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import json
from typing import Any
import pandas as pd
import streamlit as st
from functools import reduce
def get_filter_values(df: pd.DataFrame, column_name: str) -> list:
return df[column_name].unique().tolist()
def build_filter(
meta_data: pd.DataFrame,
authors_filter: list[str],
draft_cats_filter: list[str],
round_filter: list[int],
) -> dict[str, int | str] | dict:
authors = authors_filter
round_number = round_filter
draft_cats = draft_cats_filter
# set authors_flag to True if not empty list
authors_flag = True if len(authors) > 0 else False
draft_cats_flag = True if len(draft_cats) > 0 else False
round_number_flag = True if len(round_number) > 0 else False
conditions = []
if authors_flag:
authors_condition = (meta_data[col] == 1 for col in authors)
authors_conditions_list = reduce(lambda a, b: a | b, authors_condition)
conditions.append(authors_conditions_list)
if draft_cats_flag:
draft_cat_condition = (meta_data[col] for col in draft_cats)
draft_cat_conditions_list = reduce(lambda a, b: a | b, draft_cat_condition)
conditions.append(draft_cat_conditions_list)
if round_number_flag:
round_condition = meta_data["round"].isin(round_number)
conditions.append(round_condition)
if len(conditions) == 0:
filtered_retriever_ids = []
else:
final_condition = reduce(lambda a, b: a & b, conditions)
filtered_retriever_ids = meta_data[final_condition]["retriever_id"].tolist()
if len(filtered_retriever_ids) == 0:
return {}
else:
return {"retriever_id": filtered_retriever_ids}
def load_json(file_path: str) -> dict:
with open(file_path, "r") as f:
return json.load(f)
def save_json(file_path: str, data: dict) -> None:
with open(file_path, "w") as f:
json.dump(data, f, indent=4)
def get_meta(result: dict[str, Any]) -> list[dict[str, Any]]:
meta_data = []
for doc in result["documents"]:
current_meta = doc.meta
current_meta["content"] = doc.content
meta_data.append(current_meta)
return meta_data
def load_css(file_name) -> None:
with open(file_name) as f:
st.markdown(f"<style>{f.read()}</style>", unsafe_allow_html=True)
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