GeoLLM/test.py

# from openai import OpenAI
#
#
# client = OpenAI(
#     api_key='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'
# )
#
# system_prompt = '''You are a professional geographer. Your task is to extract all geopolitical entities from a given text. Geopolitical entities can include countries, regions, cities, autonomous regions, or other administrative divisions. For each geopolitical entity, wrap the name in a unique character sequence, such as [###ENTITY###]. If there are multiple entities, output them in the following format:\n[###ENTITY1###, ###ENTITY2###, ###ENTITY3###]\nHere is an example:\n Example:\n\nText:\n"China and India are two of the most populous countries in Asia."\n\nExpected Output:\n[###China###, ###India###]'''
# sent = 'Where is France?'
#
# math_bot_messages = [
#     {"role": "system",
#      "content": system_prompt},
#     {"role": "user", "content": sent},
# ]
#
# chat_completion = client.chat.completions.create(
#     messages=math_bot_messages,
#     model="gpt-3.5-turbo",
# )
#
# result = chat_completion.choices[0].message.content
#
#
# print(result)
#
#
import ../reregex_spatial


regex_spatial.get_level1_regex()