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1 コミット

作成者 SHA1 メッセージ 日付
みてるぞ ffebce36b9 #371 2026-06-16 00:34:48 +09:00
17個のファイルの変更826行の追加2120行の削除
-58
ファイルの表示
@@ -125,64 +125,6 @@ npm run preview
- TypeScript and TSX use 4-space logical indentation. - TypeScript and TSX use 4-space logical indentation.
- In TypeScript and TSX only, replace every leading run of 8 spaces with a tab. - In TypeScript and TSX only, replace every leading run of 8 spaces with a tab.
- Tabs are only for leading indentation, never for spaces after non-space text. - Tabs are only for leading indentation, never for spaces after non-space text.
- TypeScript and TSX imports may stay on one line if they remain within the
line limit; do not expand short type-only imports mechanically.
- In TypeScript and TSX, when a function takes one destructured object
argument plus an inline type, prefer this shape when it fits locally:
```ts
const helper = (
{ value, flag }: { value: string
flag: boolean },
): Result => {
// ...
}
```
- In TypeScript and TSX, put `switch` case block braces on their own lines
when a case needs a lexical block:
```ts
case 'yes':
case 'no':
{
const expected = valueFor (item)
return expected == null || expected === answer
}
```
- In TypeScript and TSX, use `value == null` and `value != null` as the
default nullish checks. Do not use `=== null`, `=== undefined`,
`!== null`, or `!== undefined`.
- If code appears to need a distinction between `null` and `undefined`, treat
that as a design smell and revise the logic to avoid the distinction.
External library APIs that explicitly require distinguishing the two are the
only exception.
- In TypeScript and TSX, keep short arrays on one line when they fit under the
line limit; break arrays only when readability or line length requires it.
- In TypeScript and TSX, when a ternary expression is split across multiple
lines, align `?` and `:` with the condition expression. Do not indent `?` and
`:` one extra level under the condition.
```ts
const value =
condition
? consequent
: alternate
```
- In TypeScript and TSX, keep short ternary expressions on one line when they
fit cleanly under the line limit.
- In TypeScript and TSX, prefer ternary expressions for simple conditional
value selection. Do not replace a clear ternary with `if` statements, and do
not introduce immediately invoked functions just to avoid or reformat a
ternary expression.
- In TypeScript and TSX, do not write `let` followed by later `if` assignments
when the value can be expressed as a single `const` initializer. Prefer
`const` because it prevents accidental later reassignment.
- When fixing formatting, change formatting only. Do not change expression
structure, control flow, or variable mutability unless the requested style
explicitly requires it.
- Do not add production dependencies without explicit approval. - Do not add production dependencies without explicit approval.
- Do not create, modify, or run tests unless the user explicitly asks for - Do not create, modify, or run tests unless the user explicitly asks for
test work. When the user asks for tests, keep working and rerun them until test work. When the user asks for tests, keep working and rerun them until
+2 -13
ファイルの表示
@@ -50,7 +50,7 @@ class GekanatorGamesController < ApplicationController
questions, questions,
post_id: game.correct_post_id, post_id: game.correct_post_id,
user: current_user, user: current_user,
limit: 6) limit: 2)
render json: { render json: {
questions: selected.map { |question| extra_question_json(question) } questions: selected.map { |question| extra_question_json(question) }
@@ -192,10 +192,7 @@ class GekanatorGamesController < ApplicationController
answer_value = answer['answer'].to_s answer_value = answer['answer'].to_s
next if answer_value.blank? || answer_value == 'unknown' next if answer_value.blank? || answer_value == 'unknown'
question_id = game_answer_question_id(answer) question = accepted_questions[answer['question_id'].to_s]
next if question_id.blank?
question = accepted_questions[question_id.to_s]
next unless learnable_game_answer_question?(question) next unless learnable_game_answer_question?(question)
example = example =
@@ -254,7 +251,6 @@ class GekanatorGamesController < ApplicationController
end end
def learnable_game_answer_question? question def learnable_game_answer_question? question
return false if question.nil?
return true if question.kind == 'post_similarity' return true if question.kind == 'post_similarity'
return false unless question.kind == 'tag' return false unless question.kind == 'tag'
@@ -262,11 +258,4 @@ class GekanatorGamesController < ApplicationController
key = condition[:key].to_s key = condition[:key].to_s
!key.start_with?('nico:') !key.start_with?('nico:')
end end
def game_answer_question_id answer
answer['question_id'] ||
answer[:question_id] ||
answer['questionId'] ||
answer[:questionId]
end
end end
-4
ファイルの表示
@@ -1,10 +1,6 @@
require 'rails_helper' require 'rails_helper'
RSpec.describe TagNameSanitisationRule, type: :model do RSpec.describe TagNameSanitisationRule, type: :model do
before do
described_class.unscoped.delete_all
end
describe '.sanitise' do describe '.sanitise' do
before do before do
described_class.create!(priority: 10, source_pattern: '_', replacement: '') described_class.create!(priority: 10, source_pattern: '_', replacement: '')
+10 -255
ファイルの表示
@@ -151,188 +151,6 @@ RSpec.describe 'Gekanator learning API', type: :request do
expect(response).to have_http_status(:unauthorized) expect(response).to have_http_status(:unauthorized)
end end
it 'learns accepted non-nico tag answers from camelCase main game logs' do
sign_in_as admin
tag_question = GekanatorQuestion.create!(
text: 'MAD 要素がある?',
kind: 'tag',
source: 'admin_curated',
status: 'accepted',
priority_weight: 1.0,
condition: { type: 'tag', key: 'meme:MAD' },
created_by: admin
)
expect {
post '/gekanator/games', params: {
guessed_post_id: guessed_post.id,
correct_post_id: correct_post.id,
answers: [
{
questionId: 'tag:meme:MAD',
question_text: 'MAD 要素がある?',
answer: 'yes',
original_answer: 'yes'
},
{
questionId: 'tag:meme:missing',
question_text: '存在しない質問?',
answer: 'yes',
original_answer: 'yes'
},
{
questionId: 'tag:meme:MAD',
question_text: 'MAD 要素がある?',
answer: 'unknown',
original_answer: 'unknown'
}
]
}
}.to change { GekanatorQuestionExample.count }.by(1)
expect(response).to have_http_status(:created)
expect(json['learned_example_count']).to eq(1)
example = GekanatorQuestionExample.last
expect(example).to have_attributes(
gekanator_question_id: tag_question.id,
post_id: correct_post.id,
user_id: admin.id,
answer: 'yes',
source: 'post_game_answer'
)
expect(example.gekanator_game_id).to eq(json['id'])
end
it 'learns accepted post_similarity answers from main game logs' do
sign_in_as admin
question = create_post_similarity_question!(text: '泣いてる?')
expect {
post '/gekanator/games', params: {
guessed_post_id: guessed_post.id,
correct_post_id: correct_post.id,
answers: [
{
question_id: "post-similarity:#{question.id}",
question_text: '泣いてる?',
answer: 'partial',
original_answer: 'partial'
}
]
}
}.to change { GekanatorQuestionExample.count }.by(1)
expect(response).to have_http_status(:created)
expect(json['learned_example_count']).to eq(1)
example = GekanatorQuestionExample.last
expect(example).to have_attributes(
gekanator_question_id: question.id,
post_id: correct_post.id,
user_id: admin.id,
answer: 'partial',
source: 'post_game_answer'
)
expect(example.gekanator_game_id).to eq(json['id'])
end
it 'does not learn fact questions or nico tag questions from main game logs' do
sign_in_as admin
[
{
text: 'example.com 由来?',
kind: 'source',
condition: { type: 'source', host: 'example.com' }
},
{
text: '題名に結束バンドを含む?',
kind: 'title',
condition: { type: 'title-contains', text: '結束バンド' }
},
{
text: '2024 年投稿?',
kind: 'original_date',
condition: { type: 'original-year', year: 2024 }
},
{
text: 'ニコニコにぼっちタグ?',
kind: 'tag',
condition: { type: 'tag', key: 'nico:ぼっち' }
}
].each do |attributes|
GekanatorQuestion.create!(
text: attributes[:text],
kind: attributes[:kind],
source: 'admin_curated',
status: 'accepted',
priority_weight: 1.0,
condition: attributes[:condition],
created_by: admin
)
end
expect {
post '/gekanator/games', params: {
guessed_post_id: guessed_post.id,
correct_post_id: correct_post.id,
answers: [
{ question_id: 'source:example.com', answer: 'yes' },
{ question_id: 'title:contains:結束バンド', answer: 'yes' },
{ question_id: 'original-year:2024', answer: 'yes' },
{ question_id: 'tag:nico:ぼっち', answer: 'yes' }
]
}
}.not_to change { GekanatorQuestionExample.count }
expect(response).to have_http_status(:created)
expect(json['learned_example_count']).to eq(0)
end
it 'updates an existing main game example instead of duplicating it' do
sign_in_as admin
tag_question = GekanatorQuestion.create!(
text: '喜多ちゃんが関係してる?',
kind: 'tag',
source: 'admin_curated',
status: 'accepted',
priority_weight: 1.0,
condition: { type: 'tag', key: 'character:喜多郁代' },
created_by: admin
)
existing = GekanatorQuestionExample.create!(
gekanator_question: tag_question,
post: correct_post,
user: admin,
answer: 'no',
source: 'post_game_answer',
weight: 1.0
)
expect {
post '/gekanator/games', params: {
guessed_post_id: guessed_post.id,
correct_post_id: correct_post.id,
answers: [
{
question_id: 'tag:character:喜多郁代',
answer: 'yes',
original_answer: 'yes'
}
]
}
}.not_to change { GekanatorQuestionExample.count }
expect(response).to have_http_status(:created)
expect(json['learned_example_count']).to eq(1)
expect(existing.reload.answer).to eq('yes')
expect(existing.sample_count).to eq(2)
end
end end
describe 'POST /gekanator/question_suggestions' do describe 'POST /gekanator/question_suggestions' do
@@ -431,7 +249,7 @@ RSpec.describe 'Gekanator learning API', type: :request do
expect(GekanatorQuestionSuggestion.last.processed).to eq(false) expect(GekanatorQuestionSuggestion.last.processed).to eq(false)
end end
it 'allows more than three suggestions per game' do it 'limits suggestions to three per game' do
sign_in_as admin sign_in_as admin
3.times do |i| 3.times do |i|
@@ -449,10 +267,9 @@ RSpec.describe 'Gekanator learning API', type: :request do
question_text: 'fourth question?', question_text: 'fourth question?',
answer: 'yes' answer: 'yes'
} }
}.to change { GekanatorQuestionSuggestion.count }.by(1) }.not_to change { GekanatorQuestionSuggestion.count }
expect(response).to have_http_status(:created) expect(response).to have_http_status(:unprocessable_entity)
expect(json['count']).to eq(4)
end end
it 'allows a non-admin user to suggest a question for their own game' do it 'allows a non-admin user to suggest a question for their own game' do
@@ -509,59 +326,28 @@ RSpec.describe 'Gekanator learning API', type: :request do
end end
describe 'GET /gekanator/games/:id/extra_questions' do describe 'GET /gekanator/games/:id/extra_questions' do
it 'returns at most six accepted user_suggested post_similarity questions without duplicates' do it 'returns at most two accepted user_suggested post_similarity questions without duplicates' do
sign_in_as admin sign_in_as admin
lowest = create_post_similarity_question!(
text: 'lowest?',
priority_weight: 0.5
)
low = create_post_similarity_question!( low = create_post_similarity_question!(
text: 'low?', text: 'low?',
priority_weight: 1.0 priority_weight: 1.0
) )
middle = create_post_similarity_question!(
text: 'middle?',
priority_weight: 1.5
)
medium_high = create_post_similarity_question!(
text: 'medium high?',
priority_weight: 2.0
)
high = create_post_similarity_question!( high = create_post_similarity_question!(
text: 'high?', text: 'high?',
priority_weight: 2.5
)
higher = create_post_similarity_question!(
text: 'higher?',
priority_weight: 2.8
)
highest = create_post_similarity_question!(
text: 'highest?',
priority_weight: 3.0 priority_weight: 3.0
) )
overflow = create_post_similarity_question!( middle = create_post_similarity_question!(
text: 'overflow?', text: 'middle?',
priority_weight: 2.2 priority_weight: 2.0
) )
get "/gekanator/games/#{game.id}/extra_questions" get "/gekanator/games/#{game.id}/extra_questions"
expect(response).to have_http_status(:ok) expect(response).to have_http_status(:ok)
expect(json['questions'].length).to eq(6) expect(json['questions'].length).to eq(2)
expect(json['questions'].map { _1['id'] }.uniq.length).to eq(6) expect(json['questions'].map { _1['id'] }.uniq.length).to eq(2)
expect(json['questions'].map { _1['id'] }).to all( expect(json['questions'].map { _1['id'] }).to all(be_in([low.id, high.id, middle.id]))
be_in([
lowest.id,
low.id,
middle.id,
medium_high.id,
high.id,
higher.id,
highest.id,
overflow.id,
])
)
end end
it 'can return questions that already have an example for the correct post' do it 'can return questions that already have an example for the correct post' do
@@ -584,37 +370,6 @@ RSpec.describe 'Gekanator learning API', type: :request do
expect(json['questions'].map { _1['id'] }).to include(existing.id) expect(json['questions'].map { _1['id'] }).to include(existing.id)
end end
it 'prioritizes questions the current user has not answered' do
sign_in_as admin
answered = create_post_similarity_question!(
text: 'already answered?',
priority_weight: 3.0
)
GekanatorQuestionExample.create!(
gekanator_question: answered,
post: other_post,
user: admin,
answer: 'yes',
source: 'post_game_extra'
)
unanswered =
6.times.map { |index|
create_post_similarity_question!(
text: "unanswered #{index}?",
priority_weight: 0.5
)
}
get "/gekanator/games/#{game.id}/extra_questions"
expect(response).to have_http_status(:ok)
expect(json['questions'].map { _1['id'] }).to match_array(
unanswered.map(&:id)
)
end
it 'can return questions already asked in the game using snake_case question_id' do it 'can return questions already asked in the game using snake_case question_id' do
sign_in_as admin sign_in_as admin
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+1 -37
ファイルの表示
@@ -4,7 +4,6 @@ import { apiPost } from '@/lib/api'
import { import {
buildGekanatorQuestions, buildGekanatorQuestions,
expectedAnswerForQuestion, expectedAnswerForQuestion,
learnedSemanticSideForPost,
questionIdForCondition, questionIdForCondition,
restoreGekanatorQuestion, restoreGekanatorQuestion,
saveGekanatorExtraQuestionAnswers, saveGekanatorExtraQuestionAnswers,
@@ -189,33 +188,6 @@ describe('expectedAnswerForQuestion', () => {
}) })
}) })
describe('learnedSemanticSideForPost', () => {
it('classifies post_similarity examples as positive, negative, or unknown', () => {
const question: StoredGekanatorQuestion = {
id: 'post-similarity:10',
text: '喜多ちゃんが泣いてる?',
kind: 'post_similarity',
source: 'user_suggested',
priorityWeight: 1.2,
condition: {
type: 'post-similarity',
postId: 123,
answer: 'partial',
threshold: 0.65,
},
exampleAnswers: {
1: 'yes',
2: 'probably_no',
},
}
expect(learnedSemanticSideForPost(question, post({ id: 1 }))).toBe('positive')
expect(learnedSemanticSideForPost(question, post({ id: 2 }))).toBe('negative')
expect(learnedSemanticSideForPost(question, post({ id: 3 }))).toBe('unknown')
expect(learnedSemanticSideForPost(question, post({ id: 123 }))).toBe('positive')
})
})
describe('restoreGekanatorQuestion', () => { describe('restoreGekanatorQuestion', () => {
it('uses default source and priority weight when omitted', () => { it('uses default source and priority weight when omitted', () => {
const question = restoreGekanatorQuestion({ const question = restoreGekanatorQuestion({
@@ -276,7 +248,7 @@ describe('restoreGekanatorQuestion', () => {
}) })
expect(question.test(post({ id: 1 }))).toBe(true) expect(question.test(post({ id: 1 }))).toBe(true)
expect(question.test(post({ id: 2 }))).toBe(true) expect(question.test(post({ id: 2 }))).toBe(false)
}) })
it('normalizes legacy title-length-greater-than questions', () => { it('normalizes legacy title-length-greater-than questions', () => {
@@ -400,10 +372,6 @@ describe('Gekanator API writers', () => {
type: 'tag', type: 'tag',
key: 'character:喜多郁代', key: 'character:喜多郁代',
}, },
questionMode: 'normal',
questionPurpose: 'effective_user_suggested',
effectiveQuestion: true,
learningQuestion: false,
answer: 'yes', answer: 'yes',
originalAnswer: 'partial', originalAnswer: 'partial',
}, },
@@ -428,10 +396,6 @@ describe('Gekanator API writers', () => {
type: 'tag', type: 'tag',
key: 'character:喜多郁代', key: 'character:喜多郁代',
}, },
question_mode: 'normal',
question_purpose: 'effective_user_suggested',
effective_question: true,
learning_question: false,
answer: 'yes', answer: 'yes',
original_answer: 'partial', original_answer: 'partial',
}, },
+7 -54
ファイルの表示
@@ -9,24 +9,11 @@ export type GekanatorAnswerValue =
| 'probably_no' | 'probably_no'
| 'unknown' | 'unknown'
export type LearnedSemanticSide =
| 'positive'
| 'negative'
| 'unknown'
export type GekanatorQuestionPurpose =
| 'effective_user_suggested'
| 'learning_user_suggested'
| 'normal'
export type GekanatorAnswerLog = { export type GekanatorAnswerLog = {
questionId: string questionId: string
questionText: string questionText: string
questionCondition?: GekanatorQuestionCondition questionCondition?: GekanatorQuestionCondition
questionMode?: 'normal' | 'winning_run' questionMode?: 'normal' | 'winning_run'
questionPurpose?: GekanatorQuestionPurpose
effectiveQuestion?: boolean
learningQuestion?: boolean
answer: GekanatorAnswerValue answer: GekanatorAnswerValue
originalAnswer: GekanatorAnswerValue } originalAnswer: GekanatorAnswerValue }
@@ -176,26 +163,6 @@ const directExampleAnswerFor = (
return null return null
} }
export const isLearnedSemanticQuestion = (
question: StoredGekanatorQuestion | GekanatorQuestion,
): boolean =>
question.kind === 'post_similarity'
&& question.source === 'user_suggested'
export const learnedSemanticSideForAnswer = (
answer: GekanatorAnswerValue | null,
): LearnedSemanticSide => {
if (answer === 'yes' || answer === 'partial')
return 'positive'
if (answer === 'no' || answer === 'probably_no')
return 'negative'
return 'unknown'
}
const countBy = <T extends string | number> (values: T[]): Map<T, number> => { const countBy = <T extends string | number> (values: T[]): Map<T, number> => {
const counts = new Map<T, number> () const counts = new Map<T, number> ()
values.forEach (value => counts.set (value, (counts.get (value) ?? 0) + 1)) values.forEach (value => counts.set (value, (counts.get (value) ?? 0) + 1))
@@ -318,8 +285,8 @@ const questionMatches = (
): boolean => { ): boolean => {
const directAnswer = directExampleAnswerFor (question, post) const directAnswer = directExampleAnswerFor (question, post)
if (directAnswer) if (directAnswer)
return question.kind === 'post_similarity' return question.condition.type === 'post-similarity'
? learnedSemanticSideForAnswer (directAnswer) === 'positive' ? directAnswer === question.condition.answer
: directAnswer === 'yes' : directAnswer === 'yes'
switch (question.condition.type) switch (question.condition.type)
@@ -361,11 +328,6 @@ export const expectedAnswerForQuestion = (
switch (question.condition.type) switch (question.condition.type)
{ {
case 'post-similarity':
if (question.condition.postId === post.id)
return question.condition.answer
return null
case 'tag': case 'tag':
case 'source': case 'source':
case 'original-year': case 'original-year':
@@ -376,17 +338,12 @@ export const expectedAnswerForQuestion = (
case 'title-has-ascii': case 'title-has-ascii':
case 'title-contains': case 'title-contains':
return questionMatches (post, question) ? 'yes' : 'no' return questionMatches (post, question) ? 'yes' : 'no'
case 'post-similarity':
return null
} }
} }
export const learnedSemanticSideForPost = (
question: StoredGekanatorQuestion | GekanatorQuestion | undefined,
post: Post | null,
): LearnedSemanticSide =>
learnedSemanticSideForAnswer (expectedAnswerForQuestion (question, post))
export const restoreGekanatorQuestion = ( export const restoreGekanatorQuestion = (
question: StoredGekanatorQuestion, question: StoredGekanatorQuestion,
): GekanatorQuestion => { ): GekanatorQuestion => {
@@ -466,15 +423,15 @@ export const buildGekanatorQuestions = (
const originalYears = countBy ( const originalYears = countBy (
posts posts
.map (originalYearOf) .map (originalYearOf)
.filter ((year): year is number => year != null)) .filter ((year): year is number => year !== null))
const originalMonths = countBy ( const originalMonths = countBy (
posts posts
.map (originalMonthOf) .map (originalMonthOf)
.filter ((month): month is number => month != null)) .filter ((month): month is number => month !== null))
const originalMonthDays = countBy ( const originalMonthDays = countBy (
posts posts
.map (originalMonthDayOf) .map (originalMonthDayOf)
.filter ((monthDay): monthDay is string => monthDay != null)) .filter ((monthDay): monthDay is string => monthDay !== null))
const titleLengthMedian = median (posts.map (post => post.title?.length ?? 0)) const titleLengthMedian = median (posts.map (post => post.title?.length ?? 0))
const titleWordCounts = const titleWordCounts =
includeTitleContains includeTitleContains
@@ -636,10 +593,6 @@ export const saveGekanatorGame = async ({
question_id: answer.questionId, question_id: answer.questionId,
question_text: answer.questionText, question_text: answer.questionText,
question_condition: answer.questionCondition ?? null, question_condition: answer.questionCondition ?? null,
question_mode: answer.questionMode,
question_purpose: answer.questionPurpose,
effective_question: answer.effectiveQuestion,
learning_question: answer.learningQuestion,
answer: answer.answer, answer: answer.answer,
original_answer: answer.originalAnswer })) }) original_answer: answer.originalAnswer })) })
+11 -96
ファイルの表示
@@ -11,7 +11,6 @@ import type {
GekanatorAnswerValue, GekanatorAnswerValue,
GekanatorQuestion, GekanatorQuestion,
} from '@/lib/gekanator' } from '@/lib/gekanator'
import type { RecoveredCandidateState } from '@/lib/gekanatorCandidateRecovery'
import type { Post } from '@/types' import type { Post } from '@/types'
@@ -52,21 +51,6 @@ const postSimilarityQuestion = (
}) })
const sourceQuestion = (
host: string,
): GekanatorQuestion => ({
id: `source:${ host }`,
text: `${ host }?`,
kind: 'source',
condition: {
type: 'source',
host },
source: 'default',
priorityWeight: 1,
test: candidate => new URL (candidate.url).hostname === host,
})
const answer = ( const answer = (
question: GekanatorQuestion, question: GekanatorQuestion,
value: GekanatorAnswerValue, value: GekanatorAnswerValue,
@@ -79,17 +63,8 @@ const answer = (
}) })
const recoveredState = (
answerCountAtRecovery: number,
scoreAtRecovery = 0,
): RecoveredCandidateState => ({
answerCountAtRecovery,
scoreAtRecovery,
})
describe('candidatePostsFor', () => { describe('candidatePostsFor', () => {
it('does not hard-filter semantic post_similarity answers', () => { it('lets recovered candidates ignore old answers but not later answers', () => {
const posts = [post (1), post (2), post (3)] const posts = [post (1), post (2), post (3)]
const oldQuestion = postSimilarityQuestion ('old', { const oldQuestion = postSimilarityQuestion ('old', {
1: 'no', 1: 'no',
@@ -109,31 +84,8 @@ describe('candidatePostsFor', () => {
softenedQuestionIds: new Set (), softenedQuestionIds: new Set (),
rejectedPostIds: new Set (), rejectedPostIds: new Set (),
recoveredCandidatePosts: new Map ([ recoveredCandidatePosts: new Map ([
[1, recoveredState (1)], [1, 1],
[3, recoveredState (1)], [3, 1],
]) })
expect(candidates.map (candidate => candidate.id)).toEqual ([1, 2, 3])
})
it('lets recovered candidates ignore old fact answers but not later fact answers', () => {
const posts = [
{ ...post (1), url: 'https://other.example/posts/1' },
post (2),
{ ...post (3), url: 'https://example.com/posts/3' },
]
const oldQuestion = sourceQuestion ('old.example.com')
const laterQuestion = sourceQuestion ('example.com')
const candidates = candidatePostsFor ({
posts,
questions: [oldQuestion, laterQuestion],
answers: [answer (oldQuestion, 'yes'), answer (laterQuestion, 'yes')],
softenedQuestionIds: new Set (),
rejectedPostIds: new Set (),
recoveredCandidatePosts: new Map ([
[1, recoveredState (1)],
[3, recoveredState (1)],
]) }) ]) })
expect(candidates.map (candidate => candidate.id)).toEqual ([3]) expect(candidates.map (candidate => candidate.id)).toEqual ([3])
@@ -152,7 +104,7 @@ describe('candidatePostsFor', () => {
answers: [answer (question, 'yes')], answers: [answer (question, 'yes')],
softenedQuestionIds: new Set (), softenedQuestionIds: new Set (),
rejectedPostIds: new Set ([1]), rejectedPostIds: new Set ([1]),
recoveredCandidatePosts: new Map ([[1, recoveredState (1)]]) }) recoveredCandidatePosts: new Map ([[1, 1]]) })
expect(candidates.map (candidate => candidate.id)).toEqual ([2]) expect(candidates.map (candidate => candidate.id)).toEqual ([2])
}) })
@@ -160,7 +112,7 @@ describe('candidatePostsFor', () => {
describe('hardFilteredPostsForAnswer', () => { describe('hardFilteredPostsForAnswer', () => {
it('keeps the original pool for semantic post_similarity answers', () => { it('returns zero candidates without falling back to the original pool', () => {
const posts = [post (1), post (2)] const posts = [post (1), post (2)]
const question = postSimilarityQuestion ('question', { const question = postSimilarityQuestion ('question', {
1: 'yes', 1: 'yes',
@@ -171,41 +123,7 @@ describe('hardFilteredPostsForAnswer', () => {
posts, posts,
question, question,
answer: 'no', answer: 'no',
})).toEqual (posts) })).toEqual ([])
})
it('hard-filters fact answers only for yes and no', () => {
const posts = [
{ ...post (1), url: 'https://example.com/posts/1' },
{ ...post (2), url: 'https://other.example/posts/2' },
]
const question = sourceQuestion ('example.com')
expect(hardFilteredPostsForAnswer ({
posts,
question,
answer: 'yes',
}).map (candidate => candidate.id)).toEqual ([1])
expect(hardFilteredPostsForAnswer ({
posts,
question,
answer: 'no',
}).map (candidate => candidate.id)).toEqual ([2])
expect(hardFilteredPostsForAnswer ({
posts,
question,
answer: 'partial',
})).toEqual (posts)
expect(hardFilteredPostsForAnswer ({
posts,
question,
answer: 'probably_no',
})).toEqual (posts)
expect(hardFilteredPostsForAnswer ({
posts,
question,
answer: 'unknown',
})).toEqual (posts)
}) })
}) })
@@ -219,7 +137,7 @@ describe('recoverCandidatePosts', () => {
posts, posts,
scores, scores,
rejectedPostIds: new Set ([10]), rejectedPostIds: new Set ([10]),
recoveredCandidatePosts: new Map ([[8, recoveredState (1, 8)]]), recoveredCandidatePosts: new Map ([[8, 1]]),
eligiblePostIds: new Set ([9]), eligiblePostIds: new Set ([9]),
answerCountAtRecovery: 2, answerCountAtRecovery: 2,
recoveryStepCount: 0, recoveryStepCount: 0,
@@ -228,10 +146,7 @@ describe('recoverCandidatePosts', () => {
expect(recovered?.recoveryStepCount).toBe (1) expect(recovered?.recoveryStepCount).toBe (1)
expect([...(recovered?.recoveredCandidatePosts.keys () ?? [])]) expect([...(recovered?.recoveredCandidatePosts.keys () ?? [])])
.toEqual ([8, 7, 6, 5, 4]) .toEqual ([8, 7, 6, 5, 4])
expect(recovered?.recoveredCandidatePosts.get (7)).toEqual ({ expect(recovered?.recoveredCandidatePosts.get (7)).toBe (2)
answerCountAtRecovery: 2,
scoreAtRecovery: 7,
})
}) })
it('does not add posts when recovered and eligible candidates already hit the target', () => { it('does not add posts when recovered and eligible candidates already hit the target', () => {
@@ -243,9 +158,9 @@ describe('recoverCandidatePosts', () => {
scores, scores,
rejectedPostIds: new Set (), rejectedPostIds: new Set (),
recoveredCandidatePosts: new Map ([ recoveredCandidatePosts: new Map ([
[1, recoveredState (1, 1)], [1, 1],
[2, recoveredState (1, 2)], [2, 1],
[3, recoveredState (1, 3)], [3, 1],
]), ]),
eligiblePostIds: new Set ([4, 5, 6]), eligiblePostIds: new Set ([4, 5, 6]),
answerCountAtRecovery: 2, answerCountAtRecovery: 2,
+92 -80
ファイルの表示
@@ -1,49 +1,53 @@
import { isLearnedSemanticQuestion, import { expectedAnswerForQuestion } from '@/lib/gekanator'
learnedSemanticSideForPost } from '@/lib/gekanator'
import type { GekanatorAnswerLog, GekanatorAnswerValue, GekanatorQuestion } from '@/lib/gekanator' import type {
GekanatorAnswerLog,
GekanatorAnswerValue,
GekanatorQuestion,
} from '@/lib/gekanator'
import type { Post } from '@/types' import type { Post } from '@/types'
export type RecoveredCandidatePost = { export type RecoveredCandidatePost = {
postId: number postId: number
answerCountAtRecovery: number answerCountAtRecovery: number }
scoreAtRecovery: number }
export type RecoveredCandidateState = {
answerCountAtRecovery: number
scoreAtRecovery: number }
const questionSupportsAnswerBasedHardFiltering = (question: GekanatorQuestion): boolean => const questionIsFactLikeForHardFiltering = (
!(isLearnedSemanticQuestion (question) question: GekanatorQuestion,
|| (question.kind === 'tag' ): boolean =>
!(question.kind === 'post_similarity'
|| (
question.kind === 'tag'
&& question.condition.type === 'tag' && question.condition.type === 'tag'
&& !(question.condition.key.startsWith ('nico:')))) && !(question.condition.key.startsWith ('nico:'))))
export const candidatePostsFor = ( export const candidatePostsFor = ({
{ posts, posts,
questions, questions,
answers, answers,
softenedQuestionIds, softenedQuestionIds,
rejectedPostIds, rejectedPostIds,
recoveredCandidatePosts }: { posts: Post[] recoveredCandidatePosts,
questions: GekanatorQuestion[] }: {
answers: GekanatorAnswerLog[] posts: Post[]
softenedQuestionIds: Set<string> questions: GekanatorQuestion[]
rejectedPostIds: Set<number> answers: GekanatorAnswerLog[]
recoveredCandidatePosts: Map<number, RecoveredCandidateState> }, softenedQuestionIds: Set<string>
): Post[] => { rejectedPostIds: Set<number>
recoveredCandidatePosts: Map<number, number>
}): Post[] => {
const questionById = new Map (questions.map (question => [question.id, question])) const questionById = new Map (questions.map (question => [question.id, question]))
return posts.filter (post => { return posts.filter (post => {
if (rejectedPostIds.has (post.id)) if (rejectedPostIds.has (post.id))
return false return false
const recoveredCandidate = recoveredCandidatePosts.get (post.id) const answerCountAtRecovery = recoveredCandidatePosts.get (post.id)
return answers.every ((answer, index) => { return answers.every ((answer, index) => {
if (recoveredCandidate != null && index < recoveredCandidate.answerCountAtRecovery) if (answerCountAtRecovery !== undefined && index < answerCountAtRecovery)
return true return true
if (softenedQuestionIds.has (answer.questionId)) if (softenedQuestionIds.has (answer.questionId))
@@ -52,19 +56,16 @@ export const candidatePostsFor = (
const question = questionById.get (answer.questionId) const question = questionById.get (answer.questionId)
if (!(question)) if (!(question))
return true return true
if (!(questionSupportsAnswerBasedHardFiltering (question))) if (!(questionIsFactLikeForHardFiltering (question)))
return true return true
switch (answer.answer) switch (answer.answer)
{ {
case 'yes': case 'yes':
case 'no': case 'no': {
{ const expected = expectedAnswerForQuestion (question, post)
const expected = learnedSemanticSideForPost (question, post) return expected === null || expected === 'unknown' || expected === answer.answer
return expected === 'unknown' }
|| (answer.answer === 'yes' && expected === 'positive')
|| (answer.answer === 'no' && expected === 'negative')
}
default: default:
return true return true
} }
@@ -73,27 +74,33 @@ export const candidatePostsFor = (
} }
export const hardFilteredPostsForAnswer = ( export const hardFilteredPostsForAnswer = ({
{ posts, question, answer }: { posts: Post[] posts,
question: GekanatorQuestion question,
answer: GekanatorAnswerValue }, answer,
): Post[] => { }: {
if (!(questionSupportsAnswerBasedHardFiltering (question))) posts: Post[]
question: GekanatorQuestion
answer: GekanatorAnswerValue
}): Post[] => {
if (!(questionIsFactLikeForHardFiltering (question)))
return posts return posts
if (!(answer === 'yes' || answer === 'no')) if (answer === 'unknown')
return posts return posts
return posts.filter (post => { return posts.filter (post => {
const side = learnedSemanticSideForPost (question, post) const expected = expectedAnswerForQuestion (question, post)
return side === 'unknown' return expected === null || expected === 'unknown' || expected === answer
|| (answer === 'yes' && side === 'positive')
|| (answer === 'no' && side === 'negative')
}) })
} }
const concreteAnswerOptions: GekanatorAnswerValue[] = ['yes', 'no', 'partial', 'probably_no'] const concreteAnswerOptions: GekanatorAnswerValue[] = [
'yes',
'no',
'partial',
'probably_no']
export const allConcreteAnswerOptionsExhausted = ( export const allConcreteAnswerOptionsExhausted = (
@@ -112,48 +119,53 @@ const nextRecoveryTargetSize = (recoveryStepCount: number): number =>
6 * (2 ** recoveryStepCount) 6 * (2 ** recoveryStepCount)
export const recoverCandidatePosts = ( export const recoverCandidatePosts = ({
{ posts, posts,
scores, scores,
rejectedPostIds, rejectedPostIds,
recoveredCandidatePosts, recoveredCandidatePosts,
eligiblePostIds, eligiblePostIds,
answerCountAtRecovery, answerCountAtRecovery,
recoveryStepCount }: { posts: Post[] recoveryStepCount,
scores: Map<number, number> }: {
rejectedPostIds: Set<number> posts: Post[]
recoveredCandidatePosts: Map<number, RecoveredCandidateState> scores: Map<number, number>
eligiblePostIds: Set<number> rejectedPostIds: Set<number>
answerCountAtRecovery: number recoveredCandidatePosts: Map<number, number>
recoveryStepCount: number }, eligiblePostIds: Set<number>
): { recoveredCandidatePosts: Map<number, RecoveredCandidateState> answerCountAtRecovery: number
recoveryStepCount: number } | null => { recoveryStepCount: number
}): {
recoveredCandidatePosts: Map<number, number>
recoveryStepCount: number
} | null => {
const recovered = new Map (recoveredCandidatePosts) const recovered = new Map (recoveredCandidatePosts)
const targetSize = nextRecoveryTargetSize (recoveryStepCount) const targetSize = nextRecoveryTargetSize (recoveryStepCount)
const countedPostIds = new Set ([...eligiblePostIds, ...recovered.keys ()]) const countedPostIds = new Set ([
...eligiblePostIds,
...recovered.keys ()])
const addCount = targetSize - countedPostIds.size const addCount = targetSize - countedPostIds.size
if (addCount <= 0) if (addCount <= 0)
{ return {
return { recoveredCandidatePosts: recovered, recoveredCandidatePosts: recovered,
recoveryStepCount: recoveryStepCount + 1 } recoveryStepCount: recoveryStepCount + 1 }
}
const candidates = const candidates = posts
posts .filter (post =>
.filter (post => (!(rejectedPostIds.has (post.id)) !(rejectedPostIds.has (post.id))
&& !(eligiblePostIds.has (post.id)) && !(eligiblePostIds.has (post.id))
&& !(recovered.has (post.id)))) && !(recovered.has (post.id)))
.sort ((a, b) => ((scores.get (b.id) ?? Number.NEGATIVE_INFINITY) .sort ((a, b) =>
- (scores.get (a.id) ?? Number.NEGATIVE_INFINITY))) (scores.get (b.id) ?? Number.NEGATIVE_INFINITY)
- (scores.get (a.id) ?? Number.NEGATIVE_INFINITY))
.slice (0, addCount) .slice (0, addCount)
if (candidates.length === 0) if (candidates.length === 0)
return null return null
candidates.forEach (post => recovered.set (post.id, { candidates.forEach (post => recovered.set (post.id, answerCountAtRecovery))
answerCountAtRecovery,
scoreAtRecovery: scores.get (post.id) ?? 0 }))
return { recoveredCandidatePosts: recovered, return {
recoveryStepCount: recoveryStepCount + 1 } recoveredCandidatePosts: recovered,
recoveryStepCount: recoveryStepCount + 1 }
} }
-86
ファイルの表示
@@ -1,6 +1,3 @@
import { readFileSync } from 'node:fs'
import { resolve } from 'node:path'
import { describe, expect, it } from 'vitest' import { describe, expect, it } from 'vitest'
import { isQuestionHardFilteredAfterAnswers } from '@/lib/gekanatorQuestionFilters' import { isQuestionHardFilteredAfterAnswers } from '@/lib/gekanatorQuestionFilters'
@@ -52,89 +49,6 @@ const blocked = (
isQuestionHardFilteredAfterAnswers (question (candidate), [answer (previous, value)]) isQuestionHardFilteredAfterAnswers (question (candidate), [answer (previous, value)])
const gekanatorPageSource = readFileSync (
resolve (process.cwd (), 'src/pages/GekanatorPage.tsx'),
'utf8')
const gekanatorBackdropSource = gekanatorPageSource.slice (
gekanatorPageSource.indexOf ('const GekanatorBackdrop'),
gekanatorPageSource.indexOf ('const expectedAnswerFor'))
const gekanatorChooseQuestionSource = gekanatorPageSource.slice (
gekanatorPageSource.indexOf ('const chooseQuestion'),
gekanatorPageSource.indexOf ('const winningRunPriorityFor'))
const gekanatorFallbackQuestionSource = gekanatorPageSource.slice (
gekanatorPageSource.indexOf ('const chooseFallbackQuestion'),
gekanatorPageSource.indexOf ('const shouldEnterGuessPhase'))
describe('GekanatorBackdrop regression structure', () => {
it('keeps displayedBackdropMode as the render-time source of truth', () => {
expect(gekanatorBackdropSource).not.toContain ('isLeavingGuessBackdrop')
expect(gekanatorBackdropSource).not.toContain ('renderBackdropMode')
expect(gekanatorBackdropSource).not.toContain ('renderWinningRunCount')
expect(gekanatorBackdropSource).not.toContain ('renderThumbnails')
expect(gekanatorBackdropSource).not.toContain ('renderIsCrossfading')
expect(gekanatorBackdropSource).toContain (
"const renderedSettings = settingsForMode (displayedBackdropMode)")
expect(gekanatorBackdropSource).toContain (
'scaleForMode (displayedBackdropMode, displayedWinningRunCount)')
expect(gekanatorBackdropSource).toContain (
"backdropMode === 'guess' || displayedBackdropMode === 'guess'")
})
it('does not split guess into a separate renderer or force a remount', () => {
expect(gekanatorBackdropSource).not.toContain ('renderStaticGuessBackdrop')
expect(gekanatorBackdropSource).not.toContain ('guessZoomAnimationKey')
expect(gekanatorBackdropSource).not.toContain ('shouldAnimateGuessZoomIn')
expect(gekanatorBackdropSource).not.toContain ('previousBackdropModeRef')
expect(gekanatorBackdropSource).not.toContain (
'if (isGuessPresentation && guessThumbnail)')
})
it('keeps tile keys independent from backdrop mode', () => {
expect(gekanatorBackdropSource).toContain ('key={duplicate}')
expect(gekanatorBackdropSource).toContain ('key={`${ duplicate }:${ index }`}')
expect(gekanatorBackdropSource).not.toMatch (/key=\{`\$\{\s*mode/)
expect(gekanatorBackdropSource).not.toMatch (/key=\{`\$\{\s*displayedBackdropMode/)
})
it('keeps guess on the shared scale, x, and y animation path', () => {
expect(gekanatorBackdropSource).toContain ('animate={{ scale: renderedScale')
expect(gekanatorBackdropSource).toContain (
"x: displayedBackdropMode === 'guess' ? guessFocusOffset.x : '0%'")
expect(gekanatorBackdropSource).toContain (
"y: displayedBackdropMode === 'guess' ? guessFocusOffset.y : '0%'")
})
})
describe('Gekanator question selection regression structure', () => {
it('prefers normal questions after user_suggested quota has been met', () => {
const normalFallbackIndex = gekanatorChooseQuestionSource.indexOf (
'else if (normalPool.length > 0)')
const effectiveFallbackIndex = gekanatorChooseQuestionSource.indexOf (
'else if (effectiveUserSuggestedPool.length > 0)')
expect(normalFallbackIndex).toBeGreaterThan(0)
expect(effectiveFallbackIndex).toBeGreaterThan(0)
expect(normalFallbackIndex).toBeLessThan(effectiveFallbackIndex)
})
it('does not let fallback questions bypass user_suggested purpose tracking', () => {
expect(gekanatorFallbackQuestionSource).toContain (
"question.source !== 'user_suggested'")
})
it('does not show a fixed extra-question count in the extra learning UI', () => {
expect(gekanatorPageSource).not.toContain ('追加で 2 問まで答えてください。')
expect(gekanatorPageSource).toContain ('追加で質問に答えてください。')
})
})
describe('isQuestionHardFilteredAfterAnswers', () => { describe('isQuestionHardFilteredAfterAnswers', () => {
it('blocks only contradictory or redundant month questions after a yes answer', () => { it('blocks only contradictory or redundant month questions after a yes answer', () => {
const previous: GekanatorQuestionCondition = { type: 'original-month', month: 12 } const previous: GekanatorQuestionCondition = { type: 'original-month', month: 12 }
ファイル差分が大きすぎるため省略します 差分を読込み