Update app.py

Add basic sentiment analysis tool

app.py

@@ -33,6 +33,57 @@ def get_current_time_in_timezone(timezone: str) -> str:
     except Exception as e:
         return f"Error fetching time for timezone '{timezone}': {str(e)}"
 
+from smolagent.tools.duckduckgo_search import DuckDuckGoSearchTool
+from datetime import datetime
+import re
+
+def sentiment_analysis(text: str) -> str:
+    """Basic economic sentiment analysis based on keywords"""
+    positive_keywords = ["growth", "profit", "increase", "investment", "record revenue", "expansion", "gain"]
+    negative_keywords = ["loss", "decline", "layoff", "decrease", "cut", "lawsuit", "scandal", "drop"]
+
+    text_lower = text.lower()
+    pos_hits = sum(1 for kw in positive_keywords if kw in text_lower)
+    neg_hits = sum(1 for kw in negative_keywords if kw in text_lower)
+
+    if pos_hits > neg_hits:
+        return "positive"
+    elif neg_hits > pos_hits:
+        return "negative"
+    else:
+        return "neutral"
+
+def news_date_is_today(text: str) -> bool:
+    """Check if the news mention today's date (very naive)"""
+    today = datetime.now().strftime("%B %d, %Y")  # e.g., "April 30, 2025"
+    return today.lower() in text.lower()
+
+@tool
+def company_news_sentiment(company_name: str, top_k: int) -> str:
+    """A tool that searches for the latest company news and assesses daily relevance and sentiment.
+    
+    Args:
+        company_name: the name of the company to search news for.
+        top_k: the number of top search results to analyze.
+    
+    Returns:
+        A string summarizing if there are daily news and whether the sentiment is positive or negative.
+    """
+    search_tool = DuckDuckGoSearchTool()
+    results = search_tool.run(f"{company_name} latest news")
+
+    if not results:
+        return f"No news found for {company_name}."
+
+    selected_results = results[:top_k]
+    combined_text = " ".join(res["body"] for res in selected_results if "body" in res)
+
+    has_today_news = any(news_date_is_today(res.get("body", "")) for res in selected_results)
+    sentiment = sentiment_analysis(combined_text)
+
+    daily_news_str = "There is news today" if has_today_news else "There is no news specifically from today"
+    return f"{daily_news_str} about {company_name}. Overall sentiment appears {sentiment} from an economic perspective."
+
 
 final_answer = FinalAnswerTool()
 
@@ -55,7 +106,7 @@ 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,company_news_sentiment], ## add your tools here (don't remove final answer)
     max_steps=6,
     verbosity_level=1,
     grammar=None,