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app.py

@@ -14,9 +14,10 @@ import plotly.graph_objects as go
 MODEL_NAME = "ProsusAI/finbert"
 TARGET_DATASET = "Vycka12/Base"
 HF_TOKEN = os.environ.get("HF_TOKEN")
-CRYPTOPANIC_URL = "https://cryptopanic.com/api/v1/posts/?kind=news&public=true"
+# Pataisytas CryptoPanic URL formatas
+CRYPTOPANIC_URL = "https://cryptopanic.com/api/v1/posts/"
 
-# Globalūs kintamieji su pradinėmis reikšmėmis
+# Globalūs kintamieji
 news_buffer = []
 stats = {"bullish": 0, "bearish": 0, "neutral": 0, "overall": "Laukiama...", "status": "Inicijuojama..."}
 
@@ -36,12 +37,26 @@ class SentimentSystem:
     def fetch_and_analyze(self):
         global news_buffer, stats
         stats["status"] = "Siurbiamos naujienos..."
+        
+        # Pasiimame raktą (jei vartotojas jį įdėjo į Secrets)
+        api_key = os.environ.get("CRYPTOPANIC_API_KEY", "")
+        
+        # Baziniai parametrai
+        params = {"kind": "news"}
+        if api_key:
+            params["auth_token"] = api_key
+        else:
+            # Jei rakto nėra, CryptoPanic leidžia tik viešą hot srautą
+            params["public"] = "true"
+            params["filter"] = "hot"
+
         try:
-            resp = requests.get(CRYPTOPANIC_URL, timeout=15)
+            resp = requests.get(CRYPTOPANIC_URL, params=params, timeout=15)
+            
             if resp.status_code == 200:
                 raw_news = resp.json().get("results", [])
                 if not raw_news:
-                    stats["status"] = "⚠️ Nerasta naujų žinučių."
+                    stats["status"] = "⚠️ API veikia, bet naujienų kol kas nėra."
                     return
                 
                 temp_news = []
@@ -52,21 +67,21 @@ class SentimentSystem:
                     if not title: continue
                     
                     if sentiment_pipeline:
+                        # FinBERT analizė
                         result = sentiment_pipeline(title[:512])[0]
                         label = result['label']
                         score = result['score']
                     else:
                         label, score = 'neutral', 0.5
 
-                    # Emocijų nustatymas
                     if label == 'positive': 
-                        status, emo, color = "🟢 BULLISH", "🚀", "green"
+                        status, emo = "🟢 BULLISH", "🚀"
                         pos += 1
                     elif label == 'negative': 
-                        status, emo, color = "🔴 BEARISH", "📉", "red"
+                        status, emo = "🔴 BEARISH", "📉"
                         neg += 1
                     else: 
-                        status, emo, color = "⚪ NEUTRAL", "➖", "gray"
+                        status, emo = "⚪ NEUTRAL", "➖"
                         neut += 1
 
                     temp_news.append([emo, status, title, f"{round(score*100)}%"])
@@ -81,13 +96,12 @@ class SentimentSystem:
                 news_buffer = temp_news
                 stats["status"] = f"Analizė baigta {datetime.now().strftime('%H:%M:%S')}"
             else:
-                stats["status"] = f"❌ API Klaida: {resp.status_code}"
+                stats["status"] = f"❌ API Klaida: {resp.status_code} (Reikia rakto?)"
         except Exception as e:
-            stats["status"] = f"❌ Sistemos klaida: {str(e)}"
+            stats["status"] = f"❌ Ryšio klaida: {str(e)}"
 
     def create_gauge(self):
         total = stats["bullish"] + stats["bearish"]
-        # Jei nėra duomenų, rodome 50 (neutralu)
         val = 50
         if total > 0:
             val = ((stats["bullish"] - stats["bearish"]) / total) * 50 + 50
@@ -106,7 +120,7 @@ class SentimentSystem:
                 ],
             }
         ))
-        fig.update_layout(height=280, margin=dict(l=20, r=20, t=40, b=20))
+        fig.update_layout(height=280, margin=dict(l=20, r=20, t=40, b=20), paper_bgcolor="rgba(0,0,0,0)")
         return fig
 
 sys_analyzer = SentimentSystem()
@@ -118,7 +132,6 @@ def update_loop():
 
 def get_ui_data():
     gauge = sys_analyzer.create_gauge()
-    # Užtikriname, kad lentelė visada turi stulpelius
     df = pd.DataFrame(news_buffer, columns=["Emoji", "Verdiktas", "Antraštė", "Pasitikėjimas"])
     if df.empty:
         df = pd.DataFrame([["-", "-", "Kraunamos naujienos...", "-"]], columns=["Emoji", "Verdiktas", "Antraštė", "Pasitikėjimas"])
@@ -144,18 +157,12 @@ with gr.Blocks(title="Sentiment AI Analyzer", theme=gr.themes.Soft()) as demo:
         interactive=False
     )
 
-    # Tikrinimo mygtukas
     refresh_btn.click(fn=get_ui_data, outputs=[gauge_output, table_output, info_output])
-    
-    # Automatinis atnaujinimas
-    demo.load(sys_analyzer.fetch_and_analyze) # Pirmas paleidimas
+    demo.load(sys_analyzer.fetch_and_analyze)
     demo.load(get_ui_data, outputs=[gauge_output, table_output, info_output])
     
-    # Tikrasis fono threadas
     threading.Thread(target=update_loop, daemon=True).start()
-
-    # UI atnaujinimas kas 15s
-    gr.Timer(15).tick(get_ui_data, outputs=[gauge_output, table_output, info_output])
+    gr.Timer(30).tick(get_ui_data, outputs=[gauge_output, table_output, info_output])
 
 if __name__ == "__main__":
     demo.launch(server_name="0.0.0.0", server_port=7860)