Fix gradio 5 compatibility

facteval/__init__.py

@@ -7,6 +7,17 @@ import warnings as _warnings
 import logging as _logging
 import contextlib as _contextlib
 import io as _io
+import atexit as _atexit
+
+# Suppress multiprocess ResourceTracker.__del__ error on Windows (Python 3.12+)
+# This is a known bug in the multiprocess package, not FactEval.
+def _suppress_multiprocess_error():
+    try:
+        import multiprocess.resource_tracker as _rt
+        _rt.ResourceTracker.__del__ = lambda self: None
+    except Exception:
+        pass
+_suppress_multiprocess_error()
 
 # Suppress safetensors / accelerate noise
 _os.environ.setdefault("SAFETENSORS_LOG_LEVEL", "error")
@@ -14,16 +25,22 @@ _os.environ.setdefault("ACCELERATE_LOG_LEVEL", "error")
 _logging.getLogger("safetensors").setLevel(_logging.ERROR)
 _logging.getLogger("accelerate").setLevel(_logging.ERROR)
 
-# Suppress HF Hub unauthenticated request warnings
+# Suppress HF Hub download noise (symlink warnings, progress bars)
+_os.environ.setdefault("HF_HUB_DISABLE_SYMLINKS_WARNING", "1")
+_os.environ.setdefault("HF_HUB_DISABLE_PROGRESS_BARS", "1")
 _logging.getLogger("huggingface_hub.utils._http").setLevel(_logging.ERROR)
 _logging.getLogger("huggingface_hub").setLevel(_logging.ERROR)
 
-# Suppress transformers info-level noise
+# Suppress transformers sharding + generation config noise
+_os.environ.setdefault("TRANSFORMERS_VERBOSITY", "error")
+_os.environ.setdefault("TRANSFORMERS_NO_ADVISORY_WARNINGS", "1")
+_logging.getLogger("transformers").setLevel(_logging.ERROR)
 _logging.getLogger("transformers.modeling_utils").setLevel(_logging.ERROR)
 _logging.getLogger("transformers.generation.configuration_utils").setLevel(_logging.ERROR)
 
 # Suppress FutureWarning about clean_up_tokenization_spaces
 _warnings.filterwarnings("ignore", category=FutureWarning, module="transformers")
+_warnings.filterwarnings("ignore", category=UserWarning, module="huggingface_hub")
 
 
 @_contextlib.contextmanager

facteval/cli.py

@@ -107,7 +107,7 @@ def _parse_input(args) -> tuple[str | None, list[str]]:
     """Parse answer and contexts from file or CLI flags."""
     # Option 1: JSON file
     if args.input_file:
-        with open(args.input_file, "r", encoding="utf-8") as f:
+        with open(args.input_file, "r", encoding="utf-8-sig") as f:
             data = json.load(f)
         return data.get("answer"), data.get("contexts", [])
 

facteval/core.py

@@ -37,21 +37,27 @@ _calibrator_path: str | None = None
 def _get_extractor() -> ClaimExtractor:
     global _extractor
     if _extractor is None:
+        print("⏳ Loading claim extractor (Qwen 1.5B)...", flush=True)
         _extractor = ClaimExtractor()
+        print("✅ Claim extractor ready.", flush=True)
     return _extractor
 
 
 def _get_retriever() -> EvidenceRetriever:
     global _retriever
     if _retriever is None:
+        print("⏳ Loading retriever (MiniLM + FAISS)...", flush=True)
         _retriever = EvidenceRetriever()
+        print("✅ Retriever ready.", flush=True)
     return _retriever
 
 
 def _get_verifier() -> Verifier:
     global _verifier
     if _verifier is None:
+        print("⏳ Loading verifier (DeBERTa NLI)...", flush=True)
         _verifier = Verifier()
+        print("✅ Verifier ready.", flush=True)
     return _verifier
 
 

facteval/verifier.py

@@ -228,8 +228,8 @@ class Verifier:
         """Generate a human-readable reason for the verdict."""
         ev_short = evidence[:80] + "..." if len(evidence) > 80 else evidence
         if label == FactLabel.SUPPORTED:
-            return f"Supported by evidence: \"{ev_short}\""
+            return f"Matched evidence: \"{ev_short}\""
         elif label == FactLabel.CONTRADICTED:
-            return f"Contradicts evidence: \"{ev_short}\""
+            return f"Contradicted by: \"{ev_short}\""
         else:
-            return f"Evidence is neutral — neither confirms nor denies: \"{ev_short}\""
+            return f"No strong match — evidence is neutral: \"{ev_short}\""