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import discord
import aiohttp
import ast
import os
import threading
intents = discord.Intents.default()
intents.message_content = True
bot = discord.Bot(intents = intents)
token = os.environ.get('TOKEN_DISCORD')
class Like_Dislike(discord.ui.View):
@discord.ui.button(style=discord.ButtonStyle.primary, emoji="👍")
async def like_button(self, button, interaction):
await interaction.response.send_message("You liked the response")
@discord.ui.button(style=discord.ButtonStyle.primary, emoji="👎")
async def dislike_button(self, button, interaction):
await interaction.response.send_message("You disliked the response")
@bot.event
async def on_ready():
print(f"{bot.user} is ready and online!")
@bot.slash_command(name="help", description="list of commands and other info.")
async def help(ctx: discord.ApplicationContext):
await ctx.respond("Hello! FURY Bot responds to all your messages\
\n1)Inside Forum channel and\
\n2)Those that tag the bot.")
async def llm_output(question: str, context: str) -> str:
"""
Returns output from the LLM using the given user-question and retrived context
"""
URL_LLM = 'https://robinroy03-fury-bot.hf.space'
# URL_LLM = 'http://localhost:11434' # NOTE: FOR TESTING
prompt = f"""
You are a senior FURY developer. FURY is a high level python graphics API similar to VTK.
Question: {question}
Context: {context}
"""
obj = {
'model': 'llama3-70b-8192',
'prompt': prompt,
'stream': False
}
async with aiohttp.ClientSession() as session:
async with session.post(URL_LLM + "/api/generate", json=obj) as response:
response_json = await response.json()
return response_json['choices'][0]['message']['content']
async def embedding_output(message: str) -> list:
"""
Returns embeddings for the given message
rtype: list of embeddings. Length depends on the model.
"""
URL_EMBEDDING = 'https://robinroy03-fury-embeddings-endpoint.hf.space'
async with aiohttp.ClientSession() as session:
async with session.post(URL_EMBEDDING + "/embedding", json={"text": message}) as response:
response_json = await response.json(content_type=None)
return response_json['output']
async def db_output(embedding: list) -> dict:
"""
Returns the KNN results.
rtype: JSON
"""
URL_DB = 'https://robinroy03-fury-db-endpoint.hf.space'
async with aiohttp.ClientSession() as session:
async with session.post(URL_DB + "/query", json={"embeddings": embedding}) as response:
response_json = await response.json()
return response_json
@bot.event
async def on_message(message):
"""
Returns llm answer with the relevant context.
"""
if (message.author == bot.user) or not(bot.user.mentioned_in(message)):
return
print(message.content)
await message.reply(content="Your message was received, it'll take around 30 seconds for FURY to process an answer.")
question = message.content.replace("<@1243428204124045385>", "")
embedding: list = await embedding_output(question)
db_knn: dict = await db_output(embedding)
db_context = ""
references = ""
for i in range(len(db_knn['matches'])):
data = db_knn['matches'][i]['metadata']['data']
db_context += (data + "\n")
data = ast.literal_eval(data)
references += ("<https://github.com/fury-gl/fury/tree/master/" + data['path'] + ">")
if data.get("function_name"):
references += f"\tFunction Name: {data.get('function_name')}"
else:
references += f"\tClass Name: {data.get('class_name')}"
references += "\n"
llm_answer: str = await llm_output(question, db_context) # for the highest knn result (for the test only right now) TODO: make this better
try:
await message.reply(content=llm_answer[:1990], view=Like_Dislike()) # TODO: handle large responses (>2000)
await message.reply(content=f"**References**\n{references}")
except Exception as e: # TODO: make exception handling better
print(e)
await message.reply("An error occurred. Retry again.")
def run_bot():
bot.run(token)
# ===========================================================================================================================================================
from flask import Flask
app = Flask(__name__)
@app.route("/")
def home():
return "The bot is online."
threading.Thread(target=run_bot).start()
app.run()
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