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