{
$service = new AutoMarkService();
$pendingCount = $service->getPendingUnverifiedCount();
+ $verifiedCount = $service->getLlmVerifiedCount();
+ $nextPredictionId = $service->getNextPendingPredictionId();
if ($pendingCount === 0) {
$this->stdout("Нет предсказаний для LLM-верификации.\n");
return ExitCode::OK;
}
+ $this->stdout("LLM already verified: {$verifiedCount}\n");
+ $this->stdout("LLM pending left: {$pendingCount}\n");
+ $this->stdout("LLM next prediction id: " . ($nextPredictionId ?? 'none') . "\n");
$this->stdout("Запуск LLM-верификации ({$pendingCount} предсказаний)...\n");
return $this->runLlmVerify($service);
}
$this->stdout("LLM config warning: используется legacy-конфиг LLM_ENDPOINT/LLM_API_KEY/LLM_MODEL\n");
}
- $verified = $service->llmBatchVerify();
+ $verified = $service->llmBatchVerify(function (string $event, array $data): void {
+ switch ($event) {
+ case 'batch_start':
+ $batchNumber = (int) ($data['batchNumber'] ?? 0);
+ $totalBatches = (int) ($data['totalBatches'] ?? 0);
+ $predictionIds = implode(',', $data['predictionIds'] ?? []);
+ $processedPredictions = (int) ($data['processedPredictions'] ?? 0);
+ $totalPredictions = (int) ($data['totalPredictions'] ?? 0);
+ $this->stdout(
+ sprintf(
+ "[%d/%d] request ids=[%s] processed=%d/%d\n",
+ $batchNumber,
+ $totalBatches,
+ $predictionIds,
+ $processedPredictions,
+ $totalPredictions
+ )
+ );
+ break;
+
+ case 'batch_success':
+ /** @var array<int, \yii_app\services\automark\LlmVerifyResult> $results */
+ $results = $data['results'] ?? [];
+ $summary = [];
+ foreach ($results as $result) {
+ $suffix = $result->hasCorrections() ? ':patched' : '';
+ $summary[] = sprintf('%d:%s%s', $result->predictionId, $result->verdict, $suffix);
+ }
+ $batchNumber = (int) ($data['batchNumber'] ?? 0);
+ $totalBatches = (int) ($data['totalBatches'] ?? 0);
+ $verifiedCount = (int) ($data['verified'] ?? 0);
+ $processedPredictions = (int) ($data['processedPredictions'] ?? 0);
+ $totalPredictions = (int) ($data['totalPredictions'] ?? 0);
+ $this->stdout(
+ sprintf(
+ "[%d/%d] ok %s total_verified=%d processed=%d/%d\n",
+ $batchNumber,
+ $totalBatches,
+ implode(', ', $summary),
+ $verifiedCount,
+ $processedPredictions,
+ $totalPredictions
+ )
+ );
+ break;
+
+ case 'batch_error':
+ $batchNumber = (int) ($data['batchNumber'] ?? 0);
+ $totalBatches = (int) ($data['totalBatches'] ?? 0);
+ $predictionIds = implode(',', $data['predictionIds'] ?? []);
+ $error = (string) ($data['error'] ?? 'unknown error');
+ $processedPredictions = (int) ($data['processedPredictions'] ?? 0);
+ $totalPredictions = (int) ($data['totalPredictions'] ?? 0);
+ $this->stderr(
+ sprintf(
+ "[%d/%d] error ids=[%s] processed=%d/%d %s\n",
+ $batchNumber,
+ $totalBatches,
+ $predictionIds,
+ $processedPredictions,
+ $totalPredictions,
+ $error
+ )
+ );
+ break;
+ }
+ });
$this->stdout("LLM верифицировано: {$verified}\n");
return ExitCode::OK;
} catch (\RuntimeException $e) {
$dotenv->ifPresent('POSTGRES_PORT')->isInteger();
$dotenv->ifPresent('DB_PORT')->isInteger();
$dotenv->ifPresent('DB_REMOTE_PORT')->isInteger();
+ $dotenv->ifPresent('LLM_BATCH_SIZE')->isInteger();
+ $dotenv->ifPresent('LLM_TIMEOUT')->isInteger();
+ $dotenv->ifPresent('LLM_MAX_TOKENS')->isInteger();
+ $dotenv->ifPresent('LLM_BACKEND')->allowedValues(['local', 'remote']);
} catch (\Dotenv\Exception\InvalidPathException $e) {
putenv("APP_ENV=development");
$query->andWhere(['status' => Products1cAutomarkPrediction::STATUS_PENDING]);
}
+ $llm = Yii::$app->request->get('llm');
+ if ($llm === 'verified') {
+ $query->andWhere(['not', ['llm_verdict' => null]]);
+ } elseif ($llm === 'unverified') {
+ $query->andWhere(['llm_verdict' => null]);
+ } elseif (in_array($llm, [
+ Products1cAutomarkPrediction::LLM_VERDICT_APPROVED,
+ Products1cAutomarkPrediction::LLM_VERDICT_REJECTED,
+ ], true)) {
+ $query->andWhere(['llm_verdict' => $llm]);
+ }
+
$dataProvider = new ActiveDataProvider([
'query' => $query,
'pagination' => ['pageSize' => 50],
]);
- return $this->render('index', ['dataProvider' => $dataProvider]);
+ return $this->render('index', [
+ 'dataProvider' => $dataProvider,
+ 'llmFilter' => is_string($llm) ? $llm : null,
+ ]);
}
public function actionReview(int $id): string|Response
--- /dev/null
+<?php
+
+declare(strict_types=1);
+
+use yii\db\Migration;
+
+class m260505_120000_change_size_to_decimal_in_automark_and_nomenclature extends Migration
+{
+ public const AUTOMARK_TABLE = 'erp24.products_1c_automark_predictions';
+ public const NOMENCLATURE_TABLE = 'erp24.products_1c_nomenclature';
+
+ public function safeUp()
+ {
+ $automarkSchema = $this->db->getTableSchema(self::AUTOMARK_TABLE);
+ if (isset($automarkSchema)) {
+ $this->alterColumn(self::AUTOMARK_TABLE, 'size', $this->decimal(10, 2)->null());
+ $this->update(self::AUTOMARK_TABLE, ['size' => null], ['size' => 0]);
+ }
+
+ $nomenclatureSchema = $this->db->getTableSchema(self::NOMENCLATURE_TABLE);
+ if (isset($nomenclatureSchema)) {
+ $this->alterColumn(self::NOMENCLATURE_TABLE, 'size', $this->decimal(10, 2)->null());
+ $this->update(self::NOMENCLATURE_TABLE, ['size' => null], ['size' => 0]);
+ }
+ }
+
+ public function safeDown()
+ {
+ $automarkSchema = $this->db->getTableSchema(self::AUTOMARK_TABLE);
+ if (isset($automarkSchema)) {
+ $this->update(self::AUTOMARK_TABLE, ['size' => 0], ['size' => null]);
+ $this->alterColumn(self::AUTOMARK_TABLE, 'size', $this->integer()->null());
+ }
+
+ $nomenclatureSchema = $this->db->getTableSchema(self::NOMENCLATURE_TABLE);
+ if (isset($nomenclatureSchema)) {
+ $this->update(self::NOMENCLATURE_TABLE, ['size' => 0], ['size' => null]);
+ $this->alterColumn(self::NOMENCLATURE_TABLE, 'size', $this->integer()->null());
+ }
+ }
+}
* @property string|null $species
* @property string|null $sort
* @property string|null $type
- * @property int|null $size
+ * @property float|null $size
* @property string|null $color
* @property float $confidence
* @property string $method
[['product_id', 'confidence', 'method', 'status'], 'required'],
[['product_id', 'category', 'subcategory', 'species', 'sort', 'type', 'color', 'method'], 'string', 'max' => 255],
[['llm_verdict', 'llm_comment'], 'string', 'max' => 500],
- [['size', 'status', 'approved_by'], 'integer'],
+ [['size'], 'number', 'min' => 0],
+ [['status', 'approved_by'], 'integer'],
[['confidence'], 'number', 'min' => 0, 'max' => 1],
[['method'], 'in', 'range' => [self::METHOD_RULE, self::METHOD_SIMILARITY, self::METHOD_LLM]],
[['status'], 'in', 'range' => [self::STATUS_PENDING, self::STATUS_APPROVED, self::STATUS_REJECTED]],
* @property string|null $species Вид
* @property string|null $sort Сорт
* @property string|null $type Тип
- * @property int|null $size Размер
+ * @property float|null $size Размер
* @property string|null $measure Единица измерения
* @property string|null $color Цвет
*/
return [
[['id', 'location', 'name', 'type_num', 'category'], 'required'],
[['size', 'species', 'subcategory', 'sort', 'measure', 'color', 'type'], 'default', 'value' => null],
- [['size'], 'integer'],
+ [['size'], 'number', 'min' => 0],
[['id', 'location', 'name', 'type_num',
'category', 'subcategory', 'species', 'sort', 'measure', 'color', 'type'], 'string', 'max' => 255],
[['id'], 'unique'],
{
return [
[['id', 'location', 'name', 'type_num', 'category', 'subcategory', 'species', 'sort', 'measure', 'color', 'type'], 'safe'],
- [['size'], 'integer'],
+ [['size'], 'number'],
];
}
/**
* Предсказать и сохранить разметку для одного товара.
- * Если pending предсказание уже существует — вернуть его.
+ * Если предсказание уже существует — вернуть последнее и не создавать дубликат.
*/
public function predictForProduct(string $productId): ?Products1cAutomarkPrediction
{
$existing = Products1cAutomarkPrediction::find()
- ->where(['product_id' => $productId, 'status' => Products1cAutomarkPrediction::STATUS_PENDING])
+ ->where(['product_id' => $productId])
+ ->orderBy(['id' => SORT_DESC])
->one();
if ($existing !== null) {
$count = 0;
foreach ($productIds as $id) {
+ if ($this->hasPrediction((string) $id)) {
+ continue;
+ }
+
if ($this->predictForProduct((string) $id) !== null) {
$count++;
}
species: $sim->species ?? $rule->species,
sort: $sim->sort ?? $rule->sort,
type: $sim->type ?? $rule->type,
- size: ($sim->size === null || $sim->size === 0) ? $rule->size : $sim->size,
+ size: $rule->size,
color: $sim->color ?? $rule->color,
confidence: $sim->confidence,
method: $sim->method,
return Products1c::find()
->select('products_1c.id')
->leftJoin('products_1c_nomenclature', 'products_1c.id = products_1c_nomenclature.id')
+ ->leftJoin('products_1c_automark_predictions', 'products_1c.id = products_1c_automark_predictions.product_id')
->where(['products_1c_nomenclature.id' => null])
+ ->andWhere(['products_1c_automark_predictions.id' => null])
->andWhere(['products_1c.tip' => Products1c::TYPE_PRODUCTS])
->andWhere(['OR',
['products_1c.type' => null],
->column();
}
+ private function hasPrediction(string $productId): bool
+ {
+ return Products1cAutomarkPrediction::find()
+ ->where(['product_id' => $productId])
+ ->exists();
+ }
+
/**
* Верифицировать pending-предсказания через LLM.
*
+ * @param callable|null $progressCallback function(string $event, array<string, mixed> $data): void
* @return int Количество верифицированных предсказаний
*/
- public function llmBatchVerify(): int
+ public function llmBatchVerify(?callable $progressCallback = null): int
{
$batchSize = (int)(getenv('LLM_BATCH_SIZE') ?: 20);
$verifier = new LlmVerifier($batchSize);
- return $verifier->verifyPending();
+ return $verifier->verifyPending($progressCallback);
}
/**
->count();
}
+ public function getLlmVerifiedCount(): int
+ {
+ return (int) Products1cAutomarkPrediction::find()
+ ->where(['not', ['llm_verdict' => null]])
+ ->count();
+ }
+
+ public function getNextPendingPredictionId(): ?int
+ {
+ $nextId = Products1cAutomarkPrediction::find()
+ ->select('id')
+ ->where(['status' => Products1cAutomarkPrediction::STATUS_PENDING])
+ ->andWhere(['llm_verdict' => null])
+ ->orderBy(['id' => SORT_ASC])
+ ->scalar();
+
+ return $nextId !== false && $nextId !== null ? (int) $nextId : null;
+ }
+
/**
* @return array<string, mixed>
*/
}
$responseJson = $decoded['response_json'] ?? null;
- if (is_array($responseJson) && array_is_list($responseJson)) {
- return $responseJson;
+ $normalized = LlmClient::normalizeVerifyResponse($responseJson);
+ if ($normalized !== null) {
+ return $normalized;
}
$responseText = $decoded['response_text'] ?? null;
*/
public static function parseResponse(string $raw): array
{
- $direct = json_decode(trim($raw), true);
- if (is_array($direct) && array_is_list($direct)) {
+ $direct = self::normalizeVerifyResponse(json_decode(trim($raw), true));
+ if ($direct !== null) {
return $direct;
}
if (preg_match('/\[.*\]/su', $raw, $m)) {
- $extracted = json_decode($m[0], true);
- if (is_array($extracted) && array_is_list($extracted)) {
+ $extracted = self::normalizeVerifyResponse(json_decode($m[0], true));
+ if ($extracted !== null) {
+ return $extracted;
+ }
+ }
+
+ if (preg_match('/\{.*\}/su', $raw, $m)) {
+ $extracted = self::normalizeVerifyResponse(json_decode($m[0], true));
+ if ($extracted !== null) {
return $extracted;
}
}
throw new \RuntimeException('LLM вернул невалидный JSON: ' . mb_substr($raw, 0, 200));
}
+ /**
+ * @param mixed $decoded
+ * @return array<int, array<string, mixed>>|null
+ */
+ public static function normalizeVerifyResponse(mixed $decoded): ?array
+ {
+ if (!is_array($decoded)) {
+ return null;
+ }
+
+ if (array_is_list($decoded)) {
+ return $decoded;
+ }
+
+ if (isset($decoded['id'], $decoded['verdict'])) {
+ return [$decoded];
+ }
+
+ if (isset($decoded['results']) && is_array($decoded['results']) && array_is_list($decoded['results'])) {
+ return $decoded['results'];
+ }
+
+ return null;
+ }
+
/**
* @param array<string, string> $env
* @return array<string, mixed>
/**
* Верифицировать все pending-предсказания без LLM-вердикта.
*
+ * @param callable|null $progressCallback function(string $event, array<string, mixed> $data): void
* @return int Количество верифицированных предсказаний
*/
- public function verifyPending(): int
+ public function verifyPending(?callable $progressCallback = null): int
{
$predictions = Products1cAutomarkPrediction::find()
->with('product')
}
$batches = array_chunk($predictions, $this->batchSize);
+ $totalBatches = count($batches);
+ $totalPredictions = count($predictions);
$verified = 0;
$failedBatches = 0;
$firstError = null;
+ $processedPredictions = 0;
foreach ($batches as $index => $batch) {
+ $batchNumber = $index + 1;
$items = $this->enrichBatch($batch);
$payload = $this->buildEffectiveUserPrompt(self::buildBatchPayload($items));
+ $batchIds = array_map(
+ static fn(Products1cAutomarkPrediction $prediction): int => (int) $prediction->id,
+ $batch
+ );
+
+ $progressCallback?->__invoke('batch_start', [
+ 'batchNumber' => $batchNumber,
+ 'totalBatches' => $totalBatches,
+ 'batchSize' => count($batch),
+ 'predictionIds' => $batchIds,
+ 'processedPredictions' => $processedPredictions,
+ 'totalPredictions' => $totalPredictions,
+ ]);
try {
$raw = $this->client->chat($this->buildEffectiveSystemPrompt(), $payload);
$results = self::parseVerifyResults($raw);
- $verified += $this->saveResults($results);
+ $saved = $this->saveResults($results);
+ $verified += $saved;
+ $processedPredictions += count($batch);
+
+ $progressCallback?->__invoke('batch_success', [
+ 'batchNumber' => $batchNumber,
+ 'totalBatches' => $totalBatches,
+ 'saved' => $saved,
+ 'verified' => $verified,
+ 'results' => $results,
+ 'predictionIds' => $batchIds,
+ 'processedPredictions' => $processedPredictions,
+ 'totalPredictions' => $totalPredictions,
+ ]);
} catch (\RuntimeException $e) {
$failedBatches++;
$firstError ??= sprintf('batch %d: %s', $index + 1, $e->getMessage());
+ $processedPredictions += count($batch);
+
+ $progressCallback?->__invoke('batch_error', [
+ 'batchNumber' => $batchNumber,
+ 'totalBatches' => $totalBatches,
+ 'predictionIds' => $batchIds,
+ 'error' => $e->getMessage(),
+ 'processedPredictions' => $processedPredictions,
+ 'totalPredictions' => $totalPredictions,
+ ]);
continue;
}
}
$now = date('Y-m-d H:i:s');
foreach ($results as $result) {
- $rows = Products1cAutomarkPrediction::updateAll(
- [
- 'llm_verdict' => $result->verdict,
- 'llm_verified_at' => $now,
- 'llm_comment' => $result->comment,
- ],
- ['id' => $result->predictionId]
- );
+ $prediction = Products1cAutomarkPrediction::find()
+ ->with('product')
+ ->where(['id' => $result->predictionId])
+ ->one();
+
+ if ($prediction === null) {
+ continue;
+ }
+
+ $attributes = [
+ 'llm_verdict' => $result->verdict,
+ 'llm_verified_at' => $now,
+ 'llm_comment' => $result->comment,
+ 'updated_at' => $now,
+ ];
+
+ $corrections = $this->resolveCorrections($prediction, $result);
+ if ($corrections !== []) {
+ $attributes = array_merge($attributes, $corrections);
+ $attributes['method'] = Products1cAutomarkPrediction::METHOD_LLM;
+ }
+
+ $rows = Products1cAutomarkPrediction::updateAll($attributes, ['id' => $prediction->id]);
$count += $rows;
}
return $count;
}
+ /**
+ * @return array<string, int|string|null>
+ */
+ private function resolveCorrections(Products1cAutomarkPrediction $prediction, LlmVerifyResult $result): array
+ {
+ $corrections = [];
+
+ if (!$result->isApproved() && $result->hasCorrections()) {
+ $corrections['category'] = $result->category;
+ $corrections['subcategory'] = $result->subcategory;
+ $corrections['species'] = $result->species;
+ $corrections['size'] = $result->size;
+ $corrections['color'] = $result->color;
+ }
+
+ $name = (string) ($prediction->product->name ?? '');
+ $explicitSize = $this->extractExplicitSize($name);
+ if ($explicitSize !== null && (float) ($prediction->size ?? 0) !== $explicitSize && !array_key_exists('size', $corrections)) {
+ $corrections['size'] = $explicitSize;
+ }
+
+ return $corrections;
+ }
+
+ private function extractExplicitSize(string $name): ?float
+ {
+ if (preg_match('/(\d+)\s*(?:см|cm|СМ|CM)/iu', $name, $matches)) {
+ return (float) $matches[1];
+ }
+
+ if (preg_match('/(\d+(?:[.,]\d+)?)\s*(?:л|литр(?:а|ов)?)/iu', $name, $matches)) {
+ return self::normalizeNullableFloat($matches[1]);
+ }
+
+ if (preg_match('/(\d+(?:[.,]\d+)?)\s*(?:м|метр(?:а|ов)?)(?![а-яa-z])/iu', $name, $matches)) {
+ return self::normalizeNullableFloat($matches[1]);
+ }
+
+ return null;
+ }
+
public static function buildSystemPrompt(): string
{
$taxonomy = self::TAXONOMY;
2. Используй similar_examples как эталон правильной разметки.
3. Если `similar_examples` пустой, принимай решение по `name` и `prediction`, но с более консервативной оценкой.
4. Не отклоняй товар только потому, что category использует legacy-название (`Срезы`, `Горшечные`, `букет`, `сборка`, `сервис`), если смысл разметки корректен.
-5. Вынеси вердикт: approved (разметка верна) или rejected (есть ошибки).
-6. `comment` должен быть очень коротким: не более 12 слов, без длинных объяснений.
-7. Если товар approved, `comment` должен быть null.
-
-ОТВЕТ — только JSON-массив, без пояснений вне него:
-[{"id":<int>,"verdict":"approved"|"rejected","comment":"<причина если rejected, иначе null>"}]
+5. Если в названии явно указан размер (`100см`, `65 см`, `1м`, `3.5л`, `0,5 л`), цвет, species или category, эти поля должны совпадать с prediction. Иначе verdict = rejected.
+6. Вынеси вердикт: approved (разметка верна) или rejected (есть ошибки).
+7. `comment` должен быть очень коротким: не более 12 слов, без длинных объяснений.
+8. Если товар approved, `comment` должен быть null.
+9. Если verdict = rejected, обязательно верни `corrected_prediction`.
+10. В `corrected_prediction` верни полную исправленную разметку для полей `category`, `subcategory`, `species`, `size`, `color`.
+11. Если какое-то поле уже было верным, повтори его текущее корректное значение в `corrected_prediction`, а не оставляй пустым.
+12. Если размер в названии не указан явно, не придумывай его по `similar_examples`: верни `size = null`.
+
+ОТВЕТ — только JSON. Допустим массив или одиночный объект:
+[{"id":<int>,"verdict":"approved"|"rejected","comment":"<причина если rejected, иначе null>","corrected_prediction":{"category":"<string|null>","subcategory":"<string|null>","species":"<string|null>","size":<int|null>,"color":"<string|null>"}}]
+Если verdict = approved, `corrected_prediction` должен быть null.
PROMPT;
}
if (!isset($item['id'], $item['verdict'])) {
continue;
}
+
+ $corrected = $item['corrected_prediction'] ?? null;
$results[] = new LlmVerifyResult(
predictionId: (int) $item['id'],
verdict: (string) $item['verdict'],
comment: isset($item['comment']) && $item['comment'] !== null
? (string) $item['comment']
: null,
+ category: is_array($corrected) ? self::normalizeNullableString($corrected['category'] ?? null) : null,
+ subcategory: is_array($corrected) ? self::normalizeNullableString($corrected['subcategory'] ?? null) : null,
+ species: is_array($corrected) ? self::normalizeNullableString($corrected['species'] ?? null) : null,
+ size: is_array($corrected) ? self::normalizeNullableFloat($corrected['size'] ?? null) : null,
+ color: is_array($corrected) ? self::normalizeNullableString($corrected['color'] ?? null) : null,
);
}
return $results;
}
+
+ private static function normalizeNullableString(mixed $value): ?string
+ {
+ if (!is_string($value)) {
+ return null;
+ }
+
+ $value = trim($value);
+ return $value === '' ? null : $value;
+ }
+
+ private static function normalizeNullableFloat(mixed $value): ?float
+ {
+ if ($value === null || $value === '') {
+ return null;
+ }
+
+ if (is_int($value) || is_float($value)) {
+ $numeric = (float) $value;
+ return $numeric > 0 ? $numeric : null;
+ }
+
+ if (is_string($value)) {
+ $value = str_replace(',', '.', trim($value));
+ }
+
+ if (is_numeric($value)) {
+ $numeric = (float) $value;
+ return $numeric > 0 ? $numeric : null;
+ }
+
+ return null;
+ }
}
public readonly int $predictionId,
public readonly string $verdict,
public readonly ?string $comment,
+ public readonly ?string $category = null,
+ public readonly ?string $subcategory = null,
+ public readonly ?string $species = null,
+ public readonly ?float $size = null,
+ public readonly ?string $color = null,
) {}
public function isApproved(): bool
{
return $this->verdict === 'approved';
}
+
+ public function hasCorrections(): bool
+ {
+ return $this->category !== null
+ || $this->subcategory !== null
+ || $this->species !== null
+ || $this->size !== null
+ || $this->color !== null;
+ }
}
public readonly ?string $species,
public readonly ?string $sort,
public readonly ?string $type,
- public readonly ?int $size,
+ public readonly ?float $size,
public readonly ?string $color,
public readonly float $confidence,
public readonly string $method,
private const POTTED_KEYWORDS = ['горшок', 'горшечн', 'кашпо', 'вазон'];
- private const PACKAGING_KEYWORDS = ['пакет', 'коробк', 'упаков', 'лента', 'бумага', 'сетка', 'сизаль'];
+ private const PACKAGING_KEYWORDS = ['пакет', 'коробк', 'упаков', 'лента', 'бумага', 'сетка', 'сизаль', 'пленк'];
public function parse(string $name): ?ParseResult
{
return null;
}
- private function detectSize(string $name): ?int
+ private function detectSize(string $name): ?float
{
if (preg_match('/(\d+)\s*(?:см|cm|СМ|CM)/iu', $name, $m)) {
- return (int) $m[1];
+ return (float) $m[1];
+ }
+ if (preg_match('/(\d+(?:[.,]\d+)?)\s*(?:л|литр(?:а|ов)?)/iu', $name, $m)) {
+ return $this->normalizeDecimal($m[1]);
+ }
+ if (preg_match('/(\d+(?:[.,]\d+)?)\s*(?:м|метр(?:а|ов)?)(?![а-яa-z])/iu', $name, $m)) {
+ return $this->normalizeDecimal($m[1]);
}
// Bare number in [20, 200] surrounded by spaces — stem height without unit
if (preg_match('/(?:^|\s)(\d{2,3})(?:\s|$)/', $name, $m)) {
$n = (int) $m[1];
if ($n >= 20 && $n <= 200) {
- return $n;
+ return (float) $n;
}
}
return null;
}
+ private function normalizeDecimal(string $raw): ?float
+ {
+ $normalized = str_replace(',', '.', trim($raw));
+ if (!is_numeric($normalized)) {
+ return null;
+ }
+
+ $value = (float) $normalized;
+ return $value > 0 ? $value : null;
+ }
+
private function calcConfidence(
?string $category,
?string $species,
?string $sort,
?string $color,
- ?int $size
+ ?float $size
): float {
$score = 0.5;
if ($category !== null) $score += 0.2;
species: $bestItem['species'] ?? null,
sort: $bestItem['sort'] ?? null,
type: $bestItem['type'] ?? null,
- size: isset($bestItem['size']) ? (int) $bestItem['size'] : null,
+ // Size must be extracted from the current product name, not copied from a similar item.
+ size: null,
color: $bestItem['color'] ?? null,
confidence: round($bestScore, 4),
method: Products1cAutomarkPrediction::METHOD_SIMILARITY,
LlmClient::parseResponse('{"error":"bad request"}');
}
+ public function testParsesSingleVerifyObjectResponse(): void
+ {
+ $raw = '{"id":74,"verdict":"approved","comment":null}';
+ $result = LlmClient::parseResponse($raw);
+
+ $this->assertCount(1, $result);
+ $this->assertSame(74, $result[0]['id']);
+ $this->assertSame('approved', $result[0]['verdict']);
+ }
+
public function testParsesOpenAiCompatibleResponse(): void
{
$body = json_encode([
$this->assertSame('approved', $result[0]['verdict']);
}
+ public function testCoordinatorAcceptsSingleObjectInResponseJson(): void
+ {
+ $body = json_encode([
+ 'ok' => true,
+ 'response_json' => [
+ 'id' => 6,
+ 'verdict' => 'rejected',
+ 'comment' => 'bad species',
+ ],
+ ], JSON_UNESCAPED_UNICODE);
+
+ $result = CoordinatorLlmTransport::parseAnalyzeResponse((string) $body);
+
+ $this->assertCount(1, $result);
+ $this->assertSame(6, $result[0]['id']);
+ $this->assertSame('rejected', $result[0]['verdict']);
+ }
+
public function testCoordinatorFallsBackToResponseText(): void
{
$body = json_encode([
{
$raw = [
['id' => 10, 'verdict' => 'approved', 'comment' => null],
- ['id' => 11, 'verdict' => 'rejected', 'comment' => 'Неверный цвет'],
+ [
+ 'id' => 11,
+ 'verdict' => 'rejected',
+ 'comment' => 'Неверный цвет',
+ 'corrected_prediction' => [
+ 'category' => 'Срезка',
+ 'subcategory' => 'Розы',
+ 'species' => 'Роза',
+ 'size' => 60,
+ 'color' => 'Белая',
+ ],
+ ],
];
$results = LlmVerifier::parseVerifyResults($raw);
$this->assertSame(10, $results[0]->predictionId);
$this->assertFalse($results[1]->isApproved());
$this->assertSame('Неверный цвет', $results[1]->comment);
+ $this->assertTrue($results[1]->hasCorrections());
+ $this->assertSame('Срезка', $results[1]->category);
+ $this->assertSame(60.0, $results[1]->size);
}
public function testParseVerifyResultsSkipsItemsWithoutRequiredFields(): void
$this->assertSame('Розы', $result->subcategory);
$this->assertSame('Роза', $result->species);
$this->assertSame('Premium', $result->sort);
- $this->assertSame(50, $result->size);
+ $this->assertSame(50.0, $result->size);
$this->assertSame('Красная', $result->color);
$this->assertGreaterThanOrEqual(0.9, $result->confidence);
$this->assertSame('rule', $result->method);
{
$result = $this->parser->parse('Хризантема Экстра 70 см Белая');
- $this->assertSame(70, $result->size);
+ $this->assertSame(70.0, $result->size);
$this->assertSame('Белая', $result->color);
$this->assertSame('Хризантема', $result->species);
}
{
$result = $this->parser->parse('Роза Эквадор 80 алая');
- $this->assertSame(80, $result->size);
+ $this->assertSame(80.0, $result->size);
$this->assertSame('Алая', $result->color);
$this->assertSame('Роза', $result->species);
$this->assertSame('Розы', $result->subcategory);
$this->assertSame('Упаковка', $result->category);
$this->assertNull($result->size);
}
+
+ public function testExtractsSizeInMeters(): void
+ {
+ $result = $this->parser->parse('Пленка матовая 1м белый');
+
+ $this->assertSame('Упаковка', $result->category);
+ $this->assertSame(1.0, $result->size);
+ }
+
+ public function testExtractsSizeInLiters(): void
+ {
+ $result = $this->parser->parse('Горшок-кашпо Камелия Люкс 3,5л. (Бело-Красный)');
+
+ $this->assertSame('Горшечные_растения', $result->category);
+ $this->assertSame(3.5, $result->size);
+ }
}
<?php
/** @var \yii\data\ActiveDataProvider $dataProvider */
+/** @var string|null $llmFilter */
+
use yii\grid\GridView;
use yii\helpers\Html;
use yii_app\records\Products1cAutomarkPrediction;
$this->title = 'Авторазметка товаров';
+
+$status = Yii::$app->request->get('status', Products1cAutomarkPrediction::STATUS_PENDING);
+
+$badgeMap = [
+ Products1cAutomarkPrediction::LLM_VERDICT_APPROVED => ['#1f7a1f', 'Одобрено LLM'],
+ Products1cAutomarkPrediction::LLM_VERDICT_REJECTED => ['#c62828', 'Не одобрено LLM'],
+];
+
+$formatSize = static function ($value): string {
+ if ($value === null || (float) $value <= 0.0) {
+ return '—';
+ }
+
+ $formatted = number_format((float) $value, 2, '.', '');
+ return rtrim(rtrim($formatted, '0'), '.');
+};
?>
<div class="container-fluid">
<h2><?= Html::encode($this->title) ?></h2>
<div class="mb-3">
- <?= Html::a('Pending', ['index', 'status' => Products1cAutomarkPrediction::STATUS_PENDING], ['class' => 'btn btn-warning']) ?>
- <?= Html::a('Одобренные', ['index', 'status' => Products1cAutomarkPrediction::STATUS_APPROVED], ['class' => 'btn btn-success']) ?>
- <?= Html::a('Отклонённые', ['index', 'status' => Products1cAutomarkPrediction::STATUS_REJECTED], ['class' => 'btn btn-secondary']) ?>
+ <?= Html::a('В ожидании', ['index', 'status' => Products1cAutomarkPrediction::STATUS_PENDING, 'llm' => $llmFilter], ['class' => 'btn btn-warning']) ?>
+ <?= Html::a('Одобренные', ['index', 'status' => Products1cAutomarkPrediction::STATUS_APPROVED, 'llm' => $llmFilter], ['class' => 'btn btn-success']) ?>
+ <?= Html::a('Отклонённые', ['index', 'status' => Products1cAutomarkPrediction::STATUS_REJECTED, 'llm' => $llmFilter], ['class' => 'btn btn-secondary']) ?>
+ </div>
+
+ <div class="mb-3">
+ <?= Html::a('Все с LLM', ['index', 'status' => $status, 'llm' => 'verified'], ['class' => 'btn btn-info']) ?>
+ <?= Html::a('Без LLM', ['index', 'status' => $status, 'llm' => 'unverified'], ['class' => 'btn btn-default']) ?>
+ <?= Html::a('Одобрено LLM', ['index', 'status' => $status, 'llm' => Products1cAutomarkPrediction::LLM_VERDICT_APPROVED], ['class' => 'btn btn-success']) ?>
+ <?= Html::a('Не одобрено LLM', ['index', 'status' => $status, 'llm' => Products1cAutomarkPrediction::LLM_VERDICT_REJECTED], ['class' => 'btn btn-danger']) ?>
+ <?= Html::a('Сбросить LLM фильтр', ['index', 'status' => $status], ['class' => 'btn btn-link']) ?>
</div>
<?= GridView::widget([
'species',
'sort',
'color',
- 'size',
+ [
+ 'attribute' => 'size',
+ 'value' => static fn(Products1cAutomarkPrediction $m): string => $formatSize($m->size),
+ ],
[
'label' => 'Confidence',
'value' => fn($m) => number_format($m->confidence * 100, 1) . '%',
],
- 'method',
+ [
+ 'attribute' => 'method',
+ 'format' => 'raw',
+ 'value' => static function (Products1cAutomarkPrediction $m): string {
+ $labels = [
+ Products1cAutomarkPrediction::METHOD_RULE => ['rule', '#374151'],
+ Products1cAutomarkPrediction::METHOD_SIMILARITY => ['similarity', '#374151'],
+ Products1cAutomarkPrediction::METHOD_LLM => ['llm', '#1565c0'],
+ ];
+ [$label, $color] = $labels[$m->method] ?? [$m->method, '#374151'];
+
+ return Html::tag('span', Html::encode($label), [
+ 'style' => sprintf('color:%s;font-weight:600;', $color),
+ ]);
+ },
+ ],
+ [
+ 'label' => 'LLM',
+ 'format' => 'raw',
+ 'value' => static function (Products1cAutomarkPrediction $m) use ($badgeMap): string {
+ if ($m->llm_verdict === null) {
+ return Html::tag('span', 'Не проверено LLM', [
+ 'style' => 'color:#6b7280;',
+ ]);
+ }
+
+ [$color, $label] = $badgeMap[$m->llm_verdict] ?? ['#374151', $m->llm_verdict];
+ return Html::tag('span', $label, [
+ 'style' => sprintf('color:%s;font-weight:700;', $color),
+ ]);
+ },
+ ],
+ [
+ 'attribute' => 'llm_verified_at',
+ 'label' => 'LLM at',
+ 'value' => static fn(Products1cAutomarkPrediction $m): string => $m->llm_verified_at ?? '—',
+ ],
+ [
+ 'attribute' => 'llm_comment',
+ 'label' => 'LLM comment',
+ 'value' => static fn(Products1cAutomarkPrediction $m): string => $m->llm_comment ?? '—',
+ ],
[
'label' => 'Действия',
'format' => 'raw',
use yii_app\records\Products1cAutomarkPrediction;
$this->title = 'Проверка разметки #' . $prediction->id;
+$formattedSize = '—';
+if ($prediction->size !== null && (float) $prediction->size > 0.0) {
+ $formattedSize = rtrim(rtrim(number_format((float) $prediction->size, 2, '.', ''), '0'), '.');
+}
?>
<div class="container">
<h2><?= Html::encode($this->title) ?></h2>
<tr><th>Вид</th><td><?= Html::encode($prediction->species ?? '—') ?></td></tr>
<tr><th>Сорт</th><td><?= Html::encode($prediction->sort ?? '—') ?></td></tr>
<tr><th>Тип</th><td><?= Html::encode($prediction->type ?? '—') ?></td></tr>
- <tr><th>Размер</th><td><?= $prediction->size ?? '—' ?></td></tr>
+ <tr><th>Размер</th><td><?= Html::encode($formattedSize) ?></td></tr>
<tr><th>Цвет</th><td><?= Html::encode($prediction->color ?? '—') ?></td></tr>
</table>
</div>
projects / erp24_rep / yii-erp24 / .git / commitdiff