layers/__init__.py

"""
Layers package initialization.

Three-Layer Architecture Components:
- Layer 1: IntentParser (LLM-based semantic understanding)
- Layer 2: RegulatoryDecisionEngine (Rule-based scientific decisions)
- Layer 3: ExplanationGenerator (LLM-based narrative generation)

Legacy Components (still available):
- ProfessionalAnalyzer (original 4-phase LLM pipeline)
"""

from .input_normalizer import InputNormalizer
from .prompt_orchestrator import PromptOrchestrator, PromptPackage, PromptChain
from .model_invoker import ModelInvoker, ModelResponse, ModelInvokerFactory
from .output_normalizer import OutputNormalizer
from .llm_providers import (
    LLMProvider,
    LLMConfig,
    BaseLLMClient,
    create_llm_client,
    get_available_providers,
)

# Three-Layer Architecture Components (v2.0)
try:
    from .intent_parser import IntentParser
    from .regulatory_decision_engine import RegulatoryDecisionEngine
    from .explanation_generator import ExplanationGenerator
    _HAS_THREE_LAYER = True
except ImportError:
    IntentParser = None
    RegulatoryDecisionEngine = None
    ExplanationGenerator = None
    _HAS_THREE_LAYER = False

# Legacy: Professional Analyzer (may not be deployed)
try:
    from .professional_analyzer import ProfessionalAnalyzer, professional_analyzer
    _HAS_PROFESSIONAL_ANALYZER = True
except ImportError:
    ProfessionalAnalyzer = None
    professional_analyzer = None
    _HAS_PROFESSIONAL_ANALYZER = False

__all__ = [
    # Core infrastructure
    "InputNormalizer",
    "PromptOrchestrator",
    "PromptPackage",
    "PromptChain",
    "ModelInvoker",
    "ModelResponse",
    "ModelInvokerFactory",
    "OutputNormalizer",
    "LLMProvider",
    "LLMConfig",
    "BaseLLMClient",
    "create_llm_client",
    "get_available_providers",
    # Three-Layer Architecture (v2.0)
    "IntentParser",
    "RegulatoryDecisionEngine",
    "ExplanationGenerator",
    # Legacy
    "ProfessionalAnalyzer",
    "professional_analyzer",
]