app.py

#import gradio as gr
#gr.load("models/mistralai/Mistral-7B-Instruct-v0.3").launch()
import os
import requests
import discord
from discord.ext import commands
from dotenv import load_dotenv

# Load environment variables from the .env file
load_dotenv()

DISCORD_TOKEN = os.getenv('dsTOK')
HF_API_KEY = os.getenv('HFREAD')

API_URL = "https://api-inference.huggingface.co/models/mistralai/Mistral-7B-Instruct-v0.3"
headers = {"Authorization": f"Bearer {HF_API_KEY}"}

# Function to query the Hugging Face model with a structured prompt
def query_huggingface(prompt):
    try:
        response = requests.post(API_URL, headers=headers, json={"inputs": prompt})
        response.raise_for_status()
        return response.json()
    except requests.exceptions.RequestException as e:
        print(f"Error querying the API: {e}")
        return {"error": str(e)}

# Initialize the Discord bot
intents = discord.Intents.default()
intents.messages = True
intents.message_content = True

bot = commands.Bot(command_prefix="!", intents=intents)

@bot.event
async def on_ready():
    print(f'Bot is ready. Logged in as {bot.user}')

@bot.command(name='ask')
async def ask(ctx, *, question: str):
    """
    Command to ask a question to the Hugging Face model with an instructive prompt.
    """
    # Create a structured prompt
    prompt = f"From this point forward, I require that all responses adhere to strict content guidelines. Please avoid any content that is explicit, offensive, harmful, or inappropriate. This includes, but is not limited to, content that is violent, sexually explicit, discriminatory, or offensive to any group or individual. Ensure that all information is presented in a respectful and professional manner. If a topic is deemed sensitive or inappropriate, please redirect the conversation to a more suitable subject. Please provide a detailed response to the following question: {question}"
    response = query_huggingface(prompt)
    if 'generated_text' in response:
        await ctx.send(f"Response: {response['generated_text']}")
    elif isinstance(response, list) and len(response) > 0 and 'generated_text' in response[0]:
        await ctx.send(f"Response: {response[0]['generated_text']}")
    else:
        await ctx.send("Sorry, I couldn't generate a response.")

# Run the bot
bot.run(DISCORD_TOKEN)