from typing import List
import time


# =========================
# Query Bundle Builder
# =========================
def build_query_bundle(sub: dict, chapter_title: str, section_title: str) -> List[str]:
    planning = sub.get("planning", {})
    queries = []

    if planning.get("core_idea"):
        queries.append(planning["core_idea"])

    for kp in planning.get("key_points", [])[:3]:
        if isinstance(kp, str):
            queries.append(kp)

    for q in sub.get("suggested_queries", [])[:2]:
        queries.append(q)

    queries.append(sub.get("title", ""))
    queries.append(f"{chapter_title} - {section_title}")

    seen = set()
    final = []
    for q in queries:
        q = q.strip()
        if q and q not in seen:
            seen.add(q)
            final.append(q)

    return final


# =========================
# Citations
# =========================
def make_in_text_citation(author, year, page_start):
    a = author or "مؤلف"
    y = year if isinstance(year, int) else "د.ت"
    p = page_start if isinstance(page_start, int) else "؟"
    return f"({a}، {y}، ص {p})"


def make_reference_apa(author, year, title):
    a = author or "مؤلف"
    y = year if isinstance(year, int) else "د.ت"
    t = title or "مصدر بدون عنوان"
    return f"{a}. ({y}). {t}."


# =========================
# RAG for Subsection (MULTI-BOOK)
# =========================
def build_rag_context_for_subsection(
    rag_engines: List,
    sub: dict,
    chapter_title: str,
    section_title: str,
    top_k: int = 5,
) -> dict:

    queries = build_query_bundle(sub, chapter_title, section_title)
    all_hits = []

    # 🔥 search in ALL source books
    for rag in rag_engines:
        hits = rag.retrieve(queries=queries)
        all_hits.extend(hits)

    if not all_hits:
        return {
            "query_bundle": queries,
            "selected_k": 0,
            "chunks": [],
            "coverage_note": "لم يتم العثور على مراجع مناسبة لهذا المحور.",
        }

    # sort globally
    all_hits = sorted(all_hits, key=lambda x: x.score, reverse=True)[:top_k]

    chunks = []
    for h in all_hits:
        payload = h.payload or {}
        chunks.append(
            {
                "chunk_id": h.id,
                "score": h.score,
                "doc_id": payload.get("doc_id"),
                "page_start": payload.get("page_start"),
                "page_end": payload.get("page_end"),
                "title": payload.get("title"),
                "author": payload.get("author"),
                "year": payload.get("year"),
                "text": payload.get("text"),
                "in_text_citation": make_in_text_citation(
                    payload.get("author"),
                    payload.get("year"),
                    payload.get("page_start"),
                ),
                "reference_apa": make_reference_apa(
                    payload.get("author"),
                    payload.get("year"),
                    payload.get("title"),
                ),
            }
        )

    return {
        "query_bundle": queries,
        "selected_k": len(chunks),
        "chunks": chunks,
        "coverage_note": "تم اختيار أفضل المراجع المتوافقة مع فكرة المحور وحدوده.",
    }


# =========================
# Book-Level Automation
# =========================
def run_rag_automation_on_book(
    planned_book: dict,
    rag_engines: List,
    top_k: int = 5,
    sleep_s: float = 0.1,
) -> dict:

    for chapter in planned_book.get("chapters", []):
        ch_title = chapter.get("chapter_title", "")

        for section in chapter.get("sections", []):
            sec_title = section.get("title", "")

            for sub in section.get("subsections", []):
                rag_context = build_rag_context_for_subsection(
                    rag_engines=rag_engines,
                    sub=sub,
                    chapter_title=ch_title,
                    section_title=sec_title,
                    top_k=top_k,
                )

                sub["rag_context"] = rag_context
                time.sleep(sleep_s)

    return planned_book