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Update app.py
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app.py
CHANGED
@@ -42,14 +42,15 @@ def get_current_time_in_timezone(timezone: str) -> str:
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@tool
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def get_current_stock_price(ticker_symbol: str) -> Optional[dict]:
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"""
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-
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the price change over the last 5 days
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Args:
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ticker_symbol: The stock ticker symbol to fetch the price for.
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Returns:
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dict: A dictionary containing the current stock price, the price change
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over the last 5 days, and the percentage change.
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Returns None if there's an error or no data is available.
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"""
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@@ -69,11 +70,12 @@ def get_current_stock_price(ticker_symbol: str) -> Optional[dict]:
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price_change_percent = (price_change / stock_data['Close'].iloc[0]) * 100
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# Round all values to 2 decimal places
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-
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"price": round(current_price, 2),
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"price_change": round(price_change, 2),
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"price_change_percent": round(price_change_percent, 2)
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}
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except yf.exceptions.YFinanceException as yf_err:
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logger.error(f"YFinance error for {ticker_symbol}: {str(yf_err)}")
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@@ -94,7 +96,7 @@ custom_role_conversions=None,
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)
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# Import tool from Hub
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image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True)
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with open("prompts.yaml", 'r') as stream:
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prompt_templates = yaml.safe_load(stream)
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@tool
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def get_current_stock_price(ticker_symbol: str) -> Optional[dict]:
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"""
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Get the latest stock price for the given ticker symbol and calculates
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the price change over the last 5 days and retrun current stock price ,
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price change and percentage change.
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Args:
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ticker_symbol: The stock ticker symbol to fetch the price for.
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Returns:
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price -> dict: A dictionary containing the current stock price, the price change
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over the last 5 days, and the percentage change.
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Returns None if there's an error or no data is available.
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"""
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price_change_percent = (price_change / stock_data['Close'].iloc[0]) * 100
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# Round all values to 2 decimal places
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price = {
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"price": round(current_price, 2),
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"price_change": round(price_change, 2),
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"price_change_percent": round(price_change_percent, 2)
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}
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return price
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except yf.exceptions.YFinanceException as yf_err:
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logger.error(f"YFinance error for {ticker_symbol}: {str(yf_err)}")
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)
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# Import tool from Hub
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# image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True)
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with open("prompts.yaml", 'r') as stream:
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prompt_templates = yaml.safe_load(stream)
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