[NOOK-176] OCR 장소 후보 추출 상한 확대

docs/tasks/NOOK-176/README.md

@@ -0,0 +1,22 @@
+# NOOK-176 OCR 장소 후보 탈락률 개선
+
+## 목적
+
+OCR transcript에 다수의 장소명이 포함된 게시물에서 장소 clue 추출 단계의 개수 제한 때문에 후보가 과도하게 탈락하지 않도록 한다.
+
+## 범위
+
+- 장소 clue 반환 상한을 20개에서 60개로 확대한다.
+- 본문에 `52곳`처럼 20개를 초과하는 기대 장소 개수가 있어도 OCR fallback과 recall recovery 판단에 사용한다.
+- OpenAI structured output schema, 출력 토큰 한도, 프롬프트의 장소 개수 상한을 함께 조정한다.
+
+## 제외 범위
+
+- OCR provider 교체
+- 게시물 이미지 저장 흐름 변경
+- DB 스키마 변경
+
+## 검증
+
+- `./gradlew :nook-api-application:test --tests org.every.nook.api.application.place.ProcessPlaceParsingJobUseCaseTest`
+- `./gradlew check`

nook-api-application/src/main/kotlin/org/every/nook/api/application/place/ProcessPlaceParsingJobUseCase.kt

@@ -329,7 +329,7 @@ class ProcessPlaceParsingJobUseCase(
         val logger = KotlinLogging.logger {}
         val eventLogger = LoggerFactory.getLogger(ProcessPlaceParsingJobUseCase::class.java)
 
-        const val MAX_PLACE_COUNT = 20
+        const val MAX_PLACE_COUNT = 60
         const val MAX_QUERY_COUNT = 4
         const val MAX_IMAGE_COUNT = 20
         const val CANDIDATE_LOG_LIMIT = 5
@@ -425,7 +425,7 @@ private fun String.groundingKey(): String = lowercase().filter(Char::isLetterOrD
 
 private const val MIN_GROUNDING_KEY_LENGTH = 2
 private const val MIN_EXPECTED_PLACE_COUNT = 2
-private const val MAX_EXPECTED_PLACE_COUNT = 20
+private const val MAX_EXPECTED_PLACE_COUNT = 80
 private val EXPECTED_PLACE_COUNT_PATTERN = Regex("(?<!\\d)(\\d{1,2})\\s*(?:곳|선|군데)")
 
 private fun PlaceClue.isSupportedBy(candidate: PlaceCandidate): Boolean {

nook-api-application/src/test/kotlin/org/every/nook/api/application/place/ProcessPlaceParsingJobUseCaseTest.kt

@@ -186,6 +186,79 @@ class ProcessPlaceParsingJobUseCaseTest {
         assertEquals(listOf(1, 2), port.storedImageTranscripts?.map(ImageTranscript::imageIndex))
     }
 
+    @Test
+    fun `uses image fallback when text results do not meet a high expected count`() {
+        val port = FakeJobPort(
+            body = "압구정 맛집 52곳: 텍스트 장소",
+            imageUrls = listOf("https://cdn.test/1.jpg"),
+        )
+        val requests = mutableListOf<PlaceClueExtractor.Request>()
+        val extractor = PlaceClueExtractor { request ->
+            requests += request
+            if (request.imageTranscripts.isEmpty()) {
+                listOf(PlaceClue("텍스트 장소", "압구정", listOf("텍스트 장소")))
+            } else {
+                listOf(
+                    PlaceClue(
+                        "이미지 장소",
+                        "압구정",
+                        listOf("이미지 장소"),
+                        listOf(PlaceClueEvidence(1, "이미지 장소 / 압구정")),
+                    ),
+                )
+            }
+        }
+        val useCase = useCase(
+            port,
+            extractor,
+            SearchPlaceCandidatesUseCase { request ->
+                listOf(candidate(request.query, request.query, "서울 강남구 압구정"))
+            },
+        )
+
+        assertIs<ProcessPlaceParsingJobUseCase.Result.Completed>(useCase(1))
+        assertEquals(2, requests.size)
+        assertEquals(listOf("텍스트 장소", "이미지 장소"), port.completed.map(PlaceCandidate::name))
+    }
+
+    @Test
+    fun `resolves more than twenty image place clues`() {
+        val placeCount = 25
+        val port = FakeJobPort(
+            body = "압구정 맛집 ${placeCount}곳",
+            imageUrls = (1..20).map { "https://cdn.test/$it.jpg" },
+            textClues = emptyList(),
+            imageTranscripts = (1..20).map { imageIndex ->
+                ImageTranscript(imageIndex, listOf("이미지 장소 $imageIndex"))
+            },
+        )
+        val useCase = useCase(
+            port = port,
+            extractor = PlaceClueExtractor { request ->
+                if (request.imageTranscripts.isEmpty()) {
+                    emptyList()
+                } else {
+                    (1..placeCount).map { index ->
+                        val imageIndex = ((index - 1) % 20) + 1
+                        PlaceClue(
+                            name = "이미지 장소 $index",
+                            region = "압구정",
+                            queries = listOf("이미지 장소 $index"),
+                            evidence = listOf(PlaceClueEvidence(imageIndex, "이미지 장소 $index / 압구정")),
+                        )
+                    }
+                }
+            },
+            search = SearchPlaceCandidatesUseCase { request ->
+                listOf(candidate(request.query, request.query, "서울 강남구 압구정"))
+            },
+        )
+
+        assertIs<ProcessPlaceParsingJobUseCase.Result.Completed>(useCase(1))
+        assertEquals(placeCount, port.completed.size)
+        assertEquals("이미지 장소 25", port.completed.last().name)
+    }
+
     @Test
     fun `transcribes at most twenty images in batches of five`() {
         val imageUrls = (0 until 25).map { "https://cdn.test/$it.jpg" }

nook-api-infrastructure/src/main/kotlin/org/every/nook/api/infrastructure/openai/OpenAiContentInferenceAdapter.kt

@@ -222,11 +222,11 @@ class OpenAiContentInferenceAdapter(
         const val NANOS_PER_MILLISECOND = 1_000_000
 
         const val MAX_TITLE_LENGTH = 25
-        const val MAX_PLACE_COUNT = 20
+        const val MAX_PLACE_COUNT = 60
         const val MAX_QUERY_COUNT = 4
-        const val CONTENT_INFERENCE_MAX_OUTPUT_TOKENS = 3000
-        const val PLACE_MAX_OUTPUT_TOKENS = 800
-        const val IMAGE_PLACE_MAX_OUTPUT_TOKENS = 4000
+        const val CONTENT_INFERENCE_MAX_OUTPUT_TOKENS = 8000
+        const val PLACE_MAX_OUTPUT_TOKENS = 2500
+        const val IMAGE_PLACE_MAX_OUTPUT_TOKENS = 12000
         const val CANDIDATE_SELECTION_MAX_OUTPUT_TOKENS = 100
         const val PLACE_TAG_MAX_OUTPUT_TOKENS = 600
         const val DEFAULT_TITLE = "Instagram 게시물"
@@ -316,7 +316,7 @@ class OpenAiContentInferenceAdapter(
                 "예를 들어 sourceLocationTag가 Lodge190이고 본문이 '연희동 사랑방 롯지190'이면 name은 Lodge190이고 " +
                 "queries는 원문 Lodge190, 한글 음차 롯지190, 띄어쓰기 변형 롯지 190, " +
                 "지역을 붙인 축약형 연희동 Lodge 순서로 반환한다. " +
-                "가게 근거가 없으면 places를 빈 배열로 반환한다. 최대 20개 가게와 가게당 최대 4개 검색어만 반환한다."
+                "가게 근거가 없으면 places를 빈 배열로 반환한다. 최대 60개 가게와 가게당 최대 4개 검색어만 반환한다."
         const val CONTENT_INFERENCE_INSTRUCTIONS =
             "title과 places를 하나의 응답으로 함께 반환한다. " + TITLE_INSTRUCTIONS + " " + PLACE_INSTRUCTIONS
         const val CANDIDATE_SELECTION_INSTRUCTIONS =

nook-api-infrastructure/src/main/kotlin/org/every/nook/api/infrastructure/place/NaverPlaceMapper.kt

@@ -25,7 +25,7 @@ class NaverPlaceMapper {
                 address = displayAddress,
                 latitude = latitude,
                 longitude = longitude,
-                category = item.category.toPlainText(),
+                category = item.category.toTopLevelCategory(),
                 phoneNumber = item.telephone.toNullableValue(),
                 providerUrl = item.link.toNullableValue(),
             )
@@ -51,6 +51,10 @@ class NaverPlaceMapper {
         ?.trim()
         ?.takeIf(String::isNotEmpty)
 
+    private fun String?.toTopLevelCategory(): String? = toPlainText()
+        ?.substringBefore(CATEGORY_DELIMITER)
+        ?.toNullableValue()
+
     private fun stableId(name: String, address: String, longitude: BigDecimal, latitude: BigDecimal): String =
         MessageDigest.getInstance("SHA-256")
             .digest("$name|$address|${longitude.toPlainString()}|${latitude.toPlainString()}".toByteArray())
@@ -59,6 +63,7 @@ class NaverPlaceMapper {
     private companion object {
         const val PROVIDER = "NAVER"
         const val WGS84_SCALE = 7
+        const val CATEGORY_DELIMITER = ">"
         val HTML_TAG = Regex("<[^>]+>")
         val MIN_LONGITUDE = BigDecimal("-180")
         val MAX_LONGITUDE = BigDecimal("180")

nook-api-infrastructure/src/test/kotlin/org/every/nook/api/infrastructure/openai/OpenAiContentInferenceAdapterTest.kt

@@ -70,7 +70,7 @@ class OpenAiContentInferenceAdapterTest {
             .andExpect(content().string(containsString("post_content_inference")))
             .andExpect(content().string(containsString("홍보성")))
             .andExpect(content().string(containsString("\"maxLength\":25")))
-            .andExpect(content().string(containsString("\"maxItems\":20")))
+            .andExpect(content().string(containsString("\"maxItems\":60")))
             .andRespond(
                 withSuccess(
                     response(
@@ -104,7 +104,7 @@ class OpenAiContentInferenceAdapterTest {
         val fixture = adapterFixture()
         fixture.server.expect(requestTo("https://api.openai.test/v1/responses"))
             .andExpect(content().string(containsString("place_clues")))
-            .andExpect(content().string(containsString("\"maxItems\":20")))
+            .andExpect(content().string(containsString("\"maxItems\":60")))
             .andRespond(
                 withSuccess(
                     response(
@@ -188,7 +188,7 @@ class OpenAiContentInferenceAdapterTest {
         fixture.server.expect(requestTo("https://api.openai.test/v1/responses"))
             .andExpect(content().string(not(containsString("\"type\":\"input_image\""))))
             .andExpect(content().string(containsString("빈브라더스 커피하우스 서울")))
-            .andExpect(content().string(containsString("\"max_output_tokens\":4000")))
+            .andExpect(content().string(containsString("\"max_output_tokens\":12000")))
             .andRespond(
                 withSuccess(
                     response(

nook-api-infrastructure/src/test/kotlin/org/every/nook/api/infrastructure/place/NaverPlaceMapperTest.kt

@@ -25,6 +25,7 @@ class NaverPlaceMapperTest {
         assertEquals("서울특별시 용산구 한강대로77길 4-1", candidate.address)
         assertEquals("126.972332".toBigDecimal(), candidate.longitude)
         assertEquals("37.543123".toBigDecimal(), candidate.latitude)
+        assertEquals("음식점", candidate.category)
     }
 
     @Test