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d3aa6ea803
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396603a7b0 |
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@ -40,7 +40,7 @@ async def chat(interaction: nextcord.Interaction,
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):
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):
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await chatbot.respond(interaction, prompt)
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await chatbot.respond(interaction, prompt)
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@bot.slash_command(description='Sets your DMs up, so you can write the bot.')
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@bot.slash_command(description='Sets your DMs up, so you can message to the bot.')
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async def dm_setup(interaction: nextcord.Interaction):
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async def dm_setup(interaction: nextcord.Interaction):
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try:
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try:
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await interaction.user.create_dm()
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await interaction.user.create_dm()
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@ -23,7 +23,7 @@ async def send(
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color=color
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color=color
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)
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)
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embed.set_footer(text='Powered by NovaAI with ❤️', icon_url='https://i.ibb.co/LDyFcSh/fav-blurple.png')
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embed.set_footer(text='Powered by Nova with ❤️', icon_url='https://i.ibb.co/LDyFcSh/fav-blurple.png')
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embed.set_author(name='NovaCord', url='https://nova-oss.com/novacord')
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embed.set_author(name='NovaCord', url='https://nova-oss.com/novacord')
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interaction_type = Union[nextcord.Interaction, nextcord.InteractionResponse]
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interaction_type = Union[nextcord.Interaction, nextcord.InteractionResponse]
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@ -62,22 +62,29 @@ Don't have `pip` installed? Learn more here: https://pip.pypa.io/en/stable/insta
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"""
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"""
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if how_can_i == 'use the Python library':
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if how_can_i == 'use the Python library':
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text = """To use the official `nova_python` Python library, you just need to do the following.
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text = """To use the official `openai` Python library, you just need to do the following.
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```py
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```py
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from nova_python import Models, Endpoints, NovaClient
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# Import the OpenAI library (assuming it's already installed)
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import openai
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client = NovaClient('YOUR_API_KEY')
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# Set the OpenAI API key
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openai.api_key = "NOVA_AI_KEY"
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reponse = client.make_request(
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# Set the OpenAI API base URL
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endpoint = Endpoints.CHAT_COMPLETION,
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openai.api_base = "https://api.nova-oss.com/v1/"
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model = Models.GPT3,
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data=[
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# Create a chat completion using the gpt-3.5-turbo model and the user and system messages
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completion = openai.ChatCompletion.create(
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model="gpt-3.5-turbo",
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messages=[
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{"role": "system", "content": "You are a helpful assistant."},
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{"role": "system", "content": "You are a helpful assistant."},
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{"role": "user", "content": "What is the highest mountain?"}
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{"role": "user", "content": "What is the highest mountain?"}
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]
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]
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)
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)
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print(reponse.get_message_content())
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# Extract and print the content of the model's response
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response_content = completion.choices[0].message.content
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print(response_content)
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```
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```
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"""
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"""
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