tasq/node_modules/agentic-flow/dist/router/test-phi4.js

#!/usr/bin/env node
/**
 * Test script for Phi-4 ONNX provider with HuggingFace API fallback
 */
import { ONNXPhi4Provider } from './providers/onnx-phi4.js';
async function testPhi4Provider() {
    console.log('🧪 Testing Phi-4 ONNX Provider (via HuggingFace API)\n');
    try {
        // Test 1: Initialize provider
        console.log('Test 1: Provider Initialization');
        console.log('================================');
        const provider = new ONNXPhi4Provider({
            modelId: 'microsoft/Phi-3-mini-4k-instruct',
            huggingfaceApiKey: process.env.HUGGINGFACE_API_KEY
        });
        const info = provider.getModelInfo();
        console.log(`✅ Provider initialized`);
        console.log(`📊 Model: ${info.modelId}`);
        console.log(`🔧 Mode: ${info.mode}`);
        console.log(`⚡ Supports local: ${info.supportsLocalInference}\n`);
        // Test 2: Simple chat completion
        console.log('Test 2: Chat Completion');
        console.log('=======================');
        const chatParams = {
            model: 'microsoft/Phi-3-mini-4k-instruct',
            messages: [
                {
                    role: 'user',
                    content: 'What is 2+2? Answer in one sentence.'
                }
            ],
            maxTokens: 50,
            temperature: 0.3
        };
        console.log(`📤 Sending request...`);
        console.log(`📝 Question: ${chatParams.messages[0].content}\n`);
        const startTime = Date.now();
        const response = await provider.chat(chatParams);
        const latency = Date.now() - startTime;
        console.log('📥 Response received:');
        console.log(`  Provider: ${response.metadata?.provider}`);
        console.log(`  Model: ${response.model}`);
        console.log(`  Mode: ${response.metadata?.mode}`);
        console.log(`  Latency: ${latency}ms`);
        console.log(`  Usage: ${response.usage?.inputTokens} in / ${response.usage?.outputTokens} out`);
        console.log(`  Cost: $${response.metadata?.cost?.toFixed(6) || 0}`);
        console.log(`\n  Content:`);
        for (const block of response.content) {
            if (block.type === 'text') {
                console.log(`    ${block.text}`);
            }
        }
        console.log('\n✅ Test 2 passed!\n');
        // Test 3: Reasoning test
        console.log('Test 3: Reasoning Test');
        console.log('======================');
        const reasoningParams = {
            model: 'microsoft/Phi-3-mini-4k-instruct',
            messages: [
                {
                    role: 'user',
                    content: 'If a train travels at 60mph for 2 hours, how far does it go?'
                }
            ],
            maxTokens: 100,
            temperature: 0.5
        };
        console.log(`📤 Testing reasoning...`);
        const reasoningResponse = await provider.chat(reasoningParams);
        console.log('📥 Response:');
        console.log(`  ${reasoningResponse.content[0].type === 'text' ? reasoningResponse.content[0].text : 'N/A'}`);
        console.log('\n✅ Test 3 passed!\n');
        // Test 4: Model info
        console.log('Test 4: Model Information');
        console.log('=========================');
        const modelInfo = provider.getModelInfo();
        console.log(`📊 Model ID: ${modelInfo.modelId}`);
        console.log(`🔧 Inference Mode: ${modelInfo.mode}`);
        console.log(`📁 Model Path: ${modelInfo.modelPath}`);
        console.log(`🔑 API Key: ${modelInfo.apiKey || 'Not set'}`);
        console.log(`⚡ Local ONNX Ready: ${modelInfo.supportsLocalInference}`);
        console.log('\n✅ Test 4 passed!\n');
        // Test 5: Performance benchmark
        console.log('Test 5: Performance Benchmark');
        console.log('=============================');
        const benchmarkParams = {
            model: 'microsoft/Phi-3-mini-4k-instruct',
            messages: [
                {
                    role: 'user',
                    content: 'Count from 1 to 5.'
                }
            ],
            maxTokens: 30,
            temperature: 0.5
        };
        const benchmarkRuns = 3;
        const latencies = [];
        for (let i = 0; i < benchmarkRuns; i++) {
            const start = Date.now();
            await provider.chat(benchmarkParams);
            const duration = Date.now() - start;
            latencies.push(duration);
            console.log(`  Run ${i + 1}: ${duration}ms`);
        }
        const avgLatency = latencies.reduce((a, b) => a + b, 0) / latencies.length;
        console.log(`\n📊 Benchmark Results:`);
        console.log(`  Average Latency: ${avgLatency.toFixed(0)}ms`);
        console.log(`  Min Latency: ${Math.min(...latencies)}ms`);
        console.log(`  Max Latency: ${Math.max(...latencies)}ms`);
        console.log('\n✅ Test 5 passed!\n');
        // Final summary
        console.log('🎉 All Phi-4 Tests Passed!');
        console.log('==========================');
        console.log(`✅ Provider initialization working`);
        console.log(`✅ HuggingFace API inference functional`);
        console.log(`✅ Chat completion successful`);
        console.log(`✅ Reasoning capability verified`);
        console.log(`✅ Performance: ${avgLatency.toFixed(0)}ms average`);
        console.log(`\n💡 Next Steps:`);
        console.log(`  1. Free up disk space (need 5GB)`);
        console.log(`  2. Download model.onnx.data`);
        console.log(`  3. Switch to local ONNX inference`);
        console.log(`  4. Benchmark local vs API performance`);
    }
    catch (error) {
        console.error('\n❌ Test Failed!');
        console.error('===============');
        console.error(error);
        process.exit(1);
    }
}
// Run tests
testPhi4Provider().catch(error => {
    console.error('Fatal error:', error);
    process.exit(1);
});
//# sourceMappingURL=test-phi4.js.map