adds get_stock_price tool

app.py

@@ -3,20 +3,87 @@ import datetime
 import requests
 import pytz
 import yaml
+import yfinance as yf
+from ta.momentum import RSIIndicator, StochasticOscillator
+from ta.trend import MACD
+from ta.volume import volume_weighted_average_price
 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 !
+# # Below is an example of a tool that does nothing. Amaze us with your creativity !
+# @tool
+# def my_custom_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 my_custom_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 
+def get_stock_price(ticker: str) -> Union[Dict, str]:
+    """
+    A tool that fetches the historical stock price data and technical indicators for a given ticker.
     Args:
-        arg1: the first argument
-        arg2: the second argument
+        ticker: A string representing a stocke ticker name (e.g AAPL)
     """
-    return "What magic will you build ?"
+
+    try:
+        data = yf.download(
+            ticker,
+            start=dt.datetime.now() - dt.timedelta(weeks=24 * 3),
+            end=dt.datetime.now(),
+            interval="1wk",
+        )
+        df = data.copy()
+        data.reset_index(inplace=True)
+        data.Date = data.Date.astype(str)
+
+        indicators = {}
+
+        rsi_series = RSIIndicator(df["Close"], window=14).rsi().iloc[-12:]
+        indicators["RSI"] = {
+            date.strftime("%Y-%m-%d"): int(value)
+            for date, value in rsi_series.dropna().to_dict().items()
+        }
+
+        stochastic_series = (
+            StochasticOscillator(df["High"], df["Low"], df["Close"], window=14)
+            .stoch()
+            .iloc[-12:]
+        )
+        indicators["Stochastic Oscillator"] = {
+            date.strftime("%Y-%m-%d"): int(value)
+            for date, value in stochastic_series.dropna().to_dict().items()
+        }
+
+        macd = MACD(df["Close"])
+        macd_series = macd.macd().iloc[-12:]
+        indicators["MACD"] = {
+            date.strftime("%Y-%m-%d"): int(value)
+            for date, value in macd_series.to_dict().items()
+        }
+
+        macd_signal_series = macd.macd_signal().iloc[-12:]
+        indicators["MACD Signal"] = {
+            date.strftime("%Y-%m-%d"): int(value)
+            for date, value in macd_signal_series.to_dict().items()
+        }
+
+        vwap_series = volume_weighted_average_price(
+            df["High"], df["Low"], df["Close"], df["Volume"]
+        ).iloc[-12:]
+        indicators["vwap"] = {
+            date.strftime("%Y-%m-%d"): int(value)
+            for date, value in vwap_series.to_dict().items()
+        }
+
+        return {"stock_price": data.to_dict(orient="records"), "indicators": indicators}
+    except Exception as e:
+        return f"Error fetching price data: {str(e)}"
 
 @tool
 def get_current_time_in_timezone(timezone: str) -> str:
@@ -55,7 +122,7 @@ with open("prompts.yaml", 'r') as stream:
     
 agent = CodeAgent(
     model=model,
-    tools=[final_answer], ## add your tools here (don't remove final answer)
+    tools=[final_answer, get_stock_price], ## add your tools here (don't remove final answer)
     max_steps=6,
     verbosity_level=1,
     grammar=None,