Merge pull request #61 from bucolucas/remove-discord-bot
Remove discord_inference_bot.py
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@@ -1,192 +0,0 @@
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import json
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import os
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import importlib
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import inspect
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import tempfile
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import base64
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from discord.ext import commands
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from openai import OpenAI
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from dotenv import load_dotenv
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from tools.base_tool import BaseTool
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# Load environment variables
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load_dotenv()
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client = OpenAI()
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GPT_4O = "gpt-4o"
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GPT_4O_MINI = "gpt-4o-mini"
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# Load system prompt
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with open("prompts/developer_prompt.txt", "r") as file:
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system_prompt = file.read().strip()
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# Set up Discord bot
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DISCORD_BOT_TOKEN = os.getenv('DISCORD_BOT_TOKEN')
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# Dictionary to store conversation history for each user
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conversation_history = {}
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# Dictionary to store the last image file for each user
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user_images = {}
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# Load tools
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tools = []
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tools_dir = os.path.join(os.path.dirname(__file__), 'tools')
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for filename in os.listdir(tools_dir):
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if filename.endswith('.py') and filename != '__init__.py' and filename != 'base_tool.py':
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module_name = f'tools.{filename[:-3]}'
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module = importlib.import_module(module_name)
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for name, obj in inspect.getmembers(module):
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if inspect.isclass(obj) and issubclass(obj, BaseTool) and obj != BaseTool:
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tools.append(obj())
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# Collect all function definitions
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functions = []
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for tool in tools:
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functions.extend(tool.get_functions())
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bot = commands.Bot(command_prefix='!')
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@bot.event
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async def on_ready():
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print(f'Bot is ready and logged in as {bot.user}')
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@bot.command(name='start')
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async def start(ctx):
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await ctx.send("Hello! I'm your AI assistant. How can I help you today? You can send me images and then ask questions about them.")
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@bot.command(name='clear')
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async def clear(ctx):
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user_id = ctx.author.id
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if user_id in conversation_history:
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del conversation_history[user_id]
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if user_id in user_images:
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os.remove(user_images[user_id])
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del user_images[user_id]
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await ctx.send("Conversation history and image cleared. Let's start fresh!")
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@bot.event
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async def on_message(message):
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# This is required to let commands still work, since on_message overrides the default handler
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await bot.process_commands(message)
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if message.author == bot.user:
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return
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user_id = message.author.id
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user_message = message.content
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# Initialize conversation history for new users
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if user_id not in conversation_history:
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conversation_history[user_id] = []
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# Add user message to conversation history
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conversation_history[user_id].append({"role": "user", "content": user_message})
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# Prepare messages for OpenAI API
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messages = [{"role": "system", "content": system_prompt}] + conversation_history[user_id]
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# Check if there's an image to process
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if user_id in user_images:
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with open(user_images[user_id], "rb") as image_file:
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response = client.chat_completions_create(
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model=GPT_4O_MINI,
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messages=[
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{
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"role": "user",
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"content": [
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{"type": "text", "text": user_message},
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{
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"type": "image_url",
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"image_url": {
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"url": f"data:image/jpeg;base64,{base64.b64encode(image_file.read()).decode('utf-8')}"
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}
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},
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],
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}
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],
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max_tokens=16384
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)
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# Remove the temporary image file
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os.remove(user_images[user_id])
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del user_images[user_id]
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else:
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# Call OpenAI API for inference (text-only)
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response = get_chat_response(client, messages, 4096, GPT_4O)
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# Extract the assistant's reply
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assistant_message = response.choices[0].message
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tool_use_count = 0
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if hasattr(assistant_message, 'function_call') and assistant_message.function_call:
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while hasattr(assistant_message, 'function_call') and assistant_message.function_call and tool_use_count < 10:
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tool_response = call_tool(assistant_message.function_call, messages)
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conversation_history[user_id].append({"role": "function", "name": assistant_message.function_call.name, "content": json.dumps(tool_response)})
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messages.append({
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"role": "function",
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"name": assistant_message.function_call.name,
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"content": json.dumps(tool_response)
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})
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# Call API again to get the final response
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assistant_message = get_chat_response(client, messages, 4096, GPT_4O).choices[0].message
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if not hasattr(assistant_message, 'function_call') or not assistant_message.function_call:
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assistant_reply = assistant_message.content
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conversation_history[user_id].append({"role": "assistant", "content": assistant_reply})
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else:
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assistant_reply = assistant_message.content
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# Add assistant's reply to conversation history
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conversation_history[user_id].append({"role": "assistant", "content": assistant_reply})
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# Trim conversation history if it gets too long (e.g., keep last 10 messages)
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if len(conversation_history[user_id]) > 10:
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conversation_history[user_id] = conversation_history[user_id][-10:]
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# Send the reply back to the user
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await message.channel.send(assistant_reply)
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@bot.event
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async def on_message_edit(before, after):
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await on_message(after)
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@bot.event
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async def on_reaction_add(reaction, user):
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if reaction.message.author == bot.user and user != bot.user:
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user_id = user.id
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# Save the reaction as an interaction
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conversation_history[user_id].append({"role": "user", "content": f"{user.name} reacted with {reaction.emoji}"})
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messages = [{"role": "system", "content": system_prompt}] + conversation_history[user_id]
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# Call OpenAI API for inference
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response = get_chat_response(client, messages, 4096, GPT_4O)
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assistant_message = response.choices[0].message
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assistant_reply = assistant_message.content
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conversation_history[user_id].append({"role": "assistant", "content": assistant_reply})
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# Trim conversation history if it gets too long
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if len(conversation_history[user_id]) > 10:
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conversation_history[user_id] = conversation_history[user_id][-10:]
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# Send the reply back to the user
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await reaction.message.channel.send(f"{user.name}, {assistant_reply}")
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def call_tool(function_call, messages):
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# Execute the function
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function_name = function_call.name
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function_args = function_call.arguments
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for tool in tools:
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if function_name in [f["name"] for f in tool.get_functions()]:
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return tool.execute(function_name, **eval(function_args))
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def get_chat_response(client, messages, max_tokens, model):
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response = client.chat_completions_create(
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model=model,
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messages=messages,
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functions=functions,
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function_call="auto",
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max_tokens=max_tokens
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)
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return response
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if __name__ == '__main__':
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bot.run(DISCORD_BOT_TOKEN)
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