"""Integration test: importer end-to-end against ``tests/fixtures/docs/``.

Runs the real import pipeline (walk → chunk → embed → upsert) into the
local compose Postgres, then checks the DB state *and* the API shape a
browser would consume. Embeddings come from a deterministic in-process
fake, so no network is needed.
"""
from __future__ import annotations

import asyncio
from pathlib import Path

from sqlalchemy import func, select, text

from app.models import Chunk, Document
from app.rag.importer import import_sources
from tests.fakes import FakeEmbedder

FIXTURES = Path(__file__).resolve().parents[1] / "fixtures" / "docs"

EXPECTED_DOCS = {
    ("docs", "homelab/kubernetes.md"),
    ("docs", "homelab/backups.md"),
    ("docs", "deployments/new-service.md"),
}


def test_import_fixtures_end_to_end(client, db) -> None:
    db.execute(text("TRUNCATE chunks, documents, query_log"))
    db.commit()
    llm = FakeEmbedder()

    summary = asyncio.run(import_sources([FIXTURES], llm, session=db))
    assert (summary.files, summary.added, summary.unchanged) == (3, 3, 0)
    assert summary.chunks >= 3

    docs = db.scalars(select(Document)).all()
    assert {(d.source, d.path) for d in docs} == EXPECTED_DOCS
    titles = {d.path: d.title for d in docs}
    assert titles["homelab/kubernetes.md"] == "Kubernetes Homelab Cluster"
    assert titles["deployments/new-service.md"] == "Deploying a New Service"
    # Full content is stored — that is what the RAG context will be.
    k8s = next(d for d in docs if d.path == "homelab/kubernetes.md")
    assert "Talos Linux" in k8s.content and k8s.content_hash

    n_chunks = db.scalar(select(func.count()).select_from(Chunk))
    assert n_chunks == summary.chunks
    for c in db.scalars(select(Chunk)).all():
        assert c.embedding is not None and len(c.embedding) == 768

    # The Sources page consumes exactly this shape.
    r = client.get("/api/docs")
    assert r.status_code == 200
    body = r.json()
    assert len(body["documents"]) == 3
    assert all(d["chunks"] >= 1 for d in body["documents"])

    # Idempotent re-run: nothing re-embedded.
    calls_before = len(llm.calls)
    s2 = asyncio.run(import_sources([FIXTURES], llm, session=db))
    assert s2.unchanged == 3 and s2.added == 0
    assert len(llm.calls) == calls_before  # unchanged → no embedding requests

    db.execute(text("TRUNCATE chunks, documents, query_log"))
    db.commit()