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// index.js
import { pipeline } from 'https://cdn.jsdelivr.net/npm/@xenova/transformers';
// Define available models (mirror of constants.py AVAILABLE_MODELS)
const AVAILABLE_MODELS = [
{ name: "Moonshot Kimi-K2", id: "moonshotai/Kimi-K2-Instruct" },
{ name: "DeepSeek V3", id: "deepseek-ai/DeepSeek-V3-0324" },
{ name: "DeepSeek R1", id: "deepseek-ai/DeepSeek-R1-0528" },
{ name: "ERNIE-4.5-VL", id: "baidu/ERNIE-4.5-VL-424B-A47B-Base-PT" },
{ name: "MiniMax M1", id: "MiniMaxAI/MiniMax-M1-80k" },
{ name: "Qwen3-235B-A22B", id: "Qwen/Qwen3-235B-A22B" },
{ name: "SmolLM3-3B", id: "HuggingFaceTB/SmolLM3-3B" },
{ name: "GLM-4.1V-9B-Thinking", id: "THUDM/GLM-4.1V-9B-Thinking" },
{ name: "Qwen3-235B-A22B-Instruct-2507", id: "Qwen/Qwen3-235B-A22B-Instruct-2507" },
{ name: "Qwen3-Coder-480B-A35B", id: "Qwen/Qwen3-Coder-480B-A35B-Instruct" }
];
const analyzeForm = document.getElementById('analyze-form');
const modelSelect = document.getElementById('modelSelect');
const inputText = document.getElementById('inputText');
const resultSection = document.getElementById('result');
const analyzeButton = document.getElementById('analyzeButton');
let sentimentPipeline;
// Populate model dropdown
AVAILABLE_MODELS.forEach(model => {
const opt = document.createElement('option');
opt.value = model.id;
opt.textContent = model.name;
modelSelect.appendChild(opt);
});
async function initPipeline(modelId) {
analyzeButton.disabled = true;
analyzeButton.textContent = 'Loading model...';
sentimentPipeline = await pipeline('sentiment-analysis', modelId);
analyzeButton.textContent = 'Analyze Sentiment';
analyzeButton.disabled = false;
}
// Initialize with first model
initPipeline(modelSelect.value);
// Re-init pipeline on model change
modelSelect.addEventListener('change', () => {
initPipeline(modelSelect.value);
resultSection.textContent = '';
});
analyzeForm.addEventListener('submit', async event => {
event.preventDefault();
const text = inputText.value.trim();
if (!text) return;
analyzeButton.disabled = true;
analyzeButton.textContent = 'Analyzing...';
resultSection.textContent = '';
try {
const output = await sentimentPipeline(text);
const { label, score } = output[0];
resultSection.textContent = `Sentiment: ${label} (Confidence: ${(score * 100).toFixed(2)}%)`;
} catch (err) {
resultSection.textContent = 'Error analyzing sentiment.';
}
analyzeButton.textContent = 'Analyze Sentiment';
analyzeButton.disabled = false;
}); |