimator.estimate(
+        provider=provider_raw,
+        model_name=model_name_raw,
+        output_tokens=output_tokens,
+        throughput=throughput
+    )
+
     impacts = compute_llm_impacts(
         model_active_parameter_count=active_params,
         model_total_parameter_count=total_params,
         output_token_count=output_tokens,
-        request_latency=100000,
-        if_electricity_mix_gwp=mix_gwp,
-        if_electricity_mix_adpe=mix_adpe,
-        if_electricity_mix_pe=mix_pe,
+        request_latency=estimated_latency,
+        if_electricity_mix_gwp=em_gwp,
+        if_electricity_mix_adpe=em_adpe,
+        if_electricity_mix_pe=em_pe,
+        if_electricity_mix_wue=em_wue,
+        datacenter_pue=datacenter_pue,
+        datacenter_wue=datacenter_wue
     )
 
     impacts, usage, embodied = format_impacts(impacts)
@@ -166,8 +204,8 @@ def expert_mode():
         with col_ghg_comparison:
             fig_gwp = px.pie(
                 values=[
-                    average_range_impacts(usage.gwp.value),
-                    average_range_impacts(embodied.gwp.value),
+                    usage.gwp.value if isinstance(usage.gwp.value, float) else usage.gwp.value.mean,
+                    embodied.gwp.value if isinstance(embodied.gwp.value, float) else embodied.gwp.value.mean,
                 ],
                 names=["usage", "embodied"],
                 title="GHG emissions",
@@ -181,8 +219,8 @@ def expert_mode():
         with col_adpe_comparison:
             fig_adpe = px.pie(
                 values=[
-                    average_range_impacts(usage.adpe.value),
-                    average_range_impacts(embodied.adpe.value),
+                    usage.adpe.value if isinstance(usage.adpe.value, float) else usage.adpe.value.mean,
+                    embodied.adpe.value if isinstance(embodied.adpe.value, float) else embodied.adpe.value.mean,
                 ],
                 names=["usage", "embodied"],
                 title="Abiotic depletion",
@@ -196,8 +234,8 @@ def expert_mode():
         with col_pe_comparison:
             fig_pe = px.pie(
                 values=[
-                    average_range_impacts(usage.pe.value),
-                    average_range_impacts(embodied.pe.value),
+                    usage.pe.value if isinstance(usage.pe.value, float) else usage.pe.value.mean,
+                    embodied.pe.value if isinstance(embodied.pe.value, float) else embodied.pe.value.mean,
                 ],
                 names=["usage", "embodied"],
                 title="Primary energy",
@@ -216,24 +254,25 @@ def expert_mode():
 
         countries_to_compare = st.multiselect(
             label="Countries to compare",
-            options=[x[0] for x in COUNTRY_CODES],
-            default=["🇫🇷 France", "🇺🇸 United States", "🇨🇳 China"],
+            options=[c[1] for c in COUNTRY_CODES],
+            format_func=format_country_name,
+            default=["FRA", "USA", "CHN"],
         )
 
         try:
-            df_comp = dataframe_electricity_mix(countries_to_compare)
-
             impact_type = st.selectbox(
                 label="Select an impact type to compare",
-                options=[x for x in df_comp.columns if x != "country"],
-                index=1,
+                options=["gwp", "adpe", "pe", "wue"],
+                format_func=format_electricity_mix_criterion,
+                index=0,
             )
 
-            df_comp.sort_values(by=impact_type, inplace=True)
+            df_comp = pd.DataFrame([em for em in electricity_mixes.list_electricity_mixes() if em.zone in countries_to_compare])
+            df_comp = df_comp.sort_values(by=impact_type, ascending=True)
 
             fig_2 = px.bar(
                 df_comp,
-                x=df_comp.index,
+                x=df_comp.zone.apply(format_country_name),
                 y=impact_type,
                 text=impact_type,
                 color=impact_type,

src/impacts.py

@@ -10,56 +10,58 @@ from src.utils import (
     EnergyProduction,
 )
 
-############################################################################################################
-
-
-def get_impacts(model, active_params, total_params, mix_ghg, mix_adpe, mix_pe):
-    return 1
-
-
-############################################################################################################
-
 
 def display_impacts(impacts):
     st.divider()
 
-    col1, col_energy, col_ghg, col2 = st.columns([1,2,2,1])
+    col1, col_energy, col_gwp, col2 = st.columns([1,2,2,1])
 
     with col_energy:
- 
         st.markdown(f"""<p style='font-size:30px;text-align: center;margin-bottom :2px'>⚡️</p><p style='font-size:30px;text-align: center;margin-bottom :2px'><strong>Energy</p>""", unsafe_allow_html = True)
         st.markdown(f'<p align="center">Electricity consumption</p>', unsafe_allow_html = True)
-        range_plot(impacts.energy.magnitude,impacts.energy_min.magnitude, impacts.energy_max.magnitude, impacts.energy.units)
-                
-
-    with col_ghg:
+        if impacts.ranges:
+            range_plot(impacts.energy.magnitude,impacts.energy_min.magnitude, impacts.energy_max.magnitude, impacts.energy.units)
+        else:
+            st.latex(f'\Large {impacts.energy.magnitude:.3g} \ \large {impacts.energy.units}')
 
+    with col_gwp:
         st.markdown(f"""<p style='font-size:30px;text-align: center;margin-bottom :2px'>🌍️</p><p style='font-size:30px;text-align: center;margin-bottom :2px'><strong>GHG Emissions</p>""", unsafe_allow_html = True)
-        st.markdown(f'<p align="center">Effect on global warming</p>', unsafe_allow_html = True)    
-        range_plot(impacts.gwp.magnitude,impacts.gwp_min.magnitude, impacts.gwp_max.magnitude, impacts.gwp.units)
+        st.markdown(f'<p align="center">Effect on global warming</p>', unsafe_allow_html = True)
+        if impacts.ranges:
+            range_plot(impacts.gwp.magnitude,impacts.gwp_min.magnitude, impacts.gwp_max.magnitude, impacts.gwp.units)
+        else:
+            st.latex(f'\Large {impacts.gwp.magnitude:.3g} \ \large {impacts.gwp.units}')
 
     st.markdown(f'<br>', unsafe_allow_html = True)
     
-    col_adpe, col_pe, col_water = st.columns(3)
+    col_adpe, col_pe, col_wcf = st.columns(3)
 
     with col_adpe:
         st.markdown(f"""<p style='font-size:30px;text-align: center;margin-bottom :2px'>🪨</p>""", unsafe_allow_html = True)
         st.markdown(f"""<p style='font-size:30px;text-align: center;margin-bottom :2px'><strong>Abiotic Resources</p>""", unsafe_allow_html = True)
         st.markdown('<p align="center"> Use of metals and minerals</p>', unsafe_allow_html = True)
-        range_plot(impacts.adpe.magnitude,impacts.adpe_min.magnitude, impacts.adpe_max.magnitude, impacts.adpe.units)
-    
+        if impacts.ranges:
+            range_plot(impacts.adpe.magnitude, impacts.adpe_min.magnitude, impacts.adpe_max.magnitude, impacts.adpe.units)
+        else:
+            st.latex(f'\Large {impacts.adpe.magnitude:.3g} \ \large {impacts.adpe.units}')
 
     with col_pe:
         st.markdown(f"""<p style='font-size:30px;text-align: center;margin-bottom :2px'>⛽️</p>""", unsafe_allow_html = True)
         st.markdown(f"""<p style='font-size:30px;text-align: center;margin-bottom :2px'><strong>Primary Energy</p>""", unsafe_allow_html = True)
         st.markdown(f'<p align="center">Use of natural energy resources</p>', unsafe_allow_html = True)
-        range_plot(impacts.pe.magnitude,impacts.pe_min.magnitude, impacts.pe_max.magnitude, impacts.pe.units)
+        if impacts.ranges:
+            range_plot(impacts.pe.magnitude, impacts.pe_min.magnitude, impacts.pe_max.magnitude, impacts.pe.units)
+        else:
+            st.latex(f'\Large {impacts.pe.magnitude:.3g} \ \large {impacts.pe.units}')
 
-    with col_water:
+    with col_wcf:
         st.markdown(f"""<p style='font-size:30px;text-align: center;margin-bottom :2px'>🚰</p>""", unsafe_allow_html = True)
         st.markdown(f"""<p style='font-size:30px;text-align: center;margin-bottom :2px'><strong>Water</p>""", unsafe_allow_html = True)
-        st.markdown(f'<p align="center">Evaluates the use of water</p>', unsafe_allow_html = True)
-        st.markdown(f"""<p style='font-size:35px;text-align: center'> Upcoming... </p>""", unsafe_allow_html = True)
+        st.markdown(f'<p align="center">Water consumption</p>', unsafe_allow_html = True)
+        if impacts.ranges:
+            range_plot(impacts.wcf.magnitude, impacts.wcf_min.magnitude, impacts.wcf_max.magnitude, impacts.wcf.units)
+        else:
+            st.latex(f'\Large {impacts.wcf.magnitude:.3g} \ \large {impacts.wcf.units}')
         
         
 

src/latency_estimator.py

@@ -0,0 +1,33 @@
+from __future__ import annotations
+
+import json
+from pathlib import Path
+
+_BASE_PATH = Path(__file__).parent / "data" / "throughputs.json"
+
+
+class LatencyEstimator:
+    __DEFAULT_TPS = 80.0
+
+    def __init__(self, file_path: str | Path) -> None:
+        with open(file_path, "r") as fd:
+            data = json.load(fd)
+
+        self.__throughputs = {}
+        for el in data["models"]:
+            self.__throughputs[(el["provider"], el["name"])] = el["throughput"]
+
+    def get_throughput(self, provider: str, model_name: str) -> float:
+        return float(self.__throughputs.get((provider, model_name), self.__DEFAULT_TPS))
+
+    def estimate(self,
+                 provider: str,
+                 model_name: str,
+                 output_tokens: int,
+                 throughput: float | None = None) -> float:
+        if throughput is None:
+            throughput = self.__throughputs.get((provider, model_name), self.__DEFAULT_TPS)
+        return float(output_tokens / throughput)
+
+
+latency_estimator = LatencyEstimator(file_path=_BASE_PATH)

src/models.py

@@ -1,8 +1,13 @@
-import requests
 import json
+
+import requests
 import pandas as pd
-from src.constants import MODEL_REPOSITORY_URL, MAIN_MODELS
 import streamlit as st
+from ecologits.model_repository import models as model_repository, ArchitectureTypes
+from ecologits.status_messages import ModelArchNotReleasedWarning, ModelArchMultimodalWarning
+from ecologits.utils.range_value import RangeValue
+
+from src.constants import MODEL_REPOSITORY_URL, MAIN_MODELS
 
 
 def clean_models_data(df, with_filter=True):
@@ -70,10 +75,68 @@ def clean_models_data(df, with_filter=True):
     ]
 
 
+PROVIDERS_FORMAT = {
+    "anthropic": "Anthropic",
+    "cohere": "Cohere",
+    "google_genai": "Google",
+    "mistralai": "Mistral AI",
+    "openai": "OpenAI",
+}
+
+
 @st.cache_data
-def load_models(filter_main=True):
-    resp = requests.get(MODEL_REPOSITORY_URL)
-    data = json.loads(resp.text)
-    df = pd.DataFrame(data["models"])
+def load_models(filter_main=True) -> pd.DataFrame:
+    data = []
+    for m in model_repository.list_models():
+        if filter_main and m.name not in MAIN_MODELS:
+            continue    # Ignore "not main" models when filter is enabled
+
+        if m.architecture.type == ArchitectureTypes.DENSE:
+            if isinstance(m.architecture.parameters, RangeValue):
+                total_parameters = dict(m.architecture.parameters)
+            else:
+                total_parameters = m.architecture.parameters
+            active_parameters = total_parameters
+
+        elif m.architecture.type == ArchitectureTypes.MOE:
+            if isinstance(m.architecture.parameters.total, RangeValue):
+                total_parameters = dict(m.architecture.parameters.total)
+            else:
+                total_parameters = m.architecture.parameters.total
+
+            if isinstance(m.architecture.parameters.active, RangeValue):
+                active_parameters = dict(m.architecture.parameters.active)
+            else:
+                active_parameters = m.architecture.parameters.active
+
+        else:
+            continue    # Ignore model
+
+        warning_arch = False
+        warning_multi_modal = False
+        for w in m.warnings:
+            if isinstance(w, ModelArchNotReleasedWarning):
+                warning_arch = True
+            if isinstance(w, ModelArchMultimodalWarning):
+                warning_multi_modal = True
+
+        data.append({
+            "provider": m.provider.value,
+            "provider_clean": PROVIDERS_FORMAT.get(m.provider.value, m.provider.value),
+            "name": m.name,
+            "name_clean": clean_model_name(m.name),
+            "architecture_type": m.architecture.type.value,
+            "total_parameters": total_parameters,
+            "active_parameters": active_parameters,
+            "warning_arch": warning_arch,
+            "warning_multi_modal": warning_multi_modal,
+        })
+
+    return pd.DataFrame(data)
+
 
-    return clean_models_data(df, filter_main)
+def clean_model_name(model_name: str) -> str:
+    model_name = model_name.replace("latest", "")
+    model_name = model_name.replace("-", " ")
+    model_name = model_name.replace("_", " ")
+    return model_name

src/style.css

@@ -4,7 +4,7 @@ html, body, [class*="css"] {
     font-family: 'Montserrat', sans-serif; 
     font-size: 18px;
     font-weight: 500;
-    color: #091747;
+    color: #062522;
 }
 
 [data-testid="metric-container"] {

src/utils.py

@@ -1,12 +1,10 @@
 from dataclasses import dataclass
 from enum import Enum
 
-from ecologits.impacts.modeling import Impacts, Energy, GWP, ADPe, PE
+from ecologits.impacts.modeling import Impacts, Energy, GWP, ADPe, PE, WCF, Usage, Embodied
 
-# from ecologits.tracers.utils import llm_impacts
 from pint import UnitRegistry, Quantity
 import streamlit as st
-import plotly.express as px
 import plotly.graph_objects as go
 
 #####################################################################################
@@ -15,16 +13,23 @@ import plotly.graph_objects as go
 
 u = UnitRegistry()
 u.define("Wh = watt_hour")
+u.define("mWh = milliwatt_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("mgCO2eq = milligram")
 u.define("kgCO2eq = kilogram")
 u.define("tCO2eq = metricton")
 u.define("kgSbeq = kilogram")
+u.define("gSbeq = gram")
+u.define("mgSbeq = milligram")
+u.define("µgSbeq = microgram")
 u.define("kJ = kilojoule")
 u.define("MJ = megajoule")
+u.define("L = liter")
+u.define("mL = milliliter")
 u.define("m = meter")
 u.define("km = kilometer")
 u.define("s = second")
@@ -36,17 +41,22 @@ q = u.Quantity
 @dataclass
 class QImpacts:
     energy: Quantity
-    energy_min : Quantity
-    energy_max : Quantity
     gwp: Quantity
-    gwp_min : Quantity
-    gwp_max : Quantity
     adpe: Quantity
-    adpe_min : Quantity
-    adpe_max : Quantity
     pe: Quantity
-    pe_min : Quantity
-    pe_max : Quantity
+    wcf: Quantity
+    ranges: bool = False
+    energy_min: Quantity | None = None
+    energy_max: Quantity | None = None
+    gwp_min: Quantity | None = None
+    gwp_max: Quantity | None = None
+    adpe_min: Quantity | None = None
+    adpe_max: Quantity | None = None
+    pe_min: Quantity | None = None
+    pe_max: Quantity | None = None
+    wcf_min: Quantity | None = None
+    wcf_max: Quantity | None = None
+
 
 
 class PhysicalActivity(str, Enum):
@@ -108,119 +118,84 @@ AIRPLANE_PARIS_NYC_GWP_EQ = q("177000 kgCO2eq")
 #####################################################################################
 
 
-def format_energy(energy: Energy) -> Quantity:
-    
-    val_min = q(energy.value.min, energy.unit)
-    val_max = q(energy.value.max, energy.unit)
-    val_mean = (val_min + val_max)/2
-    
-    if val_max < q("1 kWh"):
-        val_min = val_min.to("Wh")
-        val_max = val_max.to("Wh")
-        val_mean = val_mean.to("Wh")
-    
-    return val_mean, val_min, val_max
+def format_energy(energy_value: float, energy_unit = Energy(value=0.).unit) -> Quantity:
+    val = q(energy_value, energy_unit)
+    if val < q("1 kWh"):
+        val = val.to("Wh")
+    if val < q("1 Wh"):
+        val = val.to("mWh")
+    return val
  
 
-def format_gwp(gwp: GWP) -> Quantity:
-
-    val_min = q(gwp.value.min, gwp.unit)
-    val_max =q(gwp.value.max, gwp.unit)
-    val_mean = (val_min + val_max)/2
-
-    if val_max < q("1 kgCO2eq"):
-        val_min = val_min.to("gCO2eq")
-        val_max = val_max.to("gCO2eq")
-        val_mean = val_mean.to("gCO2eq")
-    
-    return val_mean, val_min, val_max
-
-
-def format_adpe(adpe: ADPe) -> Quantity:
-
-    val_min = q(adpe.value.min, adpe.unit)
-    val_max = q(adpe.value.max, adpe.unit)
-    val_mean = (val_min + val_max)/2
-    return val_mean, val_min, val_max
-
-
-def format_pe(pe: PE) -> Quantity:
-
-    val_min = q(pe.value.min, pe.unit)
-    val_max = q(pe.value.max, pe.unit)
-    val_mean = (val_min + val_max)/2
-    
-    if val_max < q("1 MJ"):
-        val_min = val_min.to("kJ")
-        val_max = val_max.to("kJ")
-        val_mean = val_mean.to("kJ")
-    
-    return val_mean, val_min, val_max
-
-
-def format_impacts(impacts: Impacts) -> QImpacts:
-    energy, energy_min, energy_max = format_energy(impacts.energy)
-    gwp, gwp_min, gwp_max = format_gwp(impacts.gwp)
-    adpe, adpe_min, adpe_max = format_adpe(impacts.adpe)
-    pe, pe_min, pe_max = format_pe(impacts.pe)
-    return QImpacts(
-                energy= energy,
-                energy_min=energy_min,
-                energy_max=energy_max,
-                gwp = gwp,
-                gwp_min = gwp_min,
-                gwp_max = gwp_max,
-                adpe = adpe,
-                adpe_min = adpe_min,
-                adpe_max = adpe_max,
-                pe = pe,
-                pe_min = pe_min,
-                pe_max = pe_max
-                                ), impacts.usage, impacts.embodied   
-    
-
-def split_impacts_u_e(impacts: Impacts) -> QImpacts:
-    return impacts.usage, impacts.embodied
-
-
-def average_range_impacts(x):
-    if isinstance(x, float):
-        return x
-    else:
-        return (x.max + x.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,
-        )
+def format_gwp(gwp_value: float, gwp_unit = GWP(value=0.).unit) -> Quantity:
+    val = q(gwp_value, gwp_unit)
+    if val < q("1 kgCO2eq"):
+        val = val.to("gCO2eq")
+    if val < q("1 gCO2eq"):
+        val = val.to("mgCO2eq")
+    return val
+
+
+def format_adpe(adpe_value: float, adpe_unit = ADPe(value=0.).unit) -> Quantity:
+    val = q(adpe_value, adpe_unit)
+    if val < q("1 kgSbeq"):
+        val = val.to("gSbeq")
+    if val < q("1 gSbeq"):
+        val = val.to("mgSbeq")
+    if val < q("1 mgSbeq"):
+        val = val.to("µgSbeq")
+    return val
+
+
+def format_pe(pe_value: float, pe_unit = PE(value=0.).unit) -> Quantity:
+    val = q(pe_value, pe_unit)
+    if val < q("1 MJ"):
+        val = val.to("kJ")
+    return val
+
+
+def format_wcf(wcf_value: float, wcf_unit = WCF(value=0.).unit) -> Quantity:
+    val = q(wcf_value, wcf_unit)
+    if val < q("1 L"):
+        val = val.to("mL")
+    return val
+
+
+def format_impacts(impacts: Impacts) -> tuple[QImpacts, Usage, Embodied]:
+    if isinstance(impacts.energy.value, float):
+        return QImpacts(
+            energy=format_energy(impacts.energy.value),
+            gwp=format_gwp(impacts.gwp.value),
+            adpe=format_adpe(impacts.adpe.value),
+            pe=format_pe(impacts.pe.value),
+            wcf=format_wcf(impacts.wcf.value)
+        ), 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,
-        )
+        energy = format_energy(impacts.energy.value.mean)
+        gwp = format_gwp(impacts.gwp.value.mean)
+        adpe = format_adpe(impacts.adpe.value.mean)
+        pe = format_pe(impacts.pe.value.mean)
+        wcf = format_wcf(impacts.wcf.value.mean)
+
+        return QImpacts(
+            energy=energy,
+            energy_min=format_energy(impacts.energy.value.min).to(energy.units),
+            energy_max=format_energy(impacts.energy.value.max).to(energy.units),
+            gwp=gwp,
+            gwp_min=format_gwp(impacts.gwp.value.min).to(gwp.units),
+            gwp_max=format_gwp(impacts.gwp.value.max).to(gwp.units),
+            adpe=adpe,
+            adpe_min=format_adpe(impacts.adpe.value.min).to(adpe.units),
+            adpe_max=format_adpe(impacts.adpe.value.max).to(adpe.units),
+            pe=pe,
+            pe_min=format_pe(impacts.pe.value.min).to(pe.units),
+            pe_max=format_pe(impacts.pe.value.max).to(pe.units),
+            wcf=wcf,
+            wcf_min=format_wcf(impacts.wcf.value.min).to(wcf.units),
+            wcf_max=format_wcf(impacts.wcf.value.max).to(wcf.units),
+            ranges=True
+        ), impacts.usage, impacts.embodied
 
 
 #####################################################################################
@@ -280,7 +255,7 @@ def format_energy_eq_electricity_consumption_ireland(energy: Quantity) -> Quanti
 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 PARAMETER####################################################################################
+    return gwp_eq / AIRPLANE_PARIS_NYC_GWP_EQ
 
 #####################################################################################
 ### VISUALIZATIONS
@@ -339,4 +314,4 @@ def range_plot (mean_val, min_val, max_val, unit):
     )
 
     # Show the plot in Streamlit
-    st.plotly_chart(fig, use_container_width=True)    
+    st.plotly_chart(fig, use_container_width=True)

uv.lock

@@ -1,5 +1,5 @@
 version = 1
-revision = 2
+revision = 3
 requires-python = ">=3.11"
 resolution-markers = [
     "python_full_version >= '3.12'",
@@ -31,20 +31,6 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/78/b6/6307fbef88d9b5ee7421e68d78a9f162e0da4900bc5f5793f6d3d0e34fb8/annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53", size = 13643, upload-time = "2024-05-20T21:33:24.1Z" },
 ]
 
-[[package]]
-name = "anyio"
-version = "4.9.0"
-source = { registry = "https://pypi.org/simple" }
-dependencies = [
-    { name = "idna" },
-    { name = "sniffio" },
-    { name = "typing-extensions", marker = "python_full_version < '3.13'" },
-]
-sdist = { url = "https://files.pythonhosted.org/packages/95/7d/4c1bd541d4dffa1b52bd83fb8527089e097a106fc90b467a7313b105f840/anyio-4.9.0.tar.gz", hash = "sha256:673c0c244e15788651a4ff38710fea9675823028a6f08a5eda409e0c9840a028", size = 190949, upload-time = "2025-03-17T00:02:54.77Z" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/a1/ee/48ca1a7c89ffec8b6a0c5d02b89c305671d5ffd8d3c94acf8b8c408575bb/anyio-4.9.0-py3-none-any.whl", hash = "sha256:9f76d541cad6e36af7beb62e978876f3b41e3e04f2c1fbf0884604c0a9c4d93c", size = 100916, upload-time = "2025-03-17T00:02:52.713Z" },
-]
-
 [[package]]
 name = "attrs"
 version = "25.3.0"
@@ -152,20 +138,13 @@ wheels = [
 
 [[package]]
 name = "ecologits"
-version = "0.7.3"
-source = { registry = "https://pypi.org/simple" }
+version = "0.8.2"
+source = { git = "https://github.com/genai-impact/ecologits#81f70cf8b3e81490da226d0fa5bdaf8512e6446d" }
 dependencies = [
-    { name = "httpx" },
     { name = "packaging" },
     { name = "pydantic" },
-    { name = "requests" },
-    { name = "tqdm" },
     { name = "wrapt" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/a4/99/6c7855fecbf28f90a7add8db581b7da700709765d128842303c28133b0a1/ecologits-0.7.3.tar.gz", hash = "sha256:ec6294eb0d0e271effe5f913dd65150da040e438738d960098e783cb1894e277", size = 33335, upload-time = "2025-07-15T17:52:26.27Z" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/f5/b1/2459cc5385ff3cb7467cf10b7ec94b54685920563b7030280c665d190d40/ecologits-0.7.3-py3-none-any.whl", hash = "sha256:91c1b91800333dbfd710a4411278d6f71c9c8f0efa3942144f8eb7cb65f19e14", size = 42390, upload-time = "2025-07-15T17:52:24.954Z" },
-]
 
 [[package]]
 name = "ecologits-calculator"
@@ -179,15 +158,23 @@ dependencies = [
     { name = "tiktoken" },
 ]
 
+[package.dev-dependencies]
+dev = [
+    { name = "watchdog" },
+]
+
 [package.metadata]
 requires-dist = [
-    { name = "ecologits", specifier = ">=0.7.3,<0.8.0" },
+    { name = "ecologits", git = "https://github.com/genai-impact/ecologits" },
     { name = "pint", specifier = ">=0.24.4" },
     { name = "plotly", specifier = ">=6.2.0" },
     { name = "streamlit", specifier = ">=1.47.1" },
     { name = "tiktoken", specifier = ">=0.9.0" },
 ]
 
+[package.metadata.requires-dev]
+dev = [{ name = "watchdog", specifier = ">=6.0.0" }]
+
 [[package]]
 name = "flexcache"
 version = "0.3"
@@ -236,43 +223,6 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/01/61/d4b89fec821f72385526e1b9d9a3a0385dda4a72b206d28049e2c7cd39b8/gitpython-3.1.45-py3-none-any.whl", hash = "sha256:8908cb2e02fb3b93b7eb0f2827125cb699869470432cc885f019b8fd0fccff77", size = 208168, upload-time = "2025-07-24T03:45:52.517Z" },
 ]
 
-[[package]]
-name = "h11"
-version = "0.16.0"
-source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/01/ee/02a2c011bdab74c6fb3c75474d40b3052059d95df7e73351460c8588d963/h11-0.16.0.tar.gz", hash = "sha256:4e35b956cf45792e4caa5885e69fba00bdbc6ffafbfa020300e549b208ee5ff1", size = 101250, upload-time = "2025-04-24T03:35:25.427Z" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl", hash = "sha256:63cf8bbe7522de3bf65932fda1d9c2772064ffb3dae62d55932da54b31cb6c86", size = 37515, upload-time = "2025-04-24T03:35:24.344Z" },
-]
-
-[[package]]
-name = "httpcore"
-version = "1.0.9"
-source = { registry = "https://pypi.org/simple" }
-dependencies = [
-    { name = "certifi" },
-    { name = "h11" },
-]
-sdist = { url = "https://files.pythonhosted.org/packages/06/94/82699a10bca87a5556c9c59b5963f2d039dbd239f25bc2a63907a05a14cb/httpcore-1.0.9.tar.gz", hash = "sha256:6e34463af53fd2ab5d807f399a9b45ea31c3dfa2276f15a2c3f00afff6e176e8", size = 85484, upload-time = "2025-04-24T22:06:22.219Z" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl", hash = "sha256:2d400746a40668fc9dec9810239072b40b4484b640a8c38fd654a024c7a1bf55", size = 78784, upload-time = "2025-04-24T22:06:20.566Z" },
-]
-
-[[package]]
-name = "httpx"
-version = "0.28.1"
-source = { registry = "https://pypi.org/simple" }
-dependencies = [
-    { name = "anyio" },
-    { name = "certifi" },
-    { name = "httpcore" },
-    { name = "idna" },
-]
-sdist = { url = "https://files.pythonhosted.org/packages/b1/df/48c586a5fe32a0f01324ee087459e112ebb7224f646c0b5023f5e79e9956/httpx-0.28.1.tar.gz", hash = "sha256:75e98c5f16b0f35b567856f597f06ff2270a374470a5c2392242528e3e3e42fc", size = 141406, upload-time = "2024-12-06T15:37:23.222Z" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl", hash = "sha256:d909fcccc110f8c7faf814ca82a9a4d816bc5a6dbfea25d6591d6985b8ba59ad", size = 73517, upload-time = "2024-12-06T15:37:21.509Z" },
-]
-
 [[package]]
 name = "idna"
 version = "3.10"
@@ -682,7 +632,7 @@ wheels = [
 
 [[package]]
 name = "pydantic"
-version = "2.11.7"
+version = "2.12.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "annotated-types" },
@@ -690,74 +640,98 @@ dependencies = [
     { name = "typing-extensions" },
     { name = "typing-inspection" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/00/dd/4325abf92c39ba8623b5af936ddb36ffcfe0beae70405d456ab1fb2f5b8c/pydantic-2.11.7.tar.gz", hash = "sha256:d989c3c6cb79469287b1569f7447a17848c998458d49ebe294e975b9baf0f0db", size = 788350, upload-time = "2025-06-14T08:33:17.137Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/c3/da/b8a7ee04378a53f6fefefc0c5e05570a3ebfdfa0523a878bcd3b475683ee/pydantic-2.12.0.tar.gz", hash = "sha256:c1a077e6270dbfb37bfd8b498b3981e2bb18f68103720e51fa6c306a5a9af563", size = 814760, upload-time = "2025-10-07T15:58:03.467Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/6a/c0/ec2b1c8712ca690e5d61979dee872603e92b8a32f94cc1b72d53beab008a/pydantic-2.11.7-py3-none-any.whl", hash = "sha256:dde5df002701f6de26248661f6835bbe296a47bf73990135c7d07ce741b9623b", size = 444782, upload-time = "2025-06-14T08:33:14.905Z" },
+    { url = "https://files.pythonhosted.org/packages/f4/9d/d5c855424e2e5b6b626fbc6ec514d8e655a600377ce283008b115abb7445/pydantic-2.12.0-py3-none-any.whl", hash = "sha256:f6a1da352d42790537e95e83a8bdfb91c7efbae63ffd0b86fa823899e807116f", size = 459730, upload-time = "2025-10-07T15:58:01.576Z" },
 ]
 
 [[package]]
 name = "pydantic-core"
-version = "2.33.2"
+version = "2.41.1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "typing-extensions" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/ad/88/5f2260bdfae97aabf98f1778d43f69574390ad787afb646292a638c923d4/pydantic_core-2.33.2.tar.gz", hash = "sha256:7cb8bc3605c29176e1b105350d2e6474142d7c1bd1d9327c4a9bdb46bf827acc", size = 435195, upload-time = "2025-04-23T18:33:52.104Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/7d/14/12b4a0d2b0b10d8e1d9a24ad94e7bbb43335eaf29c0c4e57860e8a30734a/pydantic_core-2.41.1.tar.gz", hash = "sha256:1ad375859a6d8c356b7704ec0f547a58e82ee80bb41baa811ad710e124bc8f2f", size = 454870, upload-time = "2025-10-07T10:50:45.974Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/3f/8d/71db63483d518cbbf290261a1fc2839d17ff89fce7089e08cad07ccfce67/pydantic_core-2.33.2-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:4c5b0a576fb381edd6d27f0a85915c6daf2f8138dc5c267a57c08a62900758c7", size = 2028584, upload-time = "2025-04-23T18:31:03.106Z" },
-    { url = "https://files.pythonhosted.org/packages/24/2f/3cfa7244ae292dd850989f328722d2aef313f74ffc471184dc509e1e4e5a/pydantic_core-2.33.2-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:e799c050df38a639db758c617ec771fd8fb7a5f8eaaa4b27b101f266b216a246", size = 1855071, upload-time = "2025-04-23T18:31:04.621Z" },
-    { url = "https://files.pythonhosted.org/packages/b3/d3/4ae42d33f5e3f50dd467761304be2fa0a9417fbf09735bc2cce003480f2a/pydantic_core-2.33.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:dc46a01bf8d62f227d5ecee74178ffc448ff4e5197c756331f71efcc66dc980f", size = 1897823, upload-time = "2025-04-23T18:31:06.377Z" },
-    { url = "https://files.pythonhosted.org/packages/f4/f3/aa5976e8352b7695ff808599794b1fba2a9ae2ee954a3426855935799488/pydantic_core-2.33.2-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:a144d4f717285c6d9234a66778059f33a89096dfb9b39117663fd8413d582dcc", size = 1983792, upload-time = "2025-04-23T18:31:07.93Z" },
-    { url = "https://files.pythonhosted.org/packages/d5/7a/cda9b5a23c552037717f2b2a5257e9b2bfe45e687386df9591eff7b46d28/pydantic_core-2.33.2-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:73cf6373c21bc80b2e0dc88444f41ae60b2f070ed02095754eb5a01df12256de", size = 2136338, upload-time = "2025-04-23T18:31:09.283Z" },
-    { url = "https://files.pythonhosted.org/packages/2b/9f/b8f9ec8dd1417eb9da784e91e1667d58a2a4a7b7b34cf4af765ef663a7e5/pydantic_core-2.33.2-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3dc625f4aa79713512d1976fe9f0bc99f706a9dee21dfd1810b4bbbf228d0e8a", size = 2730998, upload-time = "2025-04-23T18:31:11.7Z" },
-    { url = "https://files.pythonhosted.org/packages/47/bc/cd720e078576bdb8255d5032c5d63ee5c0bf4b7173dd955185a1d658c456/pydantic_core-2.33.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:881b21b5549499972441da4758d662aeea93f1923f953e9cbaff14b8b9565aef", size = 2003200, upload-time = "2025-04-23T18:31:13.536Z" },
-    { url = "https://files.pythonhosted.org/packages/ca/22/3602b895ee2cd29d11a2b349372446ae9727c32e78a94b3d588a40fdf187/pydantic_core-2.33.2-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:bdc25f3681f7b78572699569514036afe3c243bc3059d3942624e936ec93450e", size = 2113890, upload-time = "2025-04-23T18:31:15.011Z" },
-    { url = "https://files.pythonhosted.org/packages/ff/e6/e3c5908c03cf00d629eb38393a98fccc38ee0ce8ecce32f69fc7d7b558a7/pydantic_core-2.33.2-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:fe5b32187cbc0c862ee201ad66c30cf218e5ed468ec8dc1cf49dec66e160cc4d", size = 2073359, upload-time = "2025-04-23T18:31:16.393Z" },
-    { url = "https://files.pythonhosted.org/packages/12/e7/6a36a07c59ebefc8777d1ffdaf5ae71b06b21952582e4b07eba88a421c79/pydantic_core-2.33.2-cp311-cp311-musllinux_1_1_armv7l.whl", hash = "sha256:bc7aee6f634a6f4a95676fcb5d6559a2c2a390330098dba5e5a5f28a2e4ada30", size = 2245883, upload-time = "2025-04-23T18:31:17.892Z" },
-    { url = "https://files.pythonhosted.org/packages/16/3f/59b3187aaa6cc0c1e6616e8045b284de2b6a87b027cce2ffcea073adf1d2/pydantic_core-2.33.2-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:235f45e5dbcccf6bd99f9f472858849f73d11120d76ea8707115415f8e5ebebf", size = 2241074, upload-time = "2025-04-23T18:31:19.205Z" },
-    { url = "https://files.pythonhosted.org/packages/e0/ed/55532bb88f674d5d8f67ab121a2a13c385df382de2a1677f30ad385f7438/pydantic_core-2.33.2-cp311-cp311-win32.whl", hash = "sha256:6368900c2d3ef09b69cb0b913f9f8263b03786e5b2a387706c5afb66800efd51", size = 1910538, upload-time = "2025-04-23T18:31:20.541Z" },
-    { url = "https://files.pythonhosted.org/packages/fe/1b/25b7cccd4519c0b23c2dd636ad39d381abf113085ce4f7bec2b0dc755eb1/pydantic_core-2.33.2-cp311-cp311-win_amd64.whl", hash = "sha256:1e063337ef9e9820c77acc768546325ebe04ee38b08703244c1309cccc4f1bab", size = 1952909, upload-time = "2025-04-23T18:31:22.371Z" },
-    { url = "https://files.pythonhosted.org/packages/49/a9/d809358e49126438055884c4366a1f6227f0f84f635a9014e2deb9b9de54/pydantic_core-2.33.2-cp311-cp311-win_arm64.whl", hash = "sha256:6b99022f1d19bc32a4c2a0d544fc9a76e3be90f0b3f4af413f87d38749300e65", size = 1897786, upload-time = "2025-04-23T18:31:24.161Z" },
-    { url = "https://files.pythonhosted.org/packages/18/8a/2b41c97f554ec8c71f2a8a5f85cb56a8b0956addfe8b0efb5b3d77e8bdc3/pydantic_core-2.33.2-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:a7ec89dc587667f22b6a0b6579c249fca9026ce7c333fc142ba42411fa243cdc", size = 2009000, upload-time = "2025-04-23T18:31:25.863Z" },
-    { url = "https://files.pythonhosted.org/packages/a1/02/6224312aacb3c8ecbaa959897af57181fb6cf3a3d7917fd44d0f2917e6f2/pydantic_core-2.33.2-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:3c6db6e52c6d70aa0d00d45cdb9b40f0433b96380071ea80b09277dba021ddf7", size = 1847996, upload-time = "2025-04-23T18:31:27.341Z" },
-    { url = "https://files.pythonhosted.org/packages/d6/46/6dcdf084a523dbe0a0be59d054734b86a981726f221f4562aed313dbcb49/pydantic_core-2.33.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4e61206137cbc65e6d5256e1166f88331d3b6238e082d9f74613b9b765fb9025", size = 1880957, upload-time = "2025-04-23T18:31:28.956Z" },
-    { url = "https://files.pythonhosted.org/packages/ec/6b/1ec2c03837ac00886ba8160ce041ce4e325b41d06a034adbef11339ae422/pydantic_core-2.33.2-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:eb8c529b2819c37140eb51b914153063d27ed88e3bdc31b71198a198e921e011", size = 1964199, upload-time = "2025-04-23T18:31:31.025Z" },
-    { url = "https://files.pythonhosted.org/packages/2d/1d/6bf34d6adb9debd9136bd197ca72642203ce9aaaa85cfcbfcf20f9696e83/pydantic_core-2.33.2-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:c52b02ad8b4e2cf14ca7b3d918f3eb0ee91e63b3167c32591e57c4317e134f8f", size = 2120296, upload-time = "2025-04-23T18:31:32.514Z" },
-    { url = "https://files.pythonhosted.org/packages/e0/94/2bd0aaf5a591e974b32a9f7123f16637776c304471a0ab33cf263cf5591a/pydantic_core-2.33.2-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:96081f1605125ba0855dfda83f6f3df5ec90c61195421ba72223de35ccfb2f88", size = 2676109, upload-time = "2025-04-23T18:31:33.958Z" },
-    { url = "https://files.pythonhosted.org/packages/f9/41/4b043778cf9c4285d59742281a769eac371b9e47e35f98ad321349cc5d61/pydantic_core-2.33.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8f57a69461af2a5fa6e6bbd7a5f60d3b7e6cebb687f55106933188e79ad155c1", size = 2002028, upload-time = "2025-04-23T18:31:39.095Z" },
-    { url = "https://files.pythonhosted.org/packages/cb/d5/7bb781bf2748ce3d03af04d5c969fa1308880e1dca35a9bd94e1a96a922e/pydantic_core-2.33.2-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:572c7e6c8bb4774d2ac88929e3d1f12bc45714ae5ee6d9a788a9fb35e60bb04b", size = 2100044, upload-time = "2025-04-23T18:31:41.034Z" },
-    { url = "https://files.pythonhosted.org/packages/fe/36/def5e53e1eb0ad896785702a5bbfd25eed546cdcf4087ad285021a90ed53/pydantic_core-2.33.2-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:db4b41f9bd95fbe5acd76d89920336ba96f03e149097365afe1cb092fceb89a1", size = 2058881, upload-time = "2025-04-23T18:31:42.757Z" },
-    { url = "https://files.pythonhosted.org/packages/01/6c/57f8d70b2ee57fc3dc8b9610315949837fa8c11d86927b9bb044f8705419/pydantic_core-2.33.2-cp312-cp312-musllinux_1_1_armv7l.whl", hash = "sha256:fa854f5cf7e33842a892e5c73f45327760bc7bc516339fda888c75ae60edaeb6", size = 2227034, upload-time = "2025-04-23T18:31:44.304Z" },
-    { url = "https://files.pythonhosted.org/packages/27/b9/9c17f0396a82b3d5cbea4c24d742083422639e7bb1d5bf600e12cb176a13/pydantic_core-2.33.2-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:5f483cfb75ff703095c59e365360cb73e00185e01aaea067cd19acffd2ab20ea", size = 2234187, upload-time = "2025-04-23T18:31:45.891Z" },
-    { url = "https://files.pythonhosted.org/packages/b0/6a/adf5734ffd52bf86d865093ad70b2ce543415e0e356f6cacabbc0d9ad910/pydantic_core-2.33.2-cp312-cp312-win32.whl", hash = "sha256:9cb1da0f5a471435a7bc7e439b8a728e8b61e59784b2af70d7c169f8dd8ae290", size = 1892628, upload-time = "2025-04-23T18:31:47.819Z" },
-    { url = "https://files.pythonhosted.org/packages/43/e4/5479fecb3606c1368d496a825d8411e126133c41224c1e7238be58b87d7e/pydantic_core-2.33.2-cp312-cp312-win_amd64.whl", hash = "sha256:f941635f2a3d96b2973e867144fde513665c87f13fe0e193c158ac51bfaaa7b2", size = 1955866, upload-time = "2025-04-23T18:31:49.635Z" },
-    { url = "https://files.pythonhosted.org/packages/0d/24/8b11e8b3e2be9dd82df4b11408a67c61bb4dc4f8e11b5b0fc888b38118b5/pydantic_core-2.33.2-cp312-cp312-win_arm64.whl", hash = "sha256:cca3868ddfaccfbc4bfb1d608e2ccaaebe0ae628e1416aeb9c4d88c001bb45ab", size = 1888894, upload-time = "2025-04-23T18:31:51.609Z" },
-    { url = "https://files.pythonhosted.org/packages/46/8c/99040727b41f56616573a28771b1bfa08a3d3fe74d3d513f01251f79f172/pydantic_core-2.33.2-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:1082dd3e2d7109ad8b7da48e1d4710c8d06c253cbc4a27c1cff4fbcaa97a9e3f", size = 2015688, upload-time = "2025-04-23T18:31:53.175Z" },
-    { url = "https://files.pythonhosted.org/packages/3a/cc/5999d1eb705a6cefc31f0b4a90e9f7fc400539b1a1030529700cc1b51838/pydantic_core-2.33.2-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:f517ca031dfc037a9c07e748cefd8d96235088b83b4f4ba8939105d20fa1dcd6", size = 1844808, upload-time = "2025-04-23T18:31:54.79Z" },
-    { url = "https://files.pythonhosted.org/packages/6f/5e/a0a7b8885c98889a18b6e376f344da1ef323d270b44edf8174d6bce4d622/pydantic_core-2.33.2-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0a9f2c9dd19656823cb8250b0724ee9c60a82f3cdf68a080979d13092a3b0fef", size = 1885580, upload-time = "2025-04-23T18:31:57.393Z" },
-    { url = "https://files.pythonhosted.org/packages/3b/2a/953581f343c7d11a304581156618c3f592435523dd9d79865903272c256a/pydantic_core-2.33.2-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:2b0a451c263b01acebe51895bfb0e1cc842a5c666efe06cdf13846c7418caa9a", size = 1973859, upload-time = "2025-04-23T18:31:59.065Z" },
-    { url = "https://files.pythonhosted.org/packages/e6/55/f1a813904771c03a3f97f676c62cca0c0a4138654107c1b61f19c644868b/pydantic_core-2.33.2-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1ea40a64d23faa25e62a70ad163571c0b342b8bf66d5fa612ac0dec4f069d916", size = 2120810, upload-time = "2025-04-23T18:32:00.78Z" },
-    { url = "https://files.pythonhosted.org/packages/aa/c3/053389835a996e18853ba107a63caae0b9deb4a276c6b472931ea9ae6e48/pydantic_core-2.33.2-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0fb2d542b4d66f9470e8065c5469ec676978d625a8b7a363f07d9a501a9cb36a", size = 2676498, upload-time = "2025-04-23T18:32:02.418Z" },
-    { url = "https://files.pythonhosted.org/packages/eb/3c/f4abd740877a35abade05e437245b192f9d0ffb48bbbbd708df33d3cda37/pydantic_core-2.33.2-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9fdac5d6ffa1b5a83bca06ffe7583f5576555e6c8b3a91fbd25ea7780f825f7d", size = 2000611, upload-time = "2025-04-23T18:32:04.152Z" },
-    { url = "https://files.pythonhosted.org/packages/59/a7/63ef2fed1837d1121a894d0ce88439fe3e3b3e48c7543b2a4479eb99c2bd/pydantic_core-2.33.2-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:04a1a413977ab517154eebb2d326da71638271477d6ad87a769102f7c2488c56", size = 2107924, upload-time = "2025-04-23T18:32:06.129Z" },
-    { url = "https://files.pythonhosted.org/packages/04/8f/2551964ef045669801675f1cfc3b0d74147f4901c3ffa42be2ddb1f0efc4/pydantic_core-2.33.2-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:c8e7af2f4e0194c22b5b37205bfb293d166a7344a5b0d0eaccebc376546d77d5", size = 2063196, upload-time = "2025-04-23T18:32:08.178Z" },
-    { url = "https://files.pythonhosted.org/packages/26/bd/d9602777e77fc6dbb0c7db9ad356e9a985825547dce5ad1d30ee04903918/pydantic_core-2.33.2-cp313-cp313-musllinux_1_1_armv7l.whl", hash = "sha256:5c92edd15cd58b3c2d34873597a1e20f13094f59cf88068adb18947df5455b4e", size = 2236389, upload-time = "2025-04-23T18:32:10.242Z" },
-    { url = "https://files.pythonhosted.org/packages/42/db/0e950daa7e2230423ab342ae918a794964b053bec24ba8af013fc7c94846/pydantic_core-2.33.2-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:65132b7b4a1c0beded5e057324b7e16e10910c106d43675d9bd87d4f38dde162", size = 2239223, upload-time = "2025-04-23T18:32:12.382Z" },
-    { url = "https://files.pythonhosted.org/packages/58/4d/4f937099c545a8a17eb52cb67fe0447fd9a373b348ccfa9a87f141eeb00f/pydantic_core-2.33.2-cp313-cp313-win32.whl", hash = "sha256:52fb90784e0a242bb96ec53f42196a17278855b0f31ac7c3cc6f5c1ec4811849", size = 1900473, upload-time = "2025-04-23T18:32:14.034Z" },
-    { url = "https://files.pythonhosted.org/packages/a0/75/4a0a9bac998d78d889def5e4ef2b065acba8cae8c93696906c3a91f310ca/pydantic_core-2.33.2-cp313-cp313-win_amd64.whl", hash = "sha256:c083a3bdd5a93dfe480f1125926afcdbf2917ae714bdb80b36d34318b2bec5d9", size = 1955269, upload-time = "2025-04-23T18:32:15.783Z" },
-    { url = "https://files.pythonhosted.org/packages/f9/86/1beda0576969592f1497b4ce8e7bc8cbdf614c352426271b1b10d5f0aa64/pydantic_core-2.33.2-cp313-cp313-win_arm64.whl", hash = "sha256:e80b087132752f6b3d714f041ccf74403799d3b23a72722ea2e6ba2e892555b9", size = 1893921, upload-time = "2025-04-23T18:32:18.473Z" },
-    { url = "https://files.pythonhosted.org/packages/a4/7d/e09391c2eebeab681df2b74bfe6c43422fffede8dc74187b2b0bf6fd7571/pydantic_core-2.33.2-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:61c18fba8e5e9db3ab908620af374db0ac1baa69f0f32df4f61ae23f15e586ac", size = 1806162, upload-time = "2025-04-23T18:32:20.188Z" },
-    { url = "https://files.pythonhosted.org/packages/f1/3d/847b6b1fed9f8ed3bb95a9ad04fbd0b212e832d4f0f50ff4d9ee5a9f15cf/pydantic_core-2.33.2-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:95237e53bb015f67b63c91af7518a62a8660376a6a0db19b89acc77a4d6199f5", size = 1981560, upload-time = "2025-04-23T18:32:22.354Z" },
-    { url = "https://files.pythonhosted.org/packages/6f/9a/e73262f6c6656262b5fdd723ad90f518f579b7bc8622e43a942eec53c938/pydantic_core-2.33.2-cp313-cp313t-win_amd64.whl", hash = "sha256:c2fc0a768ef76c15ab9238afa6da7f69895bb5d1ee83aeea2e3509af4472d0b9", size = 1935777, upload-time = "2025-04-23T18:32:25.088Z" },
-    { url = "https://files.pythonhosted.org/packages/7b/27/d4ae6487d73948d6f20dddcd94be4ea43e74349b56eba82e9bdee2d7494c/pydantic_core-2.33.2-pp311-pypy311_pp73-macosx_10_12_x86_64.whl", hash = "sha256:dd14041875d09cc0f9308e37a6f8b65f5585cf2598a53aa0123df8b129d481f8", size = 2025200, upload-time = "2025-04-23T18:33:14.199Z" },
-    { url = "https://files.pythonhosted.org/packages/f1/b8/b3cb95375f05d33801024079b9392a5ab45267a63400bf1866e7ce0f0de4/pydantic_core-2.33.2-pp311-pypy311_pp73-macosx_11_0_arm64.whl", hash = "sha256:d87c561733f66531dced0da6e864f44ebf89a8fba55f31407b00c2f7f9449593", size = 1859123, upload-time = "2025-04-23T18:33:16.555Z" },
-    { url = "https://files.pythonhosted.org/packages/05/bc/0d0b5adeda59a261cd30a1235a445bf55c7e46ae44aea28f7bd6ed46e091/pydantic_core-2.33.2-pp311-pypy311_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2f82865531efd18d6e07a04a17331af02cb7a651583c418df8266f17a63c6612", size = 1892852, upload-time = "2025-04-23T18:33:18.513Z" },
-    { url = "https://files.pythonhosted.org/packages/3e/11/d37bdebbda2e449cb3f519f6ce950927b56d62f0b84fd9cb9e372a26a3d5/pydantic_core-2.33.2-pp311-pypy311_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2bfb5112df54209d820d7bf9317c7a6c9025ea52e49f46b6a2060104bba37de7", size = 2067484, upload-time = "2025-04-23T18:33:20.475Z" },
-    { url = "https://files.pythonhosted.org/packages/8c/55/1f95f0a05ce72ecb02a8a8a1c3be0579bbc29b1d5ab68f1378b7bebc5057/pydantic_core-2.33.2-pp311-pypy311_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:64632ff9d614e5eecfb495796ad51b0ed98c453e447a76bcbeeb69615079fc7e", size = 2108896, upload-time = "2025-04-23T18:33:22.501Z" },
-    { url = "https://files.pythonhosted.org/packages/53/89/2b2de6c81fa131f423246a9109d7b2a375e83968ad0800d6e57d0574629b/pydantic_core-2.33.2-pp311-pypy311_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:f889f7a40498cc077332c7ab6b4608d296d852182211787d4f3ee377aaae66e8", size = 2069475, upload-time = "2025-04-23T18:33:24.528Z" },
-    { url = "https://files.pythonhosted.org/packages/b8/e9/1f7efbe20d0b2b10f6718944b5d8ece9152390904f29a78e68d4e7961159/pydantic_core-2.33.2-pp311-pypy311_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:de4b83bb311557e439b9e186f733f6c645b9417c84e2eb8203f3f820a4b988bf", size = 2239013, upload-time = "2025-04-23T18:33:26.621Z" },
-    { url = "https://files.pythonhosted.org/packages/3c/b2/5309c905a93811524a49b4e031e9851a6b00ff0fb668794472ea7746b448/pydantic_core-2.33.2-pp311-pypy311_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:82f68293f055f51b51ea42fafc74b6aad03e70e191799430b90c13d643059ebb", size = 2238715, upload-time = "2025-04-23T18:33:28.656Z" },
-    { url = "https://files.pythonhosted.org/packages/32/56/8a7ca5d2cd2cda1d245d34b1c9a942920a718082ae8e54e5f3e5a58b7add/pydantic_core-2.33.2-pp311-pypy311_pp73-win_amd64.whl", hash = "sha256:329467cecfb529c925cf2bbd4d60d2c509bc2fb52a20c1045bf09bb70971a9c1", size = 2066757, upload-time = "2025-04-23T18:33:30.645Z" },
+    { url = "https://files.pythonhosted.org/packages/f6/a9/ec440f02e57beabdfd804725ef1e38ac1ba00c49854d298447562e119513/pydantic_core-2.41.1-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:4f276a6134fe1fc1daa692642a3eaa2b7b858599c49a7610816388f5e37566a1", size = 2111456, upload-time = "2025-10-06T21:10:09.824Z" },
+    { url = "https://files.pythonhosted.org/packages/f0/f9/6bc15bacfd8dcfc073a1820a564516d9c12a435a9a332d4cbbfd48828ddd/pydantic_core-2.41.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:07588570a805296ece009c59d9a679dc08fab72fb337365afb4f3a14cfbfc176", size = 1915012, upload-time = "2025-10-06T21:10:11.599Z" },
+    { url = "https://files.pythonhosted.org/packages/38/8a/d9edcdcdfe80bade17bed424284427c08bea892aaec11438fa52eaeaf79c/pydantic_core-2.41.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:28527e4b53400cd60ffbd9812ccb2b5135d042129716d71afd7e45bf42b855c0", size = 1973762, upload-time = "2025-10-06T21:10:13.154Z" },
+    { url = "https://files.pythonhosted.org/packages/d5/b3/ff225c6d49fba4279de04677c1c876fc3dc6562fd0c53e9bfd66f58c51a8/pydantic_core-2.41.1-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:46a1c935c9228bad738c8a41de06478770927baedf581d172494ab36a6b96575", size = 2065386, upload-time = "2025-10-06T21:10:14.436Z" },
+    { url = "https://files.pythonhosted.org/packages/47/ba/183e8c0be4321314af3fd1ae6bfc7eafdd7a49bdea5da81c56044a207316/pydantic_core-2.41.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:447ddf56e2b7d28d200d3e9eafa936fe40485744b5a824b67039937580b3cb20", size = 2252317, upload-time = "2025-10-06T21:10:15.719Z" },
+    { url = "https://files.pythonhosted.org/packages/57/c5/aab61e94fd02f45c65f1f8c9ec38bb3b33fbf001a1837c74870e97462572/pydantic_core-2.41.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:63892ead40c1160ac860b5debcc95c95c5a0035e543a8b5a4eac70dd22e995f4", size = 2373405, upload-time = "2025-10-06T21:10:17.017Z" },
+    { url = "https://files.pythonhosted.org/packages/e5/4f/3aaa3bd1ea420a15acc42d7d3ccb3b0bbc5444ae2f9dbc1959f8173e16b8/pydantic_core-2.41.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f4a9543ca355e6df8fbe9c83e9faab707701e9103ae857ecb40f1c0cf8b0e94d", size = 2073794, upload-time = "2025-10-06T21:10:18.383Z" },
+    { url = "https://files.pythonhosted.org/packages/58/bd/e3975cdebe03ec080ef881648de316c73f2a6be95c14fc4efb2f7bdd0d41/pydantic_core-2.41.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:f2611bdb694116c31e551ed82e20e39a90bea9b7ad9e54aaf2d045ad621aa7a1", size = 2194430, upload-time = "2025-10-06T21:10:19.638Z" },
+    { url = "https://files.pythonhosted.org/packages/2b/b8/6b7e7217f147d3b3105b57fb1caec3c4f667581affdfaab6d1d277e1f749/pydantic_core-2.41.1-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:fecc130893a9b5f7bfe230be1bb8c61fe66a19db8ab704f808cb25a82aad0bc9", size = 2154611, upload-time = "2025-10-06T21:10:21.28Z" },
+    { url = "https://files.pythonhosted.org/packages/fe/7b/239c2fe76bd8b7eef9ae2140d737368a3c6fea4fd27f8f6b4cde6baa3ce9/pydantic_core-2.41.1-cp311-cp311-musllinux_1_1_armv7l.whl", hash = "sha256:1e2df5f8344c99b6ea5219f00fdc8950b8e6f2c422fbc1cc122ec8641fac85a1", size = 2329809, upload-time = "2025-10-06T21:10:22.678Z" },
+    { url = "https://files.pythonhosted.org/packages/bd/2e/77a821a67ff0786f2f14856d6bd1348992f695ee90136a145d7a445c1ff6/pydantic_core-2.41.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:35291331e9d8ed94c257bab6be1cb3a380b5eee570a2784bffc055e18040a2ea", size = 2327907, upload-time = "2025-10-06T21:10:24.447Z" },
+    { url = "https://files.pythonhosted.org/packages/fd/9a/b54512bb9df7f64c586b369328c30481229b70ca6a5fcbb90b715e15facf/pydantic_core-2.41.1-cp311-cp311-win32.whl", hash = "sha256:2876a095292668d753f1a868c4a57c4ac9f6acbd8edda8debe4218d5848cf42f", size = 1989964, upload-time = "2025-10-06T21:10:25.676Z" },
+    { url = "https://files.pythonhosted.org/packages/9d/72/63c9a4f1a5c950e65dd522d7dd67f167681f9d4f6ece3b80085a0329f08f/pydantic_core-2.41.1-cp311-cp311-win_amd64.whl", hash = "sha256:b92d6c628e9a338846a28dfe3fcdc1a3279388624597898b105e078cdfc59298", size = 2025158, upload-time = "2025-10-06T21:10:27.522Z" },
+    { url = "https://files.pythonhosted.org/packages/d8/16/4e2706184209f61b50c231529257c12eb6bd9eb36e99ea1272e4815d2200/pydantic_core-2.41.1-cp311-cp311-win_arm64.whl", hash = "sha256:7d82ae99409eb69d507a89835488fb657faa03ff9968a9379567b0d2e2e56bc5", size = 1972297, upload-time = "2025-10-06T21:10:28.814Z" },
+    { url = "https://files.pythonhosted.org/packages/ee/bc/5f520319ee1c9e25010412fac4154a72e0a40d0a19eb00281b1f200c0947/pydantic_core-2.41.1-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:db2f82c0ccbce8f021ad304ce35cbe02aa2f95f215cac388eed542b03b4d5eb4", size = 2099300, upload-time = "2025-10-06T21:10:30.463Z" },
+    { url = "https://files.pythonhosted.org/packages/31/14/010cd64c5c3814fb6064786837ec12604be0dd46df3327cf8474e38abbbd/pydantic_core-2.41.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:47694a31c710ced9205d5f1e7e8af3ca57cbb8a503d98cb9e33e27c97a501601", size = 1910179, upload-time = "2025-10-06T21:10:31.782Z" },
+    { url = "https://files.pythonhosted.org/packages/8e/2e/23fc2a8a93efad52df302fdade0a60f471ecc0c7aac889801ac24b4c07d6/pydantic_core-2.41.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:93e9decce94daf47baf9e9d392f5f2557e783085f7c5e522011545d9d6858e00", size = 1957225, upload-time = "2025-10-06T21:10:33.11Z" },
+    { url = "https://files.pythonhosted.org/packages/b9/b6/6db08b2725b2432b9390844852e11d320281e5cea8a859c52c68001975fa/pydantic_core-2.41.1-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ab0adafdf2b89c8b84f847780a119437a0931eca469f7b44d356f2b426dd9741", size = 2053315, upload-time = "2025-10-06T21:10:34.87Z" },
+    { url = "https://files.pythonhosted.org/packages/61/d9/4de44600f2d4514b44f3f3aeeda2e14931214b6b5bf52479339e801ce748/pydantic_core-2.41.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:5da98cc81873f39fd56882e1569c4677940fbc12bce6213fad1ead784192d7c8", size = 2224298, upload-time = "2025-10-06T21:10:36.233Z" },
+    { url = "https://files.pythonhosted.org/packages/7a/ae/dbe51187a7f35fc21b283c5250571a94e36373eb557c1cba9f29a9806dcf/pydantic_core-2.41.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:209910e88afb01fd0fd403947b809ba8dba0e08a095e1f703294fda0a8fdca51", size = 2351797, upload-time = "2025-10-06T21:10:37.601Z" },
+    { url = "https://files.pythonhosted.org/packages/b5/a7/975585147457c2e9fb951c7c8dab56deeb6aa313f3aa72c2fc0df3f74a49/pydantic_core-2.41.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:365109d1165d78d98e33c5bfd815a9b5d7d070f578caefaabcc5771825b4ecb5", size = 2074921, upload-time = "2025-10-06T21:10:38.927Z" },
+    { url = "https://files.pythonhosted.org/packages/62/37/ea94d1d0c01dec1b7d236c7cec9103baab0021f42500975de3d42522104b/pydantic_core-2.41.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:706abf21e60a2857acdb09502bc853ee5bce732955e7b723b10311114f033115", size = 2187767, upload-time = "2025-10-06T21:10:40.651Z" },
+    { url = "https://files.pythonhosted.org/packages/d3/fe/694cf9fdd3a777a618c3afd210dba7b414cb8a72b1bd29b199c2e5765fee/pydantic_core-2.41.1-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:bf0bd5417acf7f6a7ec3b53f2109f587be176cb35f9cf016da87e6017437a72d", size = 2136062, upload-time = "2025-10-06T21:10:42.09Z" },
+    { url = "https://files.pythonhosted.org/packages/0f/ae/174aeabd89916fbd2988cc37b81a59e1186e952afd2a7ed92018c22f31ca/pydantic_core-2.41.1-cp312-cp312-musllinux_1_1_armv7l.whl", hash = "sha256:2e71b1c6ceb9c78424ae9f63a07292fb769fb890a4e7efca5554c47f33a60ea5", size = 2317819, upload-time = "2025-10-06T21:10:43.974Z" },
+    { url = "https://files.pythonhosted.org/packages/65/e8/e9aecafaebf53fc456314f72886068725d6fba66f11b013532dc21259343/pydantic_core-2.41.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:80745b9770b4a38c25015b517451c817799bfb9d6499b0d13d8227ec941cb513", size = 2312267, upload-time = "2025-10-06T21:10:45.34Z" },
+    { url = "https://files.pythonhosted.org/packages/35/2f/1c2e71d2a052f9bb2f2df5a6a05464a0eb800f9e8d9dd800202fe31219e1/pydantic_core-2.41.1-cp312-cp312-win32.whl", hash = "sha256:83b64d70520e7890453f1aa21d66fda44e7b35f1cfea95adf7b4289a51e2b479", size = 1990927, upload-time = "2025-10-06T21:10:46.738Z" },
+    { url = "https://files.pythonhosted.org/packages/b1/78/562998301ff2588b9c6dcc5cb21f52fa919d6e1decc75a35055feb973594/pydantic_core-2.41.1-cp312-cp312-win_amd64.whl", hash = "sha256:377defd66ee2003748ee93c52bcef2d14fde48fe28a0b156f88c3dbf9bc49a50", size = 2034703, upload-time = "2025-10-06T21:10:48.524Z" },
+    { url = "https://files.pythonhosted.org/packages/b2/53/d95699ce5a5cdb44bb470bd818b848b9beadf51459fd4ea06667e8ede862/pydantic_core-2.41.1-cp312-cp312-win_arm64.whl", hash = "sha256:c95caff279d49c1d6cdfe2996e6c2ad712571d3b9caaa209a404426c326c4bde", size = 1972719, upload-time = "2025-10-06T21:10:50.256Z" },
+    { url = "https://files.pythonhosted.org/packages/27/8a/6d54198536a90a37807d31a156642aae7a8e1263ed9fe6fc6245defe9332/pydantic_core-2.41.1-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:70e790fce5f05204ef4403159857bfcd587779da78627b0babb3654f75361ebf", size = 2105825, upload-time = "2025-10-06T21:10:51.719Z" },
+    { url = "https://files.pythonhosted.org/packages/4f/2e/4784fd7b22ac9c8439db25bf98ffed6853d01e7e560a346e8af821776ccc/pydantic_core-2.41.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:9cebf1ca35f10930612d60bd0f78adfacee824c30a880e3534ba02c207cceceb", size = 1910126, upload-time = "2025-10-06T21:10:53.145Z" },
+    { url = "https://files.pythonhosted.org/packages/f3/92/31eb0748059ba5bd0aa708fb4bab9fcb211461ddcf9e90702a6542f22d0d/pydantic_core-2.41.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:170406a37a5bc82c22c3274616bf6f17cc7df9c4a0a0a50449e559cb755db669", size = 1961472, upload-time = "2025-10-06T21:10:55.754Z" },
+    { url = "https://files.pythonhosted.org/packages/ab/91/946527792275b5c4c7dde4cfa3e81241bf6900e9fee74fb1ba43e0c0f1ab/pydantic_core-2.41.1-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:12d4257fc9187a0ccd41b8b327d6a4e57281ab75e11dda66a9148ef2e1fb712f", size = 2063230, upload-time = "2025-10-06T21:10:57.179Z" },
+    { url = "https://files.pythonhosted.org/packages/31/5d/a35c5d7b414e5c0749f1d9f0d159ee2ef4bab313f499692896b918014ee3/pydantic_core-2.41.1-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a75a33b4db105dd1c8d57839e17ee12db8d5ad18209e792fa325dbb4baeb00f4", size = 2229469, upload-time = "2025-10-06T21:10:59.409Z" },
+    { url = "https://files.pythonhosted.org/packages/21/4d/8713737c689afa57ecfefe38db78259d4484c97aa494979e6a9d19662584/pydantic_core-2.41.1-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:08a589f850803a74e0fcb16a72081cafb0d72a3cdda500106942b07e76b7bf62", size = 2347986, upload-time = "2025-10-06T21:11:00.847Z" },
+    { url = "https://files.pythonhosted.org/packages/f6/ec/929f9a3a5ed5cda767081494bacd32f783e707a690ce6eeb5e0730ec4986/pydantic_core-2.41.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7a97939d6ea44763c456bd8a617ceada2c9b96bb5b8ab3dfa0d0827df7619014", size = 2072216, upload-time = "2025-10-06T21:11:02.43Z" },
+    { url = "https://files.pythonhosted.org/packages/26/55/a33f459d4f9cc8786d9db42795dbecc84fa724b290d7d71ddc3d7155d46a/pydantic_core-2.41.1-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:d2ae423c65c556f09569524b80ffd11babff61f33055ef9773d7c9fabc11ed8d", size = 2193047, upload-time = "2025-10-06T21:11:03.787Z" },
+    { url = "https://files.pythonhosted.org/packages/77/af/d5c6959f8b089f2185760a2779079e3c2c411bfc70ea6111f58367851629/pydantic_core-2.41.1-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:4dc703015fbf8764d6a8001c327a87f1823b7328d40b47ce6000c65918ad2b4f", size = 2140613, upload-time = "2025-10-06T21:11:05.607Z" },
+    { url = "https://files.pythonhosted.org/packages/58/e5/2c19bd2a14bffe7fabcf00efbfbd3ac430aaec5271b504a938ff019ac7be/pydantic_core-2.41.1-cp313-cp313-musllinux_1_1_armv7l.whl", hash = "sha256:968e4ffdfd35698a5fe659e5e44c508b53664870a8e61c8f9d24d3d145d30257", size = 2327641, upload-time = "2025-10-06T21:11:07.143Z" },
+    { url = "https://files.pythonhosted.org/packages/93/ef/e0870ccda798c54e6b100aff3c4d49df5458fd64217e860cb9c3b0a403f4/pydantic_core-2.41.1-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:fff2b76c8e172d34771cd4d4f0ade08072385310f214f823b5a6ad4006890d32", size = 2318229, upload-time = "2025-10-06T21:11:08.73Z" },
+    { url = "https://files.pythonhosted.org/packages/b1/4b/c3b991d95f5deb24d0bd52e47bcf716098fa1afe0ce2d4bd3125b38566ba/pydantic_core-2.41.1-cp313-cp313-win32.whl", hash = "sha256:a38a5263185407ceb599f2f035faf4589d57e73c7146d64f10577f6449e8171d", size = 1997911, upload-time = "2025-10-06T21:11:10.329Z" },
+    { url = "https://files.pythonhosted.org/packages/a7/ce/5c316fd62e01f8d6be1b7ee6b54273214e871772997dc2c95e204997a055/pydantic_core-2.41.1-cp313-cp313-win_amd64.whl", hash = "sha256:b42ae7fd6760782c975897e1fdc810f483b021b32245b0105d40f6e7a3803e4b", size = 2034301, upload-time = "2025-10-06T21:11:12.113Z" },
+    { url = "https://files.pythonhosted.org/packages/29/41/902640cfd6a6523194123e2c3373c60f19006447f2fb06f76de4e8466c5b/pydantic_core-2.41.1-cp313-cp313-win_arm64.whl", hash = "sha256:ad4111acc63b7384e205c27a2f15e23ac0ee21a9d77ad6f2e9cb516ec90965fb", size = 1977238, upload-time = "2025-10-06T21:11:14.1Z" },
+    { url = "https://files.pythonhosted.org/packages/04/04/28b040e88c1b89d851278478842f0bdf39c7a05da9e850333c6c8cbe7dfa/pydantic_core-2.41.1-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:440d0df7415b50084a4ba9d870480c16c5f67c0d1d4d5119e3f70925533a0edc", size = 1875626, upload-time = "2025-10-06T21:11:15.69Z" },
+    { url = "https://files.pythonhosted.org/packages/d6/58/b41dd3087505220bb58bc81be8c3e8cbc037f5710cd3c838f44f90bdd704/pydantic_core-2.41.1-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:71eaa38d342099405dae6484216dcf1e8e4b0bebd9b44a4e08c9b43db6a2ab67", size = 2045708, upload-time = "2025-10-06T21:11:17.258Z" },
+    { url = "https://files.pythonhosted.org/packages/d7/b8/760f23754e40bf6c65b94a69b22c394c24058a0ef7e2aa471d2e39219c1a/pydantic_core-2.41.1-cp313-cp313t-win_amd64.whl", hash = "sha256:555ecf7e50f1161d3f693bc49f23c82cf6cdeafc71fa37a06120772a09a38795", size = 1997171, upload-time = "2025-10-06T21:11:18.822Z" },
+    { url = "https://files.pythonhosted.org/packages/41/12/cec246429ddfa2778d2d6301eca5362194dc8749ecb19e621f2f65b5090f/pydantic_core-2.41.1-cp314-cp314-macosx_10_12_x86_64.whl", hash = "sha256:05226894a26f6f27e1deb735d7308f74ef5fa3a6de3e0135bb66cdcaee88f64b", size = 2107836, upload-time = "2025-10-06T21:11:20.432Z" },
+    { url = "https://files.pythonhosted.org/packages/20/39/baba47f8d8b87081302498e610aefc37142ce6a1cc98b2ab6b931a162562/pydantic_core-2.41.1-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:85ff7911c6c3e2fd8d3779c50925f6406d770ea58ea6dde9c230d35b52b16b4a", size = 1904449, upload-time = "2025-10-06T21:11:22.185Z" },
+    { url = "https://files.pythonhosted.org/packages/50/32/9a3d87cae2c75a5178334b10358d631bd094b916a00a5993382222dbfd92/pydantic_core-2.41.1-cp314-cp314-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:47f1f642a205687d59b52dc1a9a607f45e588f5a2e9eeae05edd80c7a8c47674", size = 1961750, upload-time = "2025-10-06T21:11:24.348Z" },
+    { url = "https://files.pythonhosted.org/packages/27/42/a96c9d793a04cf2a9773bff98003bb154087b94f5530a2ce6063ecfec583/pydantic_core-2.41.1-cp314-cp314-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:df11c24e138876ace5ec6043e5cae925e34cf38af1a1b3d63589e8f7b5f5cdc4", size = 2063305, upload-time = "2025-10-06T21:11:26.556Z" },
+    { url = "https://files.pythonhosted.org/packages/3e/8d/028c4b7d157a005b1f52c086e2d4b0067886b213c86220c1153398dbdf8f/pydantic_core-2.41.1-cp314-cp314-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:7f0bf7f5c8f7bf345c527e8a0d72d6b26eda99c1227b0c34e7e59e181260de31", size = 2228959, upload-time = "2025-10-06T21:11:28.426Z" },
+    { url = "https://files.pythonhosted.org/packages/08/f7/ee64cda8fcc9ca3f4716e6357144f9ee71166775df582a1b6b738bf6da57/pydantic_core-2.41.1-cp314-cp314-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:82b887a711d341c2c47352375d73b029418f55b20bd7815446d175a70effa706", size = 2345421, upload-time = "2025-10-06T21:11:30.226Z" },
+    { url = "https://files.pythonhosted.org/packages/13/c0/e8ec05f0f5ee7a3656973ad9cd3bc73204af99f6512c1a4562f6fb4b3f7d/pydantic_core-2.41.1-cp314-cp314-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b5f1d5d6bbba484bdf220c72d8ecd0be460f4bd4c5e534a541bb2cd57589fb8b", size = 2065288, upload-time = "2025-10-06T21:11:32.019Z" },
+    { url = "https://files.pythonhosted.org/packages/0a/25/d77a73ff24e2e4fcea64472f5e39b0402d836da9b08b5361a734d0153023/pydantic_core-2.41.1-cp314-cp314-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:2bf1917385ebe0f968dc5c6ab1375886d56992b93ddfe6bf52bff575d03662be", size = 2189759, upload-time = "2025-10-06T21:11:33.753Z" },
+    { url = "https://files.pythonhosted.org/packages/66/45/4a4ebaaae12a740552278d06fe71418c0f2869537a369a89c0e6723b341d/pydantic_core-2.41.1-cp314-cp314-musllinux_1_1_aarch64.whl", hash = "sha256:4f94f3ab188f44b9a73f7295663f3ecb8f2e2dd03a69c8f2ead50d37785ecb04", size = 2140747, upload-time = "2025-10-06T21:11:35.781Z" },
+    { url = "https://files.pythonhosted.org/packages/da/6d/b727ce1022f143194a36593243ff244ed5a1eb3c9122296bf7e716aa37ba/pydantic_core-2.41.1-cp314-cp314-musllinux_1_1_armv7l.whl", hash = "sha256:3925446673641d37c30bd84a9d597e49f72eacee8b43322c8999fa17d5ae5bc4", size = 2327416, upload-time = "2025-10-06T21:11:37.75Z" },
+    { url = "https://files.pythonhosted.org/packages/6f/8c/02df9d8506c427787059f87c6c7253435c6895e12472a652d9616ee0fc95/pydantic_core-2.41.1-cp314-cp314-musllinux_1_1_x86_64.whl", hash = "sha256:49bd51cc27adb980c7b97357ae036ce9b3c4d0bb406e84fbe16fb2d368b602a8", size = 2318138, upload-time = "2025-10-06T21:11:39.463Z" },
+    { url = "https://files.pythonhosted.org/packages/98/67/0cf429a7d6802536941f430e6e3243f6d4b68f41eeea4b242372f1901794/pydantic_core-2.41.1-cp314-cp314-win32.whl", hash = "sha256:a31ca0cd0e4d12ea0df0077df2d487fc3eb9d7f96bbb13c3c5b88dcc21d05159", size = 1998429, upload-time = "2025-10-06T21:11:41.989Z" },
+    { url = "https://files.pythonhosted.org/packages/38/60/742fef93de5d085022d2302a6317a2b34dbfe15258e9396a535c8a100ae7/pydantic_core-2.41.1-cp314-cp314-win_amd64.whl", hash = "sha256:1b5c4374a152e10a22175d7790e644fbd8ff58418890e07e2073ff9d4414efae", size = 2028870, upload-time = "2025-10-06T21:11:43.66Z" },
+    { url = "https://files.pythonhosted.org/packages/31/38/cdd8ccb8555ef7720bd7715899bd6cfbe3c29198332710e1b61b8f5dd8b8/pydantic_core-2.41.1-cp314-cp314-win_arm64.whl", hash = "sha256:4fee76d757639b493eb600fba668f1e17475af34c17dd61db7a47e824d464ca9", size = 1974275, upload-time = "2025-10-06T21:11:45.476Z" },
+    { url = "https://files.pythonhosted.org/packages/e7/7e/8ac10ccb047dc0221aa2530ec3c7c05ab4656d4d4bd984ee85da7f3d5525/pydantic_core-2.41.1-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:f9b9c968cfe5cd576fdd7361f47f27adeb120517e637d1b189eea1c3ece573f4", size = 1875124, upload-time = "2025-10-06T21:11:47.591Z" },
+    { url = "https://files.pythonhosted.org/packages/c3/e4/7d9791efeb9c7d97e7268f8d20e0da24d03438a7fa7163ab58f1073ba968/pydantic_core-2.41.1-cp314-cp314t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f1ebc7ab67b856384aba09ed74e3e977dded40e693de18a4f197c67d0d4e6d8e", size = 2043075, upload-time = "2025-10-06T21:11:49.542Z" },
+    { url = "https://files.pythonhosted.org/packages/2d/c3/3f6e6b2342ac11ac8cd5cb56e24c7b14afa27c010e82a765ffa5f771884a/pydantic_core-2.41.1-cp314-cp314t-win_amd64.whl", hash = "sha256:8ae0dc57b62a762985bc7fbf636be3412394acc0ddb4ade07fe104230f1b9762", size = 1995341, upload-time = "2025-10-06T21:11:51.497Z" },
+    { url = "https://files.pythonhosted.org/packages/16/89/d0afad37ba25f5801735af1472e650b86baad9fe807a42076508e4824a2a/pydantic_core-2.41.1-graalpy311-graalpy242_311_native-macosx_10_12_x86_64.whl", hash = "sha256:68f2251559b8efa99041bb63571ec7cdd2d715ba74cc82b3bc9eff824ebc8bf0", size = 2124001, upload-time = "2025-10-07T10:49:54.369Z" },
+    { url = "https://files.pythonhosted.org/packages/8e/c4/08609134b34520568ddebb084d9ed0a2a3f5f52b45739e6e22cb3a7112eb/pydantic_core-2.41.1-graalpy311-graalpy242_311_native-macosx_11_0_arm64.whl", hash = "sha256:c7bc140c596097cb53b30546ca257dbe3f19282283190b1b5142928e5d5d3a20", size = 1941841, upload-time = "2025-10-07T10:49:56.248Z" },
+    { url = "https://files.pythonhosted.org/packages/2a/43/94a4877094e5fe19a3f37e7e817772263e2c573c94f1e3fa2b1eee56ef3b/pydantic_core-2.41.1-graalpy311-graalpy242_311_native-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2896510fce8f4725ec518f8b9d7f015a00db249d2fd40788f442af303480063d", size = 1961129, upload-time = "2025-10-07T10:49:58.298Z" },
+    { url = "https://files.pythonhosted.org/packages/a2/30/23a224d7e25260eb5f69783a63667453037e07eb91ff0e62dabaadd47128/pydantic_core-2.41.1-graalpy311-graalpy242_311_native-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ced20e62cfa0f496ba68fa5d6c7ee71114ea67e2a5da3114d6450d7f4683572a", size = 2148770, upload-time = "2025-10-07T10:49:59.959Z" },
+    { url = "https://files.pythonhosted.org/packages/2b/3e/a51c5f5d37b9288ba30683d6e96f10fa8f1defad1623ff09f1020973b577/pydantic_core-2.41.1-graalpy312-graalpy250_312_native-macosx_10_12_x86_64.whl", hash = "sha256:b04fa9ed049461a7398138c604b00550bc89e3e1151d84b81ad6dc93e39c4c06", size = 2115344, upload-time = "2025-10-07T10:50:02.466Z" },
+    { url = "https://files.pythonhosted.org/packages/5a/bd/389504c9e0600ef4502cd5238396b527afe6ef8981a6a15cd1814fc7b434/pydantic_core-2.41.1-graalpy312-graalpy250_312_native-macosx_11_0_arm64.whl", hash = "sha256:b3b7d9cfbfdc43c80a16638c6dc2768e3956e73031fca64e8e1a3ae744d1faeb", size = 1927994, upload-time = "2025-10-07T10:50:04.379Z" },
+    { url = "https://files.pythonhosted.org/packages/ff/9c/5111c6b128861cb792a4c082677e90dac4f2e090bb2e2fe06aa5b2d39027/pydantic_core-2.41.1-graalpy312-graalpy250_312_native-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:eec83fc6abef04c7f9bec616e2d76ee9a6a4ae2a359b10c21d0f680e24a247ca", size = 1959394, upload-time = "2025-10-07T10:50:06.335Z" },
+    { url = "https://files.pythonhosted.org/packages/14/3f/cfec8b9a0c48ce5d64409ec5e1903cb0b7363da38f14b41de2fcb3712700/pydantic_core-2.41.1-graalpy312-graalpy250_312_native-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6771a2d9f83c4038dfad5970a3eef215940682b2175e32bcc817bdc639019b28", size = 2147365, upload-time = "2025-10-07T10:50:07.978Z" },
+    { url = "https://files.pythonhosted.org/packages/e6/6c/fa3e45c2b054a1e627a89a364917f12cbe3abc3e91b9004edaae16e7b3c5/pydantic_core-2.41.1-pp311-pypy311_pp73-macosx_10_12_x86_64.whl", hash = "sha256:af2385d3f98243fb733862f806c5bb9122e5fba05b373e3af40e3c82d711cef1", size = 2112094, upload-time = "2025-10-07T10:50:25.513Z" },
+    { url = "https://files.pythonhosted.org/packages/e5/17/7eebc38b4658cc8e6902d0befc26388e4c2a5f2e179c561eeb43e1922c7b/pydantic_core-2.41.1-pp311-pypy311_pp73-macosx_11_0_arm64.whl", hash = "sha256:6550617a0c2115be56f90c31a5370261d8ce9dbf051c3ed53b51172dd34da696", size = 1935300, upload-time = "2025-10-07T10:50:27.715Z" },
+    { url = "https://files.pythonhosted.org/packages/2b/00/9fe640194a1717a464ab861d43595c268830f98cb1e2705aa134b3544b70/pydantic_core-2.41.1-pp311-pypy311_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:dc17b6ecf4983d298686014c92ebc955a9f9baf9f57dad4065e7906e7bee6222", size = 1970417, upload-time = "2025-10-07T10:50:29.573Z" },
+    { url = "https://files.pythonhosted.org/packages/b2/ad/f4cdfaf483b78ee65362363e73b6b40c48e067078d7b146e8816d5945ad6/pydantic_core-2.41.1-pp311-pypy311_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:42ae9352cf211f08b04ea110563d6b1e415878eea5b4c70f6bdb17dca3b932d2", size = 2190745, upload-time = "2025-10-07T10:50:31.48Z" },
+    { url = "https://files.pythonhosted.org/packages/cb/c1/18f416d40a10f44e9387497ba449f40fdb1478c61ba05c4b6bdb82300362/pydantic_core-2.41.1-pp311-pypy311_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:e82947de92068b0a21681a13dd2102387197092fbe7defcfb8453e0913866506", size = 2150888, upload-time = "2025-10-07T10:50:33.477Z" },
+    { url = "https://files.pythonhosted.org/packages/42/30/134c8a921630d8a88d6f905a562495a6421e959a23c19b0f49b660801d67/pydantic_core-2.41.1-pp311-pypy311_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:e244c37d5471c9acdcd282890c6c4c83747b77238bfa19429b8473586c907656", size = 2324489, upload-time = "2025-10-07T10:50:36.48Z" },
+    { url = "https://files.pythonhosted.org/packages/9c/48/a9263aeaebdec81e941198525b43edb3b44f27cfa4cb8005b8d3eb8dec72/pydantic_core-2.41.1-pp311-pypy311_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:1e798b4b304a995110d41ec93653e57975620ccb2842ba9420037985e7d7284e", size = 2322763, upload-time = "2025-10-07T10:50:38.751Z" },
+    { url = "https://files.pythonhosted.org/packages/1d/62/755d2bd2593f701c5839fc084e9c2c5e2418f460383ad04e3b5d0befc3ca/pydantic_core-2.41.1-pp311-pypy311_pp73-win_amd64.whl", hash = "sha256:f1fc716c0eb1663c59699b024428ad5ec2bcc6b928527b8fe28de6cb89f47efb", size = 2144046, upload-time = "2025-10-07T10:50:40.686Z" },
 ]
 
 [[package]]
@@ -1006,15 +980,6 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/04/be/d09147ad1ec7934636ad912901c5fd7667e1c858e19d355237db0d0cd5e4/smmap-5.0.2-py3-none-any.whl", hash = "sha256:b30115f0def7d7531d22a0fb6502488d879e75b260a9db4d0819cfb25403af5e", size = 24303, upload-time = "2025-01-02T07:14:38.724Z" },
 ]
 
-[[package]]
-name = "sniffio"
-version = "1.3.1"
-source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/a2/87/a6771e1546d97e7e041b6ae58d80074f81b7d5121207425c964ddf5cfdbd/sniffio-1.3.1.tar.gz", hash = "sha256:f4324edc670a0f49750a81b895f35c3adb843cca46f0530f79fc1babb23789dc", size = 20372, upload-time = "2024-02-25T23:20:04.057Z" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/e9/44/75a9c9421471a6c4805dbf2356f7c181a29c1879239abab1ea2cc8f38b40/sniffio-1.3.1-py3-none-any.whl", hash = "sha256:2f6da418d1f1e0fddd844478f41680e794e6051915791a034ff65e5f100525a2", size = 10235, upload-time = "2024-02-25T23:20:01.196Z" },
-]
-
 [[package]]
 name = "streamlit"
 version = "1.47.1"
@@ -1111,18 +1076,6 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/55/a7/535c44c7bea4578e48281d83c615219f3ab19e6abc67625ef637c73987be/tornado-6.5.1-cp39-abi3-win_arm64.whl", hash = "sha256:02420a0eb7bf617257b9935e2b754d1b63897525d8a289c9d65690d580b4dcf7", size = 443596, upload-time = "2025-05-22T18:15:37.433Z" },
 ]
 
-[[package]]
-name = "tqdm"
-version = "4.67.1"
-source = { registry = "https://pypi.org/simple" }
-dependencies = [
-    { name = "colorama", marker = "sys_platform == 'win32'" },
-]
-sdist = { url = "https://files.pythonhosted.org/packages/a8/4b/29b4ef32e036bb34e4ab51796dd745cdba7ed47ad142a9f4a1eb8e0c744d/tqdm-4.67.1.tar.gz", hash = "sha256:f8aef9c52c08c13a65f30ea34f4e5aac3fd1a34959879d7e59e63027286627f2", size = 169737, upload-time = "2024-11-24T20:12:22.481Z" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/d0/30/dc54f88dd4a2b5dc8a0279bdd7270e735851848b762aeb1c1184ed1f6b14/tqdm-4.67.1-py3-none-any.whl", hash = "sha256:26445eca388f82e72884e0d580d5464cd801a3ea01e63e5601bdff9ba6a48de2", size = 78540, upload-time = "2024-11-24T20:12:19.698Z" },
-]
-
 [[package]]
 name = "typing-extensions"
 version = "4.14.1"
@@ -1134,14 +1087,14 @@ wheels = [
 
 [[package]]
 name = "typing-inspection"
-version = "0.4.1"
+version = "0.4.2"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "typing-extensions" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/f8/b1/0c11f5058406b3af7609f121aaa6b609744687f1d158b3c3a5bf4cc94238/typing_inspection-0.4.1.tar.gz", hash = "sha256:6ae134cc0203c33377d43188d4064e9b357dba58cff3185f22924610e70a9d28", size = 75726, upload-time = "2025-05-21T18:55:23.885Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/55/e3/70399cb7dd41c10ac53367ae42139cf4b1ca5f36bb3dc6c9d33acdb43655/typing_inspection-0.4.2.tar.gz", hash = "sha256:ba561c48a67c5958007083d386c3295464928b01faa735ab8547c5692e87f464", size = 75949, upload-time = "2025-10-01T02:14:41.687Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/17/69/cd203477f944c353c31bade965f880aa1061fd6bf05ded0726ca845b6ff7/typing_inspection-0.4.1-py3-none-any.whl", hash = "sha256:389055682238f53b04f7badcb49b989835495a96700ced5dab2d8feae4b26f51", size = 14552, upload-time = "2025-05-21T18:55:22.152Z" },
+    { url = "https://files.pythonhosted.org/packages/dc/9b/47798a6c91d8bdb567fe2698fe81e0c6b7cb7ef4d13da4114b41d239f65d/typing_inspection-0.4.2-py3-none-any.whl", hash = "sha256:4ed1cacbdc298c220f1bd249ed5287caa16f34d44ef4e9c3d0cbad5b521545e7", size = 14611, upload-time = "2025-10-01T02:14:40.154Z" },
 ]
 
 [[package]]
@@ -1168,6 +1121,15 @@ version = "6.0.0"
 source = { registry = "https://pypi.org/simple" }
 sdist = { url = "https://files.pythonhosted.org/packages/db/7d/7f3d619e951c88ed75c6037b246ddcf2d322812ee8ea189be89511721d54/watchdog-6.0.0.tar.gz", hash = "sha256:9ddf7c82fda3ae8e24decda1338ede66e1c99883db93711d8fb941eaa2d8c282", size = 131220, upload-time = "2024-11-01T14:07:13.037Z" }
 wheels = [
+    { url = "https://files.pythonhosted.org/packages/e0/24/d9be5cd6642a6aa68352ded4b4b10fb0d7889cb7f45814fb92cecd35f101/watchdog-6.0.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:6eb11feb5a0d452ee41f824e271ca311a09e250441c262ca2fd7ebcf2461a06c", size = 96393, upload-time = "2024-11-01T14:06:31.756Z" },
+    { url = "https://files.pythonhosted.org/packages/63/7a/6013b0d8dbc56adca7fdd4f0beed381c59f6752341b12fa0886fa7afc78b/watchdog-6.0.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:ef810fbf7b781a5a593894e4f439773830bdecb885e6880d957d5b9382a960d2", size = 88392, upload-time = "2024-11-01T14:06:32.99Z" },
+    { url = "https://files.pythonhosted.org/packages/d1/40/b75381494851556de56281e053700e46bff5b37bf4c7267e858640af5a7f/watchdog-6.0.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:afd0fe1b2270917c5e23c2a65ce50c2a4abb63daafb0d419fde368e272a76b7c", size = 89019, upload-time = "2024-11-01T14:06:34.963Z" },
+    { url = "https://files.pythonhosted.org/packages/39/ea/3930d07dafc9e286ed356a679aa02d777c06e9bfd1164fa7c19c288a5483/watchdog-6.0.0-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:bdd4e6f14b8b18c334febb9c4425a878a2ac20efd1e0b231978e7b150f92a948", size = 96471, upload-time = "2024-11-01T14:06:37.745Z" },
+    { url = "https://files.pythonhosted.org/packages/12/87/48361531f70b1f87928b045df868a9fd4e253d9ae087fa4cf3f7113be363/watchdog-6.0.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:c7c15dda13c4eb00d6fb6fc508b3c0ed88b9d5d374056b239c4ad1611125c860", size = 88449, upload-time = "2024-11-01T14:06:39.748Z" },
+    { url = "https://files.pythonhosted.org/packages/5b/7e/8f322f5e600812e6f9a31b75d242631068ca8f4ef0582dd3ae6e72daecc8/watchdog-6.0.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:6f10cb2d5902447c7d0da897e2c6768bca89174d0c6e1e30abec5421af97a5b0", size = 89054, upload-time = "2024-11-01T14:06:41.009Z" },
+    { url = "https://files.pythonhosted.org/packages/68/98/b0345cabdce2041a01293ba483333582891a3bd5769b08eceb0d406056ef/watchdog-6.0.0-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:490ab2ef84f11129844c23fb14ecf30ef3d8a6abafd3754a6f75ca1e6654136c", size = 96480, upload-time = "2024-11-01T14:06:42.952Z" },
+    { url = "https://files.pythonhosted.org/packages/85/83/cdf13902c626b28eedef7ec4f10745c52aad8a8fe7eb04ed7b1f111ca20e/watchdog-6.0.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:76aae96b00ae814b181bb25b1b98076d5fc84e8a53cd8885a318b42b6d3a5134", size = 88451, upload-time = "2024-11-01T14:06:45.084Z" },
+    { url = "https://files.pythonhosted.org/packages/fe/c4/225c87bae08c8b9ec99030cd48ae9c4eca050a59bf5c2255853e18c87b50/watchdog-6.0.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:a175f755fc2279e0b7312c0035d52e27211a5bc39719dd529625b1930917345b", size = 89057, upload-time = "2024-11-01T14:06:47.324Z" },
     { url = "https://files.pythonhosted.org/packages/a9/c7/ca4bf3e518cb57a686b2feb4f55a1892fd9a3dd13f470fca14e00f80ea36/watchdog-6.0.0-py3-none-manylinux2014_aarch64.whl", hash = "sha256:7607498efa04a3542ae3e05e64da8202e58159aa1fa4acddf7678d34a35d4f13", size = 79079, upload-time = "2024-11-01T14:06:59.472Z" },
     { url = "https://files.pythonhosted.org/packages/5c/51/d46dc9332f9a647593c947b4b88e2381c8dfc0942d15b8edc0310fa4abb1/watchdog-6.0.0-py3-none-manylinux2014_armv7l.whl", hash = "sha256:9041567ee8953024c83343288ccc458fd0a2d811d6a0fd68c4c22609e3490379", size = 79078, upload-time = "2024-11-01T14:07:01.431Z" },
     { url = "https://files.pythonhosted.org/packages/d4/57/04edbf5e169cd318d5f07b4766fee38e825d64b6913ca157ca32d1a42267/watchdog-6.0.0-py3-none-manylinux2014_i686.whl", hash = "sha256:82dc3e3143c7e38ec49d61af98d6558288c415eac98486a5c581726e0737c00e", size = 79076, upload-time = "2024-11-01T14:07:02.568Z" },
@@ -1182,53 +1144,59 @@ wheels = [
 
 [[package]]
 name = "wrapt"
-version = "1.17.2"
+version = "1.17.3"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/c3/fc/e91cc220803d7bc4db93fb02facd8461c37364151b8494762cc88b0fbcef/wrapt-1.17.2.tar.gz", hash = "sha256:41388e9d4d1522446fe79d3213196bd9e3b301a336965b9e27ca2788ebd122f3", size = 55531, upload-time = "2025-01-14T10:35:45.465Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/95/8f/aeb76c5b46e273670962298c23e7ddde79916cb74db802131d49a85e4b7d/wrapt-1.17.3.tar.gz", hash = "sha256:f66eb08feaa410fe4eebd17f2a2c8e2e46d3476e9f8c783daa8e09e0faa666d0", size = 55547, upload-time = "2025-08-12T05:53:21.714Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/cd/f7/a2aab2cbc7a665efab072344a8949a71081eed1d2f451f7f7d2b966594a2/wrapt-1.17.2-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:ff04ef6eec3eee8a5efef2401495967a916feaa353643defcc03fc74fe213b58", size = 53308, upload-time = "2025-01-14T10:33:33.992Z" },
-    { url = "https://files.pythonhosted.org/packages/50/ff/149aba8365fdacef52b31a258c4dc1c57c79759c335eff0b3316a2664a64/wrapt-1.17.2-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:4db983e7bca53819efdbd64590ee96c9213894272c776966ca6306b73e4affda", size = 38488, upload-time = "2025-01-14T10:33:35.264Z" },
-    { url = "https://files.pythonhosted.org/packages/65/46/5a917ce85b5c3b490d35c02bf71aedaa9f2f63f2d15d9949cc4ba56e8ba9/wrapt-1.17.2-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:9abc77a4ce4c6f2a3168ff34b1da9b0f311a8f1cfd694ec96b0603dff1c79438", size = 38776, upload-time = "2025-01-14T10:33:38.28Z" },
-    { url = "https://files.pythonhosted.org/packages/ca/74/336c918d2915a4943501c77566db41d1bd6e9f4dbc317f356b9a244dfe83/wrapt-1.17.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0b929ac182f5ace000d459c59c2c9c33047e20e935f8e39371fa6e3b85d56f4a", size = 83776, upload-time = "2025-01-14T10:33:40.678Z" },
-    { url = "https://files.pythonhosted.org/packages/09/99/c0c844a5ccde0fe5761d4305485297f91d67cf2a1a824c5f282e661ec7ff/wrapt-1.17.2-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f09b286faeff3c750a879d336fb6d8713206fc97af3adc14def0cdd349df6000", size = 75420, upload-time = "2025-01-14T10:33:41.868Z" },
-    { url = "https://files.pythonhosted.org/packages/b4/b0/9fc566b0fe08b282c850063591a756057c3247b2362b9286429ec5bf1721/wrapt-1.17.2-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1a7ed2d9d039bd41e889f6fb9364554052ca21ce823580f6a07c4ec245c1f5d6", size = 83199, upload-time = "2025-01-14T10:33:43.598Z" },
-    { url = "https://files.pythonhosted.org/packages/9d/4b/71996e62d543b0a0bd95dda485219856def3347e3e9380cc0d6cf10cfb2f/wrapt-1.17.2-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:129a150f5c445165ff941fc02ee27df65940fcb8a22a61828b1853c98763a64b", size = 82307, upload-time = "2025-01-14T10:33:48.499Z" },
-    { url = "https://files.pythonhosted.org/packages/39/35/0282c0d8789c0dc9bcc738911776c762a701f95cfe113fb8f0b40e45c2b9/wrapt-1.17.2-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:1fb5699e4464afe5c7e65fa51d4f99e0b2eadcc176e4aa33600a3df7801d6662", size = 75025, upload-time = "2025-01-14T10:33:51.191Z" },
-    { url = "https://files.pythonhosted.org/packages/4f/6d/90c9fd2c3c6fee181feecb620d95105370198b6b98a0770cba090441a828/wrapt-1.17.2-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:9a2bce789a5ea90e51a02dfcc39e31b7f1e662bc3317979aa7e5538e3a034f72", size = 81879, upload-time = "2025-01-14T10:33:52.328Z" },
-    { url = "https://files.pythonhosted.org/packages/8f/fa/9fb6e594f2ce03ef03eddbdb5f4f90acb1452221a5351116c7c4708ac865/wrapt-1.17.2-cp311-cp311-win32.whl", hash = "sha256:4afd5814270fdf6380616b321fd31435a462019d834f83c8611a0ce7484c7317", size = 36419, upload-time = "2025-01-14T10:33:53.551Z" },
-    { url = "https://files.pythonhosted.org/packages/47/f8/fb1773491a253cbc123c5d5dc15c86041f746ed30416535f2a8df1f4a392/wrapt-1.17.2-cp311-cp311-win_amd64.whl", hash = "sha256:acc130bc0375999da18e3d19e5a86403667ac0c4042a094fefb7eec8ebac7cf3", size = 38773, upload-time = "2025-01-14T10:33:56.323Z" },
-    { url = "https://files.pythonhosted.org/packages/a1/bd/ab55f849fd1f9a58ed7ea47f5559ff09741b25f00c191231f9f059c83949/wrapt-1.17.2-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:d5e2439eecc762cd85e7bd37161d4714aa03a33c5ba884e26c81559817ca0925", size = 53799, upload-time = "2025-01-14T10:33:57.4Z" },
-    { url = "https://files.pythonhosted.org/packages/53/18/75ddc64c3f63988f5a1d7e10fb204ffe5762bc663f8023f18ecaf31a332e/wrapt-1.17.2-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:3fc7cb4c1c744f8c05cd5f9438a3caa6ab94ce8344e952d7c45a8ed59dd88392", size = 38821, upload-time = "2025-01-14T10:33:59.334Z" },
-    { url = "https://files.pythonhosted.org/packages/48/2a/97928387d6ed1c1ebbfd4efc4133a0633546bec8481a2dd5ec961313a1c7/wrapt-1.17.2-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:8fdbdb757d5390f7c675e558fd3186d590973244fab0c5fe63d373ade3e99d40", size = 38919, upload-time = "2025-01-14T10:34:04.093Z" },
-    { url = "https://files.pythonhosted.org/packages/73/54/3bfe5a1febbbccb7a2f77de47b989c0b85ed3a6a41614b104204a788c20e/wrapt-1.17.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5bb1d0dbf99411f3d871deb6faa9aabb9d4e744d67dcaaa05399af89d847a91d", size = 88721, upload-time = "2025-01-14T10:34:07.163Z" },
-    { url = "https://files.pythonhosted.org/packages/25/cb/7262bc1b0300b4b64af50c2720ef958c2c1917525238d661c3e9a2b71b7b/wrapt-1.17.2-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:d18a4865f46b8579d44e4fe1e2bcbc6472ad83d98e22a26c963d46e4c125ef0b", size = 80899, upload-time = "2025-01-14T10:34:09.82Z" },
-    { url = "https://files.pythonhosted.org/packages/2a/5a/04cde32b07a7431d4ed0553a76fdb7a61270e78c5fd5a603e190ac389f14/wrapt-1.17.2-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bc570b5f14a79734437cb7b0500376b6b791153314986074486e0b0fa8d71d98", size = 89222, upload-time = "2025-01-14T10:34:11.258Z" },
-    { url = "https://files.pythonhosted.org/packages/09/28/2e45a4f4771fcfb109e244d5dbe54259e970362a311b67a965555ba65026/wrapt-1.17.2-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:6d9187b01bebc3875bac9b087948a2bccefe464a7d8f627cf6e48b1bbae30f82", size = 86707, upload-time = "2025-01-14T10:34:12.49Z" },
-    { url = "https://files.pythonhosted.org/packages/c6/d2/dcb56bf5f32fcd4bd9aacc77b50a539abdd5b6536872413fd3f428b21bed/wrapt-1.17.2-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:9e8659775f1adf02eb1e6f109751268e493c73716ca5761f8acb695e52a756ae", size = 79685, upload-time = "2025-01-14T10:34:15.043Z" },
-    { url = "https://files.pythonhosted.org/packages/80/4e/eb8b353e36711347893f502ce91c770b0b0929f8f0bed2670a6856e667a9/wrapt-1.17.2-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:e8b2816ebef96d83657b56306152a93909a83f23994f4b30ad4573b00bd11bb9", size = 87567, upload-time = "2025-01-14T10:34:16.563Z" },
-    { url = "https://files.pythonhosted.org/packages/17/27/4fe749a54e7fae6e7146f1c7d914d28ef599dacd4416566c055564080fe2/wrapt-1.17.2-cp312-cp312-win32.whl", hash = "sha256:468090021f391fe0056ad3e807e3d9034e0fd01adcd3bdfba977b6fdf4213ea9", size = 36672, upload-time = "2025-01-14T10:34:17.727Z" },
-    { url = "https://files.pythonhosted.org/packages/15/06/1dbf478ea45c03e78a6a8c4be4fdc3c3bddea5c8de8a93bc971415e47f0f/wrapt-1.17.2-cp312-cp312-win_amd64.whl", hash = "sha256:ec89ed91f2fa8e3f52ae53cd3cf640d6feff92ba90d62236a81e4e563ac0e991", size = 38865, upload-time = "2025-01-14T10:34:19.577Z" },
-    { url = "https://files.pythonhosted.org/packages/ce/b9/0ffd557a92f3b11d4c5d5e0c5e4ad057bd9eb8586615cdaf901409920b14/wrapt-1.17.2-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:6ed6ffac43aecfe6d86ec5b74b06a5be33d5bb9243d055141e8cabb12aa08125", size = 53800, upload-time = "2025-01-14T10:34:21.571Z" },
-    { url = "https://files.pythonhosted.org/packages/c0/ef/8be90a0b7e73c32e550c73cfb2fa09db62234227ece47b0e80a05073b375/wrapt-1.17.2-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:35621ae4c00e056adb0009f8e86e28eb4a41a4bfa8f9bfa9fca7d343fe94f998", size = 38824, upload-time = "2025-01-14T10:34:22.999Z" },
-    { url = "https://files.pythonhosted.org/packages/36/89/0aae34c10fe524cce30fe5fc433210376bce94cf74d05b0d68344c8ba46e/wrapt-1.17.2-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:a604bf7a053f8362d27eb9fefd2097f82600b856d5abe996d623babd067b1ab5", size = 38920, upload-time = "2025-01-14T10:34:25.386Z" },
-    { url = "https://files.pythonhosted.org/packages/3b/24/11c4510de906d77e0cfb5197f1b1445d4fec42c9a39ea853d482698ac681/wrapt-1.17.2-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5cbabee4f083b6b4cd282f5b817a867cf0b1028c54d445b7ec7cfe6505057cf8", size = 88690, upload-time = "2025-01-14T10:34:28.058Z" },
-    { url = "https://files.pythonhosted.org/packages/71/d7/cfcf842291267bf455b3e266c0c29dcb675b5540ee8b50ba1699abf3af45/wrapt-1.17.2-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:49703ce2ddc220df165bd2962f8e03b84c89fee2d65e1c24a7defff6f988f4d6", size = 80861, upload-time = "2025-01-14T10:34:29.167Z" },
-    { url = "https://files.pythonhosted.org/packages/d5/66/5d973e9f3e7370fd686fb47a9af3319418ed925c27d72ce16b791231576d/wrapt-1.17.2-cp313-cp313-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8112e52c5822fc4253f3901b676c55ddf288614dc7011634e2719718eaa187dc", size = 89174, upload-time = "2025-01-14T10:34:31.702Z" },
-    { url = "https://files.pythonhosted.org/packages/a7/d3/8e17bb70f6ae25dabc1aaf990f86824e4fd98ee9cadf197054e068500d27/wrapt-1.17.2-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:9fee687dce376205d9a494e9c121e27183b2a3df18037f89d69bd7b35bcf59e2", size = 86721, upload-time = "2025-01-14T10:34:32.91Z" },
-    { url = "https://files.pythonhosted.org/packages/6f/54/f170dfb278fe1c30d0ff864513cff526d624ab8de3254b20abb9cffedc24/wrapt-1.17.2-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:18983c537e04d11cf027fbb60a1e8dfd5190e2b60cc27bc0808e653e7b218d1b", size = 79763, upload-time = "2025-01-14T10:34:34.903Z" },
-    { url = "https://files.pythonhosted.org/packages/4a/98/de07243751f1c4a9b15c76019250210dd3486ce098c3d80d5f729cba029c/wrapt-1.17.2-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:703919b1633412ab54bcf920ab388735832fdcb9f9a00ae49387f0fe67dad504", size = 87585, upload-time = "2025-01-14T10:34:36.13Z" },
-    { url = "https://files.pythonhosted.org/packages/f9/f0/13925f4bd6548013038cdeb11ee2cbd4e37c30f8bfd5db9e5a2a370d6e20/wrapt-1.17.2-cp313-cp313-win32.whl", hash = "sha256:abbb9e76177c35d4e8568e58650aa6926040d6a9f6f03435b7a522bf1c487f9a", size = 36676, upload-time = "2025-01-14T10:34:37.962Z" },
-    { url = "https://files.pythonhosted.org/packages/bf/ae/743f16ef8c2e3628df3ddfd652b7d4c555d12c84b53f3d8218498f4ade9b/wrapt-1.17.2-cp313-cp313-win_amd64.whl", hash = "sha256:69606d7bb691b50a4240ce6b22ebb319c1cfb164e5f6569835058196e0f3a845", size = 38871, upload-time = "2025-01-14T10:34:39.13Z" },
-    { url = "https://files.pythonhosted.org/packages/3d/bc/30f903f891a82d402ffb5fda27ec1d621cc97cb74c16fea0b6141f1d4e87/wrapt-1.17.2-cp313-cp313t-macosx_10_13_universal2.whl", hash = "sha256:4a721d3c943dae44f8e243b380cb645a709ba5bd35d3ad27bc2ed947e9c68192", size = 56312, upload-time = "2025-01-14T10:34:40.604Z" },
-    { url = "https://files.pythonhosted.org/packages/8a/04/c97273eb491b5f1c918857cd26f314b74fc9b29224521f5b83f872253725/wrapt-1.17.2-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:766d8bbefcb9e00c3ac3b000d9acc51f1b399513f44d77dfe0eb026ad7c9a19b", size = 40062, upload-time = "2025-01-14T10:34:45.011Z" },
-    { url = "https://files.pythonhosted.org/packages/4e/ca/3b7afa1eae3a9e7fefe499db9b96813f41828b9fdb016ee836c4c379dadb/wrapt-1.17.2-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:e496a8ce2c256da1eb98bd15803a79bee00fc351f5dfb9ea82594a3f058309e0", size = 40155, upload-time = "2025-01-14T10:34:47.25Z" },
-    { url = "https://files.pythonhosted.org/packages/89/be/7c1baed43290775cb9030c774bc53c860db140397047cc49aedaf0a15477/wrapt-1.17.2-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:40d615e4fe22f4ad3528448c193b218e077656ca9ccb22ce2cb20db730f8d306", size = 113471, upload-time = "2025-01-14T10:34:50.934Z" },
-    { url = "https://files.pythonhosted.org/packages/32/98/4ed894cf012b6d6aae5f5cc974006bdeb92f0241775addad3f8cd6ab71c8/wrapt-1.17.2-cp313-cp313t-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:a5aaeff38654462bc4b09023918b7f21790efb807f54c000a39d41d69cf552cb", size = 101208, upload-time = "2025-01-14T10:34:52.297Z" },
-    { url = "https://files.pythonhosted.org/packages/ea/fd/0c30f2301ca94e655e5e057012e83284ce8c545df7661a78d8bfca2fac7a/wrapt-1.17.2-cp313-cp313t-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9a7d15bbd2bc99e92e39f49a04653062ee6085c0e18b3b7512a4f2fe91f2d681", size = 109339, upload-time = "2025-01-14T10:34:53.489Z" },
-    { url = "https://files.pythonhosted.org/packages/75/56/05d000de894c4cfcb84bcd6b1df6214297b8089a7bd324c21a4765e49b14/wrapt-1.17.2-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:e3890b508a23299083e065f435a492b5435eba6e304a7114d2f919d400888cc6", size = 110232, upload-time = "2025-01-14T10:34:55.327Z" },
-    { url = "https://files.pythonhosted.org/packages/53/f8/c3f6b2cf9b9277fb0813418e1503e68414cd036b3b099c823379c9575e6d/wrapt-1.17.2-cp313-cp313t-musllinux_1_2_i686.whl", hash = "sha256:8c8b293cd65ad716d13d8dd3624e42e5a19cc2a2f1acc74b30c2c13f15cb61a6", size = 100476, upload-time = "2025-01-14T10:34:58.055Z" },
-    { url = "https://files.pythonhosted.org/packages/a7/b1/0bb11e29aa5139d90b770ebbfa167267b1fc548d2302c30c8f7572851738/wrapt-1.17.2-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:4c82b8785d98cdd9fed4cac84d765d234ed3251bd6afe34cb7ac523cb93e8b4f", size = 106377, upload-time = "2025-01-14T10:34:59.3Z" },
-    { url = "https://files.pythonhosted.org/packages/6a/e1/0122853035b40b3f333bbb25f1939fc1045e21dd518f7f0922b60c156f7c/wrapt-1.17.2-cp313-cp313t-win32.whl", hash = "sha256:13e6afb7fe71fe7485a4550a8844cc9ffbe263c0f1a1eea569bc7091d4898555", size = 37986, upload-time = "2025-01-14T10:35:00.498Z" },
-    { url = "https://files.pythonhosted.org/packages/09/5e/1655cf481e079c1f22d0cabdd4e51733679932718dc23bf2db175f329b76/wrapt-1.17.2-cp313-cp313t-win_amd64.whl", hash = "sha256:eaf675418ed6b3b31c7a989fd007fa7c3be66ce14e5c3b27336383604c9da85c", size = 40750, upload-time = "2025-01-14T10:35:03.378Z" },
-    { url = "https://files.pythonhosted.org/packages/2d/82/f56956041adef78f849db6b289b282e72b55ab8045a75abad81898c28d19/wrapt-1.17.2-py3-none-any.whl", hash = "sha256:b18f2d1533a71f069c7f82d524a52599053d4c7166e9dd374ae2136b7f40f7c8", size = 23594, upload-time = "2025-01-14T10:35:44.018Z" },
+    { url = "https://files.pythonhosted.org/packages/52/db/00e2a219213856074a213503fdac0511203dceefff26e1daa15250cc01a0/wrapt-1.17.3-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:273a736c4645e63ac582c60a56b0acb529ef07f78e08dc6bfadf6a46b19c0da7", size = 53482, upload-time = "2025-08-12T05:51:45.79Z" },
+    { url = "https://files.pythonhosted.org/packages/5e/30/ca3c4a5eba478408572096fe9ce36e6e915994dd26a4e9e98b4f729c06d9/wrapt-1.17.3-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:5531d911795e3f935a9c23eb1c8c03c211661a5060aab167065896bbf62a5f85", size = 38674, upload-time = "2025-08-12T05:51:34.629Z" },
+    { url = "https://files.pythonhosted.org/packages/31/25/3e8cc2c46b5329c5957cec959cb76a10718e1a513309c31399a4dad07eb3/wrapt-1.17.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:0610b46293c59a3adbae3dee552b648b984176f8562ee0dba099a56cfbe4df1f", size = 38959, upload-time = "2025-08-12T05:51:56.074Z" },
+    { url = "https://files.pythonhosted.org/packages/5d/8f/a32a99fc03e4b37e31b57cb9cefc65050ea08147a8ce12f288616b05ef54/wrapt-1.17.3-cp311-cp311-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:b32888aad8b6e68f83a8fdccbf3165f5469702a7544472bdf41f582970ed3311", size = 82376, upload-time = "2025-08-12T05:52:32.134Z" },
+    { url = "https://files.pythonhosted.org/packages/31/57/4930cb8d9d70d59c27ee1332a318c20291749b4fba31f113c2f8ac49a72e/wrapt-1.17.3-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:8cccf4f81371f257440c88faed6b74f1053eef90807b77e31ca057b2db74edb1", size = 83604, upload-time = "2025-08-12T05:52:11.663Z" },
+    { url = "https://files.pythonhosted.org/packages/a8/f3/1afd48de81d63dd66e01b263a6fbb86e1b5053b419b9b33d13e1f6d0f7d0/wrapt-1.17.3-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:d8a210b158a34164de8bb68b0e7780041a903d7b00c87e906fb69928bf7890d5", size = 82782, upload-time = "2025-08-12T05:52:12.626Z" },
+    { url = "https://files.pythonhosted.org/packages/1e/d7/4ad5327612173b144998232f98a85bb24b60c352afb73bc48e3e0d2bdc4e/wrapt-1.17.3-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:79573c24a46ce11aab457b472efd8d125e5a51da2d1d24387666cd85f54c05b2", size = 82076, upload-time = "2025-08-12T05:52:33.168Z" },
+    { url = "https://files.pythonhosted.org/packages/bb/59/e0adfc831674a65694f18ea6dc821f9fcb9ec82c2ce7e3d73a88ba2e8718/wrapt-1.17.3-cp311-cp311-win32.whl", hash = "sha256:c31eebe420a9a5d2887b13000b043ff6ca27c452a9a22fa71f35f118e8d4bf89", size = 36457, upload-time = "2025-08-12T05:53:03.936Z" },
+    { url = "https://files.pythonhosted.org/packages/83/88/16b7231ba49861b6f75fc309b11012ede4d6b0a9c90969d9e0db8d991aeb/wrapt-1.17.3-cp311-cp311-win_amd64.whl", hash = "sha256:0b1831115c97f0663cb77aa27d381237e73ad4f721391a9bfb2fe8bc25fa6e77", size = 38745, upload-time = "2025-08-12T05:53:02.885Z" },
+    { url = "https://files.pythonhosted.org/packages/9a/1e/c4d4f3398ec073012c51d1c8d87f715f56765444e1a4b11e5180577b7e6e/wrapt-1.17.3-cp311-cp311-win_arm64.whl", hash = "sha256:5a7b3c1ee8265eb4c8f1b7d29943f195c00673f5ab60c192eba2d4a7eae5f46a", size = 36806, upload-time = "2025-08-12T05:52:53.368Z" },
+    { url = "https://files.pythonhosted.org/packages/9f/41/cad1aba93e752f1f9268c77270da3c469883d56e2798e7df6240dcb2287b/wrapt-1.17.3-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:ab232e7fdb44cdfbf55fc3afa31bcdb0d8980b9b95c38b6405df2acb672af0e0", size = 53998, upload-time = "2025-08-12T05:51:47.138Z" },
+    { url = "https://files.pythonhosted.org/packages/60/f8/096a7cc13097a1869fe44efe68dace40d2a16ecb853141394047f0780b96/wrapt-1.17.3-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:9baa544e6acc91130e926e8c802a17f3b16fbea0fd441b5a60f5cf2cc5c3deba", size = 39020, upload-time = "2025-08-12T05:51:35.906Z" },
+    { url = "https://files.pythonhosted.org/packages/33/df/bdf864b8997aab4febb96a9ae5c124f700a5abd9b5e13d2a3214ec4be705/wrapt-1.17.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:6b538e31eca1a7ea4605e44f81a48aa24c4632a277431a6ed3f328835901f4fd", size = 39098, upload-time = "2025-08-12T05:51:57.474Z" },
+    { url = "https://files.pythonhosted.org/packages/9f/81/5d931d78d0eb732b95dc3ddaeeb71c8bb572fb01356e9133916cd729ecdd/wrapt-1.17.3-cp312-cp312-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:042ec3bb8f319c147b1301f2393bc19dba6e176b7da446853406d041c36c7828", size = 88036, upload-time = "2025-08-12T05:52:34.784Z" },
+    { url = "https://files.pythonhosted.org/packages/ca/38/2e1785df03b3d72d34fc6252d91d9d12dc27a5c89caef3335a1bbb8908ca/wrapt-1.17.3-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:3af60380ba0b7b5aeb329bc4e402acd25bd877e98b3727b0135cb5c2efdaefe9", size = 88156, upload-time = "2025-08-12T05:52:13.599Z" },
+    { url = "https://files.pythonhosted.org/packages/b3/8b/48cdb60fe0603e34e05cffda0b2a4adab81fd43718e11111a4b0100fd7c1/wrapt-1.17.3-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:0b02e424deef65c9f7326d8c19220a2c9040c51dc165cddb732f16198c168396", size = 87102, upload-time = "2025-08-12T05:52:14.56Z" },
+    { url = "https://files.pythonhosted.org/packages/3c/51/d81abca783b58f40a154f1b2c56db1d2d9e0d04fa2d4224e357529f57a57/wrapt-1.17.3-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:74afa28374a3c3a11b3b5e5fca0ae03bef8450d6aa3ab3a1e2c30e3a75d023dc", size = 87732, upload-time = "2025-08-12T05:52:36.165Z" },
+    { url = "https://files.pythonhosted.org/packages/9e/b1/43b286ca1392a006d5336412d41663eeef1ad57485f3e52c767376ba7e5a/wrapt-1.17.3-cp312-cp312-win32.whl", hash = "sha256:4da9f45279fff3543c371d5ababc57a0384f70be244de7759c85a7f989cb4ebe", size = 36705, upload-time = "2025-08-12T05:53:07.123Z" },
+    { url = "https://files.pythonhosted.org/packages/28/de/49493f962bd3c586ab4b88066e967aa2e0703d6ef2c43aa28cb83bf7b507/wrapt-1.17.3-cp312-cp312-win_amd64.whl", hash = "sha256:e71d5c6ebac14875668a1e90baf2ea0ef5b7ac7918355850c0908ae82bcb297c", size = 38877, upload-time = "2025-08-12T05:53:05.436Z" },
+    { url = "https://files.pythonhosted.org/packages/f1/48/0f7102fe9cb1e8a5a77f80d4f0956d62d97034bbe88d33e94699f99d181d/wrapt-1.17.3-cp312-cp312-win_arm64.whl", hash = "sha256:604d076c55e2fdd4c1c03d06dc1a31b95130010517b5019db15365ec4a405fc6", size = 36885, upload-time = "2025-08-12T05:52:54.367Z" },
+    { url = "https://files.pythonhosted.org/packages/fc/f6/759ece88472157acb55fc195e5b116e06730f1b651b5b314c66291729193/wrapt-1.17.3-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:a47681378a0439215912ef542c45a783484d4dd82bac412b71e59cf9c0e1cea0", size = 54003, upload-time = "2025-08-12T05:51:48.627Z" },
+    { url = "https://files.pythonhosted.org/packages/4f/a9/49940b9dc6d47027dc850c116d79b4155f15c08547d04db0f07121499347/wrapt-1.17.3-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:54a30837587c6ee3cd1a4d1c2ec5d24e77984d44e2f34547e2323ddb4e22eb77", size = 39025, upload-time = "2025-08-12T05:51:37.156Z" },
+    { url = "https://files.pythonhosted.org/packages/45/35/6a08de0f2c96dcdd7fe464d7420ddb9a7655a6561150e5fc4da9356aeaab/wrapt-1.17.3-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:16ecf15d6af39246fe33e507105d67e4b81d8f8d2c6598ff7e3ca1b8a37213f7", size = 39108, upload-time = "2025-08-12T05:51:58.425Z" },
+    { url = "https://files.pythonhosted.org/packages/0c/37/6faf15cfa41bf1f3dba80cd3f5ccc6622dfccb660ab26ed79f0178c7497f/wrapt-1.17.3-cp313-cp313-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:6fd1ad24dc235e4ab88cda009e19bf347aabb975e44fd5c2fb22a3f6e4141277", size = 88072, upload-time = "2025-08-12T05:52:37.53Z" },
+    { url = "https://files.pythonhosted.org/packages/78/f2/efe19ada4a38e4e15b6dff39c3e3f3f73f5decf901f66e6f72fe79623a06/wrapt-1.17.3-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:0ed61b7c2d49cee3c027372df5809a59d60cf1b6c2f81ee980a091f3afed6a2d", size = 88214, upload-time = "2025-08-12T05:52:15.886Z" },
+    { url = "https://files.pythonhosted.org/packages/40/90/ca86701e9de1622b16e09689fc24b76f69b06bb0150990f6f4e8b0eeb576/wrapt-1.17.3-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:423ed5420ad5f5529db9ce89eac09c8a2f97da18eb1c870237e84c5a5c2d60aa", size = 87105, upload-time = "2025-08-12T05:52:17.914Z" },
+    { url = "https://files.pythonhosted.org/packages/fd/e0/d10bd257c9a3e15cbf5523025252cc14d77468e8ed644aafb2d6f54cb95d/wrapt-1.17.3-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:e01375f275f010fcbf7f643b4279896d04e571889b8a5b3f848423d91bf07050", size = 87766, upload-time = "2025-08-12T05:52:39.243Z" },
+    { url = "https://files.pythonhosted.org/packages/e8/cf/7d848740203c7b4b27eb55dbfede11aca974a51c3d894f6cc4b865f42f58/wrapt-1.17.3-cp313-cp313-win32.whl", hash = "sha256:53e5e39ff71b3fc484df8a522c933ea2b7cdd0d5d15ae82e5b23fde87d44cbd8", size = 36711, upload-time = "2025-08-12T05:53:10.074Z" },
+    { url = "https://files.pythonhosted.org/packages/57/54/35a84d0a4d23ea675994104e667ceff49227ce473ba6a59ba2c84f250b74/wrapt-1.17.3-cp313-cp313-win_amd64.whl", hash = "sha256:1f0b2f40cf341ee8cc1a97d51ff50dddb9fcc73241b9143ec74b30fc4f44f6cb", size = 38885, upload-time = "2025-08-12T05:53:08.695Z" },
+    { url = "https://files.pythonhosted.org/packages/01/77/66e54407c59d7b02a3c4e0af3783168fff8e5d61def52cda8728439d86bc/wrapt-1.17.3-cp313-cp313-win_arm64.whl", hash = "sha256:7425ac3c54430f5fc5e7b6f41d41e704db073309acfc09305816bc6a0b26bb16", size = 36896, upload-time = "2025-08-12T05:52:55.34Z" },
+    { url = "https://files.pythonhosted.org/packages/02/a2/cd864b2a14f20d14f4c496fab97802001560f9f41554eef6df201cd7f76c/wrapt-1.17.3-cp314-cp314-macosx_10_13_universal2.whl", hash = "sha256:cf30f6e3c077c8e6a9a7809c94551203c8843e74ba0c960f4a98cd80d4665d39", size = 54132, upload-time = "2025-08-12T05:51:49.864Z" },
+    { url = "https://files.pythonhosted.org/packages/d5/46/d011725b0c89e853dc44cceb738a307cde5d240d023d6d40a82d1b4e1182/wrapt-1.17.3-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:e228514a06843cae89621384cfe3a80418f3c04aadf8a3b14e46a7be704e4235", size = 39091, upload-time = "2025-08-12T05:51:38.935Z" },
+    { url = "https://files.pythonhosted.org/packages/2e/9e/3ad852d77c35aae7ddebdbc3b6d35ec8013af7d7dddad0ad911f3d891dae/wrapt-1.17.3-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:5ea5eb3c0c071862997d6f3e02af1d055f381b1d25b286b9d6644b79db77657c", size = 39172, upload-time = "2025-08-12T05:51:59.365Z" },
+    { url = "https://files.pythonhosted.org/packages/c3/f7/c983d2762bcce2326c317c26a6a1e7016f7eb039c27cdf5c4e30f4160f31/wrapt-1.17.3-cp314-cp314-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:281262213373b6d5e4bb4353bc36d1ba4084e6d6b5d242863721ef2bf2c2930b", size = 87163, upload-time = "2025-08-12T05:52:40.965Z" },
+    { url = "https://files.pythonhosted.org/packages/e4/0f/f673f75d489c7f22d17fe0193e84b41540d962f75fce579cf6873167c29b/wrapt-1.17.3-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:dc4a8d2b25efb6681ecacad42fca8859f88092d8732b170de6a5dddd80a1c8fa", size = 87963, upload-time = "2025-08-12T05:52:20.326Z" },
+    { url = "https://files.pythonhosted.org/packages/df/61/515ad6caca68995da2fac7a6af97faab8f78ebe3bf4f761e1b77efbc47b5/wrapt-1.17.3-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:373342dd05b1d07d752cecbec0c41817231f29f3a89aa8b8843f7b95992ed0c7", size = 86945, upload-time = "2025-08-12T05:52:21.581Z" },
+    { url = "https://files.pythonhosted.org/packages/d3/bd/4e70162ce398462a467bc09e768bee112f1412e563620adc353de9055d33/wrapt-1.17.3-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:d40770d7c0fd5cbed9d84b2c3f2e156431a12c9a37dc6284060fb4bec0b7ffd4", size = 86857, upload-time = "2025-08-12T05:52:43.043Z" },
+    { url = "https://files.pythonhosted.org/packages/2b/b8/da8560695e9284810b8d3df8a19396a6e40e7518059584a1a394a2b35e0a/wrapt-1.17.3-cp314-cp314-win32.whl", hash = "sha256:fbd3c8319de8e1dc79d346929cd71d523622da527cca14e0c1d257e31c2b8b10", size = 37178, upload-time = "2025-08-12T05:53:12.605Z" },
+    { url = "https://files.pythonhosted.org/packages/db/c8/b71eeb192c440d67a5a0449aaee2310a1a1e8eca41676046f99ed2487e9f/wrapt-1.17.3-cp314-cp314-win_amd64.whl", hash = "sha256:e1a4120ae5705f673727d3253de3ed0e016f7cd78dc463db1b31e2463e1f3cf6", size = 39310, upload-time = "2025-08-12T05:53:11.106Z" },
+    { url = "https://files.pythonhosted.org/packages/45/20/2cda20fd4865fa40f86f6c46ed37a2a8356a7a2fde0773269311f2af56c7/wrapt-1.17.3-cp314-cp314-win_arm64.whl", hash = "sha256:507553480670cab08a800b9463bdb881b2edeed77dc677b0a5915e6106e91a58", size = 37266, upload-time = "2025-08-12T05:52:56.531Z" },
+    { url = "https://files.pythonhosted.org/packages/77/ed/dd5cf21aec36c80443c6f900449260b80e2a65cf963668eaef3b9accce36/wrapt-1.17.3-cp314-cp314t-macosx_10_13_universal2.whl", hash = "sha256:ed7c635ae45cfbc1a7371f708727bf74690daedc49b4dba310590ca0bd28aa8a", size = 56544, upload-time = "2025-08-12T05:51:51.109Z" },
+    { url = "https://files.pythonhosted.org/packages/8d/96/450c651cc753877ad100c7949ab4d2e2ecc4d97157e00fa8f45df682456a/wrapt-1.17.3-cp314-cp314t-macosx_10_13_x86_64.whl", hash = "sha256:249f88ed15503f6492a71f01442abddd73856a0032ae860de6d75ca62eed8067", size = 40283, upload-time = "2025-08-12T05:51:39.912Z" },
+    { url = "https://files.pythonhosted.org/packages/d1/86/2fcad95994d9b572db57632acb6f900695a648c3e063f2cd344b3f5c5a37/wrapt-1.17.3-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:5a03a38adec8066d5a37bea22f2ba6bbf39fcdefbe2d91419ab864c3fb515454", size = 40366, upload-time = "2025-08-12T05:52:00.693Z" },
+    { url = "https://files.pythonhosted.org/packages/64/0e/f4472f2fdde2d4617975144311f8800ef73677a159be7fe61fa50997d6c0/wrapt-1.17.3-cp314-cp314t-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:5d4478d72eb61c36e5b446e375bbc49ed002430d17cdec3cecb36993398e1a9e", size = 108571, upload-time = "2025-08-12T05:52:44.521Z" },
+    { url = "https://files.pythonhosted.org/packages/cc/01/9b85a99996b0a97c8a17484684f206cbb6ba73c1ce6890ac668bcf3838fb/wrapt-1.17.3-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:223db574bb38637e8230eb14b185565023ab624474df94d2af18f1cdb625216f", size = 113094, upload-time = "2025-08-12T05:52:22.618Z" },
+    { url = "https://files.pythonhosted.org/packages/25/02/78926c1efddcc7b3aa0bc3d6b33a822f7d898059f7cd9ace8c8318e559ef/wrapt-1.17.3-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:e405adefb53a435f01efa7ccdec012c016b5a1d3f35459990afc39b6be4d5056", size = 110659, upload-time = "2025-08-12T05:52:24.057Z" },
+    { url = "https://files.pythonhosted.org/packages/dc/ee/c414501ad518ac3e6fe184753632fe5e5ecacdcf0effc23f31c1e4f7bfcf/wrapt-1.17.3-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:88547535b787a6c9ce4086917b6e1d291aa8ed914fdd3a838b3539dc95c12804", size = 106946, upload-time = "2025-08-12T05:52:45.976Z" },
+    { url = "https://files.pythonhosted.org/packages/be/44/a1bd64b723d13bb151d6cc91b986146a1952385e0392a78567e12149c7b4/wrapt-1.17.3-cp314-cp314t-win32.whl", hash = "sha256:41b1d2bc74c2cac6f9074df52b2efbef2b30bdfe5f40cb78f8ca22963bc62977", size = 38717, upload-time = "2025-08-12T05:53:15.214Z" },
+    { url = "https://files.pythonhosted.org/packages/79/d9/7cfd5a312760ac4dd8bf0184a6ee9e43c33e47f3dadc303032ce012b8fa3/wrapt-1.17.3-cp314-cp314t-win_amd64.whl", hash = "sha256:73d496de46cd2cdbdbcce4ae4bcdb4afb6a11234a1df9c085249d55166b95116", size = 41334, upload-time = "2025-08-12T05:53:14.178Z" },
+    { url = "https://files.pythonhosted.org/packages/46/78/10ad9781128ed2f99dbc474f43283b13fea8ba58723e98844367531c18e9/wrapt-1.17.3-cp314-cp314t-win_arm64.whl", hash = "sha256:f38e60678850c42461d4202739f9bf1e3a737c7ad283638251e79cc49effb6b6", size = 38471, upload-time = "2025-08-12T05:52:57.784Z" },
+    { url = "https://files.pythonhosted.org/packages/1f/f6/a933bd70f98e9cf3e08167fc5cd7aaaca49147e48411c0bd5ae701bb2194/wrapt-1.17.3-py3-none-any.whl", hash = "sha256:7171ae35d2c33d326ac19dd8facb1e82e5fd04ef8c6c0e394d7af55a55051c22", size = 23591, upload-time = "2025-08-12T05:53:20.674Z" },
 ]