Remove sentiment analysis and entity recognition functions from get_news implementation

tools.py

@@ -40,64 +40,11 @@ def get_news(query: str) -> List[Dict]:
                 "index": len(last_news) + 1,
                 "title": res.get("title", "No title available"),
                 "summary": res.get("content", "No summary available"),
-                # "sentiment": analyze_sentiment(res.get("snippet", "")),
-                # "entities": recognize_entities(res.get("snippet", ""))
             })
     print(f"Found {len(last_news)} articles.")
     return last_news
 
 
-def analyze_sentiment(text: str) -> str:
-    """
-    Analyzes the sentiment of the given text and returns the sentiment label.
-
-    Args:
-        text: The input text to analyze.
-
-    Returns:
-        str: The sentiment label, such as 'positive', 'negative', or 'neutral'.
-    """
-    prompt = f"""
-    question: Tell me if the sentiment of this news is positive, negative, or neutral? 
-    context: {text}"""
-    try:
-        result = llm_openai.chat(
-            messages=[ChatMessage(role="user", content=prompt)]
-        )
-    except Exception as e:
-        return f"Error analyzing sentiment: {str(e)}"
-    sentiment_label = result.message.content
-    if "positive" in sentiment_label.lower():
-        return "POSITIVE"
-    elif "negative" in sentiment_label.lower():
-        return "NEGATIVE"
-    else:
-        return "NEUTRAL"
-
-
-def recognize_entities(text: str) -> List[str]:
-    """
-    Recognizes named entities in the given text.
-
-    Args:
-        text: The input text in which to recognize entities.
-
-    Returns:
-        List[str]: A list of recognized entity names as strings.
-    """
-    prompt = f"""
-    question: Tell me entities mentioned in this news? 
-    context: {text}"""
-    try:
-        result = llm_openai.chat(
-            messages=[ChatMessage(role="user", content=prompt)]
-        )
-    except Exception as e:
-        return f"Error recognizing entities: {str(e)}"
-    entities = result.message.content.split(", ")
-    return entities if entities else ["No entities found."]
-
-
 def generate_implications(article_index: int) -> str:
     """
     Generates a string describing the possible implications of a news article based on its index.