Pondr, Fostering Connection through Good Conversation

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import cohere
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from cohere.responses.classify import Example
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import pandas as pd

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co=cohere.Client('YOUR_API_KEY')

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#user_input is hardcoded for this example
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user_input='I am meeting up with a coworker. We are meeting at a fancy restaurant. I wanna ask some interesting questions. These questions should be deep.'
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prompt=user_input+'\nHere are 10 interesting questions to ask:\n1)'
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response=co.generate(model='xlarge', prompt=prompt, max_tokens=200, temperature=5).generations[0].text
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response

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def generation_to_df(generation):
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    generation=response.split('\n')
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    clean_questions=[]
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    for i in range(10):
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        curr_q=generation[i]
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        clean_questions.append(curr_q[curr_q.find(')')+1:])
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    clean_q_df=pd.DataFrame(clean_questions, columns=['questions'])
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    return clean_q_df

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clean_q_df = generation_to_df(response)
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pd.options.display.max_colwidth=150
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clean_q_df

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interestingness=[
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    Example("What do you think is the hardest part of what I do for a living?", "Not Interesting"),
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    Example("What\'s the first thing you noticed about me?", "Interesting"),
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    Example("Do you think plants thrive or die in my care?", "Interesting"),
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    Example("Do I seem like more of a creative or analytical type?", "Interesting"),
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    Example("What subject do you think I thrived at in school?", "Not Interesting"),
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    Example("What\'s been your happiest memory this past year?", "Interesting"),
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    Example("What lesson took you the longest to un-learn?", "Not Interesting"),
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    Example("How can you become a better person?", "Not Interesting"),
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    Example("Do you think I intimidate others? Why or why not?", "Interesting"),
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    Example("What\'s the most embarrassing thing that happened to you on a date?", "Not Interesting"),
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    Example("How would you describe what you think my type is in three words?", "Interesting"),
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    Example("What do you think I\'m most likely to splurge on?", "Interesting"),
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    Example("As a child what do you think I wanted to be when I grow up?", "Interesting"),
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    Example("Do you think you are usually early, on time, or late to events?", "Not Interesting"),
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    Example("Do you think I was popular at school?", "Interesting"),
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    Example("What questions are you trying to answer most in your life right now?", "Not Interesting")]
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specificity=[
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    Example("What\'s the first thing you noticed about me?", "Specific"),
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    Example("Do you think plants thrive or die in my care?", "Specific"),
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    Example("Do I seem like more of a creative or analytical type?", "Not Specific"),
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    Example("How would you describe what you think my type is in three words?", "Not Specific"),
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    Example("What do you think I\'m most likely to splurge on?", "Specific"),
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    Example("What subject do you think I thrived at in school?", "Not Specific"),
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    Example("As a child what do you think I wanted to be when I grow up?", "Specific"),
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    Example("Do you think I was popular at school?", "Specific"),
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    Example("Do you think you\'re usually early, on time, or late to events?", "Specific"),
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    Example("Do you think I intimidate others? Why or why not?", "Specific"),
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    Example("What\'s been your happiest memory this past year?", "Not Specific"),
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    Example("What subject do you think I thrived at in school?", "Specific"),
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    Example("What\'s the biggest mistake that you think you needed to make to become who you are now?", "Specific"),
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    Example("Is there anything you\'ve done recently that you\'re incredibly proud of?", "Not Specific"),
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    Example("How are you and your siblings similar?", "Not Specific"),
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    Example("What\'s the worst pain you have ever been in that wasn\'t physical?", "Specific"),
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    Example("Has a stranger ever changed your life?", "Specific"),
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    Example("Do you think the image you have of yourself matches the image other people see you as?", "Specific"),
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    Example("What would your younger self not believe about your life today?", "Specific")]

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def add_attribute(df, attribute, name, target):
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  response = co.classify(
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    model='medium',
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    inputs=list(df['questions']),
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    examples=attribute)
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  q_conf=[]
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  for q in response.classifications:
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    q_conf.append(q.labels[target].confidence)
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  df[name]=q_conf

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add_attribute(clean_q_df, interestingness, 'interestingness', 'Interesting')
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add_attribute(clean_q_df, specificity, 'specificity', 'Specific')
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clean_q_df['average']= clean_q_df.iloc[:,1:].mean(axis=1)
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clean_q_df.sort_values(by='average', ascending=False)