HH n8n OClick/1.0
Shared 10/21/2025
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Visual Workflow
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"jsCode": "const items = $input.all();\nconst out = [];\n\nfor (const item of items) {\n const doc = item.json.data ?? item.json;\n if (!doc) continue;\n\n // гарантируем, что sections — массив (в твоём случае они всегда есть)\n const sections = Array.isArray(doc.sections) ? doc.sections : [];\n\n let secIndex = 0;\n for (const sec of sections) {\n // безопасные дефолты\n const sectionName = sec && sec.section ? String(sec.section) : `section_${secIndex}`;\n const sectionText = sec && sec.text ? String(sec.text).trim() : '';\n\n // Unicode-safe slug (короткий, для id)\n const rawSlug = sectionName.toLowerCase().replace(/\\s+/g, '_');\n const sectionSlug = rawSlug.replace(/[^\\p{L}\\p{N}_-]/gu, '').slice(0, 50) || `sec${secIndex}`;\n\n // уникальный id чанка\n const chunkId = `${doc.id ?? 'doc'}_${secIndex}_${sectionSlug}`;\n\n // content: заголовок секции + текст\n //const content = `### ${sectionName}\\n\\n${sectionText}`;\n const content = `${sectionText}`;\n\n // сохраняем в metadata только поля, которые соответствуют исходной схеме документа\n const metadata = {\n // id чанка (уникален)\n id: chunkId,\n // оригинальный документный id\n document_id: doc.id ?? null,\n // основной набор полей из оригинального документа (копируем как есть)\n title: doc.title ?? null,\n salary_range: doc.salary_range ?? null,\n location: doc.location ?? null,\n // experience — копируем целиком (объект {id, name} или null)\n experience: doc.experience ?? null,\n // ключевые навыки — сохраняем оригинал (массив объектов или пустой массив)\n key_skills: doc.key_skills ?? [],\n source_url: doc.source_url ?? null,\n employment_type: doc.employment_type ?? null,\n work_format: doc.work_format ?? [],\n company: doc.company ?? null,\n // информация о секции для удобства поиска/фильтрации\n section: sectionName\n };\n\n out.push({ json: { content, metadata } });\n secIndex++;\n }\n\n // если sections пустой — сейчас мы не создаём чанков (поведение по умолчанию)\n}\n\nreturn out;\n"
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"useMLock": true,
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"mode": "insert",
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"mode": "id",
"value": "vacancies"
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"payload": "={\n \"vacancy_id\": {{ $('Chunking').item.json.metadata.document_id }},\n \"location\": {{ $('Chunking').item.json.metadata.location ? $('Chunking').item.json.metadata.location.toJsonString() : \"null\" }},\n \"source_url\": \"{{ $('Chunking').item.json.metadata.source_url }}\",\n \"employment_type_id\": {{ $('Chunking').item.json.metadata.employment_type.id.toJsonString() }},\n \"work_format\": {{ JSON.stringify($('Chunking').item.json.metadata.work_format) }}\n}",
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"description": "обязанности / что нужно делать;"
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{
"name": "requirements",
"required": true,
"description": "обязательные требования / необходимый опыт;"
},
{
"name": "additional",
"description": "only optional / desirable skills or experience (explicitly indicated as \"Would be a plus\", \"Welcome if\", \"Desirable\", \"preferred\", \"will be a plus\").\\n IMPORTANT RULES (must follow exactly):\\n1) Use heading-based extraction first: if input contains \"Welcome if\", \"Would be a plus\", \"Desirable\" or similar, extract the text under that heading into \"advantages\".\\n2) If there are lines/sentences containing the optional indicators (see list below), include them in \"advantages\".\\n3) **Do NOT** include in \"advantages\" any marketing/benefits/conditions text such as \"What we offer\", \"Dream job\", \"official employment\", \"paid vacation\", \"remotely\", \"schedule\", \"team\", \"adaptation\" — these are company perks, not desirable experience, and must be excluded from advantages.\\n4) If a sentence matches both optional-indicator and benefit keywords, prefer treating it as BENEFIT and therefore do NOT place it into \"advantages\" unless it clearly expresses desirable SKILL/EXPERIENCE.\\n5) If no relevant optional/desirable items are found, OMIT the \"advantages\" section entirely (do not include it with empty text).\\n6) Preserve original wording and line breaks. Do NOT summarize or paraphrase."
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"jsCode": "const items = $input.all();\n\nreturn items.map(item => {\n // Преобразуем key_skills в массив строк\n if (Array.isArray(item.json.key_skills)) {\n item.json.key_skills = item.json.key_skills.map(skill => skill.name);\n }\n\n // Преобразуем work_format в массив строк по id\n if (Array.isArray(item.json.work_format)) {\n item.json.work_format = item.json.work_format.map(format => format.id);\n }\n\n return item;\n});"
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"jsCode": "const input = $input.first().json.output;\nconst sections = Object.keys(input)\n .map(key => ({\n section: key,\n text: input[key].replace(/\\n/g, ' ')\n }))\n .filter(section => section.text.trim() !== '');\nreturn [{ json: { sections } }];"
},
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},
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"name": "Load Content/Metadata",
"type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
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],
"parameters": {
"options": {
"metadata": {
"metadataValues": [
{
"name": "chunk_id",
"value": "={{ $('Chunking').item.json.metadata.id }}"
},
{
"name": "title",
"value": "={{ $('Chunking').item.json.metadata.title }}"
},
{
"name": "experience_id",
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}
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}
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"jsonData": "={{ $('Chunking').item.json.content }}",
"jsonMode": "expressionData",
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"assignments": [
{
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"name": "id",
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"value": "={{ $json.id }}"
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{
"id": "8dc8b87c-bfb7-4655-abd7-c54e5d30a4d4",
"name": "title",
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},
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"id": "91281710-76ee-4531-bf5c-ca6e4c5707be",
"name": "salary_range",
"type": "object",
"value": "={{ $json.salary_range }}"
},
{
"id": "f1953bd7-2ba2-4fb7-b9a8-cf226bf58b25",
"name": "location",
"type": "string",
"value": "={{ $json.address.city }}"
},
{
"id": "c197a189-80ba-4834-8c3a-40e33dfa0759",
"name": "experience",
"type": "object",
"value": "={{ $json.experience }}"
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"name": "sections",
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"value": "={{ $json.description }}"
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{
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"name": "key_skills",
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"value": "={{ $json.key_skills }}"
},
{
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"name": "source_url",
"type": "string",
"value": "={{ $json.alternate_url }}"
},
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"name": "employment_type",
"type": "object",
"value": "={{ $json.employment_form }}"
},
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"type": "array",
"value": "={{ $json.work_format }}"
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"name": "company",
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"name": "Get Vacancy Details",
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"parameters": {
"url": "=https://api.hh.ru/vacancies/{{ $json.id }}",
"options": {},
"sendHeaders": true,
"headerParameters": {
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"value": "OClick/1.0 (shimorowm@gmail.com)"
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"parameters": {
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"mode": "name",
"value": "vacancies"
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"type": "n8n-nodes-base.stickyNote",
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"parameters": {
"width": 693,
"height": 410,
"content": "## Clear Databases"
},
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"parameters": {
"filter": "={\n \"must\": [\n {\n \"key\": \"vacancy_id\",\n \"match\": {\n \"value\": {{ $json.metadata.document_id }}\n }\n }\n ]\n}",
"resource": "point",
"operation": "scrollPoints",
"collectionName": {
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"mode": "list",
"value": "vacancies",
"cachedResultName": "vacancies"
},
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}
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"name": "If1",
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"parameters": {
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"options": {
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"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
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"combinator": "and",
"conditions": [
{
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"operator": {
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"operation": "notEmpty",
"singleValue": true
},
"leftValue": "={{ $json.result.points }}",
"rightValue": ""
}
]
}
},
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},
{
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"name": "Delete Points",
"type": "n8n-nodes-qdrant.qdrant",
"position": [
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],
"parameters": {
"filter": "={\n \"must\": [\n {\n \"key\": \"vacancy_id\",\n \"match\": {\n \"value\": {{ $json.result.points[0].payload.vacancy_id }}\n }\n }\n ]\n}",
"resource": "point",
"operation": "deletePoints",
"collectionName": {
"__rl": true,
"mode": "list",
"value": "vacancies",
"cachedResultName": "vacancies"
},
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},
"credentials": {
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"name": "Qdrant account"
}
},
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},
{
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"name": "AI Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
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"parameters": {
"text": "Создай очень короткое сопроводительное письмо используя актуальную вакансию из базы данных, объясняя работодателю, почему именно я подхожу на эту вакансию. Основывайся при этом на моём резюме, отвечай на русском.\nResume:\n```txt\nМаксим Кришталь\nМужчина\nshimorowm@gmail.com\nПроживает: Санкт-Петербург\nГражданство: Россия, есть разрешение на работу: Россия\nJava-разработчик\nСпециализации:\nПрограммист, разработчик\nОпыт работы — 1 год 3 месяца\nMicroRestBank\ngithub.com/22crystyle/MicroRestBank\nАвгуст 2024 — настоящее время 1 год 3 месяца\nJava-разработчик\nРазработка комплексного банковского приложения на основе микросервисной архитектуры.\nОписание: Проект MicroRestBank представляет собой платформу для управления пользователями и банковскими картами через RESTful API. Система включает в себя функции создания карт, их блокировки, управления пользователями и осуществления денежных переводов.\nАрхитектура и Реализация: Спроектировал и разработал набор независимых микросервисов на Java 21 и Spring Boot 3, включая:\n- Разрабатывал и отлаживал серверный Java-код (Spring Boot 3, Spring Data JPA, Spring Security) - опыт root-cause analysis и hotfix’ов в продакшн/стейдж окружениях.\n- Единая точка входа для всех клиентских запросов, реализованная на Spring Cloud Gateway.\n- Создал и поддерживал механизмы аутентификации и авторизации с Keycloak (OAuth2, JWT), в т.ч. стратегию ролей и прав доступа.\n- Реализация всей бизнес-логики для банковских карт, включая транзакции и управление статусами.\n- Управление данными клиентов.\n- Сервис-дискавери для динамического взаимодействия между сервисами (Spring Cloud Netflix Eureka).\n- Проектировал и реализовал интеграционные механизмы между микросервисами (REST, Kafka), обеспечив надёжную асинхронную репликацию данных.\n- Реализовал асинхронное взаимодействие между сервисами для обновления данных с помощью Apache Kafka и Debezium (Change Data Capture).\n- Управлял схемами БД и миграциями (PostgreSQL, Liquibase); писал оптимизированные SQL-запросы для аналитики и исправления ошибок.\n- Документировал API с использованием OpenAPI (Swagger).\n- Писал unit и интеграционные тесты (JUnit, Mockito) и автоматизировал сценарии сборки/деплоя.\n- Настроил CI/CD и контейнеризацию (Gradle, Docker, Docker Compose) для локальной и командной разработки.\nСтек:\n- Бэкенд: Java 21, Spring Boot 3, Spring Framework, Spring Data JPA, Spring Security\n- Микросервисы: Microservices Architecture, Spring Cloud (Gateway, Netflix Eureka), RESTful API, Event-Driven Architecture\n- Базы данных и брокеры сообщений: PostgreSQL, Liquibase, Apache Kafka, Debezium (Change Data Capture)\n- Аутентификация и Авторизация: Keycloak, JWT, OAuth2\n- DevOps и Инструменты: Docker, Docker Compose, Gradle, Git, CI/CD, JetBrains IntelliJ IDEA\n- API и Документация: OpenAPI (Swagger)\nОбразование\nВысшее\nСанкт-Петербургский государственный электротехнический университет «ЛЭТИ» имени В.И. Ульянова (Ленина), Санкт-Петербург\n2025\nФакультет компьютерных технологий и информатики, Прикладная математика и информатика\nНавыки\nЗнание языков\nРусский — Родной\nАнглийский — B1 — Средний\nНавыки\nJava; Spring Framework; Hibernate; Git; Docker; Liquibase; Apache Kafka; Gradle; Apache Maven; PostgreSQL; Linux; REST API; Java SE; JPA; Английский язык; Spring; Spring Boot; Spring Cloud; Spring Data; Spring MVC; Spring Security; Spring Web; Keycloak; Hibernate ORM; SQL; SOLID; ООП; JUnit; Debezium; Mockito\nДополнительная информация\nОбо мне\nJava backend-разработчик, ориентированный на качество и поддерживаемость кода. Владею современным стеком:\n- Бэкенд: Java 21, Spring Boot 3, Spring Framework, Spring Data JPA, Spring Security\n- Микросервисы: Microservices Architecture, Spring Cloud (Gateway, Netflix Eureka), RESTful API, Event-Driven Architecture\n- Базы данных и брокеры сообщений: PostgreSQL, Liquibase, Apache Kafka, Debezium (Change Data Capture)\n- Аутентификация и Авторизация: Keycloak, JWT, OAuth2\n- DevOps и Инструменты: Docker, Docker Compose, Gradle, Git, CI/CD, JetBrains IntelliJ IDEA\n- API и Документация: OpenAPI (Swagger)\nПрименяю принципы ООП и SOLID, практикую тестирование и автоматизацию процессов. Быстро адаптируюсь к новым задачам и технологиям.\n```",
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"position": [
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"parameters": {
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},
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{
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{
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"name": "Actual Job Vacancies",
"type": "@n8n/n8n-nodes-langchain.vectorStoreQdrant",
"position": [
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],
"parameters": {
"mode": "retrieve-as-tool",
"topK": 3,
"options": {
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},
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{
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{
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{
"id": "c008230f-1f41-4944-9ce5-646041d7624e",
"name": "Delete table or rows",
"type": "n8n-nodes-base.postgres",
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"mode": "list",
"value": "n8n_chat_histories",
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},
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},
"options": {},
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{
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"name": "Create Collection",
"type": "n8n-nodes-qdrant.qdrant",
"position": [
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],
"parameters": {
"vectors": "{\n \"size\": 4096,\n \"distance\": \"Cosine\",\n \"on_disk\": true,\n \"datatype\": \"float32\"\n}",
"operation": "createCollection",
"walConfig": "{\n \"wal_capacity_mb\": 32,\n \"wal_segments_ahead\": 0,\n \"wal_retain_closed\": 1\n}",
"hnswConfig": "{\n \"m\": 16,\n \"ef_construct\": 100,\n \"full_scan_threshold\": 10000,\n \"max_indexing_threads\": 0,\n \"on_disk\": false\n}",
"shardNumber": 1,
"onDiskPayload": true,
"collectionName": "vacancies",
"requestOptions": {},
"optimizersConfig": "{\n \"deleted_threshold\": 0.2,\n \"vacuum_min_vector_number\": 1000,\n \"default_segment_number\": 0,\n \"max_segment_size\": null,\n \"memmap_threshold\": null,\n \"indexing_threshold\": 10000,\n \"flush_interval_sec\": 5,\n \"max_optimization_threads\": null\n}",
"strictModeConfig": "{\n \"enabled\": false\n}",
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},
"credentials": {
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}
},
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],
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}
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],
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}
]
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},
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{
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},
"Merge1": {
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{
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"type": "main",
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}
]
]
},
"AI Agent": {
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{
"node": "Loop Over Items1",
"type": "main",
"index": 0
}
]
]
},
"Chunking": {
"main": [
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{
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"type": "main",
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}
]
]
},
"Split Out": {
"main": [
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{
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"type": "main",
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}
]
]
},
"Split Out1": {
"main": [
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{
"node": "Remove Duplicates",
"type": "main",
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}
]
]
},
"Auto-search": {
"main": [
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{
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"type": "main",
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}
]
]
},
"ObjToStrArr": {
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{
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"type": "main",
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},
{
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"type": "main",
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}
]
]
},
"Set Payload": {
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}
]
]
},
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}
]
]
},
"Save To Qdrant": {
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"type": "main",
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}
]
]
},
"Token Splitter": {
"ai_textSplitter": [
[
{
"node": "Load Content/Metadata",
"type": "ai_textSplitter",
"index": 0
}
]
]
},
"qwen3:4b:it:q8": {
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{
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"type": "ai_languageModel",
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}
]
]
},
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],
[
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}
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]
},
"Vacancy Details": {
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}
]
]
},
"qwen3-embedding": {
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"type": "ai_embedding",
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}
]
]
},
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},
"Schedule Trigger": {
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}
]
]
},
"Sections cleanup": {
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}
]
]
},
"Remove Duplicates": {
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}
]
]
},
"Delete Collection1": {
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{
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"type": "main",
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}
]
]
},
"Embeddings Ollama1": {
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"node": "Actual Job Vacancies",
"type": "ai_embedding",
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}
]
]
},
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}
]
]
},
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{
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},
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},
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]
},
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}
]
]
},
"When clicking ‘Execute workflow’": {
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{
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}
]
]
}
}
}