Update app.py

app.py

@@ -114,9 +114,21 @@ def soccer_predictions():
             home_news = get_team_news(home, "football")
             away_news = get_team_news(away, "football")
 
+            # Ensure we have valid news text for sentiment analysis
             labels = ["positive", "negative", "injury", "transfer", "motivation"]
-            home_sent = sentiment_model(home_news, labels)
-            away_sent = sentiment_model(away_news, labels)
+            
+            # Use fallback text if news is empty
+            home_news_text = home_news.strip() if home_news.strip() else f"Recent news about {home} football team"
+            away_news_text = away_news.strip() if away_news.strip() else f"Recent news about {away} football team"
+            
+            try:
+                home_sent = sentiment_model(home_news_text, labels)
+                away_sent = sentiment_model(away_news_text, labels)
+            except Exception as e:
+                # Fallback sentiment analysis with default text
+                default_text = f"Football team {home} vs {away} match analysis"
+                home_sent = sentiment_model(default_text, labels)
+                away_sent = sentiment_model(default_text, labels)
 
             emb_home = similarity_model.encode(home + " " + home_news, convert_to_tensor=True)
             emb_away = similarity_model.encode(away + " " + away_news, convert_to_tensor=True)
@@ -158,13 +170,32 @@ def test_api_keys():
     
     if FOOTBALL_API_KEY != "FOOTBALL_API_KEY":
         try:
+            from datetime import timedelta
+            
             headers = {"X-Auth-Token": FOOTBALL_API_KEY}
-            resp = requests.get(f"{FOOTBALL_ENDPOINT}?competitions=2021&dateFrom=2025-01-01&dateTo=2025-01-31", headers=headers)
-            results["football_api"] = {
-                "status": "working" if resp.status_code == 200 else "error",
-                "status_code": resp.status_code,
-                "response_keys": list(resp.json().keys()) if resp.status_code == 200 else None
-            }
+            
+            # Use the same date range that works (5 days back + 5 days forward)
+            today = date.today()
+            date_from = (today - timedelta(days=5)).isoformat()
+            date_to = (today + timedelta(days=5)).isoformat()
+            
+            resp = requests.get(f"{FOOTBALL_ENDPOINT}?competitions=2021&dateFrom={date_from}&dateTo={date_to}", headers=headers)
+            
+            if resp.status_code == 200:
+                data = resp.json()
+                matches = data.get("matches", [])
+                results["football_api"] = {
+                    "status": "working",
+                    "status_code": resp.status_code,
+                    "matches_found": len(matches),
+                    "date_range": f"{date_from} to {date_to}"
+                }
+            else:
+                results["football_api"] = {
+                    "status": "error",
+                    "status_code": resp.status_code,
+                    "error": resp.text[:200]
+                }
         except Exception as e:
             results["football_api"] = {"status": "error", "error": str(e)}
     else:
@@ -172,11 +203,23 @@ def test_api_keys():
     
     # Test NBA API
     try:
-        games = nba_api.nba.games.list(dates=["2025-01-15"])
-        results["nba_api"] = {
-            "status": "working",
-            "games_found": len(games) if games else 0
-        }
+        today = date.today().isoformat()
+        games_response = nba_api.nba.games.list(dates=[today])
+        
+        # Handle the PaginatedListResponse object properly
+        if hasattr(games_response, 'data'):
+            games = games_response.data
+            results["nba_api"] = {
+                "status": "working",
+                "games_found": len(games),
+                "date_tested": today
+            }
+        else:
+            results["nba_api"] = {
+                "status": "error",
+                "error": "Unexpected response format",
+                "response_type": str(type(games_response))
+            }
     except Exception as e:
         results["nba_api"] = {"status": "error", "error": str(e)}
     
@@ -244,9 +287,21 @@ def nba_predictions():
         home_news = get_team_news(home, "NBA")
         away_news = get_team_news(away, "NBA")
 
+        # Ensure we have valid news text for sentiment analysis
         labels = ["positive", "negative", "injury", "motivation"]
-        home_sent = sentiment_model(home_news, labels)
-        away_sent = sentiment_model(away_news, labels)
+        
+        # Use fallback text if news is empty
+        home_news_text = home_news.strip() if home_news.strip() else f"Recent news about {home} NBA team"
+        away_news_text = away_news.strip() if away_news.strip() else f"Recent news about {away} NBA team"
+        
+        try:
+            home_sent = sentiment_model(home_news_text, labels)
+            away_sent = sentiment_model(away_news_text, labels)
+        except Exception as e:
+            # Fallback sentiment analysis with default text
+            default_text = f"NBA team {home} vs {away} game analysis"
+            home_sent = sentiment_model(default_text, labels)
+            away_sent = sentiment_model(default_text, labels)
 
         context = f"""
         Match: {home} vs {away}.