feat: add aggregated news retrieval methods for top headlines and latest news

src/app/news/__init__.py

@@ -45,13 +45,32 @@ class NewsAPIsTool(NewsWrapper, Toolkit):
             ],
         )
 
-    # TODO Pensare se ha senso restituire gli articoli da TUTTI i wrapper o solo dal primo che funziona
-    # la modifica è banale, basta usare try_call_all invece di try_call
     def get_top_headlines(self, limit: int = 100) -> list[Article]:
         return self.wrapper_handler.try_call(lambda w: w.get_top_headlines(limit))
     def get_latest_news(self, query: str, limit: int = 100) -> list[Article]:
         return self.wrapper_handler.try_call(lambda w: w.get_latest_news(query, limit))
 
+    def get_top_headlines_aggregated(self, limit: int = 100) -> dict[str, list[Article]]:
+        """
+        Calls get_top_headlines on all wrappers/providers and returns a dictionary mapping their names to their articles.
+        Args:
+            limit (int): Maximum number of articles to retrieve from each provider.
+        Returns:
+            dict[str, list[Article]]: A dictionary mapping providers names to their list of Articles
+        """
+        return self.wrapper_handler.try_call_all(lambda w: w.get_top_headlines(limit))
+
+    def get_latest_news_aggregated(self, query: str, limit: int = 100) -> dict[str, list[Article]]:
+        """
+        Calls get_latest_news on all wrappers/providers and returns a dictionary mapping their names to their articles.
+        Args:
+            query (str): The search query to find relevant news articles.
+            limit (int): Maximum number of articles to retrieve from each provider.
+        Returns:
+            dict[str, list[Article]]: A dictionary mapping providers names to their list of Articles
+        """
+        return self.wrapper_handler.try_call_all(lambda w: w.get_latest_news(query, limit))
+
 
 NEWS_INSTRUCTIONS = """
 **TASK:** You are a specialized **Crypto News Analyst**. Your goal is to fetch the latest news or top headlines related to cryptocurrencies, and then **analyze the sentiment** of the content to provide a concise report to the team leader. Prioritize 'crypto' or specific cryptocurrency names (e.g., 'Bitcoin', 'Ethereum') in your searches.
@@ -59,6 +78,8 @@ NEWS_INSTRUCTIONS = """
 **AVAILABLE TOOLS:**
 1.  `get_latest_news(query: str, limit: int)`: Get the 'limit' most recent news articles for a specific 'query'.
 2.  `get_top_headlines(limit: int)`: Get the 'limit' top global news headlines.
+3.  `get_latest_news_aggregated(query: str, limit: int)`: Get aggregated latest news articles for a specific 'query'.
+4.  `get_top_headlines_aggregated(limit: int)`: Get aggregated top global news headlines.
 
 **USAGE GUIDELINE:**
 * Always use `get_latest_news` with a relevant crypto-related query first.

src/app/social/reddit.py

@@ -4,8 +4,8 @@ from praw.models import Submission, MoreComments
 from .base import SocialWrapper, SocialPost, SocialComment
 
 MAX_COMMENTS = 5
-# TODO mettere piu' subreddit?
-# scelti da https://lkiconsulting.io/marketing/best-crypto-subreddits/
+# metterne altri se necessario.
+# fonti: https://lkiconsulting.io/marketing/best-crypto-subreddits/
 SUBREDDITS = [
     "CryptoCurrency", 
     "Bitcoin",

src/app/utils/market_aggregation.py

@@ -63,9 +63,6 @@ def aggregate_product_info(products: dict[str, list[ProductInfo]]) -> list[Produ
         product.price = (prices / volume_sum) if volume_sum > 0 else 0.0
 
         aggregated_products.append(product)
-
-        confidence = _calculate_confidence(product_list, sources) # TODO necessary?
-
     return aggregated_products
 
 def _calculate_confidence(products: list[ProductInfo], sources: list[str]) -> float: