n8n-nodes-video-ai
Version:
n8n node for AI-powered video Operations (analysis, Review, Summarize, etc), currently supporting Google Gemini.
199 lines • 8.53 kB
JavaScript
;
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var __importStar = (this && this.__importStar) || function (mod) {
if (mod && mod.__esModule) return mod;
var result = {};
if (mod != null) for (var k in mod) if (k !== "default" && Object.prototype.hasOwnProperty.call(mod, k)) __createBinding(result, mod, k);
__setModuleDefault(result, mod);
return result;
};
Object.defineProperty(exports, "__esModule", { value: true });
exports.VideoAiAnalysis = void 0;
const n8n_workflow_1 = require("n8n-workflow");
class VideoAiAnalysis {
constructor() {
this.description = {
displayName: 'Video AI Analysis',
name: 'videoAiAnalysis',
group: ['transform'],
version: 1,
description: 'Perform AI-powered video Operations (analysis, Review, Summarize, etc). <br><em>Beta: Currently supports Google Gemini models only. More AI providers coming soon!</em>',
documentationUrl: 'https://www.hadidizflow.com/blog/unlock-ai-video-analysis-n8n-video-ai-node-hadidizflow',
defaults: {
name: 'Video AI Analysis',
},
icon: 'file:VideoAiAnalysis.svg',
subtitle: '={{$parameter["customPrompt"] ? "Custom Prompt" : ""}}',
inputs: ['main'],
outputs: ['main'],
credentials: [
{
name: 'geminiApi',
required: true,
},
],
properties: [
{
displayName: 'Video URL',
name: 'videoUrl',
type: 'string',
default: '',
required: true,
description: 'URL of the video to analyze',
},
{
displayName: 'Custom Prompt',
name: 'customPrompt',
type: 'string',
default: '',
required: true,
description: 'Custom prompt to analyze the video',
typeOptions: {
rows: 4,
},
},
{
displayName: 'Model',
name: 'model',
type: 'options',
default: 'gemini-2.0-flash-thinking-exp-01-21',
options: [
{
name: 'Gemini 2.0 Flash (Experimental)',
value: 'gemini-2.0-flash-exp',
},
{
name: 'Gemini 2.0 Flash Thinking (Experimental)',
value: 'gemini-2.0-flash-thinking-exp-01-21',
},
],
description: 'Which Gemini model to use for video analysis',
},
{
displayName: 'Options',
name: 'options',
type: 'collection',
default: {},
placeholder: 'Add Option',
options: [
{
displayName: 'Temperature',
name: 'temperature',
type: 'number',
default: 0.5,
description: 'Controls the randomness of the output. Values can range from 0.0 to 1.0.',
typeOptions: {
minValue: 0,
maxValue: 1,
},
},
{
displayName: 'Maximum Video Size (MB)',
name: 'maxVideoSize',
type: 'number',
default: 25,
description: 'Maximum size of video to download in megabytes (MB)',
},
],
},
],
};
}
async execute() {
const items = this.getInputData();
const returnData = [];
const credentials = await this.getCredentials('geminiApi');
const apiKey = credentials.apiKey;
const generativeAI = await Promise.resolve().then(() => __importStar(require('@google/generative-ai')));
const fetch = require('node-fetch');
const genAI = new generativeAI.GoogleGenerativeAI(apiKey);
for (let i = 0; i < items.length; i++) {
try {
const videoUrl = this.getNodeParameter('videoUrl', i);
const customPrompt = this.getNodeParameter('customPrompt', i);
const model = this.getNodeParameter('model', i);
const options = this.getNodeParameter('options', i, {});
const temperature = options.temperature || 0.5;
const maxVideoSize = options.maxVideoSize || 25;
this.logger.info(`Downloading video from ${videoUrl}...`);
const fetchOptions = {
method: 'GET',
};
const response = await fetch(videoUrl, fetchOptions);
if (!response.ok) {
throw new n8n_workflow_1.NodeOperationError(this.getNode(), `Failed to download video: ${response.statusText}`, { itemIndex: i });
}
const contentLength = response.headers.get('content-length');
if (contentLength) {
const sizeInMB = parseInt(contentLength) / (1024 * 1024);
if (sizeInMB > maxVideoSize) {
throw new n8n_workflow_1.NodeOperationError(this.getNode(), `Video size (${sizeInMB.toFixed(2)} MB) exceeds maximum allowed size (${maxVideoSize} MB)`, { itemIndex: i });
}
}
const contentType = response.headers.get('content-type');
const mimeType = contentType || 'video/mp4';
this.logger.info('Processing video data...');
const videoBuffer = await response.buffer();
const videoBase64 = videoBuffer.toString('base64');
const generationModel = genAI.getGenerativeModel({
model,
generationConfig: {
temperature,
},
});
this.logger.info(`Analyzing video with ${model}...`);
const req = [
{ text: customPrompt },
{
inlineData: {
mimeType,
data: videoBase64
}
}
];
const result = await generationModel.generateContent(req);
const output = {
text: result.response.text(),
model,
prompt: customPrompt,
};
returnData.push({
json: output,
pairedItem: i,
});
}
catch (error) {
if (this.continueOnFail()) {
returnData.push({
json: {
error: error.message,
},
pairedItem: i,
});
continue;
}
throw new n8n_workflow_1.NodeOperationError(this.getNode(), error, {
itemIndex: i,
});
}
}
return [returnData];
}
}
exports.VideoAiAnalysis = VideoAiAnalysis;
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