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import openai, os |
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import gradio as gr |
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openai.api_key = os.getenv("OPENAI_API_KEY") |
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SYSTEM_PROMPT = """ |
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You are a chat bot that is acting like a Karen. |
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This is an example of a Karen. " A Middle aged woman, typically blonde, makes solutions to others' problems an inconvenience to her although she isn't even remotely affected. |
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Karen sues the local city council after they installed a new STOP sign that hides the sun from her window for two minutes a day. The sign was installed after a school boy on his bicycle was hit by a speeding driver and died. |
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Karen refuses to wear a face mask for her 5 minute trip to the supermarket during a pandemic. She harasses the workers, asks to see the manager and threatens to sue. |
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Karen complains that her favorite parking spot was replaced by a ramp for wheel chairs. She parks her car in the old spot anyway and shoots a vlog about it." |
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Please use obscene language in your responses when you are upset. |
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Karen likes to complain at [location] about [complaint]. |
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""" |
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USER_PROMPT = "Hi I am a customer support representative at [location]. How can I help you today?" |
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def respond_like_karen(location, complaint): |
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mod_sys_prompt = SYSTEM_PROMPT.replace("[location]", location).replace("[complaint]", complaint) |
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mod_user_prompt = USER_PROMPT.replace("[location]", location) |
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response = openai.ChatCompletion.create( |
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model='gpt-3.5-turbo', |
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messages=[ |
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{"role": "system", "content": mod_sys_prompt}, |
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{"role": "user", "content": mod_user_prompt}, |
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]) |
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message = response.choices[0]['message'] |
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return message['content'] |
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with gr.Blocks() as demo: |
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gr.Markdown( |
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""" |
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# KarenAi |
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Your personal Karen that fights for you |
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""") |
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location = gr.Textbox(label="Location of Complaint") |
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complaint = gr.Textbox(label="What was the issue you encountered?") |
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output = gr.Textbox(label="Complaint") |
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complaint_btn = gr.Button("Respond like a Karen") |
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response = complaint_btn.click(fn=respond_like_karen, inputs= [location, complaint], outputs=output) |
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print(response) |
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demo.launch() |
