app.py

from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool
import datetime
import requests
import pytz
import yaml
from tools.final_answer import FinalAnswerTool

from Gradio_UI import GradioUI

# Below is an example of a tool that does nothing. Amaze us with your creativity !
@tool
def my_cutom_tool(arg1:str, arg2:int)-> str: #it's import to specify the return type
    #Keep this format for the description / args / args description but feel free to modify the tool
    """A tool that does nothing yet 
    Args:
        arg1: the first argument
        arg2: the second argument
    """
    return "What magic will you build ?"

@tool
def get_current_time_in_timezone(timezone: str) -> str:
    """A tool that fetches the current local time in a specified timezone.
    Args:
        timezone: A string representing a valid timezone (e.g., 'America/New_York').
    """
    try:
        # Create timezone object
        tz = pytz.timezone(timezone)
        # Get current time in that timezone
        local_time = datetime.datetime.now(tz).strftime("%Y-%m-%d %H:%M:%S")
        return f"The current local time in {timezone} is: {local_time}"
    except Exception as e:
        return f"Error fetching time for timezone '{timezone}': {str(e)}"

import baostock as bs
import pandas as pd
@tool
def get_stock_data_baostock(stock_code: str) -> str:
    """Fetch the latest stock data for a given stock code using Baostock.
    Args:
        stock_code: A string representing the stock code (e.g., 'sh.600941' for China Mobile).
    """
    try:
        # Log in to the Baostock system
        lg = bs.login()
        if lg.error_code != '0':
            return f"Failed to log in to Baostock: {lg.error_msg}"

        # Fetch daily K-line data for the stock (defaults to the most recent trading day)
        rs = bs.query_history_k_data_plus(
            code=stock_code,
            fields="date,code,open,high,low,close,volume",  # Fields to retrieve
            frequency="d",  # Daily K-line
            adjustflag="2"  # Adjustment type: 2 for forward adjustment
        )
        if rs.error_code != '0':
            return f"Failed to fetch stock data: {rs.error_msg}"

        # Convert the data to a DataFrame
        data_list = []
        while (rs.error_code == '0') & rs.next():
            data_list.append(rs.get_row_data())
        df = pd.DataFrame(data_list, columns=rs.fields)

        # Log out of the Baostock system
        bs.logout()

        # Check if the data is empty
        if df.empty:
            return f"No data found for stock code '{stock_code}'."

        # Extract the latest trading day's data
        latest_data = df.iloc[-1]  # Get the last row of data (most recent trading day)
        date = latest_data['date']  # Date
        stock_name = latest_data['code']  # Stock code
        close_price = latest_data['close']  # Closing price
        volume = latest_data['volume']  # Trading volume

        # Construct the result string
        result = f"Stock Code: {stock_name}\nDate: {date}\nClosing Price: {close_price}\nVolume: {volume}"
        return result

    except Exception as e:
        return f"An error occurred while fetching stock data: {str(e)}"

# Example call
print(get_stock_data_baostock('sh.600941'))



final_answer = FinalAnswerTool()
model = HfApiModel(
max_tokens=2096,
temperature=0.5,
model_id='Qwen/Qwen2.5-Coder-32B-Instruct',
custom_role_conversions=None,
)


# Import tool from Hub
image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True)

with open("prompts.yaml", 'r') as stream:
    prompt_templates = yaml.safe_load(stream)
    
agent = CodeAgent(
    model=model,
    tools=[
        final_answer,
        image_generation_tool,
        get_stock_data], ## add your tools here (don't remove final answer)
    max_steps=6,
    verbosity_level=1,
    grammar=None,
    planning_interval=None,
    name=None,
    description=None,
    prompt_templates=prompt_templates
)


GradioUI(agent).launch()