rimossi warnings

api.py

@@ -5,6 +5,8 @@ import os
 import time
 import hashlib
 from contextlib import asynccontextmanager
+import warnings
+import logging
 
 from src.ingestion.semantic_splitter import ActivaSemanticSplitter
 from src.extraction.extractor import NeuroSymbolicExtractor
@@ -13,6 +15,11 @@ from src.graph.graph_loader import KnowledgeGraphPersister
 from src.graph.entity_resolver import EntityResolver
 from pymongo import MongoClient
 
+warnings.filterwarnings("ignore", category=FutureWarning)
+warnings.filterwarnings("ignore", category=DeprecationWarning)
+
+logging.getLogger("transformers").setLevel(logging.ERROR)
+
 # --- GESTORE DEGLI STATI GLOBALI ---
 # Usiamo un dizionario globale per tenere in RAM i pesi dei modelli. 
 ml_models = {}

app.py

@@ -1,3 +1,4 @@
+import streamlit.components.v1 as components
 import streamlit as st
 import os
 import time
@@ -6,16 +7,22 @@ import pandas as pd
 from pymongo import MongoClient
 from neo4j import GraphDatabase
 from pyvis.network import Network
-import streamlit.components.v1 as components
 from dotenv import load_dotenv
+import warnings
+import logging
 
 # --- IMPORT MODULI SPECIFICI ---
 from src.ingestion.semantic_splitter import ActivaSemanticSplitter
-from src.extraction.extractor import NeuroSymbolicExtractor, GraphTriple
+from src.extraction.extractor import NeuroSymbolicExtractor
 from src.validation.validator import SemanticValidator
 from src.graph.graph_loader import KnowledgeGraphPersister
 from src.graph.entity_resolver import EntityResolver
 
+warnings.filterwarnings("ignore", category=FutureWarning)
+warnings.filterwarnings("ignore", category=DeprecationWarning)
+
+logging.getLogger("transformers").setLevel(logging.ERROR)
+
 # --- CONFIGURAZIONE PAGINA ---
 load_dotenv()
 st.set_page_config(
@@ -347,11 +354,11 @@ with tab_val:
         cypher_val = """
         MATCH (s)-[r]->(o) 
         RETURN elementId(r) as id, 
-               COALESCE(s["label"], s["name"], head(labels(s))) as Soggetto, 
+               COALESCE(s.label, head(labels(s))) as Soggetto, 
                type(r) as Predicato, 
-               COALESCE(o["label"], o["name"], head(labels(o))) as Oggetto,
-               COALESCE(r["evidence"], 'N/A') as Evidenza,
-               COALESCE(r["reasoning"], 'N/A') as Ragionamento
+               COALESCE(o.label, head(labels(o))) as Oggetto,
+               COALESCE(r.evidence, 'N/A') as Evidenza,
+               COALESCE(r.reasoning, 'N/A') as Ragionamento
         """
         triples_data = run_query(driver, cypher_val)