"""Dependency-free reference implementations across the complete RAG lifecycle.

The package contains real, inspectable small-scale algorithms and contracts for
corpus versioning, chunk lineage, sparse/dense/ANN indexes, fusion and evidence
selection, training objectives, structured retrieval, agents, memory, time,
security, evaluation, and operations.  Its hashed semantic retriever, heuristic
reranker, and static security signals keep the labs reproducible without model
downloads; they are explicitly not substitutes for evaluated neural models or
production security controls.
"""

from .agentic import BudgetedIterativeRetriever
from .chunking import parent_child_chunks, section_chunks, sentence_chunks
from .demo_data import demo_documents, demo_questions
from .evaluation import evaluate_pipeline, evaluate_retriever
from .indexes import ExactCosineIndex, IVFCoarseIndex, InvertedIndex
from .ingestion import ACLPolicy, CorpusManifest
from .memory import MemoryRecord, MemoryStore
from .operations import ServiceBudget, SystemCandidate, pareto_frontier
from .pipeline import RAGPipeline, build_advanced_pipeline, build_baseline_pipeline
from .selection import calibrated_comb_sum, greedy_budgeted_coverage
from .structured import late_interaction_score, personalized_pagerank
from .temporal import BitemporalStore, TemporalFact

__all__ = [
    "ACLPolicy",
    "BitemporalStore",
    "BudgetedIterativeRetriever",
    "CorpusManifest",
    "ExactCosineIndex",
    "IVFCoarseIndex",
    "InvertedIndex",
    "MemoryRecord",
    "MemoryStore",
    "RAGPipeline",
    "ServiceBudget",
    "SystemCandidate",
    "build_advanced_pipeline",
    "build_baseline_pipeline",
    "calibrated_comb_sum",
    "demo_documents",
    "demo_questions",
    "evaluate_pipeline",
    "evaluate_retriever",
    "greedy_budgeted_coverage",
    "late_interaction_score",
    "parent_child_chunks",
    "pareto_frontier",
    "personalized_pagerank",
    "section_chunks",
    "sentence_chunks",
    "TemporalFact",
]

__version__ = "0.2.0"