bilal
b2874ff580
Flush context blocks faster to avoid delayed indexing and use sender_id-based labels when Telegram sender objects are unavailable in historical messages. Co-authored-by: Cursor <cursoragent@cursor.com>
425 lines
13 KiB
JSON
425 lines
13 KiB
JSON
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"path": "tg-inbox",
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"name": "Webhook TG Inbox",
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"jsCode": "const body = $input.item.json.body || {};\nconst meta = body.metadata || {};\nconst rawText = (body.text || '').trim();\n\nif (!rawText) {\n return { json: { skip: true, reason: 'empty_text' } };\n}\n\nconst authorLabel = meta.author_label || meta.sender_name || 'Unknown';\nconst authorId = meta.sender_id || meta.author?.id || '0';\nconst repliedTo = meta.replied_to_author_label ? ` (в ответ ${meta.replied_to_author_label})` : '';\n\nreturn {\n json: {\n skip: false,\n text: `Автор ${authorLabel} (ID: ${authorId})${repliedTo}: ${rawText}`,\n metadata: {\n ...meta,\n original_text: rawText,\n source: meta.source || 'telegram_group',\n processed_at: new Date().toISOString()\n }\n }\n};"
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"id": "a9347d4b-fad0-4fb8-a23c-bcad6d2f3186",
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"name": "Normalize Telegram Payload"
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"parameters": {
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"conditions": {
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"boolean": [
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{
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"value1": "={{ $json.skip }}",
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"value2": true
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"id": "de52e6d1-98be-4c24-bc03-d90d7fa80b93",
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"name": "Skip Empty Text"
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},
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{
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"parameters": {
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"mode": "insert",
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"qdrantCollection": {
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"__rl": true,
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"value": "telegram_kb",
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"mode": "list",
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"cachedResultName": "telegram_kb"
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},
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"options": {}
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},
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"type": "@n8n/n8n-nodes-langchain.vectorStoreQdrant",
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"id": "2444f3f3-d57d-45fa-b80e-e40f73f0c70f",
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"name": "Qdrant Insert",
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"retryOnFail": true,
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"maxTries": 5,
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"waitBetweenTries": 5000
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},
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{
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"parameters": {
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"jsCode": "const WINDOW_MS = 5 * 60 * 1000;\nconst MAX_MESSAGES = 3;\nconst MIN_MESSAGES_TO_FLUSH = 1;\n\nfunction aggregateBuffer(buffer) {\n const lines = buffer.messages.map((m) => {\n const repliedTo = m.replyTo ? ` -> ${m.replyTo}` : '';\n return `[${m.date}] ${m.author}${repliedTo}: ${m.text}`;\n });\n\n return {\n skip: false,\n text: [\n `Контекст диалога (${buffer.messages.length} сообщений, участники: ${buffer.participants.join(', ')})`,\n ...lines,\n ].join('\\n'),\n metadata: {\n ...buffer.lastMeta,\n context_id: buffer.contextId,\n context_message_count: buffer.messages.length,\n context_start_date: new Date(buffer.startTs).toISOString(),\n context_end_date: new Date(buffer.lastTs).toISOString(),\n context_participants: buffer.participants,\n context_mode: 'thread_time_window_5m_fast_flush'\n }\n };\n}\n\nconst staticData = $getWorkflowStaticData('global');\nstaticData.contextBuffers = staticData.contextBuffers || {};\n\nconst meta = $json.metadata || {};\nconst rawText = (meta.original_text || '').trim();\nif (!rawText) {\n return { json: { skip: true, reason: 'empty_original_text' } };\n}\n\nconst nowTs = meta.date ? new Date(meta.date).getTime() : Date.now();\nconst safeTs = Number.isNaN(nowTs) ? Date.now() : nowTs;\nconst chatId = String(meta.chat_id || meta.group_id || 'unknown_chat');\nconst threadId = String(meta.thread_id || meta.reply_to_message_id || meta.message_id || 'single');\nconst contextId = `${chatId}:${threadId}`;\n\nlet buffer = staticData.contextBuffers[contextId];\n\nif (buffer && safeTs - buffer.lastTs > WINDOW_MS) {\n const staleBuffer = buffer;\n buffer = null;\n\n const author = meta.author_label || meta.sender_name || 'Unknown';\n staticData.contextBuffers[contextId] = {\n contextId,\n startTs: safeTs,\n lastTs: safeTs,\n participants: [author],\n lastMeta: meta,\n messages: [\n {\n date: meta.date || new Date(safeTs).toISOString(),\n author,\n replyTo: meta.replied_to_author_label || '',\n text: rawText\n }\n ]\n };\n\n if (staleBuffer.messages.length >= MIN_MESSAGES_TO_FLUSH) {\n return { json: aggregateBuffer(staleBuffer) };\n }\n\n return { json: { skip: true, reason: 'buffer_reset_on_timeout', context_id: contextId } };\n}\n\nif (!buffer) {\n buffer = {\n contextId,\n startTs: safeTs,\n lastTs: safeTs,\n participants: [],\n lastMeta: meta,\n messages: []\n };\n}\n\nconst author = meta.author_label || meta.sender_name || 'Unknown';\nif (!buffer.participants.includes(author)) {\n buffer.participants.push(author);\n}\n\nbuffer.messages.push({\n date: meta.date || new Date(safeTs).toISOString(),\n author,\n replyTo: meta.replied_to_author_label || '',\n text: rawText\n});\nbuffer.lastMeta = meta;\nbuffer.lastTs = safeTs;\n\nconst shouldFlush =\n buffer.messages.length >= MAX_MESSAGES ||\n buffer.lastTs - buffer.startTs >= WINDOW_MS;\n\nif (!shouldFlush) {\n staticData.contextBuffers[contextId] = buffer;\n return {\n json: {\n skip: true,\n reason: 'buffering',\n context_id: contextId,\n buffered_messages: buffer.messages.length\n }\n };\n}\n\ndelete staticData.contextBuffers[contextId];\nreturn { json: aggregateBuffer(buffer) };"
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},
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"type": "n8n-nodes-base.code",
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"typeVersion": 2,
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"position": [
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],
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"id": "b3866944-b7ca-4505-b89e-a5f3d331f43d",
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"name": "Build Context Block"
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},
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{
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"parameters": {
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"conditions": {
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"boolean": [
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{
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"value1": "={{ $json.skip }}",
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"value2": true
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}
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]
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},
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"options": {}
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],
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"id": "a343f1ca-2423-43e7-9b8d-ce4f48f1e5ff",
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"name": "Skip Buffered Context"
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},
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{
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"parameters": {
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"jsonMode": "expressionData",
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"jsonData": "={{ $json.text }}",
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"options": {}
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},
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"type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
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"typeVersion": 1.1,
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"position": [
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],
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"id": "3de4bfe4-bd8a-4f36-a9ec-8955f2f26f83",
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"name": "Document Loader"
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},
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{
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"parameters": {
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"model": "qwen3-embedding:8b"
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},
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"type": "@n8n/n8n-nodes-langchain.embeddingsOllama",
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"typeVersion": 1,
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"position": [
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],
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"id": "5f48d9eb-ec81-4a00-b2fa-ec6a1fc2f009",
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"name": "Embeddings For Insert",
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"retryOnFail": true,
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"maxTries": 5,
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"waitBetweenTries": 5000
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},
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{
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"parameters": {
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"updates": [
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"message"
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],
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"additionalFields": {}
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},
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"type": "n8n-nodes-base.telegramTrigger",
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"id": "163fbd89-644c-4858-a2ce-8c572a2d3593",
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"name": "Telegram Trigger",
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"retryOnFail": true,
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"maxTries": 5,
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"waitBetweenTries": 5000
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},
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{
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"parameters": {
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"promptType": "define",
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"text": "=Ответь на вопрос пользователя, используя данные из Qdrant Vector Store: {{ $json.message.text }}",
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"options": {}
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"id": "e67a8860-3c52-407e-8fd7-1f481e3c5019",
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"name": "AI Agent"
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},
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{
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"parameters": {
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"model": "qwen3:30b-a3b",
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"options": {
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"temperature": 0
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}
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},
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"type": "@n8n/n8n-nodes-langchain.lmChatOllama",
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"id": "3c7db13e-1be9-4f2f-ab26-a613db89ea71",
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"name": "Ollama Chat Model",
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"retryOnFail": true,
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"maxTries": 5,
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"waitBetweenTries": 5000
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},
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{
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"parameters": {
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"mode": "retrieve-as-tool",
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"toolDescription": "Всегда используй этот инструмент для ответа: в нем релевантные документы из базы знаний.",
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"qdrantCollection": {
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"__rl": true,
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"value": "telegram_kb",
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"mode": "list",
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"cachedResultName": "telegram_kb"
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},
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"includeDocumentMetadata": true,
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"options": {}
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},
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"type": "@n8n/n8n-nodes-langchain.vectorStoreQdrant",
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"typeVersion": 1.3,
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],
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"id": "2f204e2e-58e7-4514-9f3c-3e23949f8520",
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"name": "Qdrant Retrieve Tool",
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"retryOnFail": true,
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"maxTries": 5,
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"waitBetweenTries": 5000
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},
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{
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"parameters": {
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"model": "qwen3-embedding:8b"
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},
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"type": "@n8n/n8n-nodes-langchain.embeddingsOllama",
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"typeVersion": 1,
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"position": [
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],
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"id": "e5d5f376-bb95-4a16-ab11-e5e3e7d74524",
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"name": "Embeddings For Retrieve",
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"retryOnFail": true,
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"maxTries": 5,
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"waitBetweenTries": 5000
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},
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{
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"parameters": {
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"jsCode": "let rawText = $input.item.json.text || $input.item.json.response || $input.item.json.output || '';\nlet cleanText = rawText.replace(/<think>[\\s\\S]*?<\\/think>/g, '').trim();\n\nif (!cleanText) {\n cleanText = 'Не смог сформировать ответ. Попробуйте переформулировать вопрос.';\n}\n\nreturn {\n json: {\n clean_response: cleanText\n }\n};"
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},
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"type": "n8n-nodes-base.code",
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"typeVersion": 2,
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"position": [
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],
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"id": "81f5d5e9-3f13-4d43-b8e2-7112e2ca63e4",
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"name": "Clean Agent Output"
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},
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{
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"parameters": {
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"chatId": "={{ $('Telegram Trigger').item.json.message.from.id }}",
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"text": "={{ $json.clean_response }}",
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"additionalFields": {
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"appendAttribution": false
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}
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},
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"type": "n8n-nodes-base.telegram",
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],
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"id": "e8476b38-8344-4aaf-828e-5da8344b79d2",
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"name": "Send Telegram Reply",
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"retryOnFail": true,
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"maxTries": 5,
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"waitBetweenTries": 5000
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}
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],
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"pinData": {},
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"connections": {
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"Webhook TG Inbox": {
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"main": [
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[
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{
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"node": "Normalize Telegram Payload",
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"type": "main",
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"index": 0
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}
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]
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]
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},
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"Normalize Telegram Payload": {
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"main": [
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[
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{
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"node": "Skip Empty Text",
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"type": "main",
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"index": 0
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}
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]
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]
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},
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"Skip Empty Text": {
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"main": [
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[],
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[
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{
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"node": "Build Context Block",
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"type": "main",
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"index": 0
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}
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]
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]
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},
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"Build Context Block": {
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"main": [
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[
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{
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"node": "Skip Buffered Context",
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"type": "main",
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}
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]
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]
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},
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"Skip Buffered Context": {
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"main": [
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[],
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[
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{
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"node": "Qdrant Insert",
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"type": "main",
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"index": 0
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}
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]
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]
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},
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"Embeddings For Insert": {
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"ai_embedding": [
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[
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{
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"node": "Qdrant Insert",
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"type": "ai_embedding",
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"index": 0
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}
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]
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]
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},
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"Document Loader": {
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"ai_document": [
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[
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{
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"node": "Qdrant Insert",
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"type": "ai_document",
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"index": 0
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}
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]
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]
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},
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"Telegram Trigger": {
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"main": [
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[
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{
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"node": "AI Agent",
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"type": "main",
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"index": 0
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}
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]
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]
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},
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"Ollama Chat Model": {
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"ai_languageModel": [
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[
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{
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"node": "AI Agent",
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"type": "ai_languageModel",
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"index": 0
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}
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]
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]
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},
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"Qdrant Retrieve Tool": {
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"ai_tool": [
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[
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{
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"node": "AI Agent",
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"type": "ai_tool",
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"index": 0
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}
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]
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]
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},
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"Embeddings For Retrieve": {
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"ai_embedding": [
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[
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{
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"node": "Qdrant Retrieve Tool",
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"type": "ai_embedding",
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"index": 0
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}
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]
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]
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},
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"AI Agent": {
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"main": [
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[
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{
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"node": "Clean Agent Output",
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"type": "main",
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"index": 0
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}
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]
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]
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},
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"Clean Agent Output": {
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"main": [
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[
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{
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"node": "Send Telegram Reply",
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"type": "main",
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"index": 0
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}
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]
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]
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}
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},
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"active": false,
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"settings": {
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"executionOrder": "v1",
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"availableInMCP": false
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},
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"tags": []
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}
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