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

import pytest

from tools.answer_evaluation.answer_coverage import answer_coverage
from tools.answer_evaluation.rag_evidence import rag_evidence_context
from tools.answer_evaluation.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_long_valid_overview_is_shortened_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.' not 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': '2. Implementujte vyhľadávač.'})
    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.answer_evaluation.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) == 2 and sum(map(len, units)) <= 600
    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.answer_evaluation.verified_rag import overview_excerpts
    prose = 'Práca skúma vyhľadávanie v slovenských dokumentoch. ' * 18
    payload['sources'][0]['text'] += '\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)