from __future__ import annotations
import os, datetime
from typing import List, Dict, Tuple
from qdrant_client import QdrantClient
from qdrant_client.http import models as rest
from .qdrant import QdrantConfig, get_client, _collection_names

def ts_iso() -> str:
    return datetime.datetime.utcnow().replace(microsecond=0).isoformat() + "Z"

def points_for_chunks(prefix: str, chunk_payloads: List[Dict], vectors: List[List[float]]) -> Tuple[str, List[rest.PointStruct]]:
    assert len(chunk_payloads) == len(vectors)
    _, chunks, _ = _collection_names(prefix)
    pts = []
    for pl, vec in zip(chunk_payloads, vectors):
        pts.append(rest.PointStruct(id=pl["id"], vector=vec, payload=pl))
    return chunks, pts

def points_for_note(prefix: str, note_payload: Dict, vector: List[float] | None) -> Tuple[str, List[rest.PointStruct]]:
    notes, _, _ = _collection_names(prefix)
    if vector is None:
        # Für Notizen erlauben wir auch Payload-only Upserts (Vektor leer)
        return notes, [rest.PointStruct(id=note_payload["note_id"], payload=note_payload)]
    return notes, [rest.PointStruct(id=note_payload["note_id"], vector=vector, payload=note_payload)]

def points_for_edges(prefix: str, edges: List[Dict]) -> Tuple[str, List[rest.PointStruct]]:
    _, _, edges_col = _collection_names(prefix)
    pts = []
    for e in edges:
        pid = f"{e['src_id']}~{e['edge_type']}~{e['dst_id']}~{e.get('scope','note')}"
        # 1-dim Dummy-Vektor, weil Collection einen Vektor erwartet
        pts.append(rest.PointStruct(id=pid, vector=[0.0], payload=e))
    return edges_col, pts

def upsert_batch(client: QdrantClient, collection: str, points: List[rest.PointStruct]):
    if not points: return
    client.upsert(collection, points=points, wait=True)