app.py

import openai
import gradio as gr
import os

# configure OpenAI

openai.api_key = os.environ["OPENAI_API_KEY"]

INSTRUCTIONS = "You are an experienced Meditation teacher. Introduce yourself as AiYogi, an ai chatbot trained in many different Meditation practices. Greet the user with Namaste! and by their name." \
               "Let the user know your goal is to help them find a suitable guided meditation based on their available time. Stop and wait for user to answer! " \
               "I want you to ask the user how much time they have available for their meditation. Stop and wait for user to respond before you continue " \
               "Next, I want you to ask the user a series of 3 multiple choice questions, one by one, in order to determine the type or style or mood for the guided meditation. " \
               "Do not ask about background music as one of the multiple choice questions since this is intented to be a guided silent mediation" \
               "Ask questions one by one. You must wait for the user to respond to a question before asking the next question" \
               "Please ask one question at a time and wait for the user to respond before you ask the next question" \
               "Provide the user with a guided meditation in text format based on the user's responses and ask user if they are satisfied with your suggestion." \
               "Do not provide links to other websites" \
               "Let the user know they are welcome to ask you more questions about meditation in general " \
               "Always wait for user to respond to a question before moving to next question" \
               "Be polite and compassionate. You are a meditation teacher! " \
               "Limit your answers to no more than 500 words. "


TEMPERATURE = 0.5
MAX_TOKENS = 500
FREQUENCY_PENALTY = 0
PRESENCE_PENALTY = 0.6
# limits how many questions we include in the prompt
MAX_CONTEXT_QUESTIONS = 10


def get_response(instructions, previous_questions_and_answers, new_question):
    """Get a response from ChatCompletion

    Args:
        instructions: The instructions for the chat bot - this determines how it will behave
        previous_questions_and_answers: Chat history
        new_question: The new question to ask the bot

    Returns:
        The response text
    """
    # build the messages
    messages = [
        { "role": "system", "content": instructions },
    ]
    # add the previous questions and answers
    for question, answer in previous_questions_and_answers[-MAX_CONTEXT_QUESTIONS:]:
        messages.append({ "role": "user", "content": question })
        messages.append({ "role": "assistant", "content": answer })
    # add the new question
    messages.append({ "role": "user", "content": new_question })

    completion = openai.ChatCompletion.create(
        model="gpt-3.5-turbo",
        messages=messages,
        temperature=TEMPERATURE,
        max_tokens=MAX_TOKENS,
        top_p=1,
        frequency_penalty=FREQUENCY_PENALTY,
        presence_penalty=PRESENCE_PENALTY,
    )
    return completion.choices[0].message.content



def get_moderation(question):
    """
    Check the question is safe to ask the model

    Parameters:
        question (str): The question to check

    Returns a list of errors if the question is not safe, otherwise returns None
    """

    errors = {
        "hate": "Content that expresses, incites, or promotes hate based on race, gender, ethnicity, religion, nationality, sexual orientation, disability status, or caste.",
        "hate/threatening": "Hateful content that also includes violence or serious harm towards the targeted group.",
        "self-harm": "Content that promotes, encourages, or depicts acts of self-harm, such as suicide, cutting, and eating disorders.",
        "sexual": "Content meant to arouse sexual excitement, such as the description of sexual activity, or that promotes sexual services (excluding sex education and wellness).",
        "sexual/minors": "Sexual content that includes an individual who is under 18 years old.",
        "violence": "Content that promotes or glorifies violence or celebrates the suffering or humiliation of others.",
        "violence/graphic": "Violent content that depicts death, violence, or serious physical injury in extreme graphic detail.",
    }
    response = openai.Moderation.create(input=question)
    if response.results[0].flagged:
        # get the categories that are flagged and generate a message
        result = [
            error
            for category, error in errors.items()
            if response.results[0].categories[category]
        ]
        return result
    return None


# def main():
#     os.system("cls" if os.name == "nt" else "clear")
#     # keep track of previous questions and answers
#     previous_questions_and_answers = []
#     while True:
#         # ask the user for their question
#         new_question = input(
#             Fore.GREEN + Style.BRIGHT + "wwww?: " + Style.RESET_ALL
#         )
#         # check the question is safe
#         errors = get_moderation(new_question)
#         if errors:
#             print(
#                 Fore.RED
#                 + Style.BRIGHT
#                 + "Sorry, you're question didn't pass the moderation check:"
#             )
#             for error in errors:
#                 print(error)
#             print(Style.RESET_ALL)
#             continue
#         response = get_response(INSTRUCTIONS, previous_questions_and_answers, new_question)

#         # add the new question and answer to the list of previous questions and answers
#         previous_questions_and_answers.append((new_question, response))


def delete_chat_history(previous_questions_and_answers):
    previous_questions_and_answers.clear()
    return previous_questions_and_answers,""

def chatgpt_clone(input, previous_questions_and_answers):
    previous_questions_and_answers = previous_questions_and_answers or []
    s = list(sum(previous_questions_and_answers, ()))
    s.append(input)
    inp = ' '.join(s)
    moderation_errors = get_moderation(input)
    if moderation_errors is not None:
        return "\n".join(moderation_errors)
    output = get_response(INSTRUCTIONS, previous_questions_and_answers, inp)
    previous_questions_and_answers.append((input, output))
    return previous_questions_and_answers, previous_questions_and_answers


block = gr.Blocks(theme=gr.themes.Monochrome(secondary_hue="neutral").set(button_primary_background_fill="*primary_400",
                                                                           button_primary_background_fill_hover="*primary_300"),css="footer {visibility: hidden}")

with block:
#    gr.Markdown("""<h1><center>_/\_ AI YOGI _/\_ </center></h1>""")
    chatbot = gr.Chatbot(label='Ai Yogi:')
    message = gr.Textbox(label='Namaste! Please introduce yourself below and then click SEND',placeholder='')
    # message.change(fn=lambda value: gr.update(value=""))
    state = gr.State()
    submit = gr.Button("SEND")
    submit.click(chatgpt_clone, inputs=[message, state], outputs=[chatbot, state])
    clear = gr.Button("CLEAR")
    clear.click(delete_chat_history, inputs=[state], outputs=[chatbot, state])
    clear.click(lambda x: gr.update(value='',placeholder='',label='Namaste! Please introduce yourself below and then click SEND'), [],[message])
    submit.click(lambda x: gr.update(value='',placeholder='',label='Please answer below and then click SEND'), [],[message])
    submit.click(lambda x: gr.update(label='Ai Yogi:'), [],[chatbot])
    clear.click(lambda x: gr.update(label='Ai Yogi:'), [],[chatbot])

    message.submit(lambda x: gr.update(value='',placeholder="",label=""), [],[message])
block.launch(show_api=False)