"""Recursive semantic decomposition: split text into atomic units."""

from __future__ import annotations

import re
import uuid
from typing import Any

from fusionagi.reasoning.native import analyze_prompt
from fusionagi.schemas.atomic import (
    AtomicSemanticUnit,
    AtomicUnitType,
    DecompositionResult,
    RelationType,
    SemanticRelation,
)
from fusionagi._logger import logger


def _make_unit_id(prefix: str = "asu") -> str:
    """Generate unique unit ID."""
    return f"{prefix}_{uuid.uuid4().hex[:12]}"


def _is_atomic(text: str, min_words: int = 3) -> bool:
    """Check if text is irreducible (atomic)."""
    content = " ".join(text.split()).strip()
    if not content or len(content) < 10:
        return True
    words = len(content.split())
    return words <= min_words


def _extract_questions(text: str) -> list[str]:
    """Extract explicit questions from text."""
    questions: list[str] = []
    content = " ".join(text.split()).strip()
    q_parts = re.split(r"\?+", content)
    for part in q_parts[:-1]:
        q = part.strip()
        if len(q) > 10:
            questions.append(q + "?")
    if not questions and any(w in content.lower() for w in ["how", "what", "why", "when", "where", "who"]):
        questions.append(content)
    return questions[:5]


def _extract_constraints(text: str) -> list[str]:
    """Extract constraint signals from text."""
    constraints: list[str] = []
    patterns = [
        r"must\s+(\w[\w\s]+?)(?:\.|$)",
        r"should\s+(\w[\w\s]+?)(?:\.|$)",
        r"cannot\s+(\w[\w\s]+?)(?:\.|$)",
        r"require[sd]?\s+(\w[\w\s]+?)(?:\.|$)",
        r"constraint[s]?:\s*(\w[\w\s]+?)(?:\.|$)",
        r"assume[sd]?\s+(\w[\w\s]+?)(?:\.|$)",
    ]
    for pat in patterns:
        for m in re.finditer(pat, text, re.I):
            constraints.append(m.group(1).strip())
    return list(dict.fromkeys(constraints))[:10]


def _extract_entities(text: str) -> list[str]:
    """Extract entity-like phrases."""
    entities = re.findall(r'"([^"]+)"', text)
    entities += re.findall(r"\b[A-Z][a-z]+(?:\s+[A-Z][a-z]+)*\b", text)
    return list(dict.fromkeys(e for e in entities if len(e) > 2))[:10]


def decompose_recursive(
    text: str,
    max_depth: int = 3,
    parent_id: str | None = None,
    current_depth: int = 0,
    source_ref: str | None = None,
) -> DecompositionResult:
    """
    Recursively decompose text into atomic semantic units.

    Extracts entities, constraints, intents, assumptions, questions; recurses
    on non-atomic segments. Integrates with native analyze_prompt for intent
    and domain signals.

    Args:
        text: Input text to decompose.
        max_depth: Maximum recursion depth.
        parent_id: Parent unit ID for decomposition tree.
        current_depth: Current recursion depth.
        source_ref: Optional source reference.

    Returns:
        DecompositionResult with units and relations.
    """
    content = " ".join(text.split()).strip()
    if not content:
        return DecompositionResult(units=[], relations=[], depth=current_depth)

    units: list[AtomicSemanticUnit] = []
    relations: list[SemanticRelation] = []

    analysis = analyze_prompt(content)

    # Root unit for this segment (if not already atomic)
    root_id = _make_unit_id()
    root_unit = AtomicSemanticUnit(
        unit_id=root_id,
        content=content[:500] + ("..." if len(content) > 500 else ""),
        type=AtomicUnitType.INTENT if analysis.intent == "question" else AtomicUnitType.FACT,
        confidence=0.8,
        parent_id=parent_id,
        source_ref=source_ref,
        metadata={"intent": analysis.intent},
    )
    units.append(root_unit)
    if parent_id:
        relations.append(
            SemanticRelation(from_id=parent_id, to_id=root_id, relation_type=RelationType.LOGICAL)
        )

    # Extract questions as atomic units
    for q in _extract_questions(content):
        q_id = _make_unit_id()
        units.append(
            AtomicSemanticUnit(
                unit_id=q_id,
                content=q,
                type=AtomicUnitType.QUESTION,
                confidence=0.9,
                parent_id=root_id,
                source_ref=source_ref,
            )
        )
        relations.append(
            SemanticRelation(from_id=root_id, to_id=q_id, relation_type=RelationType.LOGICAL)
        )

    # Extract constraints as atomic units
    for c in _extract_constraints(content):
        c_id = _make_unit_id()
        units.append(
            AtomicSemanticUnit(
                unit_id=c_id,
                content=c,
                type=AtomicUnitType.CONSTRAINT,
                confidence=0.85,
                parent_id=root_id,
                source_ref=source_ref,
            )
        )
        relations.append(
            SemanticRelation(from_id=root_id, to_id=c_id, relation_type=RelationType.LOGICAL)
        )

    # Extract entities as atomic units
    for e in _extract_entities(content):
        e_id = _make_unit_id()
        units.append(
            AtomicSemanticUnit(
                unit_id=e_id,
                content=e,
                type=AtomicUnitType.FACT,
                confidence=0.9,
                parent_id=root_id,
                source_ref=source_ref,
            )
        )
        relations.append(
            SemanticRelation(from_id=root_id, to_id=e_id, relation_type=RelationType.LOGICAL)
        )

    # If not atomic and depth allows, split and recurse
    if not _is_atomic(content, min_words=8) and current_depth < max_depth:
        sentences = re.split(r"[.!?]\s+", content)
        if len(sentences) > 1:
            for sent in sentences:
                sent = sent.strip()
                if len(sent) > 20:
                    sub = decompose_recursive(
                        sent,
                        max_depth=max_depth,
                        parent_id=root_id,
                        current_depth=current_depth + 1,
                        source_ref=source_ref,
                    )
                    units.extend(sub.units)
                    relations.extend(sub.relations)

    # Dedupe by unit_id
    seen: set[str] = set()
    unique_units: list[AtomicSemanticUnit] = []
    for u in units:
        if u.unit_id not in seen:
            seen.add(u.unit_id)
            unique_units.append(u)

    logger.debug(
        "Decomposition complete",
        extra={"depth": current_depth, "units": len(unique_units), "relations": len(relations)},
    )

    return DecompositionResult(
        units=unique_units,
        relations=relations,
        depth=current_depth,
    )