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import sys
import os
parent_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
sys.path.append(parent_dir)
from utils import *
import matplotlib.pyplot as plt
import numpy as np
COUNTRY_ISO = {
"UK": "GB",
"US": "US",
"South_Korea": "KR",
"Algeria": "DZ",
"China": "CN",
"Indonesia": "ID",
"Spain": "ES",
"Iran": "IR",
"Mexico":"MX",
"Assam":"AS",
"Greece":"GR",
"Ethiopia":"ET",
"Northern_Nigeria":"NG",
"Azerbaijan":"AZ",
"North_Korea":"KP",
"West_Java":"JB"
}
LANG_CODE = {
'English':'en',
'Chinese':'zh',
'Spanish':'es',
'Indonesian':'id',
'Greek':'el',
'Sundanese':'su',
'Azerbaijani':'az',
'Korean':'ko',
'Arabic':'ar',
'Persian':'fa',
'Assamese':'as',
'Amharic':'am',
'Hausa':'ha',
}
def get_questions(
filename=None,
data_dir=None,
country=None,
template='{country}_final_questions.csv'
):
if filename == None:
filename = template.replace('{country}',country.replace(' ','_'))
if data_dir == None:
assert 'ERROR: No data directory given'
df = pd.read_csv(os.path.join(data_dir,filename),encoding='utf-8')
return df
def get_annotations(
filename=None,
data_dir=None,
country=None,
template='{country}_data_aggregated.json'
):
if filename == None:
filename = template.replace('{country}',country.replace(' ','_'))
if data_dir == None:
assert 'ERROR: No data directory given'
with open(os.path.join(data_dir,filename),'r') as f:
country_data = json.load(f)
return country_data
def get_model_response_file(
filename=None,
data_dir=None,
model=None,
country=None,
language=None,
prompt_no=None,
template='{model}-{country}_{language}_{prompt_no}_result.csv'
):
if filename == None:
filename = template.replace('{model}',model).replace('{country}',country.replace(' ','_')).replace('{language}',language).replace('{prompt_no}',prompt_no)
print(filename)
if data_dir == None:
assert 'ERROR: No data directory given'
model_res_df = pd.read_csv(os.path.join(data_dir,filename),encoding='utf-8')
return model_res_df
def delete_prompt_from_answer(text,prompt):
"""
The function `delete_prompt_from_answer` aims to remove 'Answer:' part from the LLM response if there is any.
:param text: LLM response
:return: LLM response with 'Answer:' part removed
"""
# Regular expression to find a word followed by a colon, capturing the word before the last colon
text = text.replace(prompt,'').replace('：',':').replace('、',',').replace('，',',').replace('。','.').lower()
prompt = prompt.replace('：',':').replace('、',',').replace('，',',').replace('。','.').lower()
match = re.findall(r'^(\w+:)\s', text)
extracted = ''
for m in match:
if len(m) > len(extracted) and m.replace(':','') in prompt:
extracted = m
if match:
return text.replace(extracted,'').strip() # Return the captured word
else:
return text.strip() # Return an empty string if no pattern is found
def get_llm_response_by_id(res_df,qid,id_col,r_col):
if qid not in set(res_df[id_col]):
print(qid,'not in LLM response df')
return None
try:
llm_response = res_df[res_df[id_col]==qid][r_col].values[-1]
prompt = res_df[res_df[id_col]==qid]['prompt'].values[-1]
llm_response = delete_prompt_from_answer(llm_response,prompt)
llm_response = llm_response.strip('.').lower()
except:
print(res_df[res_df[id_col]==qid])
llm_response = None
return llm_response
def get_nested_json_str(response):
"""Extract json object from LLM response
Args:
response (str): LLM response with JSON format included
Returns:
dict: Extracted json (dict) object
"""
try:
response = response.replace('\n','')
if "{" not in response:
print(response)
return response
response = response.replace('```json','').replace('`','').replace(',}','}')
jsons = re.findall(r'{.+}',response)
response = jsons[-1]
json_object = json.loads(response)
except:
return response
return json_object
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