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import numpy as np
import openai
import os
import random
import string
def is_climate_change_related(sentence: str, classifier) -> bool:
"""_summary_
Args:
sentence (str): your sentence to classify
classifier (_type_): zero shot hugging face pipeline classifier
Returns:
bool: is_climate_change_related or not
"""
results = classifier(
sequences=sentence,
candidate_labels=["climate change related", "non climate change related"],
)
print(f" ## Result from is climate change related {results}")
return results["labels"][np.argmax(results["scores"])] == "climate change related"
def make_pairs(lst):
"""From a list of even lenght, make tupple pairs
Args:
lst (list): a list of even lenght
Returns:
list: the list as tupple pairs
"""
assert not (l := len(lst) % 2), f"your list is of lenght {l} which is not even"
return [(lst[i], lst[i + 1]) for i in range(0, len(lst), 2)]
def set_openai_api_key(text):
"""Set the api key and return chain.If no api_key, then None is returned.
To do : add raise error & Warning message
Args:
text (str): openai api key
Returns:
str: Result of connection
"""
openai.api_key = os.environ["api_key"]
if text.startswith("sk-") and len(text) > 10:
openai.api_key = text
return f"You're all set: this is your api key: {openai.api_key}"
def create_user_id(length):
"""Create user_id
Args:
length (int): length of user id
Returns:
str: String to id user
"""
letters = string.ascii_lowercase
user_id = "".join(random.choice(letters) for i in range(length))
return user_id
def to_completion(messages):
s = []
for message in messages:
s.append(f"<|im_start|>{message['role']}\n{message['content']}<|im_end|>")
s.append("<|im_start|>assistant\n")
return "\n".join(s)
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