Fin_Agent_App.py

app.py

@@ -1,11 +1,18 @@
-from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool
+from smolagents import CodeAgent, HfApiModel, tool, load_tool
 import datetime
 import requests
 import pytz
 import yaml
 from tools.final_answer import FinalAnswerTool
-
 from Gradio_UI import GradioUI
+from bs4 import BeautifulSoup
+
+# ---------------------------------------------------------------------------
+# Define a custom tool for investment advice.
+# This tool fetches the top 5 headlines from Yahoo Finance,
+# does a simple sentiment analysis by counting positive and negative words,
+# and then provides advice based on the provided risk tolerance.
+# ---------------------------------------------------------------------------
 
 # Below is an example of a tool that does nothing. Amaze us with your creativity !
 @tool
@@ -19,19 +26,66 @@ def my_custom_tool(arg1:str, arg2:int)-> str: #it's import to specify the return
     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.
+def investment_advice_tool(risk_tolerance: str) -> str:
+    """
+    Provides investment advice based on current market sentiment and the investor's risk tolerance.
+    
     Args:
-        timezone: A string representing a valid timezone (e.g., 'America/New_York').
+        risk_tolerance: A string representing risk tolerance ('low', 'medium', or 'high').
     """
     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}"
+        # Fetch market news from Yahoo Finance
+        url = "https://finance.yahoo.com/"
+        response = requests.get(url)
+        if response.status_code != 200:
+            return f"Error fetching market news: HTTP {response.status_code}"
+        
+        # Parse the top headlines using BeautifulSoup
+        soup = BeautifulSoup(response.text, "html.parser")
+        headlines = soup.find_all("h3", limit=5)
+        news = [headline.get_text() for headline in headlines]
+        
+        # Perform a simple sentiment analysis based on keywords
+        positive_words = ["rise", "gain", "growth", "bullish", "record high"]
+        negative_words = ["fall", "loss", "drop", "bearish", "recession"]
+        sentiment_score = 0
+        for article in news:
+            for word in positive_words:
+                if word in article.lower():
+                    sentiment_score += 1
+            for word in negative_words:
+                if word in article.lower():
+                    sentiment_score -= 1
+        sentiment = "Bullish" if sentiment_score > 0 else "Bearish" if sentiment_score < 0 else "Neutral"
+        
+        # Provide advice based on risk tolerance and market sentiment
+        if risk_tolerance.lower() == "low":
+            if sentiment == "Bullish":
+                advice = "Invest in stable index funds or blue-chip stocks for steady growth."
+            elif sentiment == "Bearish":
+                advice = "Consider bonds or fixed-income securities to minimize risk."
+            else:
+                advice = "Maintain a diversified portfolio focused on stability."
+        elif risk_tolerance.lower() == "medium":
+            if sentiment == "Bullish":
+                advice = "Consider a balanced mix of growth stocks and dividend-paying stocks."
+            elif sentiment == "Bearish":
+                advice = "Look for undervalued defensive stocks and ETFs."
+            else:
+                advice = "A balanced portfolio combining growth and value stocks would be wise."
+        elif risk_tolerance.lower() == "high":
+            if sentiment == "Bullish":
+                advice = "Explore high-growth sectors like tech or emerging markets for potentially high returns."
+            elif sentiment == "Bearish":
+                advice = "Adopt a cautious approach, perhaps allocating only a small portion to speculative investments."
+            else:
+                advice = "A portfolio with a mix of high-risk and stable investments might suit you."
+        else:
+            advice = "Invalid risk tolerance. Please choose 'low', 'medium', or 'high'."
+        
+        return f"Market sentiment is {sentiment}. Based on your {risk_tolerance} risk tolerance, {advice}"
     except Exception as e:
-        return f"Error fetching time for timezone '{timezone}': {str(e)}"
+        return f"Error in investment advice tool: {str(e)}"
 
 
 final_answer = FinalAnswerTool()
@@ -46,6 +100,10 @@ model_id='Qwen/Qwen2.5-Coder-32B-Instruct',# it is possible that this model may
 custom_role_conversions=None,
 )
 
+# ---------------------------------------------------------------------------
+# Load prompt templates from the prompts.yaml file.
+# This file guides how the agent constructs prompts for the LLM.
+# ---------------------------------------------------------------------------
 
 # Import tool from Hub
 image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True)
@@ -53,15 +111,19 @@ image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_co
 with open("prompts.yaml", 'r') as stream:
     prompt_templates = yaml.safe_load(stream)
     
+# ---------------------------------------------------------------------------
+# Create the Financial Advisor Agent.
+# We add our investment advice tool to the agent's tools list.
+# ---------------------------------------------------------------------------
 agent = CodeAgent(
     model=model,
-    tools=[final_answer], ## add your tools here (don't remove final answer)
+    tools=[final_answer, investment_advice_tool],  # Add your custom financial tool here
     max_steps=6,
     verbosity_level=1,
     grammar=None,
     planning_interval=None,
-    name=None,
-    description=None,
+    name="Financial Advisor Agent",
+    description="An agent that provides investment suggestions based on current market sentiment and your risk tolerance.",
     prompt_templates=prompt_templates
 )