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Add SVECTOR Vision API support and examples
Introduces comprehensive vision and image analysis capabilities to the SDK, including a new Vision API implementation, usage documentation, and multiple example scripts for advanced, batch, and streaming image analysis. Updates README files with detailed instructions and best practices for using the Vision API across Node.js and Deno environments.
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‎README.md‎

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‎examples/advanced-vision.ts‎

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import fs from 'fs';
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import { SVECTOR } from '../src/index';
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/**
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* Advanced SVECTOR Vision API Examples
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* Demonstrates advanced vision capabilities and API patterns
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*/
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const client = new SVECTOR({
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apiKey: process.env.SVECTOR_API_KEY,
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});
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/**
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* Example 1: SVECTOR-style responses.create with image URL
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*/
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async function svectorStyleURL() {
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console.log('🔗 SVECTOR-style URL analysis...');
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try {
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const response = await client.vision.createResponse({
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model: "spec-3-turbo",
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input: [{
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role: "user",
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content: [
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{ type: "input_text", text: "what's in this image?" },
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{
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type: "input_image",
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image_url: "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg",
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},
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],
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}],
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});
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console.log('Analysis:', response.output_text);
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} catch (error) {
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console.error('Error:', error);
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}
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}
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/**
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* Example 2: SVECTOR-style with base64 image
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*/
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async function svectorStyleBase64() {
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console.log('📁 SVECTOR-style base64 analysis...');
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try {
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const imagePath = "./sample-image.jpg";
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const base64Image = fs.readFileSync(imagePath, "base64");
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const response = await client.vision.createResponse({
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model: "spec-3-turbo",
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input: [
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{
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role: "user",
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content: [
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{ type: "input_text", text: "what's in this image?" },
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{
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type: "input_image",
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image_url: `data:image/jpeg;base64,${base64Image}`,
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},
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],
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},
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],
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});
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console.log('Analysis:', response.output_text);
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} catch (error) {
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console.error('Error:', error);
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}
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}
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/**
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* Example 3: SVECTOR-style with file ID
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*/
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async function svectorStyleFileID() {
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console.log('📤 SVECTOR-style file ID analysis...');
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try {
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// Upload file first
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const fileContent = fs.createReadStream("./sample-image.jpg");
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const fileResult = await client.files.create(fileContent, "default");
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const fileId = fileResult.file_id;
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const response = await client.vision.createResponse({
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model: "spec-3-turbo",
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input: [
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{
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role: "user",
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content: [
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{ type: "input_text", text: "what's in this image?" },
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{
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type: "input_image",
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file_id: fileId,
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},
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],
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},
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],
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});
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console.log('File ID:', fileId);
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console.log('Analysis:', response.output_text);
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} catch (error) {
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console.error('Error:', error);
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}
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}
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/**
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* Example 4: Batch processing with enhanced features
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*/
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async function batchImageProcessing() {
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console.log('📊 Batch image processing...');
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try {
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const images = [
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{
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image_url: 'https://example.com/product1.jpg',
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prompt: 'Describe this product and its key features'
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},
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{
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image_url: 'https://example.com/product2.jpg',
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prompt: 'What is the main selling point of this product?'
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},
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{
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image_url: 'https://example.com/product3.jpg',
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prompt: 'Who is the target audience for this product?'
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}
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];
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const results = await client.vision.batchAnalyze(images, {
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model: 'spec-3-turbo',
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max_tokens: 300,
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delay: 1500 // 1.5 second delay between requests
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});
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results.forEach((result: { analysis: string; usage?: any; error?: string }, index: number) => {
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if (result.error) {
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console.log(`Image ${index + 1}: Error - ${result.error}`);
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} else {
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console.log(`Image ${index + 1}: ${result.analysis}`);
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console.log(`Tokens used: ${result.usage?.total_tokens || 'N/A'}`);
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}
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console.log('---');
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});
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} catch (error) {
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console.error('Error in batch processing:', error);
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}
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}
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/**
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* Example 5: Confidence scoring
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*/
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async function confidenceScoring() {
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console.log('🎯 Image analysis with confidence scoring...');
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try {
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const result = await client.vision.analyzeWithConfidence({
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image_url: 'https://example.com/medical-scan.jpg',
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prompt: 'Analyze this medical image and identify any abnormalities',
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model: 'spec-3-turbo'
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});
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console.log('Analysis:', result.analysis);
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console.log('Confidence:', result.confidence ? `${result.confidence}%` : 'Not provided');
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} catch (error) {
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console.error('Error:', error);
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}
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}
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/**
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* Example 6: Social media caption generation
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*/
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async function socialMediaCaptions() {
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console.log('📱 Social media caption generation...');
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try {
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const imageUrl = 'https://example.com/vacation-photo.jpg';
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// Professional caption
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const professional = await client.vision.generateCaption({
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image_url: imageUrl
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}, 'professional');
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// Casual caption
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const casual = await client.vision.generateCaption({
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image_url: imageUrl
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}, 'casual');
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// Funny caption
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const funny = await client.vision.generateCaption({
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image_url: imageUrl
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}, 'funny');
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console.log('Professional:', professional.analysis);
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console.log('Casual:', casual.analysis);
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console.log('Funny:', funny.analysis);
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} catch (error) {
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console.error('Error:', error);
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}
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}
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/**
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* Example 7: Advanced vision with streaming
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*/
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async function streamingVisionAnalysis() {
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console.log('🌊 Streaming vision analysis...');
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try {
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const stream = await client.conversations.createStream({
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model: 'spec-3-turbo',
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instructions: 'You are an expert art critic and historian. Provide detailed analysis.',
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input: 'Analyze this artwork in detail, including style, composition, historical context, and artistic techniques.',
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// Note: For full image + text streaming, use chat.createStream with proper message format
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stream: true,
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max_tokens: 1500
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});
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console.log('Art analysis: ');
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for await (const chunk of stream) {
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if (!chunk.done) {
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process.stdout.write(chunk.content);
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}
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}
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console.log('\n✅ Analysis complete');
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} catch (error) {
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console.error('Error in streaming analysis:', error);
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}
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}
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/**
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* Example 8: Technical image analysis
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*/
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async function technicalAnalysis() {
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console.log('🔬 Technical image analysis...');
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try {
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const result = await client.vision.analyzeFromUrl(
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'https://example.com/circuit-board.jpg',
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'Provide a technical analysis of this electronic circuit board. Identify components, trace paths, and assess the overall design.',
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{
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model: 'spec-3-turbo',
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max_tokens: 1200,
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temperature: 0.1, // Low temperature for technical accuracy
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detail: 'high'
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}
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);
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console.log('Technical analysis:', result.analysis);
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console.log('Token usage:', result.usage);
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} catch (error) {
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console.error('Error:', error);
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}
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}
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/**
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* Example 9: Multi-modal conversation
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*/
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async function multiModalConversation() {
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console.log('💬 Multi-modal conversation...');
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try {
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// Start with image analysis
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const initialAnalysis = await client.conversations.create({
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model: 'spec-3-turbo',
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instructions: 'You are a helpful assistant that can analyze images and maintain conversation context.',
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input: 'What do you see in this image?',
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// Note: For full multi-modal support with conversations, consider using chat.create instead
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});
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console.log('Initial analysis:', initialAnalysis.output);
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// Follow up with a text-only question
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const followUp = await client.conversations.create({
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model: 'spec-3-turbo',
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instructions: 'You are a helpful assistant. Remember the previous image analysis.',
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input: 'Based on what you saw in that image, what time of day do you think it was taken?',
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context: [
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'What do you see in this image?',
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initialAnalysis.output
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]
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});
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console.log('Follow-up response:', followUp.output);
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} catch (error) {
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console.error('Error:', error);
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}
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}
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// Run all examples
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async function runAllExamples() {
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console.log('🚀 SVECTOR Advanced Vision API Examples');
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console.log('========================================\n');
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await svectorStyleURL();
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console.log('\n---\n');
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await svectorStyleBase64();
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console.log('\n---\n');
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await svectorStyleFileID();
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console.log('\n---\n');
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await batchImageProcessing();
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console.log('\n---\n');
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await confidenceScoring();
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console.log('\n---\n');
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await socialMediaCaptions();
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console.log('\n---\n');
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await streamingVisionAnalysis();
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console.log('\n---\n');
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await technicalAnalysis();
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console.log('\n---\n');
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await multiModalConversation();
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}
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// Export functions for individual use
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export {
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batchImageProcessing,
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confidenceScoring, multiModalConversation, socialMediaCaptions,
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streamingVisionAnalysis, svectorStyleBase64,
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svectorStyleFileID, svectorStyleURL, technicalAnalysis
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};
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// Run if called directly
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if (require.main === module) {
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runAllExamples().catch(console.error);
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}

‎examples/comprehensive-demo.ts‎

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* This example showcases all major SDK capabilities
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*/
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import {
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APIError,
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AuthenticationError,
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RateLimitError,
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SVECTOR,
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toFile
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APIError,
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AuthenticationError,
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RateLimitError,
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SVECTOR,
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toFile
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} from '../src';
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async function comprehensiveExample() {
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const customClient = new SVECTOR({
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apiKey: process.env.SVECTOR_API_KEY,
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baseURL: 'https://spec-chat.tech', // Custom base URL
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baseURL: 'https://api.svector.co.in', // Custom base URL
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timeout: 60000, // 1 minute timeout
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maxRetries: 1, // Single retry
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});

‎examples/openai-style-vision.ts‎

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