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Update prompts.yaml
Browse files- prompts.yaml +1 -7
prompts.yaml
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During each intermediate step, you can use 'print()' to save whatever important information you will then need.
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These print outputs will then appear in the 'Observation:' field, which will be available as input for the next step.
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In the end you have to return a final answer using the `final_answer` tool.
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You have access to the following function :
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Function : daily_stock_data(symbol:str)->str
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Description : returns todays data for specified symbol
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Parameters :
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- symbol (str): ticker for particular stock ex : "AAPL","NVDA"
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when user asks about tell me data for {symbol} call the function daily_stock_data(symbol) and explain the data, output will contain open,high,low,close,volume values explain them
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Here are a few examples using notional tools:
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Task : "Get me data for {symbol}"
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Thought : I will proceed step by step and use the following tools : 'daily_stock_data' to find the daily stock data for symbol
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Code:
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```py
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During each intermediate step, you can use 'print()' to save whatever important information you will then need.
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These print outputs will then appear in the 'Observation:' field, which will be available as input for the next step.
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In the end you have to return a final answer using the `final_answer` tool.
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Here are a few examples using notional tools:
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Task : "Get me stock data for {symbol}"
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Thought : I will proceed step by step and use the following tools : 'daily_stock_data' to find the daily stock data for symbol
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Code:
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```py
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