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38 KiB

2 years ago
import datetime
import re
import traceback
import aiohttp
import discord
from discord.ext import pages
from models.embed_statics_model import EmbedStatics
2 years ago
from services.deletion_service import Deletion
from models.openai_model import Model
from models.user_model import EmbeddedConversationItem, RedoUser
from services.environment_service import EnvService
BOT_NAME = EnvService.get_custom_bot_name()
2 years ago
class TextService:
def __init__(self):
pass
@staticmethod
async def encapsulated_send(
converser_cog,
id,
prompt,
ctx,
response_message=None,
temp_override=None,
top_p_override=None,
frequency_penalty_override=None,
presence_penalty_override=None,
instruction=None,
from_ask_command=False,
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from_edit_command=False,
codex=False,
model=None,
user=None,
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custom_api_key=None,
edited_request=False,
redo_request=False,
from_action=False,
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):
"""General service function for sending and recieving gpt generations
Args:
converser_cog (Cog): The conversation cog with our gpt commands
id (user or thread id): A user or thread id for keeping track of conversations
prompt (str): The prompt to use for generation
ctx (ApplicationContext): The interaction which called this
response_message (discord.Message, optional): For when we're doing redos. Defaults to None.
temp_override (float, optional): Sets the temperature for the generation. Defaults to None.
top_p_override (float, optional): Sets the top p for the generation. Defaults to None.
frequency_penalty_override (float, optional): Sets the frequency penalty for the generation. Defaults to None.
presence_penalty_override (float, optional): Sets the presence penalty for the generation. Defaults to None.
instruction (str, optional): Instruction for use with the edit endpoint. Defaults to None.
from_ask_command (bool, optional): Called from the ask command. Defaults to False.
from_edit_command (bool, optional): Called from the edit command. Defaults to False.
codex (bool, optional): Pass along that we want to use a codex model. Defaults to False.
model (str, optional): Which model to genereate output with. Defaults to None.
custom_api_key (str, optional): per-user api key. Defaults to None.
edited_request (bool, optional): If we're doing an edited message. Defaults to False.
redo_request (bool, optional): If we're redoing a previous prompt. Defaults to False.
from_action (bool, optional): If the function is being called from a message action. Defaults to False.
"""
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new_prompt = (
prompt + "\n" + BOT_NAME
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if not from_ask_command and not from_edit_command
else prompt
)
stop = f"{ctx.author.display_name if user is None else user.display_name}:"
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from_context = isinstance(ctx, discord.ApplicationContext)
if not instruction:
tokens = converser_cog.usage_service.count_tokens(new_prompt)
else:
tokens = converser_cog.usage_service.count_tokens(
new_prompt
) + converser_cog.usage_service.count_tokens(instruction)
try:
# Pinecone is enabled, we will create embeddings for this conversation.
if (
converser_cog.pinecone_service
and ctx.channel.id in converser_cog.conversation_threads
):
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# Delete "GPTie: <|endofstatement|>" from the user's conversation history if it exists
for item in converser_cog.conversation_threads[ctx.channel.id].history:
if item.text.strip() == BOT_NAME + "<|endofstatement|>":
converser_cog.conversation_threads[
ctx.channel.id
].history.remove(item)
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# The conversation_id is the id of the thread
conversation_id = ctx.channel.id
# Create an embedding and timestamp for the prompt
new_prompt = prompt.encode("ascii", "ignore").decode()
prompt_less_author = f"{new_prompt} <|endofstatement|>\n"
user_displayname = ctx.author.display_name
new_prompt = (
f"\n'{user_displayname}': {new_prompt} <|endofstatement|>\n"
)
new_prompt = new_prompt.encode("ascii", "ignore").decode()
timestamp = int(
str(datetime.datetime.now().timestamp()).replace(".", "")
)
new_prompt_item = EmbeddedConversationItem(new_prompt, timestamp)
if not redo_request:
converser_cog.conversation_threads[conversation_id].history.append(
new_prompt_item
)
if edited_request:
new_prompt = "".join(
[
item.text
for item in converser_cog.conversation_threads[
ctx.channel.id
].history
]
)
converser_cog.redo_users[ctx.author.id].prompt = new_prompt
else:
# Create and upsert the embedding for the conversation id, prompt, timestamp
await converser_cog.pinecone_service.upsert_conversation_embedding(
converser_cog.model,
conversation_id,
new_prompt,
timestamp,
custom_api_key=custom_api_key,
)
embedding_prompt_less_author = await converser_cog.model.send_embedding_request(
prompt_less_author, custom_api_key=custom_api_key
) # Use the version of the prompt without the author's name for better clarity on retrieval.
# Now, build the new prompt by getting the X most similar with pinecone
similar_prompts = converser_cog.pinecone_service.get_n_similar(
conversation_id,
embedding_prompt_less_author,
n=converser_cog.model.num_conversation_lookback,
)
# When we are in embeddings mode, only the pre-text is contained in converser_cog.conversation_threads[message.channel.id].history, so we
# can use that as a base to build our new prompt
prompt_with_history = [
converser_cog.conversation_threads[ctx.channel.id].history[0]
]
# Append the similar prompts to the prompt with history
prompt_with_history += [
EmbeddedConversationItem(prompt, timestamp)
for prompt, timestamp in similar_prompts
]
# iterate UP TO the last X prompts in the history
for i in range(
1,
min(
len(
converser_cog.conversation_threads[
ctx.channel.id
].history
),
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converser_cog.model.num_static_conversation_items,
),
):
prompt_with_history.append(
converser_cog.conversation_threads[ctx.channel.id].history[
-i
]
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)
# remove duplicates from prompt_with_history and set the conversation history
prompt_with_history = list(dict.fromkeys(prompt_with_history))
converser_cog.conversation_threads[
ctx.channel.id
].history = prompt_with_history
# Sort the prompt_with_history by increasing timestamp if pinecone is enabled
if converser_cog.pinecone_service:
prompt_with_history.sort(key=lambda x: x.timestamp)
# Ensure that the last prompt in this list is the prompt we just sent (new_prompt_item)
if prompt_with_history[-1] != new_prompt_item:
try:
prompt_with_history.remove(new_prompt_item)
except ValueError:
pass
prompt_with_history.append(new_prompt_item)
prompt_with_history = "".join(
[item.text for item in prompt_with_history]
)
new_prompt = prompt_with_history + "\n" + BOT_NAME
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tokens = converser_cog.usage_service.count_tokens(new_prompt)
# No pinecone, we do conversation summarization for long term memory instead
elif (
id in converser_cog.conversation_threads
and tokens > converser_cog.model.summarize_threshold
and not from_ask_command
and not from_edit_command
and not converser_cog.pinecone_service # This should only happen if we are not doing summarizations.
):
# We don't need to worry about the differences between interactions and messages in this block,
# because if we are in this block, we can only be using a message object for ctx
if converser_cog.model.summarize_conversations:
await ctx.reply(
"I'm currently summarizing our current conversation so we can keep chatting, "
"give me one moment!"
)
await converser_cog.summarize_conversation(ctx, new_prompt)
# Check again if the prompt is about to go past the token limit
new_prompt = (
"".join(
[
item.text
for item in converser_cog.conversation_threads[
id
].history
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]
)
+ "\n"
+ BOT_NAME
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)
tokens = converser_cog.usage_service.count_tokens(new_prompt)
if (
tokens > converser_cog.model.summarize_threshold - 150
): # 150 is a buffer for the second stage
await ctx.reply(
"I tried to summarize our current conversation so we could keep chatting, "
"but it still went over the token "
"limit. Please try again later."
)
await converser_cog.end_conversation(ctx)
converser_cog.remove_awaiting(ctx.author.id, ctx.channel.id)
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return
else:
await ctx.reply("The conversation context limit has been reached.")
await converser_cog.end_conversation(ctx)
return
# Send the request to the model
if from_edit_command:
response = await converser_cog.model.send_edit_request(
text=new_prompt,
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instruction=instruction,
temp_override=temp_override,
top_p_override=top_p_override,
codex=codex,
custom_api_key=custom_api_key,
)
else:
response = await converser_cog.model.send_request(
new_prompt,
tokens=tokens,
temp_override=temp_override,
top_p_override=top_p_override,
frequency_penalty_override=frequency_penalty_override,
presence_penalty_override=presence_penalty_override,
model=model,
stop=stop if not from_ask_command else None,
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custom_api_key=custom_api_key,
)
# Clean the request response
response_text = converser_cog.cleanse_response(
str(response["choices"][0]["text"])
)
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if from_ask_command or from_action:
response_text = f"***{prompt}***{response_text}"
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elif from_edit_command:
if codex:
response_text = response_text.strip()
response_text = f"***Prompt: {prompt}***\n***Instruction: {instruction}***\n\n```\n{response_text}\n```"
else:
response_text = response_text.strip()
response_text = f"***Prompt: {prompt}***\n***Instruction: {instruction}***\n\n{response_text}\n"
# If gpt3 tries writing a user mention try to replace it with their name
response_text = await converser_cog.mention_to_username(ctx, response_text)
# If the user is conversing, add the GPT response to their conversation history.
if (
id in converser_cog.conversation_threads
and not from_ask_command
and not converser_cog.pinecone_service
):
if not redo_request:
converser_cog.conversation_threads[id].history.append(
EmbeddedConversationItem(
"\n"
+ BOT_NAME
+ str(response_text)
+ "<|endofstatement|>\n",
0,
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)
)
# Embeddings case!
elif (
id in converser_cog.conversation_threads
and not from_ask_command
and not from_edit_command
and converser_cog.pinecone_service
):
conversation_id = id
# Create an embedding and timestamp for the prompt
response_text = (
"\n" + BOT_NAME + str(response_text) + "<|endofstatement|>\n"
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)
response_text = response_text.encode("ascii", "ignore").decode()
# Print the current timestamp
timestamp = int(
str(datetime.datetime.now().timestamp()).replace(".", "")
)
converser_cog.conversation_threads[conversation_id].history.append(
EmbeddedConversationItem(response_text, timestamp)
)
# Create and upsert the embedding for the conversation id, prompt, timestamp
embedding = (
await converser_cog.pinecone_service.upsert_conversation_embedding(
converser_cog.model,
conversation_id,
response_text,
timestamp,
custom_api_key=custom_api_key,
)
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)
# Cleanse again
response_text = converser_cog.cleanse_response(response_text)
# escape any other mentions like @here or @everyone
response_text = discord.utils.escape_mentions(response_text)
# If we don't have a response message, we are not doing a redo, send as a new message(s)
if not response_message:
if len(response_text) > converser_cog.TEXT_CUTOFF:
if not from_context:
paginator = None
await converser_cog.paginate_and_send(response_text, ctx)
else:
embed_pages = await converser_cog.paginate_embed(
response_text, codex, prompt, instruction
)
view = ConversationView(
ctx,
converser_cog,
ctx.channel.id,
model,
from_ask_command,
from_edit_command,
custom_api_key=custom_api_key,
)
paginator = pages.Paginator(
pages=embed_pages,
timeout=None,
custom_view=view,
author_check=True,
)
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response_message = await paginator.respond(ctx.interaction)
else:
paginator = None
if not from_context:
response_message = await ctx.reply(
response_text,
view=ConversationView(
ctx,
converser_cog,
ctx.channel.id,
model,
custom_api_key=custom_api_key,
),
)
elif from_edit_command:
response_message = await ctx.respond(
response_text,
view=ConversationView(
ctx,
converser_cog,
ctx.channel.id,
model,
from_edit_command=from_edit_command,
custom_api_key=custom_api_key,
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),
)
else:
response_message = await ctx.respond(
response_text,
view=ConversationView(
ctx,
converser_cog,
ctx.channel.id,
model,
from_ask_command=from_ask_command,
custom_api_key=custom_api_key,
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),
)
if response_message:
# Get the actual message object of response_message in case it's an WebhookMessage
actual_response_message = (
response_message
if not from_context
else await ctx.fetch_message(response_message.id)
)
converser_cog.redo_users[ctx.author.id] = RedoUser(
prompt=new_prompt,
instruction=instruction,
ctx=ctx,
message=ctx,
response=actual_response_message,
codex=codex,
paginator=paginator,
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)
converser_cog.redo_users[ctx.author.id].add_interaction(
actual_response_message.id
)
# We are doing a redo, edit the message.
else:
paginator = converser_cog.redo_users.get(ctx.author.id).paginator
if isinstance(paginator, pages.Paginator):
embed_pages = await converser_cog.paginate_embed(
response_text, codex, prompt, instruction
)
view = ConversationView(
ctx,
converser_cog,
ctx.channel.id,
model,
from_ask_command,
from_edit_command,
custom_api_key=custom_api_key,
)
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await paginator.update(pages=embed_pages, custom_view=view)
elif len(response_text) > converser_cog.TEXT_CUTOFF:
if not from_context:
await response_message.channel.send(
"Over 2000 characters", delete_after=5
)
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else:
await response_message.edit(content=response_text)
await converser_cog.send_debug_message(
converser_cog.generate_debug_message(prompt, response),
converser_cog.debug_channel,
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)
converser_cog.remove_awaiting(
ctx.author.id, ctx.channel.id, from_ask_command, from_edit_command
)
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# Error catching for AIOHTTP Errors
except aiohttp.ClientResponseError as e:
embed = EmbedStatics.get_invalid_api_response_embed(e)
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if from_context:
await ctx.send_followup(embed=embed)
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else:
await ctx.reply(embed=embed)
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converser_cog.remove_awaiting(
ctx.author.id, ctx.channel.id, from_ask_command, from_edit_command
)
# Error catching for OpenAI model value errors
except ValueError as e:
embed = EmbedStatics.get_invalid_value_embed(e)
if from_action:
await ctx.respond(embed=embed, ephemeral=True)
elif from_context:
await ctx.send_followup(embed=embed, ephemeral=True)
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else:
await ctx.reply(e)
converser_cog.remove_awaiting(
ctx.author.id, ctx.channel.id, from_ask_command, from_edit_command
)
# General catch case for everything
except Exception as e:
embed = EmbedStatics.get_general_error_embed(e)
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if not from_context:
await ctx.send_followup(embed=embed)
elif from_ask_command:
await ctx.respond(embed=embed)
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else:
await ctx.reply(embed=embed)
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converser_cog.remove_awaiting(
ctx.author.id, ctx.channel.id, from_ask_command, from_edit_command
)
traceback.print_exc()
try:
await converser_cog.end_conversation(ctx)
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except Exception:
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pass
return
@staticmethod
async def process_conversation_message(
converser_cog, message, USER_INPUT_API_KEYS, USER_KEY_DB
):
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content = message.content.strip()
conversing = converser_cog.check_conversing(message.channel.id, content)
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# If the user is conversing and they want to end it, end it immediately before we continue any further.
if conversing and message.content.lower() in converser_cog.END_PROMPTS:
await converser_cog.end_conversation(message)
return
if conversing:
user_api_key = None
if USER_INPUT_API_KEYS:
user_api_key = await TextService.get_user_api_key(
message.author.id, message, USER_KEY_DB
)
if not user_api_key:
return
prompt = await converser_cog.mention_to_username(message, content)
await converser_cog.check_conversation_limit(message)
# If the user is in a conversation thread
if message.channel.id in converser_cog.conversation_threads:
# Since this is async, we don't want to allow the user to send another prompt while a conversation
# prompt is processing, that'll mess up the conversation history!
if message.author.id in converser_cog.awaiting_responses:
message = await message.reply(
embed=discord.Embed(
title=f"You are already waiting for a response, please wait and speak afterwards.",
color=0x808080,
)
)
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# get the current date, add 10 seconds to it, and then turn it into a timestamp.
# we need to use our deletion service because this isn't an interaction, it's a regular message.
deletion_time = datetime.datetime.now() + datetime.timedelta(
seconds=10
)
deletion_time = deletion_time.timestamp()
deletion_message = Deletion(message, deletion_time)
await converser_cog.deletion_queue.put(deletion_message)
return
if message.channel.id in converser_cog.awaiting_thread_responses:
message = await message.reply(
embed=discord.Embed(
title=f"This thread is already waiting for a response, please wait and speak afterwards.",
color=0x808080,
)
)
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# get the current date, add 10 seconds to it, and then turn it into a timestamp.
# we need to use our deletion service because this isn't an interaction, it's a regular message.
deletion_time = datetime.datetime.now() + datetime.timedelta(
seconds=10
)
deletion_time = deletion_time.timestamp()
deletion_message = Deletion(message, deletion_time)
await converser_cog.deletion_queue.put(deletion_message)
return
converser_cog.awaiting_responses.append(message.author.id)
converser_cog.awaiting_thread_responses.append(message.channel.id)
if not converser_cog.pinecone_service:
converser_cog.conversation_threads[
message.channel.id
].history.append(
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EmbeddedConversationItem(
f"\n{message.author.display_name}: {prompt} <|endofstatement|>\n",
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0,
)
)
# increment the conversation counter for the user
converser_cog.conversation_threads[message.channel.id].count += 1
# Send the request to the model
# If conversing, the prompt to send is the history, otherwise, it's just the prompt
if (
converser_cog.pinecone_service
or message.channel.id not in converser_cog.conversation_threads
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):
primary_prompt = prompt
else:
primary_prompt = "".join(
[
item.text
for item in converser_cog.conversation_threads[
message.channel.id
].history
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]
)
# set conversation overrides
overrides = converser_cog.conversation_threads[
message.channel.id
].get_overrides()
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await TextService.encapsulated_send(
converser_cog,
message.channel.id,
primary_prompt,
message,
temp_override=overrides["temperature"],
top_p_override=overrides["top_p"],
frequency_penalty_override=overrides["frequency_penalty"],
presence_penalty_override=overrides["presence_penalty"],
model=converser_cog.conversation_threads[message.channel.id].model,
custom_api_key=user_api_key,
)
return True
@staticmethod
async def get_user_api_key(user_id, ctx, USER_KEY_DB):
user_api_key = None if user_id not in USER_KEY_DB else USER_KEY_DB[user_id]
if user_api_key is None or user_api_key == "":
modal = SetupModal(user_key_db=USER_KEY_DB)
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if isinstance(ctx, discord.ApplicationContext):
await ctx.send_modal(modal)
await ctx.send_followup(
"You must set up your API key before using this command."
)
else:
await ctx.reply(
"You must set up your API key before typing in a GPT3 powered channel, type `/setup` to enter your API key."
)
return user_api_key
@staticmethod
async def process_conversation_edit(converser_cog, after, original_message):
if after.author.id in converser_cog.redo_users:
if after.id == original_message[after.author.id]:
response_message = converser_cog.redo_users[after.author.id].response
ctx = converser_cog.redo_users[after.author.id].ctx
await response_message.edit(content="Redoing prompt 🔄...")
edited_content = await converser_cog.mention_to_username(
after, after.content
)
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if after.channel.id in converser_cog.conversation_threads:
# Remove the last two elements from the history array and add the new <username>: prompt
converser_cog.conversation_threads[
after.channel.id
].history = converser_cog.conversation_threads[
after.channel.id
].history[
:-2
]
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pinecone_dont_reinsert = None
if not converser_cog.pinecone_service:
converser_cog.conversation_threads[
after.channel.id
].history.append(
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EmbeddedConversationItem(
f"\n{after.author.display_name}: {after.content}<|endofstatement|>\n",
0,
)
)
converser_cog.conversation_threads[after.channel.id].count += 1
overrides = converser_cog.conversation_threads[
after.channel.id
].get_overrides()
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await TextService.encapsulated_send(
converser_cog,
id=after.channel.id,
prompt=edited_content,
ctx=ctx,
response_message=response_message,
temp_override=overrides["temperature"],
top_p_override=overrides["top_p"],
frequency_penalty_override=overrides["frequency_penalty"],
presence_penalty_override=overrides["presence_penalty"],
model=converser_cog.conversation_threads[after.channel.id].model,
edited_request=True,
)
if not converser_cog.pinecone_service:
converser_cog.redo_users[after.author.id].prompt = edited_content
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#
# Conversation interaction buttons
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#
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class ConversationView(discord.ui.View):
def __init__(
self,
ctx,
converser_cog,
id,
model,
from_ask_command=False,
from_edit_command=False,
custom_api_key=None,
):
super().__init__(timeout=3600) # 1 hour interval to redo.
self.converser_cog = converser_cog
self.ctx = ctx
self.model = model
self.from_ask_command = from_ask_command
self.from_edit_command = from_edit_command
self.custom_api_key = custom_api_key
self.add_item(
RedoButton(
self.converser_cog,
model=model,
from_ask_command=from_ask_command,
from_edit_command=from_edit_command,
custom_api_key=self.custom_api_key,
)
)
if id in self.converser_cog.conversation_threads:
self.add_item(EndConvoButton(self.converser_cog))
async def on_timeout(self):
# Remove the button from the view/message
self.clear_items()
# Send a message to the user saying the view has timed out
if self.message:
await self.message.edit(
view=None,
)
else:
await self.ctx.edit(
view=None,
)
class EndConvoButton(discord.ui.Button["ConversationView"]):
def __init__(self, converser_cog):
super().__init__(
style=discord.ButtonStyle.danger,
label="End Conversation",
custom_id="conversation_end",
)
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self.converser_cog = converser_cog
async def callback(self, interaction: discord.Interaction):
# Get the user
user_id = interaction.user.id
if (
user_id in self.converser_cog.conversation_thread_owners
and self.converser_cog.conversation_thread_owners[user_id]
== interaction.channel.id
):
try:
await self.converser_cog.end_conversation(
interaction, opener_user_id=interaction.user.id
)
except Exception as e:
print(e)
traceback.print_exc()
await interaction.response.send_message(
e, ephemeral=True, delete_after=30
)
else:
await interaction.response.send_message(
"This is not your conversation to end!", ephemeral=True, delete_after=10
)
class RedoButton(discord.ui.Button["ConversationView"]):
def __init__(
self, converser_cog, model, from_ask_command, from_edit_command, custom_api_key
):
super().__init__(
style=discord.ButtonStyle.danger,
label="Retry",
custom_id="conversation_redo",
)
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self.converser_cog = converser_cog
self.model = model
self.from_ask_command = from_ask_command
self.from_edit_command = from_edit_command
self.custom_api_key = custom_api_key
async def callback(self, interaction: discord.Interaction):
# Get the user
user_id = interaction.user.id
if user_id in self.converser_cog.redo_users and self.converser_cog.redo_users[
user_id
].in_interaction(interaction.message.id):
# Get the message and the prompt and call encapsulated_send
prompt = self.converser_cog.redo_users[user_id].prompt
instruction = self.converser_cog.redo_users[user_id].instruction
ctx = self.converser_cog.redo_users[user_id].ctx
response_message = self.converser_cog.redo_users[user_id].response
codex = self.converser_cog.redo_users[user_id].codex
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await interaction.response.send_message(
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"Retrying your original request...", ephemeral=True, delete_after=15
)
await TextService.encapsulated_send(
self.converser_cog,
id=user_id,
prompt=prompt,
instruction=instruction,
ctx=ctx,
model=self.model,
response_message=response_message,
codex=codex,
custom_api_key=self.custom_api_key,
redo_request=True,
from_ask_command=self.from_ask_command,
from_edit_command=self.from_edit_command,
)
else:
await interaction.response.send_message(
"You can only redo the most recent prompt that you sent yourself.",
ephemeral=True,
delete_after=10,
)
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#
# The setup modal when using user input API keys
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#
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class SetupModal(discord.ui.Modal):
def __init__(self, user_key_db) -> None:
super().__init__(title="API Key Setup")
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# Get the argument named "user_key_db" and save it as USER_KEY_DB
self.USER_KEY_DB = user_key_db
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self.add_item(
discord.ui.InputText(
label="OpenAI API Key",
placeholder="sk--......",
)
)
async def callback(self, interaction: discord.Interaction):
user = interaction.user
api_key = self.children[0].value
# Validate that api_key is indeed in this format
if not re.match(r"sk-[a-zA-Z0-9]{32}", api_key):
await interaction.response.send_message(
"Your API key looks invalid, please check that it is correct before proceeding. Please run the /setup command to set your key.",
ephemeral=True,
delete_after=100,
)
else:
# We can save the key for the user to the database.
# Make a test request using the api key to ensure that it is valid.
try:
await Model.send_test_request(api_key)
await interaction.response.send_message(
"Your API key was successfully validated.",
ephemeral=True,
delete_after=10,
)
except aiohttp.ClientResponseError as e:
await interaction.response.send_message(
embed=EmbedStatics.get_invalid_api_response_embed(e),
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ephemeral=True,
delete_after=30,
)
return
except Exception as e:
await interaction.response.send_message(
f"Your API key looks invalid, the API returned: {e}. Please check that your API key is correct before proceeding",
ephemeral=True,
delete_after=30,
)
return
# Save the key to the database
try:
self.USER_KEY_DB[user.id] = api_key
self.USER_KEY_DB.commit()
await interaction.followup.send(
"Your API key was successfully saved.",
ephemeral=True,
delete_after=10,
)
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except Exception:
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traceback.print_exc()
await interaction.followup.send(
"There was an error saving your API key.",
ephemeral=True,
delete_after=30,
)
return