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import os | |
import sys | |
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) | |
import asyncio | |
from langchain_openai import ChatOpenAI | |
from langchain_anthropic import ChatAnthropic | |
from langchain_google_genai import ChatGoogleGenerativeAI |
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{ | |
"n01440764": "tench", | |
"n01443537": "goldfish", | |
"n01484850": "great_white_shark", | |
"n01491361": "tiger_shark", | |
"n01494475": "hammerhead", | |
"n01496331": "electric_ray", | |
"n01498041": "stingray", | |
"n01514668": "cock", | |
"n01514859": "hen", |
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n02119789 1 kit_fox | |
n02100735 2 English_setter | |
n02110185 3 Siberian_husky | |
n02096294 4 Australian_terrier | |
n02102040 5 English_springer | |
n02066245 6 grey_whale | |
n02509815 7 lesser_panda | |
n02124075 8 Egyptian_cat | |
n02417914 9 ibex | |
n02123394 10 Persian_cat |
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import ast | |
import pandas as pd | |
data = pd.read_csv('path_to_healthtap_file.csv') | |
all_questions = [] | |
all_answers = [] | |
for question, answer_format in zip(data.question, data.answers): | |
try: | |
if answer_format != "[]": | |
all_answers.append(ast.literal_eval(answer_format)[0]["answer"]) |