from repo_registry.core.models import ContentChunk, ObservedFact
from repo_registry.llm_extraction import (
    ExtractedAbility,
    ExtractedCapability,
    ExtractedEvidence,
    ExtractedFeature,
    LLMExtractionMapper,
)


def fact(id, kind, name, path, line=None):
    metadata = {}
    if line is not None:
        metadata["line"] = line
    return ObservedFact(
        id=id,
        repository_id=1,
        analysis_run_id=1,
        snapshot_id=1,
        kind=kind,
        path=path,
        name=name,
        value="",
        metadata=metadata,
    )


def chunk(id, kind, path, start_line=1):
    return ContentChunk(
        id=id,
        repository_id=1,
        analysis_run_id=1,
        snapshot_id=1,
        path=path,
        kind=kind,
        start_line=start_line,
        end_line=start_line + 2,
        text="source text",
    )


def test_llm_extraction_mapper_builds_candidate_drafts_with_source_refs():
    extracted = [
        ExtractedAbility(
            name="Business Email Routing",
            description="Routes email.",
            source_paths=["README.md"],
            capabilities=[
                ExtractedCapability(
                    name="Classify Incoming Email",
                    description="Classifies email.",
                    inputs=["email body"],
                    outputs=["intent"],
                    source_paths=["README.md"],
                    features=[
                        ExtractedFeature(
                            name="POST /classify",
                            type="REST endpoint",
                            location="app.py",
                            source_paths=["app.py"],
                        )
                    ],
                    evidence=[
                        ExtractedEvidence(
                            type="test",
                            reference="tests/test_app.py",
                            strength="strong",
                            source_paths=["tests/test_app.py"],
                        )
                    ],
                )
            ],
        )
    ]
    facts = [
        fact(1, "documentation", "README", "README.md"),
        fact(2, "interface", "python route decorator", "app.py", line=4),
        fact(3, "test", "test_app.py", "tests/test_app.py"),
    ]

    candidates = LLMExtractionMapper().map(extracted, facts, [])

    ability = candidates[0]
    capability = ability.capabilities[0]
    assert ability.name == "Business Email Routing"
    assert ability.confidence == 0.7
    assert ability.source_refs[0].fact_id == 1
    assert capability.inputs == ["email body"]
    assert capability.outputs == ["intent"]
    assert capability.features[0].source_refs[0].line == 4
    assert capability.evidence[0].source_refs[0].kind == "test"


def test_llm_extraction_mapper_can_use_chunk_refs_without_facts():
    extracted = [
        ExtractedAbility(
            name="Readme Ability",
            source_paths=["README.md:1-3"],
        )
    ]

    candidates = LLMExtractionMapper().map(
        extracted,
        facts=[],
        chunks=[chunk(1, "documentation", "README.md", start_line=1)],
    )

    assert candidates[0].source_refs[0].fact_id is None
    assert candidates[0].source_refs[0].path == "README.md"
    assert candidates[0].source_refs[0].line == 1