Kaveen Kumarasinghe
2 years ago
parent
825b009aa8
commit
9e0ed1b646
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import time
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import discord
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import openai
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from discord.ext import commands
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from dotenv import load_dotenv
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load_dotenv()
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import os
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class Mode:
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TOP_P = "top_p"
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TEMPERATURE = "temperature"
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class Model:
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# An enum of two modes, TOP_P or TEMPERATURE
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def __init__(self, ):
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self._mode = Mode.TEMPERATURE
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self._temp = 0.7 # Higher value means more random, lower value means more likely to be a coherent sentence
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self._top_p = 1 # 1 is equivalent to greedy sampling, 0.1 means that the model will only consider the top 10% of the probability distribution
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self._max_tokens = 2000 # The maximum number of tokens the model can generate
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self._presence_penalty = 0 # Penalize new tokens based on whether they appear in the text so far
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self._frequency_penalty = 0 # Penalize new tokens based on their existing frequency in the text so far. (Higher frequency = lower probability of being chosen.)
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self._best_of = 1 # Number of responses to compare the loglikelihoods of
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self._prompt_min_length = 25
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openai.api_key = os.getenv('OPENAI_TOKEN')
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# Use the @property and @setter decorators for all the self fields to provide value checking
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@property
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def mode(self):
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return self._mode
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@mode.setter
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def mode(self, value):
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if value not in [Mode.TOP_P, Mode.TEMPERATURE]:
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raise ValueError("mode must be either 'top_p' or 'temperature'")
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if value == Mode.TOP_P:
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self._top_p = 0.5
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self._temp = 1
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elif value == Mode.TEMPERATURE:
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self._top_p = 1
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self._temp = 0.7
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self._mode = value
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@property
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def temp(self):
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return self._temp
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@temp.setter
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def temp(self, value):
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value = float(value)
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if value < 0 or value > 1:
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raise ValueError("temperature must be greater than 0 and less than 1, it is currently " + str(value))
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if self._mode == Mode.TOP_P:
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raise ValueError("Cannot set temperature when in top_p mode")
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self._temp = value
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@property
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def top_p(self):
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return self._top_p
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@top_p.setter
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def top_p(self, value):
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value = float(value)
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if value < 0 or value > 1:
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raise ValueError("top_p must be greater than 0 and less than 1, it is currently " + str(value))
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if self._mode == Mode.TEMPERATURE:
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raise ValueError("Cannot set top_p when in temperature mode")
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self._top_p = value
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@property
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def max_tokens(self):
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return self._max_tokens
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@max_tokens.setter
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def max_tokens(self, value):
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value = int(value)
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if value < 15 or value > 4096:
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raise ValueError("max_tokens must be greater than 15 and less than 4096, it is currently " + str(value))
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self._max_tokens = value
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@property
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def presence_penalty(self):
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return self._presence_penalty
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@presence_penalty.setter
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def presence_penalty(self, value):
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if int(value) < 0:
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raise ValueError("presence_penalty must be greater than 0, it is currently " + str(value))
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self._presence_penalty = value
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@property
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def frequency_penalty(self):
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return self._frequency_penalty
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@frequency_penalty.setter
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def frequency_penalty(self, value):
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if int(value) < 0:
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raise ValueError("frequency_penalty must be greater than 0, it is currently " + str(value))
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self._frequency_penalty = value
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@property
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def best_of(self):
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return self._best_of
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@best_of.setter
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def best_of(self, value):
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value = int(value)
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if value < 1 or value > 3:
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raise ValueError("best_of must be greater than 0 and ideally less than 3 to save tokens, it is currently " + str(value))
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self._best_of = value
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@property
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def prompt_min_length(self):
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return self._prompt_min_length
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@prompt_min_length.setter
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def prompt_min_length(self, value):
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value = int(value)
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if value < 10 or value > 4096:
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raise ValueError("prompt_min_length must be greater than 10 and less than 4096, it is currently " + str(value))
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self._prompt_min_length = value
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def send_request(self, prompt):
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# Validate that all the parameters are in a good state before we send the request
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if len(prompt) < self.prompt_min_length:
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raise ValueError("Prompt must be greater than 25 characters, it is currently " + str(len(prompt)))
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print("The prompt about to be sent is " + prompt)
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response = openai.Completion.create(
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model="text-davinci-003",
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prompt=prompt,
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temperature=self.temp,
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top_p=self.top_p,
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max_tokens=self.max_tokens,
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presence_penalty=self.presence_penalty,
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frequency_penalty=self.frequency_penalty,
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best_of=self.best_of,
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)
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print(response.__dict__)
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return response
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bot = commands.Bot(command_prefix="gpt3 ")
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model = Model()
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last_used = {}
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GLOBAL_COOLDOWN_TIME = 5 # In seconds
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class DiscordBot:
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def __init__(self, bot):
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self.bot = bot
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bot.run(os.getenv('DISCORD_TOKEN'))
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self.last_used = {}
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@staticmethod
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@bot.event # Using self gives u
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async def on_ready(): # I can make self optional by
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print('We have logged in as {0.user}'.format(bot))
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@staticmethod
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@bot.event
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async def on_message(message):
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if message.author == bot.user:
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return
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if not message.content.startswith('!g'):
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return
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# Implement a global 20 second timer for using the bot:
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# If the user has used the bot in the last 20 seconds, don't let them use it again
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# We can implement that lie this:
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if message.author.id in last_used:
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if time.time() - last_used[message.author.id] < GLOBAL_COOLDOWN_TIME:
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# Tell the user the remaining global cooldown time, respond to the user's original message as a "reply"
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await message.reply("You must wait " + str(round(GLOBAL_COOLDOWN_TIME - (time.time() - last_used[message.author.id]))) + " seconds before using the bot again")
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return
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last_used[message.author.id] = time.time()
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# Print settings command
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if message.content == "!g":
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# create a discord embed with help text
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embed = discord.Embed(title="GPT3Bot Help", description="The current commands", color=0x00ff00)
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embed.add_field(name="!g <prompt>", value="Ask GPT3 something. Be clear, long, and concise in your prompt. Don't waste tokens.", inline=False)
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embed.add_field(name="!gp", value="Print the current settings of the model", inline=False)
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embed.add_field(name="!gs <model parameter> <value>", value="Change the parameter of the model named by <model parameter> to new value <value>", inline=False)
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embed.add_field(name="!g", value="See this help text", inline=False)
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await message.channel.send(embed=embed)
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elif message.content.startswith('!gp'):
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embed = discord.Embed(title="GPT3Bot Settings", description="The current settings of the model", color=0x00ff00)
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for key, value in model.__dict__.items():
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embed.add_field(name=key, value=value, inline=False)
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await message.channel.send(embed=embed)
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elif message.content.startswith('!gs'):
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# Extract the parameter and the value
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parameter = message.content[4:].split()[0]
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value = message.content[4:].split()[1]
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# Check if the parameter is a valid parameter
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if hasattr(model, parameter):
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# Check if the value is a valid value
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try:
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# Set the parameter to the value
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setattr(model, parameter, value)
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await message.channel.send("Successfully set the parameter " + parameter + " to " + value)
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if parameter == "mode":
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await message.channel.send(
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"The mode has been set to " + value + ". This has changed the temperature top_p to the mode defaults of " + str(
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model.temp) + " and " + str(model.top_p))
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except ValueError as e:
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await message.channel.send(e)
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else:
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await message.channel.send("The parameter is not a valid parameter")
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# GPT3 command
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elif message.content.startswith('!g'):
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# Extract all the text after the !g and use it as the prompt.
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prompt = message.content[2:]
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# Send the request to the model
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try:
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response = model.send_request(prompt)
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response_text = response["choices"][0]["text"]
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print(response_text)
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# If the response text is > 3500 characters, paginate and send
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if len(response_text) > 1900:
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# Split the response text into 3500 character chunks
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response_text = [response_text[i:i + 1900] for i in range(0, len(response_text), 1900)]
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# Send each chunk as a message
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for chunk in response_text:
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await message.channel.send(chunk)
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else:
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await message.channel.send(response_text)
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except ValueError as e:
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await message.channel.send(e)
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return
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except Exception as e:
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await message.channel.send("Something went wrong, please try again later")
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await message.channel.send(e)
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return
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# Run the bot with a token taken from an environment file.
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if __name__ == "__main__":
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bot = DiscordBot(bot)
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