plexus-engine 0.3.6

use super::*;
use plexus_conformance::load_cases_from_path;
use plexus_ir::mlir_text_to_plan;
use plexus_serde::{Expr, Op, VectorMetric};
use std::path::Path;

fn embedded_profile_plan() -> plexus_serde::Plan {
    plexus_serde::Plan {
        version: version(),
        ops: vec![
            Op::ConstRow,
            Op::VectorScan {
                input: 0,
                collection: "docs".to_string(),
                query_vector: Expr::ListLiteral {
                    items: vec![Expr::FloatLiteral(1.0), Expr::FloatLiteral(0.0)],
                },
                metric: VectorMetric::DotProduct,
                top_k: 8,
                approx_hint: false,
                schema: vec![
                    ColDef {
                        name: "doc".to_string(),
                        kind: ColKind::Node,
                        logical_type: LogicalType::Unknown,
                    },
                    ColDef {
                        name: "score".to_string(),
                        kind: ColKind::Float64,
                        logical_type: LogicalType::Float64,
                    },
                ],
            },
            Op::Rerank {
                input: 1,
                score_expr: Expr::VectorSimilarity {
                    metric: VectorMetric::DotProduct,
                    lhs: Box::new(Expr::PropAccess {
                        col: 0,
                        prop: "embedding".to_string(),
                    }),
                    rhs: Box::new(Expr::ListLiteral {
                        items: vec![Expr::FloatLiteral(1.0), Expr::FloatLiteral(0.0)],
                    }),
                },
                top_k: 4,
                schema: vec![
                    ColDef {
                        name: "doc".to_string(),
                        kind: ColKind::Node,
                        logical_type: LogicalType::Unknown,
                    },
                    ColDef {
                        name: "score".to_string(),
                        kind: ColKind::Float64,
                        logical_type: LogicalType::Float64,
                    },
                ],
            },
            Op::Return { input: 2 },
        ],
        root_op: 3,
    }
}

#[test]
fn embedded_graph_rag_profile_accepts_canonical_vector_plan() {
    let plan = embedded_profile_plan();
    let assessment = assess_embedded_graph_rag_plan(&plan);
    assert!(assessment.supported, "{assessment:?}");
    assert!(assessment.missing_required_ops.is_empty());
    assert!(assessment.unsupported_ops.is_empty());
    assert!(assessment.unsupported_exprs.is_empty());
    validate_embedded_graph_rag_plan(&plan).expect("embedded profile validation should pass");
}

#[test]
fn embedded_graph_rag_profile_rejects_non_profile_plan_deterministically() {
    let plan = plexus_serde::Plan {
        version: version(),
        ops: vec![
            Op::ScanNodes {
                labels: vec!["Doc".to_string()],
                schema: vec![ColDef {
                    name: "doc".to_string(),
                    kind: ColKind::Node,
                    logical_type: LogicalType::Unknown,
                }],
                must_labels: Vec::new(),
                forbidden_labels: Vec::new(),
                est_rows: 10,
                selectivity: 1.0,
                graph_ref: None,
            },
            Op::Return { input: 0 },
        ],
        root_op: 1,
    };

    let err = validate_embedded_graph_rag_plan(&plan).expect_err("plan should be rejected");
    assert_eq!(err.assessment.profile, EMBEDDED_GRAPH_RAG_PROFILE);
    assert_eq!(
        err.assessment.missing_required_ops,
        vec!["VectorScan", "Rerank"]
    );
    assert_eq!(err.assessment.unsupported_ops, vec!["ScanNodes"]);
    assert!(err.assessment.unsupported_exprs.is_empty());
    assert_eq!(
        err.to_string(),
        "plan is outside embedded-graph-rag-v0: missing required ops [VectorScan, Rerank]; unsupported ops [ScanNodes]"
    );
}

#[test]
fn embedded_graph_rag_capability_gap_reports_missing_vector_surface() {
    let mut caps = EngineCapabilities::full(VersionRange::new(
        PlanSemver::new(0, 3, 0),
        PlanSemver::new(0, 3, 0),
    ));
    caps.supported_ops.remove(&OpKind::Rerank);
    caps.supported_exprs.remove(&ExprKind::VectorSimilarity);

    let gap = assess_embedded_graph_rag_capabilities(&caps);
    assert!(!gap.supported);
    assert_eq!(gap.missing_ops, vec!["Rerank"]);
    assert_eq!(gap.missing_exprs, vec!["VectorSimilarity"]);
}

#[test]
fn embedded_graph_rag_fixture_matches_iridium_consumer_path() {
    let fixture = Path::new(env!("CARGO_MANIFEST_DIR"))
        .join("src")
        .join("tests")
        .join("fixtures")
        .join("vector")
        .join("003_embedded_graphrag.feature");
    let cases = load_cases_from_path(&fixture).expect("load embedded GraphRAG fixture");
    let case = cases
        .iter()
        .find(|case| case.tags.iter().any(|tag| tag == "iridium-consumer"))
        .expect("iridium-consumer fixture");
    let plan = mlir_text_to_plan(
        case.plan_mlir
            .as_deref()
            .expect("embedded GraphRAG fixture plan_mlir"),
    )
    .expect("parse embedded GraphRAG fixture");

    let assessment = assess_embedded_graph_rag_plan(&plan);
    assert!(assessment.supported, "{assessment:?}");
    assert_eq!(plan.ops.len(), 5);
}