[{"_1":2,"_3":-5,"_4":-5},"loaderData",{"_5":6,"_7":8,"_9":10},"actionData","errors","root",{"_262":263,"_264":265},"routes/_app.x.$handle.$name",{"_11":12,"_13":14,"_15":-7,"_18":19,"_17":-7,"_196":-5,"_20":197,"_22":198,"_199":200,"_201":202,"_25":203,"_24":-5,"_204":-5,"_205":-5,"_206":54,"_207":208,"_209":46,"_210":-5,"_211":-5,"_212":213},"routes/_app.x.$handle.$name.code.$",{"_11":12,"_13":14,"_15":16,"_17":-7,"_18":19,"_20":21,"_22":23,"_24":-7,"_25":26,"_27":-5,"_28":-5,"_29":-5,"_30":-5,"_31":-5},"handle","roxannadejesus","name","genvideo","branchName","main","version","path","","project",{"_35":138,"_13":14,"_47":139,"_140":-5,"_141":54,"_142":143,"_144":143,"_145":146,"_147":-5,"_148":149,"_150":116,"_151":46,"_152":-5,"_153":-5,"_154":49,"_155":156,"_157":158,"_159":160,"_161":162,"_163":-5,"_164":165,"_166":165,"_167":168,"_169":168,"_170":168,"_171":165,"_172":165,"_173":174,"_175":176,"_177":178,"_179":54},"tree",[70,71,72],"file","contents",[32,33,34],"upstream","pull","ahead","behind","envVars",{"_35":64,"_13":65,"_38":66,"_40":-5,"_41":42,"_43":67,"_45":46,"_47":68,"_17":49,"_50":62,"_51":-5,"_53":54,"_55":-5,"_18":69},{"_35":57,"_13":58,"_38":59,"_40":-5,"_41":42,"_43":60,"_45":46,"_47":61,"_17":49,"_50":62,"_51":-5,"_53":54,"_55":-5,"_18":63},{"_35":36,"_13":37,"_38":39,"_40":-5,"_41":42,"_43":44,"_45":46,"_47":48,"_17":49,"_50":24,"_51":52,"_53":54,"_55":-5,"_18":56},"id","be1c4b81-a6e1-45a2-90d9-c4f7cdc047b8","README.md","fileId","f5e22d74-5fd3-11f1-8b49-1607ee4eb77e","parentId","branchId","ea3360fd-ba79-42da-8ce1-59eb3178e8e0","branchVersion",11,"latest",true,"createdAt",["D",1780549939305],0,"fileType","content","# 🎬 AI Video Studio — Tạo video quảng cáo AI\n\nỨng dụng mobile tạo video quảng cáo bằng AI cho **TikTok / Facebook / YouTube Shorts**, dùng model **Wan image-to-video** của Alibaba DashScope — tạo video **kèm giọng nói lồng tiếng + lip-sync** ngay trong một bước (không cần TTS riêng).\n\n## ✨ Tính năng\n- 📷 Tải ảnh mẫu (nhân vật / sản phẩm) làm khung hình đầu\n- 📝 Ô nhập **prompt** mô tả cảnh quay (tiếng Việt & Anh)\n- 🎙️ Ô nhập **lời thoại** → AI tự đọc bằng giọng tự nhiên, khớp khẩu hình\n- 📐 Chọn tỉ lệ khung hình: 9:16 (TikTok), 1:1 (Feed), 16:9 (YouTube)\n- ⚙️ Chọn độ phân giải (720P/1080P) & thời lượng (5s/10s)\n- 📜 Lịch sử các video đã tạo (lưu SQLite)\n- 🎨 Giao diện tối, hiện đại, tối ưu cho điện thoại\n\n## 🗺️ Kiến trúc\n\n```mermaid\nflowchart TD\n UI[\"📱 Giao diện mobile
(React)\"] -->|Up ảnh| UP[\"/api/upload
→ Blob URL public\"]\n UI -->|Prompt + Lời thoại| GEN[\"/api/generate\"]\n GEN -->|model Wan i2v + audio| DS[\"☁️ Alibaba DashScope\"]\n DS -->|task_id| GEN\n UI -->|poll mỗi 5s| ST[\"/api/status/:id\"]\n ST --> DS\n ST -->|video URL có giọng| UI\n```\n\n## 🔧 Cấu hình (Environment Variables)\n| Key | Mô tả |\n|-----|-------|\n| `DASHSCOPE_API_KEY` | API key Alibaba DashScope (bắt buộc) |\n| `DASHSCOPE_HOST` | Host API (mặc định đã set) |\n| `WAN_MODEL` | Tên model, mặc định `wan2.7-i2v`. Nếu báo \"model not found\" → đổi `wan2.5-i2v-preview` |\n\n## 📁 Cấu trúc file\n- `backend/index.ts` — HTTP server (Hono), routes API + phục vụ frontend\n- `backend/aliyun.ts` — client gọi DashScope (tạo task + poll)\n- `backend/upload.ts` — lưu ảnh upload vào Blob, tạo URL public\n- `backend/db.ts` — lưu lịch sử job (SQLite)\n- `frontend/index.html` — markup + CSS\n- `frontend/app.tsx` — ứng dụng React\n\n## ⚠️ Lưu ý\n- Tạo 1 video thường mất **1–4 phút**.\n- Ảnh upload được host công khai qua route `/file/:id` để DashScope tải về làm khung hình đầu.\n","deleted",false,"label",[37],"ca670ec3-c64a-4fb9-a26c-59086a2915da","frontend","0d609300-749d-40aa-a279-09d0419fcf8e",6,["D",1780549829389],"directory",[58],"af5470b4-595b-485a-bfb9-b4ccb88dd033","backend","e698442e-61b7-42f3-bd98-77f988abcb65",2,["D",1780549746572],[65],{"_35":64,"_13":65,"_38":66,"_40":-5,"_41":42,"_43":67,"_45":46,"_47":99,"_17":49,"_50":62,"_51":-5,"_53":54,"_55":-5,"_74":100,"_18":101},{"_35":57,"_13":58,"_38":59,"_40":-5,"_41":42,"_43":60,"_45":46,"_47":77,"_17":49,"_50":62,"_51":-5,"_53":54,"_55":-5,"_74":78,"_18":79},{"_35":36,"_13":37,"_38":39,"_40":-5,"_41":42,"_43":44,"_45":46,"_47":73,"_17":49,"_50":24,"_51":52,"_53":54,"_55":-5,"_74":75,"_18":76},["D",1780549939305],"children",[],[37],["D",1780549829389],[80,81],[58],{"_35":90,"_13":91,"_38":92,"_40":59,"_41":42,"_43":93,"_45":46,"_47":94,"_17":49,"_50":95,"_51":96,"_53":54,"_55":-5,"_74":97,"_18":98},{"_35":82,"_13":83,"_38":84,"_40":59,"_41":42,"_43":85,"_45":46,"_47":86,"_17":67,"_50":24,"_51":87,"_53":54,"_55":-5,"_74":88,"_18":89},"7687e588-99b8-406a-8532-93290cf0418f","index.html","b45e8d66-5fd3-11f1-b0f3-1607ee4eb77e",10,["D",1780549919970],"\n\n\n \n \n \n AI Video Studio · Tạo video quảng cáo\n \n \n\n\n

\n \n \n \n\n\n",[],[58,83],"52e4a203-d6b6-428d-a737-3a8b38d9ff0c","app.tsx","d4094fca-5fd3-11f1-bdc8-1607ee4eb77e",8,["D",1780549882510],"script","/** @jsxImportSource https://esm.sh/react@18.2.0 */\nimport React, { useEffect, useRef, useState } from \"https://esm.sh/react@18.2.0\";\nimport { createRoot } from \"https://esm.sh/react-dom@18.2.0/client\";\n\nconst MODEL = (window as any).__MODEL__ || \"wan-i2v\";\n\ntype Phase = \"form\" | \"uploading\" | \"generating\" | \"done\" | \"error\";\n\nconst ASPECTS = [\n { id: \"9:16\", label: \"9:16\", sub: \"Dọc · TikTok\" },\n { id: \"1:1\", label: \"1:1\", sub: \"Vuông · Feed\" },\n { id: \"16:9\", label: \"16:9\", sub: \"Ngang · YouTube\" },\n];\nconst RESOLUTIONS = [\"720P\", \"1080P\"];\nconst DURATIONS = [5, 10];\n\nasync function api(path: string, opts?: RequestInit) {\n const res = await fetch(path, opts);\n const json = await res.json().catch(() => ({}));\n if (!res.ok) throw new Error(json.error || `Lỗi ${res.status}`);\n return json;\n}\n\nfunction fileToDataUrl(file: File): Promise {\n return new Promise((resolve, reject) => {\n const r = new FileReader();\n r.onload = () => resolve(r.result as string);\n r.onerror = reject;\n r.readAsDataURL(file);\n });\n}\n\nfunction App() {\n const [imgPreview, setImgPreview] = useState(\"\");\n const [imgUrl, setImgUrl] = useState(\"\");\n const [prompt, setPrompt] = useState(\"\");\n const [dialogue, setDialogue] = useState(\"\");\n const [aspect, setAspect] = useState(\"9:16\");\n const [resolution, setResolution] = useState(\"720P\");\n const [duration, setDuration] = useState(10);\n\n const [phase, setPhase] = useState(\"form\");\n const [statusText, setStatusText] = useState(\"\");\n const [progress, setProgress] = useState(0);\n const [videoUrl, setVideoUrl] = useState(\"\");\n const [error, setError] = useState(\"\");\n const [history, setHistory] = useState([]);\n const fileRef = useRef(null);\n const pollRef = useRef(null);\n\n const loadHistory = async () => {\n try {\n const { jobs } = await api(\"/api/history\");\n setHistory(jobs || []);\n } catch { /* ignore */ }\n };\n useEffect(() => { loadHistory(); }, []);\n useEffect(() => () => { if (pollRef.current) clearInterval(pollRef.current); }, []);\n\n async function handleFile(e: React.ChangeEvent) {\n const file = e.target.files?.[0];\n if (!file) return;\n setError(\"\");\n const dataUrl = await fileToDataUrl(file);\n setImgPreview(dataUrl);\n setPhase(\"uploading\");\n setStatusText(\"Đang tải ảnh lên...\");\n try {\n const { url } = await api(\"/api/upload\", {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/json\" },\n body: JSON.stringify({ dataUrl }),\n });\n setImgUrl(url);\n setPhase(\"form\");\n setStatusText(\"\");\n } catch (err: any) {\n setError(err.message);\n setPhase(\"form\");\n }\n }\n\n function removeImage(e: React.MouseEvent) {\n e.stopPropagation();\n setImgPreview(\"\");\n setImgUrl(\"\");\n if (fileRef.current) fileRef.current.value = \"\";\n }\n\n function startProgressAnim() {\n setProgress(6);\n let p = 6;\n pollRef.current && clearInterval(pollRef.current);\n const t = setInterval(() => {\n p = Math.min(p + Math.random() * 4, 92);\n setProgress(p);\n }, 1500);\n return t;\n }\n\n async function generate() {\n setError(\"\");\n if (!imgUrl) { setError(\"Vui lòng tải ảnh mẫu trước.\"); return; }\n if (!prompt.trim() && !dialogue.trim()) {\n setError(\"Nhập mô tả cảnh (prompt) hoặc lời thoại.\");\n return;\n }\n setPhase(\"generating\");\n setVideoUrl(\"\");\n setStatusText(\"Đang khởi tạo tác vụ...\");\n const animTimer = startProgressAnim();\n\n try {\n const { taskId } = await api(\"/api/generate\", {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/json\" },\n body: JSON.stringify({ prompt, dialogue, imageUrl: imgUrl, resolution, duration, aspect }),\n });\n setStatusText(\"AI đang dựng video & lồng giọng nói...\");\n\n pollRef.current = setInterval(async () => {\n try {\n const s = await api(`/api/status/${taskId}`);\n if (s.status === \"SUCCEEDED\" && s.videoUrl) {\n clearInterval(pollRef.current!); clearInterval(animTimer);\n setProgress(100);\n setVideoUrl(s.videoUrl);\n setPhase(\"done\");\n setStatusText(\"\");\n loadHistory();\n } else if (s.status === \"FAILED\") {\n clearInterval(pollRef.current!); clearInterval(animTimer);\n setError(s.message || \"Tạo video thất bại. Thử đổi ảnh/prompt.\");\n setPhase(\"error\");\n } else {\n setStatusText(`Trạng thái: ${s.status} — vui lòng đợi (thường 1–4 phút)...`);\n }\n } catch (err: any) {\n clearInterval(pollRef.current!); clearInterval(animTimer);\n setError(err.message);\n setPhase(\"error\");\n }\n }, 5000) as unknown as number;\n } catch (err: any) {\n clearInterval(animTimer);\n setError(err.message);\n setPhase(\"error\");\n }\n }\n\n function reset() {\n setPhase(\"form\");\n setVideoUrl(\"\");\n setError(\"\");\n setProgress(0);\n setStatusText(\"\");\n }\n\n const busy = phase === \"uploading\" || phase === \"generating\";\n\n return (\n

🎬

AI Video Studio

Tạo video quảng cáo cho TikTok & Facebook

\n {MODEL}\n

\n\n {phase === \"generating\" && (\n

Đang tạo video AI 🎥

{statusText}

\n )}\n\n {phase === \"done\" && videoUrl && (\n

✅ Video đã sẵn sàng!

\n )}\n\n {error && (phase === \"error\" || phase === \"form\") && (\n

⚠️ {error}

\n )}\n\n {(phase === \"form\" || phase === \"uploading\" || phase === \"error\") && (\n <>\n

🖼️ Ảnh mẫu (khung hình đầu)

\n fileRef.current?.click()}\n >\n {imgPreview ? (\n <>\n $\"preview\"$ \n \n \n ) : (\n <>\n

📷

Chạm để tải ảnh từ máy

JPG / PNG · nhân vật hoặc sản phẩm

\n \n )}\n

\n {phase === \"uploading\" &&

⏳ {statusText}

}\n {imgUrl &&

✓ Đã tải ảnh lên thành công

}\n \n

\n\n

📝 Mô tả cảnh quay (Prompt)

\n setPrompt(e.target.value)}\n />\n

Mô tả bối cảnh, hành động, ánh sáng, phong cách. Hỗ trợ tiếng Việt & tiếng Anh.

\n\n

🎙️ Lời thoại (AI tự đọc + khớp khẩu hình)

\n setDialogue(e.target.value)}\n />\n

Model {MODEL} tự sinh giọng nói lồng vào video — không cần thu âm. Để trống nếu chỉ muốn video không lời.

\n\n

📐 Tỉ lệ khung hình

\n {ASPECTS.map((a) => (\n setAspect(a.id)}\n >\n {a.label}{a.sub}\n

\n ))}\n

\n\n

⚙️ Cấu hình

Độ phân giải

\n {RESOLUTIONS.map((r) => (\n

setResolution(r)}>{r}

\n ))}\n

Thời lượng

\n {DURATIONS.map((d) => (\n

setDuration(d)}>{d}s

\n ))}\n

\n\n {history.length > 0 && (\n <>\n

Lịch sử

\n {history.map((h) => (\n

\n $\"\"$ \n

{h.prompt || h.dialogue || \"(không mô tả)\"}

{h.resolution} · {h.duration}s · {h.aspect}

\n {h.status === \"SUCCEEDED\"\n ? Xem ▶\n : h.status === \"FAILED\"\n ? Lỗi\n : Đang xử lý}\n

\n ))}\n

\n \n )}\n\n

\n \n )}\n\n {phase !== \"generating\" && (\n

\n \n

\n )}\n

\n );\n}\n\nconst root = createRoot(document.getElementById(\"root\")!);\nroot.render();\n",[],[58,91],["D",1780549746572],[102,103,104,105],[65],{"_35":131,"_13":132,"_38":133,"_40":66,"_41":42,"_43":67,"_45":46,"_47":134,"_17":49,"_50":95,"_51":135,"_53":54,"_55":-5,"_74":136,"_18":137},{"_35":123,"_13":124,"_38":125,"_40":66,"_41":42,"_43":126,"_45":46,"_47":127,"_17":49,"_50":95,"_51":128,"_53":54,"_55":-5,"_74":129,"_18":130},{"_35":114,"_13":115,"_38":116,"_40":66,"_41":42,"_43":117,"_45":46,"_47":118,"_17":49,"_50":119,"_51":120,"_53":54,"_55":-5,"_74":121,"_18":122},{"_35":106,"_13":107,"_38":108,"_40":66,"_41":42,"_43":109,"_45":46,"_47":110,"_17":49,"_50":95,"_51":111,"_53":54,"_55":-5,"_74":112,"_18":113},"a72ae28b-9708-4937-b7a1-bfbeeba387b0","upload.ts","8ed72ddc-5fd3-11f1-9354-1607ee4eb77e",4,["D",1780549766429],"import { blob } from \"https://esm.town/v/std/blob\";\n\n// Stores an uploaded image in blob storage and returns a PUBLIC url that the\n// Aliyun API can fetch as first_frame. The public url points back at this val's\n// /file/:key route (see backend/index.ts).\n\nconst PREFIX = \"genvideo/uploads/\";\n\nexport interface StoredFile {\n key: string;\n contentType: string;\n}\n\nexport async function storeBase64(\n dataUrl: string,\n): Promise {\n // dataUrl: \"data:image/png;base64,....\"\n const m = dataUrl.match(/^data:([^;]+);base64,(.*)$/s);\n if (!m) throw new Error(\"Invalid data URL\");\n const contentType = m[1];\n const b64 = m[2];\n const bytes = Uint8Array.from(atob(b64), (c) => c.charCodeAt(0));\n const ext = contentType.split(\"/\")[1]?.split(\"+\")[0] || \"bin\";\n const id = crypto.randomUUID();\n const key = `${PREFIX}${id}.${ext}`;\n await blob.set(key, bytes);\n // store content type alongside\n await blob.setJSON(`${key}.meta`, { contentType });\n return { key, contentType };\n}\n\nexport async function readStored(\n key: string,\n): Promise<{ bytes: Uint8Array; contentType: string } | null> {\n if (!key.startsWith(PREFIX)) return null;\n try {\n const buf = await blob.get(key);\n if (!buf) return null;\n const bytes = new Uint8Array(await buf.arrayBuffer());\n let contentType = \"application/octet-stream\";\n try {\n const meta = await blob.getJSON<{ contentType: string }>(`${key}.meta`);\n if (meta?.contentType) contentType = meta.contentType;\n } catch { /* ignore */ }\n return { bytes, contentType };\n } catch {\n return null;\n }\n}\n",[],[65,107],"c274a596-45cf-4788-8246-47587cdf07fb","index.ts","9bc7b8ea-5fd3-11f1-91ec-1607ee4eb77e",5,["D",1780549788135],"http","import { Hono } from \"npm:hono\";\nimport { readFile } from \"https://esm.town/v/std/utils/index.ts\";\nimport { createTask, getTask, MODEL } from \"./aliyun.ts\";\nimport { insertJob, listJobs, updateJob } from \"./db.ts\";\nimport { readStored, storeBase64 } from \"./upload.ts\";\n\nconst app = new Hono();\napp.onError((err) => Promise.reject(err));\n\n// Build a public base url for this request (so Aliyun can fetch uploaded images)\nfunction baseUrl(req: Request) {\n const u = new URL(req.url);\n return `${u.protocol}//${u.host}`;\n}\n\n// Combine the marketing prompt + the dialogue (lời thoại) so the Wan model\n// generates a spoken voiceover with lip-sync.\nfunction buildPrompt(prompt: string, dialogue: string): string {\n const base = prompt.trim();\n if (!dialogue.trim()) return base;\n // Instruct the model to speak the dialogue as the video's voiceover.\n return `${base}\\n\\nNhân vật trong video nói rõ ràng bằng giọng tự nhiên: \"${dialogue.trim()}\". Âm thanh của video là lời thoại này, khẩu hình (lip-sync) khớp với lời nói.`;\n}\n\n// ---- Static frontend ----\napp.get(\"/\", async (c) => {\n let html = await readFile(\"/frontend/index.html\", import.meta.url);\n html = html.replace(\"{{MODEL}}\", MODEL);\n return c.html(html);\n});\n\napp.get(\"/frontend/app.tsx\", async (c) => {\n const code = await readFile(\"/frontend/app.tsx\", import.meta.url);\n return new Response(code, {\n headers: { \"Content-Type\": \"text/javascript; charset=utf-8\" },\n });\n});\n\n// Serve uploaded files so Aliyun can fetch them as a public URL.\napp.get(\"/file/:id\", async (c) => {\n const id = c.req.param(\"id\");\n const key = `genvideo/uploads/${id}`;\n const stored = await readStored(key);\n if (!stored) return c.notFound();\n return new Response(stored.bytes, {\n headers: {\n \"Content-Type\": stored.contentType,\n \"Cache-Control\": \"public, max-age=86400\",\n },\n });\n});\n\n// ---- API ----\n\n// Upload an image (data URL) -> returns a public URL.\napp.post(\"/api/upload\", async (c) => {\n try {\n const body = await c.req.json();\n const dataUrl: string = body.dataUrl;\n if (!dataUrl) return c.json({ error: \"Thiếu dataUrl\" }, 400);\n const stored = await storeBase64(dataUrl);\n const id = stored.key.replace(\"genvideo/uploads/\", \"\");\n const url = `${baseUrl(c.req.raw)}/file/${id}`;\n return c.json({ url });\n } catch (e) {\n return c.json({ error: String(e) }, 500);\n }\n});\n\n// Start a generation job.\napp.post(\"/api/generate\", async (c) => {\n try {\n const body = await c.req.json();\n const {\n prompt = \"\",\n dialogue = \"\",\n imageUrl = \"\",\n resolution = \"720P\",\n duration = 10,\n aspect = \"9:16\",\n audioUrl = \"\",\n } = body;\n\n if (!imageUrl) return c.json({ error: \"Vui lòng tải ảnh mẫu trước\" }, 400);\n if (!prompt.trim() && !dialogue.trim()) {\n return c.json({ error: \"Vui lòng nhập prompt hoặc lời thoại\" }, 400);\n }\n\n const finalPrompt = buildPrompt(prompt, dialogue);\n const task = await createTask({\n prompt: finalPrompt,\n imageUrl,\n resolution,\n duration: Number(duration),\n audioUrl: audioUrl || undefined,\n promptExtend: true,\n watermark: false,\n });\n\n await insertJob({\n task_id: task.task_id,\n prompt,\n dialogue,\n image_url: imageUrl,\n resolution,\n duration: Number(duration),\n aspect,\n status: task.task_status || \"PENDING\",\n video_url: null,\n error: null,\n created_at: Date.now(),\n });\n\n return c.json({ taskId: task.task_id, status: task.task_status });\n } catch (e) {\n return c.json({ error: String(e) }, 500);\n }\n});\n\n// Poll a job status.\napp.get(\"/api/status/:taskId\", async (c) => {\n try {\n const taskId = c.req.param(\"taskId\");\n const t = await getTask(taskId);\n const status = t.task_status;\n if (status === \"SUCCEEDED\") {\n await updateJob(taskId, { status, video_url: t.video_url ?? null });\n } else if (status === \"FAILED\") {\n await updateJob(taskId, { status, error: t.message ?? \"Tạo video thất bại\" });\n } else {\n await updateJob(taskId, { status });\n }\n return c.json({\n status,\n videoUrl: t.video_url ?? null,\n message: t.message ?? null,\n });\n } catch (e) {\n return c.json({ error: String(e) }, 500);\n }\n});\n\n// History of jobs.\napp.get(\"/api/history\", async (c) => {\n const jobs = await listJobs(30);\n return c.json({ jobs });\n});\n\nexport default app.fetch;\n",[],[65,115],"06be88bb-b8cd-4e6c-88d4-b19d4cccfe9c","db.ts","8826e55e-5fd3-11f1-bdea-1607ee4eb77e",3,["D",1780549755207],"import { sqlite } from \"https://esm.town/v/std/sqlite/main.ts\";\n\nconst TABLE = \"genvideo_jobs_v1\";\n\nexport async function initDb() {\n await sqlite.execute(`CREATE TABLE IF NOT EXISTS ${TABLE} (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n task_id TEXT UNIQUE,\n prompt TEXT,\n dialogue TEXT,\n image_url TEXT,\n resolution TEXT,\n duration INTEGER,\n aspect TEXT,\n status TEXT,\n video_url TEXT,\n error TEXT,\n created_at INTEGER\n )`);\n}\n\nexport interface JobRow {\n id: number;\n task_id: string;\n prompt: string;\n dialogue: string;\n image_url: string;\n resolution: string;\n duration: number;\n aspect: string;\n status: string;\n video_url: string | null;\n error: string | null;\n created_at: number;\n}\n\nexport async function insertJob(j: Omit) {\n await initDb();\n await sqlite.execute({\n sql:\n `INSERT INTO ${TABLE} (task_id, prompt, dialogue, image_url, resolution, duration, aspect, status, video_url, error, created_at)\n VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)`,\n args: [\n j.task_id,\n j.prompt,\n j.dialogue,\n j.image_url,\n j.resolution,\n j.duration,\n j.aspect,\n j.status,\n j.video_url,\n j.error,\n j.created_at,\n ],\n });\n}\n\nexport async function updateJob(\n taskId: string,\n patch: { status?: string; video_url?: string | null; error?: string | null },\n) {\n await initDb();\n const sets: string[] = [];\n const args: (string | null)[] = [];\n if (patch.status !== undefined) {\n sets.push(\"status = ?\");\n args.push(patch.status);\n }\n if (patch.video_url !== undefined) {\n sets.push(\"video_url = ?\");\n args.push(patch.video_url);\n }\n if (patch.error !== undefined) {\n sets.push(\"error = ?\");\n args.push(patch.error);\n }\n if (!sets.length) return;\n args.push(taskId);\n await sqlite.execute({\n sql: `UPDATE ${TABLE} SET ${sets.join(\", \")} WHERE task_id = ?`,\n args,\n });\n}\n\nexport async function listJobs(limit = 20): Promise {\n await initDb();\n const res = await sqlite.execute({\n sql: `SELECT * FROM ${TABLE} ORDER BY created_at DESC LIMIT ?`,\n args: [limit],\n });\n return res.rows as unknown as JobRow[];\n}\n",[],[65,124],"9eb054b4-d530-48f0-a99d-2300beea6aab","aliyun.ts","83049274-5fd3-11f1-85f7-1607ee4eb77e",["D",1780549746572],"// Aliyun DashScope Wan image-to-video (with native audio) client.\n// Docs pattern: POST async task -> poll task_id until SUCCEEDED.\n\nconst HOST = Deno.env.get(\"DASHSCOPE_HOST\") ||\n \"ws-t016nv3snw0xntrt.ap-southeast-1.maas.aliyuncs.com\";\nconst API_KEY = Deno.env.get(\"DASHSCOPE_API_KEY\") || \"\";\nconst BASE = `https://${HOST}/api/v1`;\n\n// Model is configurable. The key you provided targets this model. If the API\n// returns \"model not found\", change this to \"wan2.5-i2v-preview\".\nexport const MODEL = Deno.env.get(\"WAN_MODEL\") || \"wan2.7-i2v\";\n\nexport interface GenerateParams {\n prompt: string;\n imageUrl: string; // public URL for first_frame\n resolution?: string; // e.g. \"720P\", \"1080P\"\n duration?: number; // seconds\n audioUrl?: string; // optional driving_audio; if omitted model generates voice\n promptExtend?: boolean;\n watermark?: boolean;\n}\n\nexport interface TaskCreated {\n task_id: string;\n task_status: string;\n}\n\nfunction authHeaders(extra: Record = {}) {\n return {\n \"Authorization\": `Bearer ${API_KEY}`,\n \"Content-Type\": \"application/json\",\n ...extra,\n };\n}\n\n/** Create an async video-generation task. Returns the task_id. */\nexport async function createTask(p: GenerateParams): Promise {\n const media: Array<{ type: string; url: string }> = [\n { type: \"first_frame\", url: p.imageUrl },\n ];\n if (p.audioUrl) media.push({ type: \"driving_audio\", url: p.audioUrl });\n\n const body = {\n model: MODEL,\n input: {\n prompt: p.prompt,\n media,\n },\n parameters: {\n resolution: p.resolution ?? \"720P\",\n duration: p.duration ?? 10,\n prompt_extend: p.promptExtend ?? true,\n watermark: p.watermark ?? false,\n },\n };\n\n const res = await fetch(\n `${BASE}/services/aigc/video-generation/video-synthesis`,\n {\n method: \"POST\",\n headers: authHeaders({ \"X-DashScope-Async\": \"enable\" }),\n body: JSON.stringify(body),\n },\n );\n\n const json = await res.json().catch(() => ({}));\n if (!res.ok) {\n throw new Error(\n `DashScope create task failed (${res.status}): ${JSON.stringify(json)}`,\n );\n }\n const output = json.output ?? {};\n if (!output.task_id) {\n throw new Error(\n 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