"""Ингест-пайплайн: источник → чанки → атомы → PG + outbox."""
from __future__ import annotations
import psycopg
from . import db, distill, ingest
from .ingest import ParsedDoc

def ingest_doc(conn, doc: ParsedDoc, *, verify: bool = False,
               min_confidence: float = 0.4, dedup: bool = True,
               dedup_threshold: float = 0.93) -> dict:
    """Прогнать документ через пайплайн. Возвращает статистику.

    dedup: семантическая дедупликация по эмбеддингам (Qdrant) против
    существующих атомов — вариации одного факта от LLM не дублируются.
    """
    doc_id = db.upsert_document(
        conn, kind=doc.kind, uri=doc.uri, title=doc.title,
        content_hash=doc.content_hash,
    )
    stats = {"doc_id": doc_id, "chunks": 0, "atoms_created": 0,
             "atoms_skipped": 0, "duplicates": 0}

    with conn.cursor() as cur:
        for ch in doc.chunks:
            cur.execute(
                "INSERT INTO pm_chunk (doc_id, seq, content, locator) VALUES (%s, %s, %s, %s) RETURNING id",
                (doc_id, ch.seq, ch.content, __import__("json").dumps(ch.locator, ensure_ascii=False)),
            )
            stats["chunks"] += 1

            # дистилляция чанка в атомы
            atoms = distill.distill_chunk(ch.content)
            for a in atoms:
                if a.get("confidence", 0.5) < min_confidence:
                    stats["atoms_skipped"] += 1
                    continue
                # семантическая дедупликация
                if dedup:
                    from . import dedup as _dedup
                    dup_id = _dedup.find_duplicate(
                        (a.get("claim") or "") + " " + str(a["content"])[:800],
                        threshold=dedup_threshold,
                    )
                    if dup_id is not None:
                        stats["duplicates"] += 1
                        stats["atoms_skipped"] += 1
                        continue
                atom_id, created = db.upsert_atom(
                    conn,
                    type=a["type"],
                    claim=a.get("claim"),
                    content=a["content"],
                    confidence=a.get("confidence", 0.5),
                    doc_id=doc_id,
                    locator=ch.locator,
                    metadata=a.get("metadata") or a.get("content_json"),
                )
                if created:
                    stats["atoms_created"] += 1
                    db.enqueue_outbox(conn, entity_type="atom", entity_id=atom_id)
                else:
                    stats["atoms_skipped"] += 1
    conn.commit()
    return stats

def ingest_text(conn, text: str, *, title: str | None = None, uri: str | None = None,
                **kw) -> dict:
    doc = ingest.parse_text(text, title=title, uri=uri)
    return ingest_doc(conn, doc, **kw)

def ingest_file(conn, path: str, **kw) -> dict:
    low = path.lower()
    if low.endswith(".pdf"):
        doc = ingest.parse_pdf(path)
    elif low.endswith(".epub"):
        doc = ingest.parse_epub(path)
    else:
        doc = ingest.parse_text(open(path, encoding="utf-8").read(),
                                title=path.split("/")[-1], uri=path)
    return ingest_doc(conn, doc, **kw)

def ingest_url(conn, url: str, **kw) -> dict:
    doc = ingest.parse_web(url)
    return ingest_doc(conn, doc, **kw)