File size: 2,536 Bytes
963c6da fbcd930 ca8fe98 fbcd930 12f938b ca8fe98 fbcd930 12f938b ff0c7de |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 |
import streamlit as st
import pandas as pd
@st.cache_data
def load_dataframe() -> pd.DataFrame:
"""
Load dataframe from the csv file in public directory
Returns
dataframe: a pd.DataFrame of the average scores of the LLMs on each task
"""
dataframe = pd.read_csv("public/datasets/models_scores.csv")
dataframe = dataframe.drop(columns = "Unnamed: 0")
return dataframe
@st.cache_data
def show_dataframe_top(n:int , dataframe: pd.DataFrame) -> pd.DataFrame:
"""
read only the n-th first row
Arguments
-n: an integer telling the number of row
-dataframe: the dataframe to slice
Returns
dataframe: a pd.DataFrame of the average scores of the LLMs on each task
"""
return dataframe.head(n)
@st.cache_data
def sort_by(dataframe: pd.DataFrame, column_name: str, ascending:bool = False) -> pd.DataFrame:
"""
Sort the dataframe by column_name
Arguments:
- dataframe: a pandas dataframe to sort
- column_name: a string stating the column to sort the dataframe by
- ascending: a boolean stating to sort in ascending order or not, default to False
Returns:
a sorted dataframe
"""
return dataframe.sort_values(by = column_name, ascending = ascending )
@st.cache_data
def search_by_name(name: str) -> pd.DataFrame:
"""
Search a model by its name
Arguments:
- name: the name of the model or part of it
Returns:
a pandas Dataframe of every row that contains name
"""
dataframe = load_dataframe()
indexes = dataframe["model_name"].str.contains(name)
return dataframe[indexes]
def validate_categories(categories: list) -> bool:
"""
validate a list of categories to the columns in the dataframe
Arguments:
- categories: a list of categories for the ordering of the columns in the dataframe
This expects a list with six elements that should be (not necessary in order):
- ARC
- GSM8K
- TruthfulQA
- Winogrande
- HellaSwag
- MMLU
Returns
- True if the list has the right number of element and right elements
- False otherwise
"""
valid_categories = False
if len(categories) == 6:
if ("ARC" in categories and "GSM8K" in categories and "TruthfulQA" in categories
and "Winogrande" in categories and "HellaSwag" in categories and "MMLU" in categories):
valid_categories = True
else:
valid_categories = False
else:
valid_categories = False
return valid_categories |