Spaces:
Sleeping
Sleeping
add persistence
Browse files
app.py
CHANGED
@@ -3,6 +3,12 @@ import discord
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from gradio_client import Client
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from huggingface_hub import InferenceClient
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import os
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# Get tokens from environment variables (Hugging Face Spaces secrets)
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TOKEN = os.getenv("DISCORD_TOKEN")
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@@ -25,11 +31,7 @@ hf_client = InferenceClient(api_key=HF_TOKEN)
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# Function to process message and get response
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async def get_ai_response(message_content):
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try:
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messages = [
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{"role": "user", "content": message_content}
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]
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# Create a streaming response
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response = ""
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stream = hf_client.chat.completions.create(
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model="Qwen/Qwen2.5-72B-Instruct",
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@@ -39,44 +41,29 @@ async def get_ai_response(message_content):
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top_p=0.7,
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stream=True
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)
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# Collect the streamed response
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for chunk in stream:
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content = chunk.choices[0].delta.content
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if content:
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response += content
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return response if response else "I couldn't generate a response."
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except Exception as e:
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return f"An error occurred: {str(e)}"
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@client.event
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async def on_ready():
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@client.event
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async def on_message(message):
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# Ignore messages from the bot itself
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if message.author == client.user:
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return
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# Check if the bot is mentioned in the message
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if client.user in message.mentions:
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# Extract the message content without the bot mention
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clean_message = message.content.replace(f"<@{client.user.id}>", "").strip()
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if not clean_message:
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await message.channel.send("Please provide some text for me to respond to!")
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return
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-
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# Send initial response to show bot is processing
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processing_message = await message.channel.send("Processing your request...")
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# Get AI response
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response = await get_ai_response(clean_message)
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# Split response if it's too long for Discord's 2000 character limit
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if len(response) > 2000:
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chunks = [response[i:i+2000] for i in range(0, len(response), 2000)]
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await processing_message.delete()
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@@ -85,21 +72,34 @@ async def on_message(message):
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else:
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await processing_message.edit(content=response)
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# Error handling for connection issues
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@client.event
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async def on_error(event, *args, **kwargs):
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with open('error.log', 'a') as f:
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f.write(f"{event}\n")
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#
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def
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try:
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client.run(TOKEN)
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except Exception as e:
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with open('error.log', 'a') as f:
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f.write(f"Failed to start bot: {e}\n")
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if __name__ == "__main__":
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from gradio_client import Client
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from huggingface_hub import InferenceClient
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import os
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import logging
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import gradio as gr
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import threading
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# Set up logging
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logging.basicConfig(level=logging.INFO, format='[%(asctime)s] [%(levelname)s] %(message)s')
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# Get tokens from environment variables (Hugging Face Spaces secrets)
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TOKEN = os.getenv("DISCORD_TOKEN")
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# Function to process message and get response
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async def get_ai_response(message_content):
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try:
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messages = [{"role": "user", "content": message_content}]
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response = ""
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stream = hf_client.chat.completions.create(
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model="Qwen/Qwen2.5-72B-Instruct",
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top_p=0.7,
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stream=True
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)
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for chunk in stream:
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content = chunk.choices[0].delta.content
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if content:
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response += content
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return response if response else "I couldn't generate a response."
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except Exception as e:
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return f"An error occurred: {str(e)}"
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@client.event
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async def on_ready():
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logging.info(f'We have logged in as {client.user}')
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@client.event
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async def on_message(message):
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if message.author == client.user:
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return
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if client.user in message.mentions:
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clean_message = message.content.replace(f"<@{client.user.id}>", "").strip()
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if not clean_message:
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await message.channel.send("Please provide some text for me to respond to!")
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return
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processing_message = await message.channel.send("Processing your request...")
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response = await get_ai_response(clean_message)
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if len(response) > 2000:
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chunks = [response[i:i+2000] for i in range(0, len(response), 2000)]
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await processing_message.delete()
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else:
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await processing_message.edit(content=response)
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@client.event
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async def on_error(event, *args, **kwargs):
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logging.error(f"An error occurred: {event}")
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with open('error.log', 'a') as f:
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f.write(f"{event}\n")
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# Function to run the Discord bot in a separate thread
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def run_discord_bot():
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try:
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logging.info("Starting the Discord bot...")
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client.run(TOKEN)
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except Exception as e:
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logging.error(f"Failed to start bot: {e}")
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with open('error.log', 'a') as f:
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f.write(f"Failed to start bot: {e}\n")
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# Gradio interface to keep the Space alive
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def create_interface():
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invite_url = "Add this bot to your server by following this URL: https://discord.com/oauth2/authorize?client_id=1347942347077582880&permissions=377957238784&integration_type=0&scope=bot"
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with gr.Blocks(title="Discord Bot Invite") as demo:
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gr.Markdown(f"# Discord Bot\n{invite_url}")
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return demo
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if __name__ == "__main__":
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# Start the Discord bot in a separate thread
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bot_thread = threading.Thread(target=run_discord_bot, daemon=True)
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bot_thread.start()
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# Launch the Gradio interface
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interface = create_interface()
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interface.launch(server_name="0.0.0.0", server_port=7860)
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