Update app.py

app.py

@@ -51,15 +51,27 @@ def compute_moving_average(prices, window):
 
 ### 🔹 1. Fetch Latest BTC News ###
 @tool
-def fetch_btc_news() -> List[Dict[str, str]]:
+def analyze_btc_news(articles: List[Dict[str, str]]) -> Dict[str, any]:
     """
-    Fetches the latest Bitcoin news from CryptoPanic API.
-    Returns a list of dictionaries containing 'title' and 'url' of the articles.
+    Analyzes sentiment of Bitcoin news articles using TextBlob.
+    
+    Arguments:
+    articles (List[Dict[str, str]]): A list of dictionaries representing Bitcoin news articles.
+                                        Each dictionary contains the 'title' and 'url' of the article.
+    
+    Returns:
+    Dict[str, any]: A dictionary containing the sentiment score, sentiment label, and keywords.
     """
-    url = "https://cryptopanic.com/api/v1/posts/?auth_token=ccbeafb47d266a78086f76c3f547546f6b747e88&currencies=BTC"
-    data = fetch_data(url)
-    return [{"title": post["title"], "url": post["url"]} for post in data.get("results", [])[:5]]
-
+    sentiments = [TextBlob(article["title"]).sentiment.polarity for article in articles]
+    avg_sentiment = np.mean(sentiments) if sentiments else 0
+    sentiment_label = "Positive 😊" if avg_sentiment > 0 else "Negative 😡" if avg_sentiment < 0 else "Neutral 😐"
+    keywords = list(set([word for article in articles for word in article["title"].split()[:5]]))
+    
+    return {
+        "sentiment_score": avg_sentiment, 
+        "sentiment_label": sentiment_label, 
+        "keywords": keywords
+    }
     
 ### 🔹 2. Analyze News Sentiment ###
 @tool