"""Technical retrieval limits must not become false claims about answer quality."""

import copy
import json

import pytest

from tools.answers.answer_coverage import answer_coverage
from tools.answers.rag_evidence import rag_evidence_context
from tools.answers.verified_rag import generate_verified_rag, rag_answer_issues, render_rag_answer
from tools.rag.rag_utils import build_context_text

URL = "https://example.test/eva"
GOALS = "1. Preskúmajte metódy vyhľadávania.\n2. Implementujte vyhľadávač.\n3. Vyhodnoťte presnosť.\n4. Navrhnite zlepšenia."


@pytest.fixture
def payload():
    sources = [
        {
            "source_id": "S1",
            "title": "Eva Nová",
            "document_path": "pages/students/2020/eva_nova/README.md",
            "source_url": URL,
            "text": "Sekcia: Diplomová práca 2026\nNázov: Vyhľadávanie informácií.\nZadanie:\n"
            + GOALS,
        }
    ]
    return {
        "status": "ok",
        "reason": None,
        "complete": False,
        "truncated": True,
        "truncation_reasons": ["candidate_limit", "per_document_limit", "result_limit"],
        "index_version": {"version": "fixture"},
        "sources": sources,
        "context": build_context_text(sources),
    }


def answer():
    return {
        "status": "ok",
        "answer": "",
        "claims": [
            {
                "person": "Eva Nová",
                "work_type": "diploma_thesis",
                "title": "Vyhľadávanie informácií",
                "year": 2026,
            }
        ],
        "evidence_quotes": [],
        "source_urls": [URL],
    }


def quote(text):
    return {
        "status": "ok",
        "answer": "",
        "claims": [],
        "source_urls": [URL],
        "evidence_quotes": [{"source_id": "S1", "quote": text}],
    }


@pytest.mark.parametrize(
    "complete,truncated,reasons",
    [
        (False, True, ["candidate_limit", "per_document_limit", "result_limit"]),
        (None, False, []),
        (False, True, ["llm_context_budget"]),
    ],
)
def test_supported_fact_is_not_an_incomplete_answer(payload, complete, truncated, reasons):
    payload.update(complete=complete, truncated=truncated, truncation_reasons=reasons)
    c = rag_evidence_context("Aký je názov a rok diplomovej práce Evy Novej?", payload)
    before = copy.deepcopy(c)
    coverage = answer_coverage(answer(), c)
    assert coverage["status"] == "supported" and coverage["warnings"] == []
    text = render_rag_answer(answer(), c)
    assert "2026" in text and URL in text and "neúpln" not in text
    assert c == before  # Never fake complete=true or remove diagnostic limits.


@pytest.mark.parametrize(
    "question",
    [
        "Vypíš všetky práce Evy Novej.",
        "Aké práce má Eva Nová?",
        "Uveď kompletný zoznam prác Evy Novej.",
        "Vypíš všetky bakalárske a diplomové práce Evy Novej.",
    ],
)
def test_limited_record_list_still_warns(payload, question):
    c = rag_evidence_context(question, payload)
    coverage = answer_coverage(answer(), c)
    assert coverage["scope"] == "list" and coverage["status"] == "partial"
    assert "Uvedený zoznam nemusí obsahovať všetky záznamy." in render_rag_answer(answer(), c)


def test_explicitly_complete_retrieval_does_not_add_a_list_warning(payload):
    payload.update(complete=True, truncated=False, truncation_reasons=[])
    c = rag_evidence_context("Vypíš všetky práce Evy Novej.", payload)
    assert answer_coverage(answer(), c)["warnings"] == []


def test_quoted_title_is_not_an_exhaustive_list_request(payload):
    c = rag_evidence_context("Aký je rok diplomovej práce „Všetky práce v katalógu“?", payload)
    assert answer_coverage(answer(), c)["scope"] == "fact"


def test_unknown_list_coverage_is_not_silently_exhaustive(payload):
    payload.update(complete=None, truncated=False, truncation_reasons=[])
    c = rag_evidence_context("Aké práce má Eva Nová?", payload)
    assert answer_coverage(answer(), c)["warnings"] == ["list_may_be_incomplete"]


def test_legacy_context_without_limit_metadata_remains_usable(payload):
    payload.pop("truncation_reasons")
    payload.pop("complete")
    payload.pop("truncated")
    c = rag_evidence_context("Aký je názov diplomovej práce Evy Novej?", payload)
    assert answer_coverage(answer(), c)["warnings"] == []
    assert "Vyhľadávanie informácií" in render_rag_answer(answer(), c)


def test_regular_assignment_can_show_all_supplied_goals_without_global_warning(payload):
    c = rag_evidence_context("Aké je zadanie diplomovej práce Evy Novej?", payload)
    a = quote(GOALS)
    assert rag_answer_issues(a, c) == []
    text = render_rag_answer(a, c)
    assert "1. Preskúmanie metód vyhľadávania." in text
    assert "4. Návrh zlepšení." in text
    assert "neúpln" not in text and "Zo zdroja" not in text
    assert answer_coverage(a, c)["scope"] == "assignment"


def test_clipped_assignment_gets_specific_warning(payload):
    payload["sources"][0]["text"] += "\n[OBSAH ZDROJA OREZANÝ]"
    payload["context"] = build_context_text(payload["sources"])
    c = rag_evidence_context("Aké je zadanie diplomovej práce Evy Novej?", payload)
    a = quote("1. Preskúmajte metódy vyhľadávania.")
    coverage = answer_coverage(a, c)
    assert coverage["status"] == "partial" and coverage["warnings"] == ["assignment_text_clipped"]
    assert "uvedené body nemusia tvoriť celé zadanie" in render_rag_answer(a, c)


def test_request_for_all_assignment_items_preserves_uncertainty(payload):
    c = rag_evidence_context("Uveď všetky body zadania diplomovej práce Evy Novej.", payload)
    assert answer_coverage(quote(GOALS), c)["warnings"] == ["assignment_completeness_unknown"]


@pytest.mark.parametrize("budget", [False, True])
def test_no_answer_is_bounded_and_only_reports_actual_context_cut(payload, budget):
    payload["truncation_reasons"] = ["llm_context_budget"] if budget else ["result_limit"]
    c = rag_evidence_context("Aké je zadanie diplomovej práce Evy Novej v roku 1999?", payload)
    a = {"status": "no_answer", "claims": [], "evidence_quotes": [], "source_urls": []}
    text = render_rag_answer(a, c)
    assert (
        "Eva Nová" in text
        and "v dostupných podkladoch sa nenašiel záznam diplomovej práce z roku **1999**" in text
    )
    assert "Výpis je neúplný" not in text
    assert ("Časť podkladov bola pri príprave kontextu skrátená." in text) == budget
    assert answer_coverage(a, c)["status"] == "not_found"


def test_irrelevant_dropped_source_does_not_make_cited_assignment_partial(payload):
    payload["sources"].append(
        {
            "source_id": "S2",
            "title": "Iný dokument",
            "source_url": "https://example.test/other",
            "document_path": "pages/topics/other/README.md",
            "text": "Iný obsah\n[OBSAH ZDROJA OREZANÝ]",
        }
    )
    payload["context"] = build_context_text(payload["sources"])
    payload["truncation_reasons"].append("llm_context_budget")
    c = rag_evidence_context("Aké je zadanie diplomovej práce Evy Novej?", payload)
    assert answer_coverage(quote(GOALS), c)["warnings"] == []


def test_exact_aggregate_can_be_supported_despite_limited_evidence(payload):
    c = rag_evidence_context("Koľko prác je evidovaných?", payload)
    c["aggregation"] = {"count": 2, "complete": True}
    a = {"status": "ok", "claims": [], "evidence_quotes": [], "source_urls": [], "count": 2}
    assert answer_coverage(a, c)["status"] == "supported"
    c["aggregation"]["complete"] = False
    assert "count_not_established" in answer_coverage(a, c)["warnings"]


def test_overview_preserves_all_main_assignment_items_without_another_model_request(payload):
    question = "Čomu sa venuje diplomová práca Evy Novej?"
    short = "1. Preskúmanie metód vyhľadávania.\n2. Implementácia vyhľadávača."
    c = rag_evidence_context(question, payload)
    assert rag_answer_issues(quote(GOALS), c) == []
    calls = []

    def complete(messages):
        calls.append(messages)
        return {"choices": [{"message": {"content": json.dumps(quote(GOALS))}}]}

    result = generate_verified_rag(question, payload, complete)
    assert result["accepted_for_delivery"] and len(result["attempts"]) == len(calls) == 1
    assert short in result["answer"] and "3. Vyhodnotenie presnosti." in result["answer"]
    assert "4. Návrh zlepšení." in result["answer"]
    assert result["attempts"][0]["parsed_answer"]["evidence_quotes"][0]["quote"] == GOALS
    assert (
        result["complete"] is False
        and result["truncation_reasons"] == payload["truncation_reasons"]
    )
    assert (
        result["answer_coverage"]["status"] == "supported"
        and result["answer_coverage"]["warnings"] == []
    )


def test_short_comparison_can_cover_three_people_instead_of_dropping_one(payload):
    sources = []
    quotes = []
    for index, (name, slug) in enumerate(
        [("Eva Nová", "eva_nova"), ("Boris Nový", "boris_novy"), ("Cyril Malý", "cyril_maly")], 1
    ):
        source = {
            **payload["sources"][0],
            "source_id": f"S{index}",
            "title": name,
            "source_url": f"https://example.test/{slug}",
            "document_path": f"pages/students/2020/{slug}/README.md",
        }
        sources.append(source)
        quotes.append({"source_id": source["source_id"], "quote": GOALS})
    payload["sources"] = sources
    payload["context"] = build_context_text(sources)
    c = rag_evidence_context(
        "Porovnaj obsah diplomových prác osôb Eva Nová, Boris Nový a Cyril Malý.", payload
    )
    assert len(c["requirements"]["people"]) == 3
    a = {
        "status": "ok",
        "claims": [],
        "evidence_quotes": quotes,
        "source_urls": [s["source_url"] for s in sources],
    }
    assert rag_answer_issues(a, c) == []
    a["evidence_quotes"].pop()
    assert "missing_bound_content_evidence" in rag_answer_issues(a, c)


def test_overview_renderer_only_selects_literal_units_and_preserves_full_evidence(payload):
    from tools.answers.verified_rag import overview_excerpts

    extra = "Stav:\n\n- Implementované indexovanie dokumentov."
    payload["sources"][0]["text"] += "\n" + extra
    payload["context"] = build_context_text(payload["sources"])
    c = rag_evidence_context("Čomu sa venuje diplomová práca Evy Novej?", payload)
    a = quote(GOALS)
    a["evidence_quotes"].append({"source_id": "S1", "quote": extra})
    before = copy.deepcopy(a)
    assert rag_answer_issues(a, c) == []
    units = overview_excerpts(a, c)
    assert len(units) == 4 and all(line in units for line in GOALS.splitlines())
    assert all(
        any(unit in evidence["quote"] for evidence in a["evidence_quotes"]) for unit in units
    )
    assert a == before


def test_long_prose_excerpt_is_selected_without_inventing_a_summary(payload):
    from tools.answers.verified_rag import overview_excerpts

    prose = "Práca skúma vyhľadávanie v slovenských dokumentoch. " * 18
    payload["sources"][0]["text"] = (
        "Sekcia: Diplomová práca 2026\nNázov: Vyhľadávanie informácií.\n" + prose
    )
    payload["context"] = build_context_text(payload["sources"])
    c = rag_evidence_context("Čomu sa venuje diplomová práca Evy Novej?", payload)
    a = quote(prose)
    assert rag_answer_issues(a, c) == []
    units = overview_excerpts(a, c)
    assert units and sum(map(len, units)) <= 600 and all(unit in prose for unit in units)