"""L2: tht memory save-one against real pgvector (spec D11, L2).

Validates D11 end-to-end: a single promoted decision is upserted to the real
pgvector via the WRITER key (not a full resync), and a subsequent search_similar
finds the memory. L1 tested the pure save_one_memory core; here the REST writer +
real pgvector + real embeddings are in the loop.

Run: pytest -m l2 tests/l2/test_memory_save_one_real.py -s  (needs .env + VPN + Ollama)
"""
from datetime import datetime
from pathlib import Path
from unittest.mock import MagicMock

import pytest

from tht.memory import MemoryRecord, save_one_memory
from tht.workspace import load_workspace

pytestmark = [pytest.mark.l2]
WORKSPACE = Path(__file__).resolve().parents[2] / "workspaces" / "tht-test.yaml"


def test_save_one_upserts_to_real_pgvector(l2_env):
    """save_one_memory pushes one row to the real pgvector via the writer key, and
    a subsequent search_similar retrieves it. Idempotent (re-running upserts >= 0)."""
    from tht.vectorstore.embeddings import OllamaEmbeddings
    from tht.vectorstore.rest_client import VectorRestClient

    ws = load_workspace(WORKSPACE)
    if not ws.vector_write_rest or not ws.vector_write_rest.api_key.strip():
        pytest.skip("vector_write_rest not configured (no writer key)")

    writer = VectorRestClient(ws.vector_write_rest)
    embedder = OllamaEmbeddings(ws.embeddings)

    record = MemoryRecord(
        id="mem-l2test", ts=datetime.now(), session_id="l2-self-test",
        decision_seq=999, type="table_promoted", subject="fct_ricoveri",
        detail="ablazione", rationale="L2 self-test (idempotent)",
        question_context="ablazione 2025", tables=["fct_ricoveri"], concepts=[],
    )
    from tht.adapters.vector import ThothHttpVectorStore

    store = ThothHttpVectorStore(reader=writer, writer=writer)
    upserted = save_one_memory([record], decision_seq=999, store=store, embedder=embedder)
    assert upserted >= 0  # idempotent: 0 on unchanged, >=1 on new/updated

    # read it back via the READER key (vector_rest, path /vector/v1/)
    reader = VectorRestClient(ws.vector_rest)
    qvec = embedder.embed_query("ablazione")
    hits = reader.search_similar("memory", qvec, 10)
    ids = {h.get("metadata", {}).get("record_key", "") for h in hits}
    assert "memory:mem-l2test" in ids, "upserted memory not retrievable via search_similar"