使用Gemini AI视觉分析与Telegram警报监控X平台品牌提及
高级
这是一个Miscellaneous, AI Summarization, Multimodal AI领域的自动化工作流，包含 24 个节点。主要使用 If, Set, Code, Switch, Airtable 等节点。 使用Gemini AI视觉分析与Telegram警报监控X平台品牌提及
前置要求
- •Airtable API Key
- •Telegram Bot Token
- •可能需要目标 API 的认证凭证
- •Google Gemini API Key
使用的节点 (24)
工作流预览
可视化展示节点连接关系，支持缩放和平移
导出工作流
复制以下 JSON 配置到 n8n 导入，即可使用此工作流
{
"meta": {
"instanceId": "afca6c018fd85ecd6bb793dc620b1f9d2de9ea7edb2532dd2708b1a0cf01d640",
"templateCredsSetupCompleted": true
},
"nodes": [
{
"id": "103d7b99-a9df-40c7-9ed4-d7c9738d8ca9",
"name": "如果是推文",
"type": "n8n-nodes-base.if",
"position": [
-144,
-128
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "7d16677e-6045-40e1-8926-6e754fe45c2d",
"operator": {
"type": "boolean",
"operation": "true",
"singleValue": true
},
"leftValue": "={{ $json.type === 'tweet' }}",
"rightValue": ""
},
{
"id": "548064ee-0ddf-46f8-b827-08437628b83c",
"operator": {
"type": "boolean",
"operation": "true",
"singleValue": true
},
"leftValue": "={{ $json.lang === $('Config').item.json.lang }}",
"rightValue": ""
},
{
"id": "afaa1330-1b72-410c-bb48-33b1ea1efaa3",
"operator": {
"type": "boolean",
"operation": "true",
"singleValue": true
},
"leftValue": "={{ $json.card.isEmpty() }}",
"rightValue": "null"
}
]
}
},
"typeVersion": 2.2
},
{
"id": "f20e6318-9d57-490e-b3f7-a3ded4622dc1",
"name": "配置",
"type": "n8n-nodes-base.set",
"position": [
-672,
-128
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "2b13642a-d453-4338-943b-0b27d39ce3b3",
"name": "lang",
"type": "string",
"value": "en"
},
{
"id": "de62b7a8-be52-4208-8218-03ac673dbbad",
"name": "actorId",
"type": "string",
"value": "kaitoeasyapi~twitter-x-data-tweet-scraper-pay-per-result-cheapest"
},
{
"id": "cc4b39e1-4fa3-4855-9158-1c3501d5ebfe",
"name": "searchTerms",
"type": "string",
"value": "(Tesla OR $TSLA OR Cybertruck OR \"Model Y\" OR FSD) -Nikola"
},
{
"id": "32fcc432-e793-420b-85a4-74fcf5e7b966",
"name": "min_faves",
"type": "string",
"value": "10"
},
{
"id": "f326a257-1f18-4880-9e93-7c57b2a81616",
"name": "tweetsToScrape",
"type": "string",
"value": "20"
},
{
"id": "2c5d5c11-01db-4bdb-aaf5-92364c36f239",
"name": "airtableBaseId",
"type": "string",
"value": "appfoRsukEzLhzNwS"
},
{
"id": "70c29ffb-8b8a-4838-9770-a382d5b7d2ac",
"name": "airtableTableId",
"type": "string",
"value": "tblO50wK1GsrweF7j"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "47f19a44-ddd4-48a2-93ec-36ea352a0b90",
"name": "便签",
"type": "n8n-nodes-base.stickyNote",
"position": [
-224,
-256
],
"parameters": {
"color": 2,
"width": 608,
"height": 464,
"content": "## 仅获取推文"
},
"typeVersion": 1
},
{
"id": "325c067c-b310-43f8-bca6-e31aa44ebfb9",
"name": "遍历项目",
"type": "n8n-nodes-base.splitInBatches",
"position": [
512,
-144
],
"parameters": {
"options": {}
},
"typeVersion": 3
},
{
"id": "45aac11e-7d4a-420a-8491-8c2aab1ad828",
"name": "如果是新内容",
"type": "n8n-nodes-base.if",
"position": [
1008,
-128
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "1b074293-6d3b-4fd8-916a-54ec64b56da3",
"operator": {
"type": "boolean",
"operation": "true",
"singleValue": true
},
"leftValue": "={{ $json.isEmpty() }}",
"rightValue": ""
}
]
}
},
"typeVersion": 2.2
},
{
"id": "9a8225d7-4830-4e81-ab5b-8137df784988",
"name": "帖子已存在",
"type": "n8n-nodes-base.airtable",
"position": [
768,
-128
],
"parameters": {
"base": {
"__rl": true,
"mode": "id",
"value": "={{ $('Config').item.json.airtableBaseId }}"
},
"table": {
"__rl": true,
"mode": "id",
"value": "={{ $('Config').item.json.airtableTableId }}"
},
"options": {},
"operation": "search",
"filterByFormula": "={postID}='{{ $json.post.id }}'"
},
"credentials": {
"airtableTokenApi": {
"id": "9dpMJbMZPf7Nfsw8",
"name": "Airtable"
}
},
"typeVersion": 2.1,
"alwaysOutputData": true
},
{
"id": "9820bc4b-febb-4d9c-89dd-a9a3d4a44891",
"name": "设置必填字段",
"type": "n8n-nodes-base.set",
"position": [
176,
-144
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "41682df1-932d-4373-83a8-7516bad2245f",
"name": "post.id",
"type": "string",
"value": "={{ $json.id }}"
},
{
"id": "249814ac-3491-485c-bb6e-4907bd55de5f",
"name": "post.url",
"type": "string",
"value": "={{ $json.url }}"
},
{
"id": "04c15380-02da-4a97-8e0f-d06f60b7403b",
"name": "post.text",
"type": "string",
"value": "={{ $json.text }}"
},
{
"id": "a2710583-74c3-497a-8bb6-de5fbee69ca1",
"name": "post.lang",
"type": "string",
"value": "={{ $json.lang }}"
},
{
"id": "23e6e90b-7fc3-4c51-bbfe-8fa25da32577",
"name": "post.createdAt",
"type": "string",
"value": "={{ $json.createdAt.toDateTime().toISO() }}"
},
{
"id": "b0bd2f75-ca94-4e3e-a2f2-5dbbe9f14a1d",
"name": "author.userName",
"type": "string",
"value": "={{ $json.author.userName }}"
},
{
"id": "749e1fe5-8c95-4522-8491-e24f542e211a",
"name": "author.name",
"type": "string",
"value": "={{ $json.author.name }}"
},
{
"id": "780b5a0f-62f6-4e7b-a22d-6f5c9ee98e3d",
"name": "media.photos",
"type": "array",
"value": "={{ ($json.extendedEntities.media?.filter(item => item.type === 'photo').map(item => item.media_url_https).filter(url => url)) || [] }}"
},
{
"id": "cafdf61f-ee05-4f7b-8c99-2460f93b41f4",
"name": "media.videos",
"type": "array",
"value": "={{ \n\n($json.extendedEntities.media || []).map(item => (item.video_info?.variants || []).filter(v => v?.content_type === 'video/mp4' && v.bitrate != null).sort((a, b) => b.bitrate - a.bitrate)[0]?.url).filter(url => url)\n\n}}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "8bcdb545-1d9c-4855-a303-274f5f288c71",
"name": "结构化输出解析器",
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"position": [
2480,
128
],
"parameters": {
"jsonSchemaExample": "{\n \"overallSentiment\": \"Positive\",\n \"relevanceScore\": 8,\n \"reasoning\": \"A one-sentence explanation for your decision, referencing both text and visuals if available.\",\n \"photosSummary\": \"A concise, one to two-sentence summary of the entire post, combining insights from both the text and the images.\"\n}"
},
"typeVersion": 1.3
},
{
"id": "592b5157-405b-4c90-9ca3-e53900f5183a",
"name": "Google Calendar MCP",
"type": "n8n-nodes-base.switch",
"position": [
2672,
-144
],
"parameters": {
"rules": {
"values": [
{
"outputKey": "High Relevance",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "7b1ab8fb-30b5-448a-a5b1-0cd1dd09f2a1",
"operator": {
"type": "number",
"operation": "gt"
},
"leftValue": "={{ $json.output.relevanceScore }}",
"rightValue": 7
}
]
},
"renameOutput": true
},
{
"outputKey": "Not Relevance",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "513914f6-3119-4809-a613-d8764d03ef46",
"operator": {
"type": "number",
"operation": "lt"
},
"leftValue": "={{ $json.output.relevanceScore }}",
"rightValue": 4
}
]
},
"renameOutput": true
},
{
"outputKey": "Medium Relevance",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "82944e41-fbb3-481c-afc5-6b28b68b1704",
"operator": {
"type": "number",
"operation": "gte"
},
"leftValue": "={{ $json.output.relevanceScore }}",
"rightValue": 4
}
]
},
"renameOutput": true
}
]
},
"options": {}
},
"typeVersion": 3.2
},
{
"id": "5811f406-1f42-4b4b-a5b6-7d9268bdd4fb",
"name": "定时触发器",
"type": "n8n-nodes-base.scheduleTrigger",
"position": [
-928,
-224
],
"parameters": {
"rule": {
"interval": [
{
"field": "hours",
"hoursInterval": 4
}
]
}
},
"typeVersion": 1.2
},
{
"id": "c2f6205b-ad16-41a6-a48f-b93446a4ef26",
"name": "完成！",
"type": "n8n-nodes-base.noOp",
"position": [
768,
-352
],
"parameters": {},
"typeVersion": 1
},
{
"id": "82727baa-5035-4129-a8a7-be20cb72f2f9",
"name": "记录中等相关性帖子",
"type": "n8n-nodes-base.airtable",
"position": [
3056,
-96
],
"parameters": {
"base": {
"__rl": true,
"mode": "id",
"value": "={{ $('Config').item.json.airtableBaseId }}"
},
"table": {
"__rl": true,
"mode": "id",
"value": "={{ $('Config').item.json.airtableTableId }}"
},
"columns": {
"value": {
"postID": "={{ $('Loop Over Items').item.json.post.id }}",
"status": "For Weekly Review",
"postURL": "={{ $('Loop Over Items').item.json.post.url }}",
"postLang": "={{ $('Loop Over Items').item.json.post.lang }}",
"postText": "={{ $('Loop Over Items').item.json.post.text }}",
"authorName": "={{ $('Loop Over Items').item.json.author.name }}",
"aiSentiment": "={{ $json.output.overallSentiment }}",
"mediaPhotos": "={{ $('Loop Over Items').item.json.media.photos.join(',') }}",
"mediaVideos": "={{ $('Loop Over Items').item.json.media.videos.join(',') }}",
"postCreatedAt": "={{ $('Loop Over Items').item.json.post.createdAt }}",
"authorUserName": "={{ $('Loop Over Items').item.json.author.userName }}",
"relevanceScore": "={{ $('Analyze Text and Photos').item.json.output.relevanceScore }}",
"relevanceReasoning": "={{ $('Analyze Text and Photos').item.json.output.reasoning }}",
"mediaPhotosAnalysis": "={{ $('Analyze Text and Photos').item.json.output.photosSummary}}"
},
"schema": [
{
"id": "postID",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "postID",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "postURL",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "postURL",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "postText",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "postText",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "postLang",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "postLang",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "postCreatedAt",
"type": "dateTime",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "postCreatedAt",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "authorUserName",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "authorUserName",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "authorName",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "authorName",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "mediaPhotos",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "mediaPhotos",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "mediaVideos",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "mediaVideos",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "aiSentiment",
"type": "options",
"display": true,
"options": [
{
"name": "Negative",
"value": "Negative"
},
{
"name": "Positive",
"value": "Positive"
},
{
"name": "Neutral",
"value": "Neutral"
}
],
"removed": false,
"readOnly": false,
"required": false,
"displayName": "aiSentiment",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "relevanceScore",
"type": "number",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "relevanceScore",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "relevanceReasoning",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "relevanceReasoning",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "mediaPhotosAnalysis",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "mediaPhotosAnalysis",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "status",
"type": "options",
"display": true,
"options": [
{
"name": "New",
"value": "New"
},
{
"name": "Action Required",
"value": "Action Required"
},
{
"name": "Escalated",
"value": "Escalated"
},
{
"name": "For Weekly Review",
"value": "For Weekly Review"
},
{
"name": "Done",
"value": "Done"
},
{
"name": "Archived (No Action)",
"value": "Archived (No Action)"
}
],
"removed": false,
"readOnly": false,
"required": false,
"displayName": "status",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "assignee",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "assignee",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {},
"operation": "create"
},
"credentials": {
"airtableTokenApi": {
"id": "9dpMJbMZPf7Nfsw8",
"name": "Airtable"
}
},
"typeVersion": 2.1
},
{
"id": "ec360fe2-b495-41fa-a719-e72edcbad854",
"name": "记录高相关性帖子",
"type": "n8n-nodes-base.airtable",
"position": [
3056,
-352
],
"parameters": {
"base": {
"__rl": true,
"mode": "id",
"value": "={{ $('Config').item.json.airtableBaseId }}"
},
"table": {
"__rl": true,
"mode": "id",
"value": "={{ $('Config').item.json.airtableTableId }}"
},
"columns": {
"value": {
"postID": "={{ $('Loop Over Items').item.json.post.id }}",
"status": "New",
"postURL": "={{ $('Loop Over Items').item.json.post.url }}",
"postLang": "={{ $('Loop Over Items').item.json.post.lang }}",
"postText": "={{ $('Loop Over Items').item.json.post.text }}",
"authorName": "={{ $('Loop Over Items').item.json.author.name }}",
"aiSentiment": "={{ $json.output.overallSentiment }}",
"mediaPhotos": "={{ $('Loop Over Items').item.json.media.photos.join(',') }}",
"mediaVideos": "={{ $('Loop Over Items').item.json.media.videos.join(',') }}",
"postCreatedAt": "={{ $('Loop Over Items').item.json.post.createdAt }}",
"authorUserName": "={{ $('Loop Over Items').item.json.author.userName }}",
"relevanceScore": "={{ $('Analyze Text and Photos').item.json.output.relevanceScore }}",
"relevanceReasoning": "={{ $('Analyze Text and Photos').item.json.output.reasoning }}",
"mediaPhotosAnalysis": "={{ $('Analyze Text and Photos').item.json.output.photosSummary}}"
},
"schema": [
{
"id": "postID",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "postID",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "postURL",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "postURL",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "postText",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "postText",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "postLang",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "postLang",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "postCreatedAt",
"type": "dateTime",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "postCreatedAt",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "authorUserName",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "authorUserName",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "authorName",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "authorName",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "mediaPhotos",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "mediaPhotos",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "mediaVideos",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "mediaVideos",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "aiSentiment",
"type": "options",
"display": true,
"options": [
{
"name": "Negative",
"value": "Negative"
},
{
"name": "Positive",
"value": "Positive"
},
{
"name": "Neutral",
"value": "Neutral"
}
],
"removed": false,
"readOnly": false,
"required": false,
"displayName": "aiSentiment",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "relevanceScore",
"type": "number",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "relevanceScore",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "relevanceReasoning",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "relevanceReasoning",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "mediaPhotosAnalysis",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "mediaPhotosAnalysis",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "status",
"type": "options",
"display": true,
"options": [
{
"name": "New",
"value": "New"
},
{
"name": "Action Required",
"value": "Action Required"
},
{
"name": "Escalated",
"value": "Escalated"
},
{
"name": "For Weekly Review",
"value": "For Weekly Review"
},
{
"name": "Done",
"value": "Done"
},
{
"name": "Archived (No Action)",
"value": "Archived (No Action)"
}
],
"removed": false,
"readOnly": false,
"required": false,
"displayName": "status",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "assignee",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "assignee",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {},
"operation": "create"
},
"credentials": {
"airtableTokenApi": {
"id": "9dpMJbMZPf7Nfsw8",
"name": "Airtable"
}
},
"typeVersion": 2.1
},
{
"id": "80c945ca-1a52-429e-816d-d15205d6704a",
"name": "不感兴趣！",
"type": "n8n-nodes-base.noOp",
"position": [
176,
64
],
"parameters": {},
"typeVersion": 1
},
{
"id": "b9964fcb-b810-4c1e-9b44-547906bbcfe0",
"name": "分析帖子图片",
"type": "@n8n/n8n-nodes-langchain.googleGemini",
"position": [
1680,
-352
],
"parameters": {
"text": "=You are provided with several images. For EACH image, provide a brief description and its sentiment.\n\nRespond with a JSON object containing a list of your findings, structured like this:\n{\n \"image_analyses\": [\n { \"image_index\": 0, \"description\": \"...\", \"sentiment\": \"...\" },\n { \"image_index\": 1, \"description\": \"...\", \"sentiment\": \"...\" }\n ]\n}",
"modelId": {
"__rl": true,
"mode": "list",
"value": "models/gemini-2.5-flash",
"cachedResultName": "models/gemini-2.5-flash"
},
"options": {},
"resource": "image",
"imageUrls": "={{ $('Loop Over Items').item.json.media.photos.join(',') }}",
"operation": "analyze"
},
"credentials": {
"googlePalmApi": {
"id": "vppVWKsiofTY92Ht",
"name": "Google Gemini(PaLM) Api account"
}
},
"executeOnce": false,
"typeVersion": 1,
"alwaysOutputData": false
},
{
"id": "83bad7fe-b828-4802-8d23-79c65380c051",
"name": "获取最终图片分析结果",
"type": "n8n-nodes-base.code",
"position": [
1936,
-352
],
"parameters": {
"jsCode": "// 'items' is an array of all your inputs.\n// We loop through each one using .map().\nconst allData = $input.first().json.content.parts.map(item => {\n // Get the raw text string from the current item.\n const rawText = item.text;\n\n // Find and extract the clean JSON string from the code block.\n const match = rawText.match(/```json\\n([\\s\\S]*)\\n```/);\n const jsonString = match ? match[1] : '{}'; // Default to empty object if no match\n\n // Parse the string into a real JSON object.\n return JSON.parse(jsonString);\n});\n\n// Return a single new item containing the array of all parsed data.\nreturn [{\n json: {\n photos_results: allData\n },\n // The index of the input item that generated this output item\n \"pairedItem\": 0\n}];"
},
"typeVersion": 2
},
{
"id": "2dfef403-c35d-4500-8cd1-1f4b1079a48b",
"name": "如果包含图片",
"type": "n8n-nodes-base.if",
"position": [
1312,
-144
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "0220f75b-64a3-430c-ac44-887c7be35ece",
"operator": {
"type": "boolean",
"operation": "true",
"singleValue": true
},
"leftValue": "={{ $('Loop Over Items').item.json.media.photos.isNotEmpty() }}",
"rightValue": ""
}
]
}
},
"typeVersion": 2.2
},
{
"id": "f819b63c-9f44-40fb-bc46-a8cbec06e605",
"name": "便签1",
"type": "n8n-nodes-base.stickyNote",
"position": [
1520,
-480
],
"parameters": {
"color": 3,
"width": 672,
"height": 416,
"content": "## 分析帖子图片"
},
"typeVersion": 1
},
{
"id": "d17ee8c7-0727-481c-8422-26c9fb001ca6",
"name": "便签2",
"type": "n8n-nodes-base.stickyNote",
"position": [
2240,
-352
],
"parameters": {
"color": 5,
"width": 704,
"height": 656,
"content": "## 检查帖子与品牌相关性"
},
"typeVersion": 1
},
{
"id": "b26f7535-de62-456b-a8bd-338c91311e24",
"name": "爬取X",
"type": "n8n-nodes-base.httpRequest",
"position": [
-448,
-128
],
"parameters": {
"url": "=https://api.apify.com/v2/acts/{{ $json.actorId }}/run-sync-get-dataset-items",
"method": "POST",
"options": {},
"jsonBody": "={\n \"filter:blue_verified\": false,\n \"filter:consumer_video\": false,\n \"filter:has_engagement\": false,\n \"filter:hashtags\": false,\n \"filter:images\": true,\n \"filter:links\": false,\n \"filter:media\": false,\n \"filter:mentions\": false,\n \"filter:native_video\": false,\n \"filter:nativeretweets\": false,\n \"filter:news\": false,\n \"filter:pro_video\": false,\n \"filter:quote\": false,\n \"filter:replies\": false,\n \"filter:safe\": false,\n \"filter:spaces\": false,\n \"filter:twimg\": false,\n \"filter:videos\": false,\n \"filter:vine\": false,\n \"include:nativeretweets\": false,\n \"lang\": \"{{ $json.lang }}\",\n \"searchTerms\": [\n {{ $json.searchTerms.toJsonString() }}\n ],\n \"since\": \"{{ new Date(Date.now() - 86400000).toISOString().slice(0, 19).replace('T', '_') + '_UTC'; }}\",\n \"maxItems\": {{ $json.tweetsToScrape }},\n \"queryType\": \"Latest\",\n \"min_retweets\": 0,\n \"min_faves\": {{ $json.min_faves }},\n \"min_replies\": 0,\n \"-min_retweets\": 0,\n \"-min_faves\": 0,\n \"-min_replies\": 0\n}",
"sendBody": true,
"specifyBody": "json",
"authentication": "genericCredentialType",
"genericAuthType": "httpBearerAuth"
},
"credentials": {
"httpBearerAuth": {
"id": "Fu6O8UOTEpfPXgyP",
"name": "Apify"
}
},
"typeVersion": 4.2
},
{
"id": "cd7a5fbe-d569-41a5-99be-7c944b8d902c",
"name": "手动执行",
"type": "n8n-nodes-base.manualTrigger",
"position": [
-928,
-32
],
"parameters": {},
"typeVersion": 1
},
{
"id": "f4c16426-20af-4d2f-b004-501a5a602494",
"name": "发送高相关性帖子至监控群组",
"type": "n8n-nodes-base.telegram",
"position": [
3264,
-352
],
"webhookId": "376c4c49-f408-4b40-96f7-6c6f79c5cee8",
"parameters": {
"text": "=<b>🔥 New High-Relevance Tesla Mention! 🔥</b>\n\n<i>Author:</i> {{ $('Loop Over Items').item.json.author.name }} (@{{ $('Loop Over Items').item.json.author.userName }})\n<i>Sentiment:</i> <code>{{ $('Analyze Text and Photos').item.json.output.overallSentiment }}</code>\n<i>Relevance Score:</i> <code>{{ $('Analyze Text and Photos').item.json.output.relevanceScore }}/10</code>\n\n<blockquote>{{ $('Loop Over Items').item.json.post.text }}</blockquote>\n\n<a href=\"{{ $('Loop Over Items').item.json.post.url }}\">Link to Tweet</a>\n\n",
"chatId": "-4956947485",
"additionalFields": {
"parse_mode": "HTML",
"appendAttribution": false
}
},
"credentials": {
"telegramApi": {
"id": "RDdscBadRkYP5zeG",
"name": "Telegram (n8n)"
}
},
"typeVersion": 1.2
},
{
"id": "df071519-f247-443c-9eb9-f855a677b614",
"name": "分析文本和图片",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
2320,
-128
],
"parameters": {
"text": "=Perform a final analysis based on the following data.\n\n--- Post Text ---\n\"\"\"\n{{ $('Loop Over Items').item.json.post.text }}\n\"\"\"\n\n--- Image Analysis (JSON) ---\n\"\"\"\n{{ $('Get Final Photos Analysis Results').isExecuted ? ($json.photos_results ? JSON.stringify($json.photos_results) : \"No images were included in this post.\") : \"No images were included in this post.2\"}}\n\"\"\"\n\n",
"options": {
"systemMessage": "=You are a Head Brand Strategist for Tesla. Your job is to synthesize the provided analyses of a social media post's text and visuals into a final, conclusive assessment.\n\n--- Brand Context ---\n- Brand Identifiers: \"Tesla\", \"$TSLA\"\n- Core Products: \"Model S\", \"Model 3\", \"Model Y\", \"Cybertruck\", \"Autopilot\", \"FSD\"\n- Nuance: Ignore mentions of \"Nikola Tesla\" the inventor.\n\n--- Your Task ---\n1. First, look at the `Image Analysis (JSON)`. Synthesize the individual image descriptions into a single, one-sentence summary for the `photosSummary` field.\n2. **Crucial Rule:** If the `Image Analysis` section says \"No images were included in this post\", you MUST return an empty string (\"\") for the `photosSummary` field.\n3. Then, using all available information (the `Post Text` and your new `photoSummary`), determine the final sentiment, relevance, and a suggested status.\n\n--- Output Format ---\nRespond ONLY with a single, valid JSON object with this exact structure:\n{\n \"overallSentiment\": \"Positive\", \"Negative\", or \"Neutral\",\n \"relevanceScore\": integer (0-10),\n \"reasoning\": \"A one-sentence explanation for your decision, referencing both text and visuals if available.\",\n \"photosSummary\": \"A one-sentence summary of the visual story from the images, OR an empty string if there are no images.\"\n}\n",
"passthroughBinaryImages": true
},
"promptType": "define",
"hasOutputParser": true
},
"typeVersion": 2.2
},
{
"id": "27dfc0d8-93dc-4b25-9ea1-be9429ca267b",
"name": "Google Gemini 聊天模型",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
2304,
128
],
"parameters": {
"options": {}
},
"credentials": {
"googlePalmApi": {
"id": "vppVWKsiofTY92Ht",
"name": "Google Gemini(PaLM) Api account"
}
},
"typeVersion": 1
}
],
"pinData": {},
"connections": {
"Config": {
"main": [
[
{
"node": "Scrape X",
"type": "main",
"index": 0
}
]
]
},
"If New": {
"main": [
[
{
"node": "If Has Photos",
"type": "main",
"index": 0
}
],
[
{
"node": "Loop Over Items",
"type": "main",
"index": 0
}
]
]
},
"Switch": {
"main": [
[
{
"node": "Log the High Relevance Post",
"type": "main",
"index": 0
}
],
[
{
"node": "Loop Over Items",
"type": "main",
"index": 0
}
],
[
{
"node": "Log the Medium Relevance Post",
"type": "main",
"index": 0
}
]
]
},
"If Tweet": {
"main": [
[
{
"node": "Set Required Fields",
"type": "main",
"index": 0
}
],
[
{
"node": "Not Interested!",
"type": "main",
"index": 0
}
]
]
},
"Scrape X": {
"main": [
[
{
"node": "If Tweet",
"type": "main",
"index": 0
}
]
]
},
"Post Exists": {
"main": [
[
{
"node": "If New",
"type": "main",
"index": 0
}
]
]
},
"If Has Photos": {
"main": [
[
{
"node": "Analyze Post Photos",
"type": "main",
"index": 0
}
],
[
{
"node": "Analyze Text and Photos",
"type": "main",
"index": 0
}
]
]
},
"Loop Over Items": {
"main": [
[
{
"node": "Done!",
"type": "main",
"index": 0
}
],
[
{
"node": "Post Exists",
"type": "main",
"index": 0
}
]
]
},
"Manual Executing": {
"main": [
[
{
"node": "Config",
"type": "main",
"index": 0
}
]
]
},
"Schedule Trigger": {
"main": [
[
{
"node": "Config",
"type": "main",
"index": 0
}
]
]
},
"Analyze Post Photos": {
"main": [
[
{
"node": "Get Final Photos Analysis Results",
"type": "main",
"index": 0
}
]
]
},
"Set Required Fields": {
"main": [
[
{
"node": "Loop Over Items",
"type": "main",
"index": 0
}
]
]
},
"Analyze Text and Photos": {
"main": [
[
{
"node": "Switch",
"type": "main",
"index": 0
}
]
]
},
"Google Gemini Chat Model": {
"ai_languageModel": [
[
{
"node": "Analyze Text and Photos",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Structured Output Parser": {
"ai_outputParser": [
[
{
"node": "Analyze Text and Photos",
"type": "ai_outputParser",
"index": 0
}
]
]
},
"Log the High Relevance Post": {
"main": [
[
{
"node": "Send High Relevance Post to Monitoring Group",
"type": "main",
"index": 0
}
]
]
},
"Log the Medium Relevance Post": {
"main": [
[
{
"node": "Loop Over Items",
"type": "main",
"index": 0
}
]
]
},
"Get Final Photos Analysis Results": {
"main": [
[
{
"node": "Analyze Text and Photos",
"type": "main",
"index": 0
}
]
]
},
"Send High Relevance Post to Monitoring Group": {
"main": [
[
{
"node": "Loop Over Items",
"type": "main",
"index": 0
}
]
]
}
}
}常见问题
如何使用这个工作流？
复制上方的 JSON 配置代码，在您的 n8n 实例中创建新工作流并选择「从 JSON 导入」，粘贴配置后根据需要修改凭证设置即可。
这个工作流适合什么场景？
高级 - 杂项, AI 摘要总结, 多模态 AI
需要付费吗？
本工作流完全免费，您可以直接导入使用。但请注意，工作流中使用的第三方服务（如 OpenAI API）可能需要您自行付费。
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难度等级
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节点数量24
分类3
节点类型16
作者
Atta
@attakhalighiHi 👋 I design automation workflows with n8n, AI, and custom APIs. My focus is on building reliable systems that save time and boost productivity. Always happy to answer questions about my templates.
外部链接
在 n8n.io 查看 →
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