Customer Service Discord Bot for Finance with OpenBB

!pip install "camel-ai[all]==0.2.16"

!pip install starlette
!pip install nest_asyncio

import os
from getpass import getpass

qwen_api_key = getpass('Enter your API key: ')
os.environ["QWEN_API_KEY"] = qwen_api_key

# import os
# from google.colab import userdata

# os.environ["QWEN_API_KEY"] = userdata.get("QWEN_API_KEY")

from camel.configs import QwenConfig, MistralConfig
from camel.models import ModelFactory
from camel.types import ModelPlatformType, ModelType

qwen_model = ModelFactory.create(
    model_platform=ModelPlatformType.QWEN,
    model_type=ModelType.QWEN_TURBO,
    model_config_dict=QwenConfig(temperature=0.2).as_dict(),
)

openbb_pat = getpass("Enter your OpenBB PAT: ")
os.environ["OPENBB_TOKEN"] = openbb_pat

# import os
# from google.colab import userdata

# os.environ["OPENBB_TOKEN"] = userdata.get("OPENBB_TOKEN")

from camel.agents import ChatAgent
from camel.messages import BaseMessage
from camel.toolkits import OpenBBToolkit, FunctionTool
from datetime import date

OPENBB_AGENT_SYSTEM_PROMPT = """
You are a helpful assistant providing detailed financial data, including stocks, coins, and similar assets, using OpenBB tools and the date tool.

Role:
    - Deliver accurate, data-driven responses about financial assets using structured ASCII tables.

Objective:
    1. Answer asset-specific queries concisely and professionally.
    2. Always display the current date prominently and interpret relative dates accurately.
    3. Use ASCII tables for all data summaries.

Instructions:
    1. Input Validation:
        - Confirm the query is specific to an asset (e.g., stock, coin, or similar).
        - If unclear, request clarification (e.g., "Could you specify which asset you're referring to?").

    2. Date Awareness:
        - Dynamically fetch and display the current date for context in all responses.
        - Interpret relative dates (e.g., "yesterday," "last week") accurately:
            - "Yesterday": Subtract one day from the current date.
            - "Last week": Provide the range for the previous 7 days from the current date.
            - Ensure the calculated date or date range is clearly displayed.

    3. Symbol Handling:
        - Extract the ticker symbol or lookup based on the asset name.
        - Correct misspellings or broaden the search scope if necessary.

    4. Information Retrieval:
        - Fetch key metrics (e.g., PE ratio, market cap, price trends, trading volume) using the tools in the OpenBB toolkit.
        - If no data could be retrieved using the OpenBB tools, kindly inform the user.
        - Avoid reliance on FMP for data.

    5. Response Composition:
        - Use a professional tone and concise formatting.
        - Represent all data in clean ASCII tables with proper alignment and headers.

Output Guidelines:
    1. Enhanced ASCII Table Format:
        Example:

2. Current Date and Context:
- Prominently include the current date or inferred relative date in all responses:
    - Example:
      *Query:* "Show data for yesterday."
      *Response:* "The data for 2025-01-21 (yesterday) is as follows:"

By following these enhanced instructions, provide clear, accurate, and professional financial data summaries for stocks, coins, and similar assets without graphical visualizations, while incorporating dynamic date awareness.
"""


# Define the date tool
def get_today_date():
r"""Get the date of today."""
return date.today()

# Set up tools to be used
openbb_toolkit = OpenBBToolkit()
openbb_tools = openbb_toolkit.get_tools()
date_tool = [FunctionTool(get_today_date)]

# Set up ChatAgent with defined prompt and tools
openbb_agent = ChatAgent(
system_message=OPENBB_AGENT_SYSTEM_PROMPT,
model=qwen_model,
tools=openbb_tools + date_tool
)

print("Start chatting! Type 'exit' to end the conversation.")
while True:
    user_input = input("User: ")

    if user_input.lower() == "exit":
        print("Ending conversation.")
        break

    assistant_response = openbb_agent.step(user_input)
    print(f"Tool call: {assistant_response.info['tool_calls']}")
    print(f"Assistant: {assistant_response.msgs[0].content}")

import os
from getpass import getpass

discord_bot_token = getpass('Enter your Discord bot token: ')
os.environ["DISCORD_BOT_TOKEN"] = discord_bot_token

# import os
# from google.colab import userdata

# os.environ["DISCORD_BOT_TOKEN"] = userdata.get("DISCORD_BOT_TOKEN")

from camel.bots import DiscordApp
import nest_asyncio
import discord

nest_asyncio.apply()
discord_bot = DiscordApp(token=discord_bot_token)

@discord_bot.client.event
async def on_message(message: discord.Message):
    if message.author == discord_bot.client.user:
        return

    if message.type != discord.MessageType.default:
        return

    if message.author.bot:
        return
    user_input = message.content

    assistant_response = openbb_agent.step(user_input)

    response_content = assistant_response.msgs[0].content

    if len(response_content) > 2000: # discord message length limit
        for chunk in [response_content[i:i+2000] for i in range(0, len(response_content), 2000)]:
            await message.channel.send(chunk)
    else:
        await message.channel.send(response_content)

discord_bot.run()