Upload src/pubguard/__init__.py with huggingface_hub

src/pubguard/__init__.py

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+"""
+PubGuard — Scientific Publication Gatekeeper
+=============================================
+
+Multi-head document classifier for the PubVerse pipeline.
+Determines whether extracted PDF text represents a genuine
+scientific publication vs. junk, and flags AI-generated or
+offensive content.
+
+Classification heads:
+    1. doc_type   – scientific_paper | poster | abstract_only | junk
+    2. ai_detect  – human | ai_generated
+    3. toxicity   – clean | toxic
+
+Architecture mirrors openalex-topic-classifier:
+    model2vec (StaticModel) → L2-normalised embeddings → per-head
+    linear classifiers (sklearn / small torch heads) stored as
+    numpy weight matrices for zero-dependency inference.
+
+Usage:
+    from pubguard import PubGuard
+
+    guard = PubGuard()
+    guard.initialize()
+    verdict = guard.screen(text)
+    # verdict = {
+    #   'doc_type': {'label': 'scientific_paper', 'score': 0.94},
+    #   'ai_generated': {'label': 'human', 'score': 0.87},
+    #   'toxicity': {'label': 'clean', 'score': 0.99},
+    #   'pass': True
+    # }
+"""
+
+from .classifier import PubGuard
+from .config import PubGuardConfig
+from .errors import (
+    PubVerseError,
+    build_pubguard_error,
+    empty_input_error,
+    unreadable_pdf_error,
+    models_missing_error,
+    gate_bypassed,
+    format_error_line,
+    PIPELINE_ERRORS,
+)
+
+__version__ = "0.1.0"
+__all__ = [
+    "PubGuard",
+    "PubGuardConfig",
+    "PubVerseError",
+    "build_pubguard_error",
+    "empty_input_error",
+    "unreadable_pdf_error",
+    "models_missing_error",
+    "gate_bypassed",
+    "format_error_line",
+    "PIPELINE_ERRORS",
+]