use alpha_id::model::{AlphaIdEntry, Config, IndexStatus};
use alpha_id::packed::{packed_path, write_packed, PackedHeader};
use alpha_id::pipeline::load_packed_or_store;

fn entry(text: &str) -> AlphaIdEntry {
    AlphaIdEntry {
        alpha_id: "X".to_string(),
        valid: true,
        icd_primary: "A00".to_string(),
        icd_star: String::new(),
        icd_addon: String::new(),
        icd_primary2: String::new(),
        orpha: String::new(),
        text: text.to_string(),
    }
}

fn cfg_in(dir: &std::path::Path) -> Config {
    let mut cfg = Config::load("config/default.toml").unwrap();
    cfg.index_dir = dir.to_str().unwrap().to_string();
    cfg.embed_model = "test/model".to_string();
    cfg
}

#[test]
fn index_status_defaults_to_absent() {
    assert_eq!(IndexStatus::default(), IndexStatus::Absent);
}

#[test]
fn index_status_serializes_externally_tagged() {
    let j = serde_json::to_string(&IndexStatus::Mismatch("x".to_string())).unwrap();
    assert!(j.contains("Mismatch"), "got {j}");
}

#[test]
fn packed_beats_store_builds_without_store() {
    let dir = tempfile::tempdir().unwrap();
    let cfg = cfg_in(dir.path());
    let entries = vec![entry("a"), entry("b")];
    let rows = vec![vec![1.0f32, 0.0], vec![0.0f32, 1.0]];
    let h = PackedHeader {
        n_rows: 2,
        dim: 2,
        embed_model: cfg.embed_model.clone(),
        corpus_sha256: "irrelevant-in-iter1".to_string(),
        corpus_name: "c.txt".to_string(),
    };
    write_packed(&packed_path(&cfg.index_dir, &cfg.embed_model), &h, &rows).unwrap();
    // No per-file store populated in `dir`; the index must come from the packed file.
    let (vector, status) = load_packed_or_store(&cfg, &entries);
    assert!(vector.is_some());
    assert_eq!(status, IndexStatus::Ok);
}

#[test]
fn n_rows_mismatch_yields_mismatch_none() {
    let dir = tempfile::tempdir().unwrap();
    let cfg = cfg_in(dir.path());
    let entries = vec![entry("a"), entry("b"), entry("c")]; // 3 entries
    let rows = vec![vec![1.0f32, 0.0], vec![0.0f32, 1.0]]; // packed claims 2 rows
    let h = PackedHeader {
        n_rows: 2,
        dim: 2,
        embed_model: cfg.embed_model.clone(),
        corpus_sha256: "x".to_string(),
        corpus_name: "c.txt".to_string(),
    };
    write_packed(&packed_path(&cfg.index_dir, &cfg.embed_model), &h, &rows).unwrap();
    let (vector, status) = load_packed_or_store(&cfg, &entries);
    assert!(vector.is_none());
    assert!(matches!(status, IndexStatus::Mismatch(_)));
}