feat: Add complete Agentic Compaction & Pipeline System
- Context Compaction System with token counting and summarization - Deterministic State Machine for flow control (no LLM decisions) - Parallel Execution Engine (up to 12 concurrent sessions) - Event-Driven Coordination via Event Bus - Agent Workspace Isolation (tools, memory, identity, files) - YAML Workflow Integration (OpenClaw/Lobster compatible) - Claude Code integration layer - Complete demo UI with real-time visualization - Comprehensive documentation and README Components: - agent-system/: Context management, token counting, subagent spawning - pipeline-system/: State machine, parallel executor, event bus, workflows - skills/: AI capabilities (LLM, ASR, TTS, VLM, image generation, etc.) - src/app/: Next.js demo application Total: ~100KB of production-ready TypeScript code
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Z User
168
skills/video-generation/scripts/video.ts
Executable file
168
skills/video-generation/scripts/video.ts
Executable file
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import ZAI from "z-ai-web-dev-sdk";
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import fs from "fs";
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async function create() {
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try {
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const zai = await ZAI.create();
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console.log("Creating video generation task...");
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const task = await zai.video.generations.create({
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prompt: "A cat is playing with a ball.",
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quality: "speed",
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with_audio: false,
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size: "1920x1080",
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fps: 30,
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duration: 5,
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});
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console.log(`Task created!`);
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console.log(`Task ID: ${task.id}`);
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console.log(`Task Status: ${task.task_status}`);
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console.log(`Model: ${task.model || 'N/A'}`);
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return { zai, task };
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} catch (err: any) {
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console.error("Video generation failed:", err?.message || err);
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throw err;
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}
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}
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/**
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* Example: Image-to-Video Generation using base64
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* IMPORTANT: Using base64-encoded image data is STRONGLY RECOMMENDED over URLs
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* for better reliability and to avoid network-related issues.
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*
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* CRITICAL: Always match the MIME type to your actual image format.
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*/
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async function createFromImage(imagePath: string) {
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try {
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const zai = await ZAI.create();
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console.log("Creating image-to-video generation task...");
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console.log(`Reading image from: ${imagePath}`);
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// Read image file and convert to base64
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const imageBuffer = fs.readFileSync(imagePath);
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// Detect MIME type from file extension
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const imageExt = imagePath.split('.').pop()?.toLowerCase() || '';
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const mimeTypeMap: Record<string, string> = {
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'jpg': 'image/jpeg',
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'jpeg': 'image/jpeg',
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'png': 'image/png',
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'gif': 'image/gif',
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'webp': 'image/webp',
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'bmp': 'image/bmp'
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};
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const mimeType = mimeTypeMap[imageExt] || 'image/jpeg'; // Default to JPEG if unknown
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const base64Image = `data:${mimeType};base64,${imageBuffer.toString('base64')}`;
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console.log(`Image format detected: ${mimeType}`);
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console.log(`Image converted to base64 (${base64Image.substring(0, 50)}...)`);
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// Create video generation task with base64 image
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const task = await zai.video.generations.create({
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image_url: base64Image, // Use base64 with correct MIME type
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prompt: "Animate this scene with gentle motion",
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quality: "quality",
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size: "1920x1080",
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fps: 30,
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duration: 5,
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});
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console.log(`Task created!`);
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console.log(`Task ID: ${task.id}`);
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console.log(`Task Status: ${task.task_status}`);
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console.log(`Model: ${task.model || 'N/A'}`);
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return { zai, task };
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} catch (err: any) {
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console.error("Image-to-video generation failed:", err?.message || err);
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throw err;
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}
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}
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async function query(zai: any, taskId: string) {
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try {
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// 首次查询
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let result = await zai.async.result.query(taskId);
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if (result.task_status === 'SUCCESS') {
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// 如果任务立即完成，直接返回结果
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console.log("\nTask completed immediately, fetching result...");
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displayResult(result);
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return result;
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}
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// 轮询查询结果
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console.log("\nPolling for result...");
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let pollCount = 0;
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const maxPolls = 30; // 最多轮询30次
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const pollInterval = 10000; // 每10秒查询一次
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while (result.task_status === 'PROCESSING' && pollCount < maxPolls) {
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pollCount++;
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console.log(`Poll ${pollCount}/${maxPolls}: Status is ${result.task_status}, waiting ${pollInterval / 1000}s...`);
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await new Promise(resolve => setTimeout(resolve, pollInterval));
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result = await zai.async.result.query(taskId);
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}
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displayResult(result);
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return result;
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} catch (err: any) {
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console.error("Query failed:", err?.message || err);
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throw err;
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}
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}
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async function main() {
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try {
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// Method 1: Text-to-Video (default)
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const { zai, task } = await create();
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// Method 2: Image-to-Video with base64 (RECOMMENDED for image input)
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// Uncomment the lines below and comment out the lines above to use image-to-video
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// Make sure to provide a valid image path
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// const { zai, task } = await createFromImage('./path/to/your/image.jpg');
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await query(zai, task.id);
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} catch (err: any) {
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console.error("Video generation failed:", err?.message || err);
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process.exit(1);
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}
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}
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function displayResult(result: any) {
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console.log("\n=== Result ===");
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console.log(`Task Status: ${result.task_status}`);
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console.log(`Model: ${result.model || 'N/A'}`);
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console.log(`Request ID: ${result.request_id || 'N/A'}`);
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if (result.task_status === 'SUCCESS') {
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// 尝试从多种可能的字段中获取视频URL
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const videoUrl =
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result.video_result?.[0]?.url ||
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result.video_url ||
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result.url ||
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result.video;
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if (videoUrl) {
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console.log(`\n✅ Video generated successfully!`);
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console.log(`Video URL: ${videoUrl}`);
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console.log(`\nYou can open this URL in your browser or download it.`);
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} else {
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console.log(`\n⚠️ Task completed but video URL not found in response.`);
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console.log(`Full response:`, JSON.stringify(result, null, 2));
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}
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} else if (result.task_status === 'PROCESSING') {
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console.log(`\n⏳ Task is still processing. Please try again later.`);
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console.log(`Task ID: ${result.id || 'N/A'}`);
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} else if (result.task_status === 'FAIL') {
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console.log(`\n❌ Task failed.`);
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console.log(`Full response:`, JSON.stringify(result, null, 2));
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}
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}
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main();
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