Merge branch 'main' into feat/cli-skill-sync

chore(release): prepare 1.15.1

.github/workflows/publish-skills.yml

@@ -0,0 +1,27 @@
+# Poke the FC publish-skills flow after skills/ changes land.
+# The FC side reconciles this repo's skills/ directory against OSS
+# (bailian-wiki/skills/) using the repo HEAD snapshot as the only
+# source of truth — the request itself carries no content. Both the
+# repo and branch params are validated against FC-side whitelists
+# (PUBLISH_REPOS / PUBLISH_BRANCHES).
+#
+# feat/cli-skill-sync is temporary for end-to-end testing; remove it
+# (here and from the FC PUBLISH_BRANCHES whitelist) once the sync
+# link is verified on main.
+name: Publish skills to OSS
+
+on:
+  push:
+    branches:
+      - main
+      - feat/cli-skill-sync
+    paths:
+      - "skills/**"
+
+jobs:
+  poke:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Trigger FC publish-skills
+        run: |
+          curl -sf -X POST "${{ vars.FC_TRIGGER_URL }}/publish-skills?repo=modelstudioai/cli&branch=${{ github.ref_name }}"

CHANGELOG.md

@@ -6,6 +6,19 @@ The format follows [Keep a Changelog](https://keepachangelog.com/en/1.1.0/), and
 
 [中文版](CHANGELOG.zh.md) · [README](README.md) · [Contributing](CONTRIBUTING.md)
 
+## [1.15.1] - 2026-08-17
+
+### Added
+
+- **Model permission management** — `bl permission list` shows per-model inference / fine-tune / deploy grants; `bl permission grant` and `bl permission revoke` manage them, with `--all` to one-key grant inference for every model in the workspace (including future ones).
+
+### Changed
+
+- **`bl quota request` renamed to `bl quota update`** — set per-model QPM/TPM via `--rpm`/`--tpm` and clear custom limits with the new `--delete`; omitted fields keep their current values, and the old `quota request` path keeps working as an alias.
+- **`bl quota list` reworked** — now reads the model-limits API and shows per-model and workspace-level request/usage limits plus async queue/concurrency limits in a single table.
+- **`bl model list` no longer requires Console login** — the model catalog and `--enrich` parameter-schema endpoints are public.
+- **`bl skill init` output simplified** — per-skill status is now `success`/`failed` (previously `installed`) with an aggregate `success`/`partial`/`failed` result; the `publishedAt` and `agents` fields were removed.
+
 ## [1.15.0] - 2026-08-14
 
 ### Added

CHANGELOG.zh.md

@@ -6,6 +6,19 @@
 
 [English](CHANGELOG.md) · [README](README.zh.md) · [参与贡献](CONTRIBUTING.zh.md)
 
+## [1.15.1] - 2026-08-17
+
+### 新增
+
+- **模型权限管理** —— `bl permission list` 查看各模型的推理 / 微调 / 部署授权；`bl permission grant` 与 `bl permission revoke` 负责授予和回收，支持 `--all` 一键为工作区全部模型（含后续新增模型）开启推理授权。
+
+### 变更
+
+- **`bl quota request` 更名为 `bl quota update`** —— 通过 `--rpm`/`--tpm` 设置单模型 QPM/TPM，新增 `--delete` 一键清除自定义限制；未指定的字段保持当前值，旧命令 `quota request` 仍作为别名可用。
+- **`bl quota list` 重构** —— 改从模型限制接口读取数据，单表展示模型级与工作区级的请求/用量限制及异步队列/并发限制。
+- **`bl model list` 不再需要控制台登录** —— 模型目录与 `--enrich` 参数结构端点均为公开接口。
+- **`bl skill init` 输出精简** —— 单技能状态改为 `success`/`failed`（原为 `installed`），新增 `success`/`partial`/`failed` 汇总结果；移除 `publishedAt` 与 `agents` 字段。
+
 ## [1.15.0] - 2026-08-14
 
 ### 新增

packages/cli/package.json

@@ -1,6 +1,6 @@
 {
   "name": "bailian-cli",
-  "version": "1.15.0",
+  "version": "1.15.1",
   "description": "CLI for Aliyun Model Studio (DashScope) AI Platform.",
   "keywords": [
     "agent",

packages/cli/src/commands.ts

@@ -67,6 +67,7 @@ import {
   finetuneTextCreate,
   finetuneAudioCreate,
   finetuneImageCreate,
+  finetuneVideoCreate,
   finetuneList,
   finetuneGet,
   finetuneCancel,
@@ -76,6 +77,7 @@ import {
   finetuneExport,
   finetuneWatch,
   finetuneCapability,
+  finetunePrice,
   deployTextCreate,
   deployAudioCreate,
   deployImageCreate,
@@ -85,6 +87,8 @@ import {
   deployScale,
   deployUpdate,
   deployDelete,
+  deployPause,
+  deployResume,
   tokenPlanListSeats,
   tokenPlanCreateKey,
   tokenPlanAssignSeats,
@@ -191,6 +195,7 @@ export const commands: Record<string, AnyCommand> = {
   "finetune text create": finetuneTextCreate,
   "finetune audio create": finetuneAudioCreate,
   "finetune image create": finetuneImageCreate,
+  "finetune video create": finetuneVideoCreate,
   "finetune list": finetuneList,
   "finetune get": finetuneGet,
   "finetune cancel": finetuneCancel,
@@ -200,6 +205,7 @@ export const commands: Record<string, AnyCommand> = {
   "finetune export": finetuneExport,
   "finetune watch": finetuneWatch,
   "finetune capability": finetuneCapability,
+  "finetune price": finetunePrice,
   "deploy text create": deployTextCreate,
   "deploy audio create": deployAudioCreate,
   "deploy image create": deployImageCreate,
@@ -209,6 +215,8 @@ export const commands: Record<string, AnyCommand> = {
   "deploy scale": deployScale,
   "deploy update": deployUpdate,
   "deploy delete": deployDelete,
+  "deploy pause": deployPause,
+  "deploy resume": deployResume,
   "token-plan list-seats": tokenPlanListSeats,
   "token-plan create-key": tokenPlanCreateKey,
   "token-plan assign-seats": tokenPlanAssignSeats,

packages/commands/package.json

@@ -1,6 +1,6 @@
 {
   "name": "bailian-cli-commands",
-  "version": "1.15.0",
+  "version": "1.15.1",
   "description": "Command library for bailian-cli products (knowledge, memory, media, …). See https://www.npmjs.com/package/bailian-cli for usage.",
   "homepage": "https://bailian.console.aliyun.com/cli",
   "bugs": {

packages/commands/src/commands/dataset/delete.ts

@@ -1,5 +1,5 @@
-import { defineCommand, detectOutputFormat, deleteDataset, type FlagsDef } from "bailian-cli-core";
-import { emitResult, emitBare, emitRequestId } from "bailian-cli-runtime";
+import { defineCommand, deleteDataset, type FlagsDef } from "bailian-cli-core";
+import { emitResult, emitBare } from "bailian-cli-runtime";
 
 const DELETE_FLAGS = {
   fileId: {
@@ -19,20 +19,18 @@ export default defineCommand({
   async run(ctx) {
     const { settings, flags } = ctx;
     const fileId = flags.fileId;
-    const format = detectOutputFormat(settings.output);
 
     if (settings.dryRun) {
-      emitResult({ action: "dataset.delete", file_id: fileId }, format);
+      emitResult({ action: "dataset.delete", file_id: fileId }, "json");
       return;
     }
 
     const response = await deleteDataset(ctx.client, fileId);
 
-    if (settings.quiet || format === "text") {
-      emitBare(`Deleted ${fileId}.`);
-      emitRequestId(response.request_id, settings.quiet);
+    if (settings.quiet) {
+      emitBare(fileId);
     } else {
-      emitResult(response, format);
+      emitResult(response, "json");
     }
   },
 });

packages/commands/src/commands/dataset/get.ts

@@ -1,5 +1,5 @@
-import { defineCommand, detectOutputFormat, getDataset, type FlagsDef } from "bailian-cli-core";
-import { emitResult, emitBare, emitRequestId } from "bailian-cli-runtime";
+import { defineCommand, getDataset, type FlagsDef } from "bailian-cli-core";
+import { emitResult, emitBare } from "bailian-cli-runtime";
 
 const GET_FLAGS = {
   fileId: {
@@ -19,10 +19,9 @@ export default defineCommand({
   async run(ctx) {
     const { settings, flags } = ctx;
     const fileId = flags.fileId;
-    const format = detectOutputFormat(settings.output);
 
     if (settings.dryRun) {
-      emitResult({ action: "dataset.get", file_id: fileId }, format);
+      emitResult({ action: "dataset.get", file_id: fileId }, "json");
       return;
     }
 
@@ -45,19 +44,10 @@ export default defineCommand({
       description: file.description ?? "",
     };
 
-    if (format === "json") {
-      emitResult({ ...item, request_id: response.request_id }, format);
-      return;
+    if (settings.quiet) {
+      emitBare(item.file_id);
+    } else {
+      emitResult({ ...item, request_id: response.request_id }, "json");
     }
-
-    // text / quiet
-    emitBare(`file_id:      ${item.file_id}`);
-    emitBare(`name:         ${item.name}`);
-    emitBare(`size:         ${item.size}`);
-    if (item.md5) emitBare(`md5:          ${item.md5}`);
-    if (item.purpose) emitBare(`purpose:      ${item.purpose}`);
-    if (item.created_at) emitBare(`created_at:   ${item.created_at}`);
-    if (item.description) emitBare(`description:  ${item.description}`);
-    emitRequestId(response.request_id, settings.quiet);
   },
 });

packages/commands/src/commands/dataset/list.ts

@@ -1,5 +1,5 @@
-import { defineCommand, detectOutputFormat, listDatasets, type FlagsDef } from "bailian-cli-core";
-import { emitResult, emitBare, emitRequestId, formatTable } from "bailian-cli-runtime";
+import { defineCommand, listDatasets, type FlagsDef } from "bailian-cli-core";
+import { emitResult, emitBare } from "bailian-cli-runtime";
 
 const LIST_FLAGS = {
   page: { type: "number", valueHint: "<n>", description: "Page number (default: 1)" },
@@ -23,7 +23,6 @@ export default defineCommand({
   exampleArgs: ["", "--purpose fine-tune", "--purpose evaluation --page-size 20", "--output json"],
   async run(ctx) {
     const { settings, flags } = ctx;
-    const format = detectOutputFormat(settings.output);
 
     if (settings.dryRun) {
       emitResult(
@@ -33,7 +32,7 @@ export default defineCommand({
           page_size: flags.pageSize,
           purpose: flags.purpose,
         },
-        format,
+        "json",
       );
       return;
     }
@@ -46,7 +45,6 @@ export default defineCommand({
     const files = response.data?.files ?? [];
     const total = response.data?.total;
 
-    // Normalize to consistent structure for both text/json output.
     const items = files.map((item) => ({
       file_id: item.file_id ?? "",
       name: item.name ?? "",
@@ -54,20 +52,10 @@ export default defineCommand({
       purpose: item.purpose ?? "",
     }));
 
-    if (format === "json") {
-      emitResult({ items, total, request_id: response.request_id }, format);
-      return;
+    if (settings.quiet) {
+      for (const item of items) emitBare(item.file_id);
+    } else {
+      emitResult({ items, total, request_id: response.request_id }, "json");
     }
-
-    // text / quiet
-    if (items.length === 0) {
-      emitBare("No dataset files found.");
-      return;
-    }
-    const headers = ["FILE_ID", "NAME", "SIZE", "PURPOSE"];
-    const rows = items.map((i) => [i.file_id, i.name, i.size, i.purpose]);
-    for (const line of formatTable(headers, rows)) emitBare(line);
-    if (total !== undefined) emitBare(`\nTotal: ${total}`);
-    emitRequestId(response.request_id, settings.quiet);
   },
 });

packages/commands/src/commands/dataset/upload.ts

@@ -1,23 +1,23 @@
 import {
   defineCommand,
-  detectOutputFormat,
   uploadDataset,
   validateDataset,
   parseDatasetSchemaFlag,
   formatIssue,
   MAX_DATASET_BYTES,
+  MAX_CPT_BYTES,
   MAX_MEDIA_ZIP_BYTES,
   BailianError,
   ExitCode,
   type FlagsDef,
 } from "bailian-cli-core";
-import { emitResult, emitBare, emitRequestId } from "bailian-cli-runtime";
+import { emitResult, emitBare } from "bailian-cli-runtime";
 
 const UPLOAD_FLAGS = {
   file: {
     type: "string",
     valueHint: "<path>",
-    description: "Local dataset file (.jsonl or .zip; ≤300MB text, ≤1GB image)",
+    description: "Local dataset file (.jsonl or .zip; ≤200MB SFT/DPO, ≤300MB CPT, ≤2GB media zip)",
     required: true,
   },
   purpose: {
@@ -29,7 +29,7 @@ const UPLOAD_FLAGS = {
     type: "string",
     valueHint: "<s>",
     description:
-      'Record schema: "chatml" (SFT), "dpo" (chosen/rejected), "cpt" (raw text), "tts" (audio), or "image" (image generation). Default auto-detects per record.',
+      'Record schema: "chatml" (SFT), "dpo" (chosen/rejected), "cpt" (raw text), "tts" (audio), "image" (image generation), or "video" (video generation). Default auto-detects per record.',
   },
   noValidate: {
     type: "switch",
@@ -45,7 +45,7 @@ export default defineCommand({
   description: "Upload a dataset file (.jsonl or .zip) to Bailian",
   auth: "apiKey",
   usageArgs:
-    "--file <path> [--purpose <name>] [--schema <chatml|dpo|cpt|tts|image>] [--no-validate] [--full-validate]",
+    "--file <path> [--purpose <name>] [--schema <chatml|dpo|cpt|tts|image|video>] [--no-validate] [--full-validate]",
   flags: UPLOAD_FLAGS,
   exampleArgs: [
     "--file train.jsonl",
@@ -58,13 +58,14 @@ export default defineCommand({
   ],
   notes: [
     "Supports .jsonl (text) and .zip (audio/image archives with a data.jsonl",
-    "manifest). Five record schemas are recognized: chatml = {messages:[...]}",
+    "manifest). Six record schemas are recognized: chatml = {messages:[...]}",
     '(SFT); dpo = {messages:[...], chosen, rejected}; cpt = {text:"..."}',
     '(continual pre-training, raw text); tts = {wav_fn:"train/xxx.wav",',
     'text:"..."} (audio fine-tuning); image = {img_path:"..."} (image',
-    "generation). With no --schema, a record carrying wav_fn is validated as",
-    "TTS, img_path as image, chosen/rejected as DPO, text (no messages) as CPT,",
-    "otherwise ChatML. Upload cap: 300MB text, 1GB image. Upload uses the",
+    "generation); video = {first_frame_path:...} (video generation). With no",
+    "--schema, a record carrying wav_fn is validated as TTS, img_path as image,",
+    "chosen/rejected as DPO, text (no messages) as CPT, otherwise ChatML.",
+    "Upload cap: 200MB SFT/DPO text, 300MB CPT, 2GB media zip. Upload uses the",
     "OpenAI-compatible /compatible-mode/v1/files endpoint so the purpose tag is",
     "persisted (the DashScope-native /api/v1/files drops it).",
   ],
@@ -73,19 +74,15 @@ export default defineCommand({
     const filePath = flags.file;
     const purpose = flags.purpose || "fine-tune";
     const schema = parseDatasetSchemaFlag(flags.schema);
-    if (schema === "video") {
-      throw new BailianError(
-        `--schema video is not supported.`,
-        ExitCode.USAGE,
-        `Supported schemas: chatml, dpo, cpt, tts, image.`,
-      );
-    }
-    const format = detectOutputFormat(settings.output);
-    // Image schema allows larger ZIPs (1 GB vs 300 MB for text).
-    const isMediaSchema = schema === "image";
+    // Size caps differ per training type: SFT/DPO 200MB, CPT 300MB, media ZIP 2GB.
+    const isMediaSchema = schema === "image" || schema === "video";
+    const maxBytes = isMediaSchema
+      ? MAX_MEDIA_ZIP_BYTES
+      : schema === "cpt"
+        ? MAX_CPT_BYTES
+        : MAX_DATASET_BYTES;
 
     if (!flags.noValidate) {
-      const maxBytes = isMediaSchema ? MAX_MEDIA_ZIP_BYTES : MAX_DATASET_BYTES;
       const result = await validateDataset(filePath, {
         fullValidate: flags.fullValidate,
         schema,
@@ -125,11 +122,11 @@ export default defineCommand({
           action: "dataset.upload",
           file: filePath,
           purpose,
-          max_bytes: isMediaSchema ? MAX_MEDIA_ZIP_BYTES : MAX_DATASET_BYTES,
+          max_bytes: maxBytes,
           validate: !flags.noValidate,
           schema: schema ?? "auto",
         },
-        format,
+        "json",
       );
       return;
     }
@@ -142,11 +139,8 @@ export default defineCommand({
 
     if (settings.quiet) {
       emitBare(file.file_id);
-    } else if (format === "text") {
-      emitBare(`Uploaded ${file.name} → file_id=${file.file_id}`);
-      emitRequestId(request_id, settings.quiet);
     } else {
-      emitResult({ ...file, request_id }, format);
+      emitResult({ ...file, request_id }, "json");
     }
   },
 });

packages/commands/src/commands/dataset/validate.ts

@@ -1,26 +1,13 @@
 import {
   defineCommand,
-  detectOutputFormat,
   validateDataset,
   parseDatasetSchemaFlag,
-  formatIssue,
   BailianError,
   ExitCode,
-  type ValidationResult,
   type FlagsDef,
 } from "bailian-cli-core";
 import { emitResult, emitBare } from "bailian-cli-runtime";
 
-function formatStats(result: ValidationResult): string[] {
-  const out: string[] = [];
-  if (result.stats.totalRecords !== undefined) out.push(`records: ${result.stats.totalRecords}`);
-  if (result.stats.sampledRecords !== undefined)
-    out.push(`sampled: ${result.stats.sampledRecords}`);
-  if (result.stats.bytes !== undefined) out.push(`bytes: ${result.stats.bytes}`);
-  if (result.stats.durationMs !== undefined) out.push(`took: ${result.stats.durationMs}ms`);
-  return out;
-}
-
 const VALIDATE_FLAGS = {
   file: {
     type: "string",
@@ -36,7 +23,7 @@ const VALIDATE_FLAGS = {
     type: "string",
     valueHint: "<s>",
     description:
-      'Record schema: "chatml" (SFT), "dpo" (chosen/rejected), "cpt" (raw text), "tts" (audio), or "image" (image generation). Default auto-detects per record.',
+      'Record schema: "chatml" (SFT), "dpo" (chosen/rejected), "cpt" (raw text), "tts" (audio), "image" (image generation), or "video" (video generation). Default auto-detects per record.',
   },
 } satisfies FlagsDef;
 
@@ -44,13 +31,14 @@ export default defineCommand({
   description: "Locally validate a dataset file (.jsonl or .zip) without uploading",
   // 纯本地校验，不触网、不需 API key（与 `pipeline validate` 一致）。
   auth: "none",
-  usageArgs: "--file <path> [--full-validate] [--schema <chatml|dpo|cpt|tts|image>]",
+  usageArgs: "--file <path> [--full-validate] [--schema <chatml|dpo|cpt|tts|image|video>]",
   flags: VALIDATE_FLAGS,
   exampleArgs: [
     "--file train.jsonl",
     "--file dpo.jsonl --schema dpo",
     "--file cpt.jsonl --schema cpt",
     "--file audio.zip --schema tts",
+    "--file wan-i2v-training-dataset.zip --schema video",
     "--file eval.jsonl --full-validate",
     "--file train.jsonl --output json",
   ],
@@ -60,27 +48,20 @@ export default defineCommand({
     "Schemas: chatml = {messages:[...]} (SFT); dpo = {messages:[...], chosen,",
     'rejected}; cpt = {text:"..."} (continual pre-training, raw text);',
     'tts = {wav_fn:"train/xxx.wav", text:"..."} (audio fine-tuning);',
-    'image = {img_path:"..."} (image generation). With no --schema, a record',
-    "carrying wav_fn is validated as TTS, img_path as image, chosen/rejected",
-    "as DPO, text (no messages) as CPT, otherwise ChatML. Pass --schema to",
-    "require a specific shape on every record. ZIP archives (.zip) are",
-    "validated structurally (data.jsonl present, media references resolve) in",
-    "addition to per-record content checks. Use --full-validate to JSON.parse",
-    "every line.",
+    'image = {img_path:"..."} (image generation);',
+    'video = {first_frame_path:"...", video_path:"..."} (video generation,',
+    "i2v first-frame or kf2v first+last-frame with last_frame_path). With no",
+    "--schema, a record carrying wav_fn is validated as TTS, img_path as image,",
+    "first_frame_path/video_path as video, chosen/rejected as DPO, text (no",
+    "messages) as CPT, otherwise ChatML. Pass --schema to require a specific",
+    "shape on every record. ZIP archives (.zip) are validated structurally",
+    "(data.jsonl present, media references resolve) in addition to per-record",
+    "content checks. Use --full-validate to JSON.parse every line.",
   ],
   async run(ctx) {
     const { settings, flags } = ctx;
     const filePath = flags.file;
     const schema = parseDatasetSchemaFlag(flags.schema);
-    if (schema === "video") {
-      throw new BailianError(
-        `--schema video is not supported.`,
-        ExitCode.USAGE,
-        `Supported schemas: chatml, dpo, cpt, tts, image.`,
-      );
-    }
-    const format = detectOutputFormat(settings.output);
-
     if (settings.dryRun) {
       emitResult(
         {
@@ -89,38 +70,17 @@ export default defineCommand({
           full: flags.fullValidate,
           schema: schema ?? "auto",
         },
-        format,
+        "json",
       );
       return;
     }
 
     const result = await validateDataset(filePath, { fullValidate: flags.fullValidate, schema });
 
-    if (format === "json") {
-      // For json output we always emit the structured result, exit code conveys validity.
-      emitResult(result, format);
-    } else if (settings.quiet) {
+    if (settings.quiet) {
       emitBare(result.valid ? "ok" : "fail");
     } else {
-      const status = result.valid ? "PASSED" : "FAILED";
-      emitBare(`Dataset validation ${status} for ${result.filePath}`);
-      const stats = formatStats(result);
-      if (stats.length) emitBare(`  ${stats.join(" · ")}`);
-
-      if (result.errors.length) {
-        emitBare(`Errors (${result.errors.length}):`);
-        for (const error of result.errors.slice(0, 20)) emitBare(formatIssue(error));
-        if (result.errors.length > 20) {
-          emitBare(`  … and ${result.errors.length - 20} more.`);
-        }
-      }
-      if (result.warnings.length) {
-        emitBare(`Warnings (${result.warnings.length}):`);
-        for (const warning of result.warnings.slice(0, 10)) emitBare(formatIssue(warning));
-        if (result.warnings.length > 10) {
-          emitBare(`  … and ${result.warnings.length - 10} more.`);
-        }
-      }
+      emitResult(result, "json");
     }
 
     if (!result.valid) {

packages/commands/src/commands/deploy/create.ts

@@ -1,6 +1,5 @@
 import {
   defineCommand,
-  detectOutputFormat,
   createDeployment,
   pickPlanStrategy,
   STRATEGIES,
@@ -11,16 +10,16 @@ import {
   type CommandContext,
   type FlagsDef,
 } from "bailian-cli-core";
-import { emitResult, emitBare, emitRequestId } from "bailian-cli-runtime";
+import { emitResult, emitBare } from "bailian-cli-runtime";
 
 const CREATE_FLAGS = {
-  model: {
+  modelName: {
     type: "string",
-    valueHint: "<name>",
-    description: "Model name (catalog model or fine-tuned output) (required)",
+    valueHint: "<model_name>",
+    description: "Model to deploy — fine-tuned output name or catalog model (required)",
     required: true,
   },
-  name: {
+  displayName: {
     type: "string",
     valueHint: "<display_name>",
     description: "Console display name for the deployment (required)",
@@ -64,7 +63,7 @@ const CREATE_FLAGS = {
 } satisfies FlagsDef;
 
 const CREATE_USAGE =
-  "--model <model_name> --name <display_name> [--plan <plan>] [--deploy-spec <id>] [--capacity <n>] [--billing-method <m>] [--input-tpm <n>] [--output-tpm <n>] [--thinking-output-tpm <n>]";
+  "--model-name <model_name> --display-name <display_name> [--plan <plan>] [--deploy-spec <id>] [--capacity <n>] [--billing-method <m>] [--input-tpm <n>] [--output-tpm <n>] [--thinking-output-tpm <n>]";
 
 const CREATE_NOTES = [
   "Plan defaults to `lora` (Token-billed) for text/image and `mu` (model-unit-",
@@ -78,14 +77,11 @@ const CREATE_NOTES = [
   "Use `bl deploy models --source base` to inspect available templates.",
   "After creation, status starts at PENDING and transitions to RUNNING.",
   "Invoke the deployed model with: bl text chat --model <deployed_model>",
-  "WARNING: --model is overloaded across commands and refers to DIFFERENT",
-  "values. `bl deploy <modality> create --model` takes the exported model_name",
-  "(e.g. `qwen3-8b-ft-...`), but the create response also returns a",
-  "`deployed_model` field (the deployment instance id, e.g.",
-  "`qwen3-8b-5ecb5f068d79`). The inference call `bl text chat --model` must use",
-  "the `deployed_model` from the create response — NOT the `model_name` you",
-  "passed to `deploy <modality> create`. Do not reuse the value across the two",
-  "commands.",
+  "NOTE: --model-name is the model being deployed (e.g. `qwen3-8b-ft-...`).",
+  "The create response also returns a `deployed_model` field — the deployment",
+  "instance id (e.g. `qwen3-8b-5ecb5f068d79`). Use that id for inference",
+  "(`bl text chat --model <deployed_model>`) and lifecycle commands",
+  "(`deploy get/scale/pause/resume/delete --deployed-model <id>`).",
 ];
 
 /**
@@ -119,10 +115,9 @@ async function runCreate(
   ctx: CommandContext<typeof CREATE_FLAGS>,
 ): Promise<void> {
   const { identity, settings, flags } = ctx;
-  const model = flags.model as string;
-  const name = flags.name as string;
+  const model = flags.modelName as string;
+  const name = flags.displayName as string;
   const plan = (flags.plan as string | undefined) || defaultDeployPlan(modality);
-  const format = detectOutputFormat(settings.output);
 
   // Plan-specific behaviour is owned by core `plans.ts`. The strategy resolves
   // the plan-specific body fragment (mu may auto-pick a template from the
@@ -146,7 +141,7 @@ async function runCreate(
   };
 
   if (settings.dryRun) {
-    emitResult({ action: "deploy.create", body }, format);
+    emitResult({ action: "deploy.create", body }, "json");
     return;
   }
 
@@ -155,17 +150,8 @@ async function runCreate(
 
   if (settings.quiet) {
     emitBare(deployment?.deployed_model ?? "");
-  } else if (format === "text") {
-    emitBare(`Created deployment.`);
-    if (deployment?.deployed_model) emitBare(`  deployed_model:  ${deployment.deployed_model}`);
-    if (deployment?.status) emitBare(`  status:          ${deployment.status}`);
-    if (deployment?.plan) emitBare(`  plan:            ${deployment.plan}`);
-    emitBare(
-      `\nNext: track readiness with: ${identity.binName} deploy get --deployed-model ${deployment?.deployed_model ?? "<id>"}`,
-    );
-    emitRequestId(response.request_id, settings.quiet);
   } else {
-    emitResult(response, format);
+    emitResult(response, "json");
   }
 }
 
@@ -176,10 +162,10 @@ export const deployTextCreate = defineCommand({
   usageArgs: CREATE_USAGE,
   flags: CREATE_FLAGS,
   exampleArgs: [
-    "--model my-qwen-sft --name my-sft-test",
-    "--model qwen3.6-flash-2026-04-16 --name my-flash --plan ptu --input-tpm 10000 --output-tpm 1000",
-    "--model qwen3-8b --name my-qwen3-mu --plan mu",
-    "--model qwen3-8b --name my-qwen3 --plan mu --deploy-spec MU1 --capacity 2",
+    "--model-name my-qwen-sft --display-name my-sft-test",
+    "--model-name qwen3.6-flash-2026-04-16 --display-name my-flash --plan ptu --input-tpm 10000 --output-tpm 1000",
+    "--model-name qwen3-8b --display-name my-qwen3-mu --plan mu",
+    "--model-name qwen3-8b --display-name my-qwen3 --plan mu --deploy-spec MU1 --capacity 2",
   ],
   notes: CREATE_NOTES,
   validate: (flags) => validateCreate("text", flags),
@@ -193,9 +179,9 @@ export const deployAudioCreate = defineCommand({
   usageArgs: CREATE_USAGE,
   flags: CREATE_FLAGS,
   exampleArgs: [
-    "--model my-cosyvoice-ft --name my-tts",
-    "--model my-cosyvoice-ft --name my-tts --deploy-spec dps-xxxx --capacity 1",
-    "--model my-cosyvoice-ft --name my-tts --dry-run",
+    "--model-name my-cosyvoice-ft --display-name my-tts",
+    "--model-name my-cosyvoice-ft --display-name my-tts --deploy-spec dps-xxxx --capacity 1",
+    "--model-name my-cosyvoice-ft --display-name my-tts --dry-run",
   ],
   notes: CREATE_NOTES,
   validate: (flags) => validateCreate("audio", flags),
@@ -209,9 +195,9 @@ export const deployImageCreate = defineCommand({
   usageArgs: CREATE_USAGE,
   flags: CREATE_FLAGS,
   exampleArgs: [
-    "--model my-wan-ft --name my-wan",
-    "--model my-wan-ft --name my-wan-mu --plan mu",
-    "--model my-wan-ft --name my-wan --dry-run",
+    "--model-name my-wan-ft --display-name my-wan",
+    "--model-name my-wan-ft --display-name my-wan-mu --plan mu",
+    "--model-name my-wan-ft --display-name my-wan --dry-run",
   ],
   notes: CREATE_NOTES,
   validate: (flags) => validateCreate("image", flags),

packages/commands/src/commands/deploy/delete.ts

@@ -1,13 +1,12 @@
 import {
   defineCommand,
-  detectOutputFormat,
   deleteDeployment,
   getDeployment,
   BailianError,
   ExitCode,
   type FlagsDef,
 } from "bailian-cli-core";
-import { emitResult, emitBare, emitRequestId } from "bailian-cli-runtime";
+import { emitResult, emitBare } from "bailian-cli-runtime";
 
 const DELETE_FLAGS = {
   deployedModel: {
@@ -38,10 +37,9 @@ export default defineCommand({
   async run(ctx) {
     const { settings, flags } = ctx;
     const deployedModel = flags.deployedModel;
-    const format = detectOutputFormat(settings.output);
 
     if (settings.dryRun) {
-      emitResult({ action: "deploy.delete", deployed_model: deployedModel }, format);
+      emitResult({ action: "deploy.delete", deployed_model: deployedModel }, "json");
       return;
     }
 
@@ -55,7 +53,8 @@ export default defineCommand({
         if (status && status !== "STOPPED" && status !== "FAILED") {
           throw new BailianError(
             `Deployment ${deployedModel} is ${status}. Only STOPPED / FAILED deployments can be deleted. ` +
-              `Stop it first via the platform console, or pass --skip-precheck to attempt deletion anyway.`,
+              `Run \`bl deploy pause --deployed-model ${deployedModel}\` to pause it first, ` +
+              `or pass --skip-precheck to attempt deletion anyway.`,
             ExitCode.USAGE,
           );
         }
@@ -69,11 +68,8 @@ export default defineCommand({
 
     if (settings.quiet) {
       emitBare(deployedModel);
-    } else if (format === "text") {
-      emitBare(`Deleted ${deployedModel}.`);
-      emitRequestId(response.request_id, settings.quiet);
     } else {
-      emitResult(response, format);
+      emitResult(response, "json");
     }
   },
 });

packages/commands/src/commands/deploy/get.ts

@@ -1,5 +1,5 @@
-import { defineCommand, detectOutputFormat, getDeployment, type FlagsDef } from "bailian-cli-core";
-import { emitResult, emitBare, emitRequestId } from "bailian-cli-runtime";
+import { defineCommand, getDeployment, type FlagsDef } from "bailian-cli-core";
+import { emitResult } from "bailian-cli-runtime";
 
 const GET_FLAGS = {
   deployedModel: {
@@ -22,10 +22,9 @@ export default defineCommand({
   async run(ctx) {
     const { settings, flags } = ctx;
     const deployedModel = flags.deployedModel;
-    const format = detectOutputFormat(settings.output);
 
     if (settings.dryRun) {
-      emitResult({ action: "deploy.get", deployed_model: deployedModel }, format);
+      emitResult({ action: "deploy.get", deployed_model: deployedModel }, "json");
       return;
     }
 
@@ -33,7 +32,7 @@ export default defineCommand({
     const deployment = response.output ?? response.data;
 
     if (!deployment) {
-      emitBare(`No data returned for ${deployedModel}`);
+      emitResult({ deployed_model: deployedModel, request_id: response.request_id }, "json");
       return;
     }
 
@@ -57,18 +56,6 @@ export default defineCommand({
     if (deployment.gmt_create) item.created_at = deployment.gmt_create;
     if (deployment.gmt_modified) item.updated_at = deployment.gmt_modified;
 
-    if (format === "json") {
-      emitResult({ ...item, request_id: response.request_id }, format);
-      return;
-    }
-
-    // text / quiet — fixed-width label column for alignment
-    const label = (key: string) => `${key}:`.padEnd(18);
-    for (const [key, value] of Object.entries(item)) {
-      if (value === "" || value === undefined) continue;
-      const display = typeof value === "string" ? value : JSON.stringify(value);
-      emitBare(`${label(key)}${display}`);
-    }
-    emitRequestId(response.request_id, settings.quiet);
+    emitResult({ ...item, request_id: response.request_id }, "json");
   },
 });

packages/commands/src/commands/deploy/list.ts

@@ -1,10 +1,5 @@
-import {
-  defineCommand,
-  detectOutputFormat,
-  listDeployments,
-  type FlagsDef,
-} from "bailian-cli-core";
-import { emitResult, emitBare, emitRequestId, formatTable } from "bailian-cli-runtime";
+import { defineCommand, listDeployments, type FlagsDef } from "bailian-cli-core";
+import { emitResult } from "bailian-cli-runtime";
 
 const LIST_FLAGS = {
   page: { type: "number", valueHint: "<n>", description: "Page number (default: 1)" },
@@ -28,13 +23,12 @@ export default defineCommand({
   exampleArgs: ["", "--status RUNNING", "--page-size 20 --output json"],
   async run(ctx) {
     const { settings, flags } = ctx;
-    const format = detectOutputFormat(settings.output);
     const status = flags.status || undefined;
 
     if (settings.dryRun) {
       emitResult(
         { action: "deploy.list", page: flags.page, page_size: flags.pageSize, status },
-        format,
+        "json",
       );
       return;
     }
@@ -57,27 +51,6 @@ export default defineCommand({
       created_at: item.gmt_create ?? "",
     }));
 
-    if (format === "json") {
-      emitResult({ items, total, request_id: response.request_id }, format);
-      return;
-    }
-
-    // text / quiet
-    if (items.length === 0) {
-      emitBare("No deployments found.");
-      return;
-    }
-    const headers = ["DEPLOYED_MODEL", "MODEL_NAME", "STATUS", "PLAN", "CAPACITY", "CREATED_AT"];
-    const rows = items.map((item) => [
-      item.deployed_model,
-      item.model_name,
-      item.status,
-      item.plan,
-      item.capacity,
-      item.created_at,
-    ]);
-    for (const line of formatTable(headers, rows)) emitBare(line);
-    if (total !== undefined) emitBare(`\nTotal: ${total}`);
-    emitRequestId(response.request_id, settings.quiet);
+    emitResult({ items, total, request_id: response.request_id }, "json");
   },
 });

packages/commands/src/commands/deploy/models.ts

@@ -1,10 +1,5 @@
-import {
-  defineCommand,
-  detectOutputFormat,
-  listDeployableModels,
-  type FlagsDef,
-} from "bailian-cli-core";
-import { emitResult, emitBare, emitRequestId, formatTable } from "bailian-cli-runtime";
+import { defineCommand, listDeployableModels, type FlagsDef } from "bailian-cli-core";
+import { emitResult } from "bailian-cli-runtime";
 
 const MODELS_FLAGS = {
   page: { type: "number", valueHint: "<n>", description: "Page number (default: 1)" },
@@ -39,7 +34,6 @@ export default defineCommand({
   ],
   async run(ctx) {
     const { settings, flags } = ctx;
-    const format = detectOutputFormat(settings.output);
     // Default version to v1.0 — without it, the API returns the legacy catalog
     // (only old fine-tune outputs). Pass --catalog-version "" to opt out.
     const version = flags.catalogVersion === "" ? undefined : (flags.catalogVersion ?? "v1.0");
@@ -54,7 +48,7 @@ export default defineCommand({
           version,
           model_source: modelSource,
         },
-        format,
+        "json",
       );
       return;
     }
@@ -72,102 +66,55 @@ export default defineCommand({
     // Two response shapes:
     //   - custom (fine-tuned): top-level supported_plans: string[]
     //   - base (catalog):      plans: [{plan, templates?, cu_specs?}]
-    // For json: surface the deployment-relevant fields preserved as a tree, so
+    // Surface the deployment-relevant fields preserved as a tree, so
     // downstream tooling can drive `bl deploy <modality> create --deploy-spec <…>`
-    // without a second round-trip. For text: keep the compact one-line summary.
-    if (format === "json") {
-      const items = models.map((model) => {
-        const out: Record<string, unknown> = {
-          model_name: model.model_name ?? "",
-        };
-        if (model.base_model) out.base_model = model.base_model;
-        if (model.model_source) out.model_source = model.model_source;
-        if (model.supported_plans && model.supported_plans.length > 0) {
-          out.supported_plans = model.supported_plans;
-        }
-        if (model.plans && model.plans.length > 0) {
-          out.plans = model.plans.map((plan) => {
-            const planEntry: Record<string, unknown> = { plan: plan.plan ?? "" };
-            if (plan.cu_specs && plan.cu_specs.length > 0) {
-              planEntry.cu_specs = plan.cu_specs;
-            }
-            if (plan.templates && plan.templates.length > 0) {
-              // Pull the top 6 fields most useful for `bl deploy <modality> create`.
-              // Drop noisy/redundant: template_source, template_type,
-              // template_version, deploy_spec (typically == template_id).
-              planEntry.templates = plan.templates.map((template) => {
-                const tpl: Record<string, unknown> = {};
-                if (template.template_id) tpl.template_id = template.template_id;
-                if (template.template_name) tpl.template_name = template.template_name;
-                if (template.charge_type) tpl.charge_type = template.charge_type;
-                // Flatten roles.unified for the common COUPLED case.
-                const unified = template.roles?.unified;
-                if (unified?.model_unit_spec) tpl.model_unit_spec = unified.model_unit_spec;
-                if (unified?.capacity_unit_per_instance !== undefined)
-                  tpl.capacity_unit_per_instance = unified.capacity_unit_per_instance;
-                // Preserve split-role configs (SEPERATED) as-is so callers
-                // can still drive prefill/decode sizing.
-                if (template.roles?.prefill || template.roles?.decode) {
-                  tpl.roles = {
-                    prefill: template.roles?.prefill,
-                    decode: template.roles?.decode,
-                  };
-                }
-                if (template.template_desc) tpl.template_desc = template.template_desc;
-                return tpl;
-              });
-            }
-            return planEntry;
-          });
-        }
-        return out;
-      });
-      emitResult({ items, total, request_id: response.request_id }, format);
-      return;
-    }
-
-    // text / quiet — keep the compact single-line summary table.
-    const textItems = models.map((model) => {
-      let plansSummary = "";
-      if (model.supported_plans && model.supported_plans.length > 0) {
-        plansSummary = model.supported_plans.join(",");
-      } else if (model.plans && model.plans.length > 0) {
-        plansSummary = model.plans
-          .map((plan) => {
-            const planName = plan.plan ?? "?";
-            if (plan.templates && plan.templates.length > 0) {
-              return `${planName}(${plan.templates.length}t)`;
-            }
-            if (plan.cu_specs && plan.cu_specs.length > 0) {
-              return `${planName}(${plan.cu_specs.join("/")})`;
-            }
-            return planName;
-          })
-          .join(",");
-      } else {
-        plansSummary = "-";
-      }
-      return {
+    // without a second round-trip.
+    const items = models.map((model) => {
+      const out: Record<string, unknown> = {
         model_name: model.model_name ?? "",
-        base_model: model.base_model ?? "",
-        source: model.model_source ?? "",
-        plans: plansSummary,
       };
+      if (model.base_model) out.base_model = model.base_model;
+      if (model.model_source) out.model_source = model.model_source;
+      if (model.supported_plans && model.supported_plans.length > 0) {
+        out.supported_plans = model.supported_plans;
+      }
+      if (model.plans && model.plans.length > 0) {
+        out.plans = model.plans.map((plan) => {
+          const planEntry: Record<string, unknown> = { plan: plan.plan ?? "" };
+          if (plan.cu_specs && plan.cu_specs.length > 0) {
+            planEntry.cu_specs = plan.cu_specs;
+          }
+          if (plan.templates && plan.templates.length > 0) {
+            // Pull the top 6 fields most useful for `bl deploy <modality> create`.
+            // Drop noisy/redundant: template_source, template_type,
+            // template_version, deploy_spec (typically == template_id).
+            planEntry.templates = plan.templates.map((template) => {
+              const tpl: Record<string, unknown> = {};
+              if (template.template_id) tpl.template_id = template.template_id;
+              if (template.template_name) tpl.template_name = template.template_name;
+              if (template.charge_type) tpl.charge_type = template.charge_type;
+              // Flatten roles.unified for the common COUPLED case.
+              const unified = template.roles?.unified;
+              if (unified?.model_unit_spec) tpl.model_unit_spec = unified.model_unit_spec;
+              if (unified?.capacity_unit_per_instance !== undefined)
+                tpl.capacity_unit_per_instance = unified.capacity_unit_per_instance;
+              // Preserve split-role configs (SEPERATED) as-is so callers
+              // can still drive prefill/decode sizing.
+              if (template.roles?.prefill || template.roles?.decode) {
+                tpl.roles = {
+                  prefill: template.roles?.prefill,
+                  decode: template.roles?.decode,
+                };
+              }
+              if (template.template_desc) tpl.template_desc = template.template_desc;
+              return tpl;
+            });
+          }
+          return planEntry;
+        });
+      }
+      return out;
     });
-
-    if (textItems.length === 0) {
-      emitBare("No deployable models found.");
-      return;
-    }
-    const headers = ["MODEL_NAME", "BASE_MODEL", "SOURCE", "PLANS"];
-    const rows = textItems.map((item) => [
-      item.model_name,
-      item.base_model,
-      item.source,
-      item.plans,
-    ]);
-    for (const line of formatTable(headers, rows)) emitBare(line);
-    if (total !== undefined) emitBare(`\nTotal: ${total}`);
-    emitRequestId(response.request_id, settings.quiet);
+    emitResult({ items, total, request_id: response.request_id }, "json");
   },
 });

packages/commands/src/commands/deploy/pause.ts

@@ -0,0 +1,85 @@
+import {
+  defineCommand,
+  stopModelService,
+  listIndependentDeployedModels,
+  findDeploymentEntry,
+  BailianError,
+  ExitCode,
+  type FlagsDef,
+} from "bailian-cli-core";
+import { emitResult, emitBare } from "bailian-cli-runtime";
+
+const PAUSE_FLAGS = {
+  deployedModel: {
+    type: "string",
+    valueHint: "<id>",
+    description: "Deployed model identifier (required)",
+    required: true,
+  },
+  skipPrecheck: {
+    type: "switch",
+    description: "Skip the local RUNNING/PENDING status precheck",
+  },
+} satisfies FlagsDef;
+
+/**
+ * `bl deploy pause` — pause a running deployment.
+ *
+ * Takes the model service offline so it no longer serves inference requests.
+ * For mu/ptu plans, billing stops while paused.
+ * Precheck: status must be RUNNING or PENDING.
+ */
+export default defineCommand({
+  description: "Pause a running model deployment (stops billing for mu/ptu)",
+  auth: "console",
+  usageArgs: "--deployed-model <id> [--skip-precheck]",
+  flags: PAUSE_FLAGS,
+  exampleArgs: [
+    "--deployed-model dep-...",
+    "--deployed-model dep-... --skip-precheck",
+    "--deployed-model dep-... --dry-run",
+  ],
+  notes: [
+    "While paused, billing ceases for mu/ptu plans. Use `deploy resume` to bring it back online or `deploy delete` to remove.",
+    "Precheck verifies status is RUNNING/PENDING before issuing the pause; pass --skip-precheck to bypass.",
+  ],
+  async run(ctx) {
+    const { settings, flags } = ctx;
+    const deployedModel = flags.deployedModel;
+
+    if (settings.dryRun) {
+      emitResult({ action: "deploy.pause", deployed_model: deployedModel }, "json");
+      return;
+    }
+
+    // Precheck: verify the deployment is in a pausable state.
+    if (!flags.skipPrecheck) {
+      try {
+        const entries = await listIndependentDeployedModels(ctx.client);
+        const entry = findDeploymentEntry(entries, deployedModel);
+        if (entry) {
+          const status = (entry.status ?? "").toUpperCase();
+          if (status && status !== "RUNNING" && status !== "PENDING") {
+            throw new BailianError(
+              `Deployment ${deployedModel} is ${status}. Only RUNNING / PENDING deployments can be paused. ` +
+                `Pass --skip-precheck to attempt the pause anyway.`,
+              ExitCode.USAGE,
+            );
+          }
+        }
+        // If entry not found in list, proceed — the server will surface the real error.
+      } catch (error) {
+        if (error instanceof BailianError) throw error;
+        // If the list call itself failed, proceed and let the API call surface the error.
+      }
+    }
+
+    const response = await stopModelService(ctx.client, deployedModel);
+
+    if (settings.quiet) {
+      emitBare(deployedModel);
+    } else {
+      emitResult({ deployed_model: deployedModel, action: "pause", ...response }, "json");
+    }
+  },
+});

packages/commands/src/commands/deploy/resume.ts

@@ -0,0 +1,84 @@
+import {
+  defineCommand,
+  startModelService,
+  listIndependentDeployedModels,
+  findDeploymentEntry,
+  BailianError,
+  ExitCode,
+  type FlagsDef,
+} from "bailian-cli-core";
+import { emitResult, emitBare } from "bailian-cli-runtime";
+
+const RESUME_FLAGS = {
+  deployedModel: {
+    type: "string",
+    valueHint: "<id>",
+    description: "Deployed model identifier (required)",
+    required: true,
+  },
+  skipPrecheck: {
+    type: "switch",
+    description: "Skip the local STOPPED status precheck",
+  },
+} satisfies FlagsDef;
+
+/**
+ * `bl deploy resume` — resume a paused deployment.
+ *
+ * Brings the model service back online so it can serve inference requests.
+ * Precheck: status must be STOPPED.
+ */
+export default defineCommand({
+  description: "Resume a paused model deployment (brings service back online)",
+  auth: "console",
+  usageArgs: "--deployed-model <id> [--skip-precheck]",
+  flags: RESUME_FLAGS,
+  exampleArgs: [
+    "--deployed-model dep-...",
+    "--deployed-model dep-... --skip-precheck",
+    "--deployed-model dep-... --dry-run",
+  ],
+  notes: [
+    "Precheck verifies status is STOPPED before issuing the resume; pass --skip-precheck to bypass.",
+    "For mu/ptu plans, billing resumes once the service is back online.",
+  ],
+  async run(ctx) {
+    const { settings, flags } = ctx;
+    const deployedModel = flags.deployedModel;
+
+    if (settings.dryRun) {
+      emitResult({ action: "deploy.resume", deployed_model: deployedModel }, "json");
+      return;
+    }
+
+    // Precheck: verify the deployment is in a resumable state.
+    if (!flags.skipPrecheck) {
+      try {
+        const entries = await listIndependentDeployedModels(ctx.client);
+        const entry = findDeploymentEntry(entries, deployedModel);
+        if (entry) {
+          const status = (entry.status ?? "").toUpperCase();
+          if (status && status !== "STOPPED") {
+            throw new BailianError(
+              `Deployment ${deployedModel} is ${status}. Only STOPPED deployments can be resumed. ` +
+                `Pass --skip-precheck to attempt the resume anyway.`,
+              ExitCode.USAGE,
+            );
+          }
+        }
+        // If entry not found in list, proceed — the server will surface the real error.
+      } catch (error) {
+        if (error instanceof BailianError) throw error;
+        // If the list call itself failed, proceed and let the API call surface the error.
+      }
+    }
+
+    const response = await startModelService(ctx.client, deployedModel);
+
+    if (settings.quiet) {
+      emitBare(deployedModel);
+    } else {
+      emitResult({ deployed_model: deployedModel, action: "resume", ...response }, "json");
+    }
+  },
+});

packages/commands/src/commands/deploy/scale.ts

@@ -1,10 +1,5 @@
-import {
-  defineCommand,
-  detectOutputFormat,
-  scaleDeployment,
-  type FlagsDef,
-} from "bailian-cli-core";
-import { emitResult, emitBare, emitRequestId } from "bailian-cli-runtime";
+import { defineCommand, scaleDeployment, type FlagsDef } from "bailian-cli-core";
+import { emitResult, emitBare } from "bailian-cli-runtime";
 
 const SCALE_FLAGS = {
   deployedModel: {
@@ -52,7 +47,6 @@ export default defineCommand({
   async run(ctx) {
     const { settings, flags } = ctx;
     const deployedModel = flags.deployedModel;
-    const format = detectOutputFormat(settings.output);
 
     const body: Record<string, unknown> = {};
     if (flags.capacity !== undefined) body.capacity = flags.capacity;
@@ -60,21 +54,16 @@ export default defineCommand({
     if (flags.outputTpm !== undefined) body.output_tpm = flags.outputTpm;
 
     if (settings.dryRun) {
-      emitResult({ action: "deploy.scale", deployed_model: deployedModel, body }, format);
+      emitResult({ action: "deploy.scale", deployed_model: deployedModel, body }, "json");
       return;
     }
 
     const response = await scaleDeployment(ctx.client, deployedModel, body);
-    const deployment = response.output ?? response.data;
 
     if (settings.quiet) {
       emitBare(deployedModel);
-    } else if (format === "text") {
-      const cap = deployment?.capacity !== undefined ? ` (capacity=${deployment.capacity})` : "";
-      emitBare(`Scaled ${deployedModel}${cap}.`);
-      emitRequestId(response.request_id, settings.quiet);
     } else {
-      emitResult(response, format);
+      emitResult(response, "json");
     }
   },
 });

packages/commands/src/commands/deploy/update.ts

@@ -1,10 +1,5 @@
-import {
-  defineCommand,
-  detectOutputFormat,
-  updateDeployment,
-  type FlagsDef,
-} from "bailian-cli-core";
-import { emitResult, emitBare, emitRequestId } from "bailian-cli-runtime";
+import { defineCommand, updateDeployment, type FlagsDef } from "bailian-cli-core";
+import { emitResult, emitBare } from "bailian-cli-runtime";
 
 const UPDATE_FLAGS = {
   deployedModel: {
@@ -48,31 +43,22 @@ export default defineCommand({
   async run(ctx) {
     const { settings, flags } = ctx;
     const deployedModel = flags.deployedModel;
-    const format = detectOutputFormat(settings.output);
 
     const body: Record<string, unknown> = {};
     if (flags.rpmLimit !== undefined) body.rpm_limit = flags.rpmLimit;
     if (flags.tpmLimit !== undefined) body.tpm_limit = flags.tpmLimit;
 
     if (settings.dryRun) {
-      emitResult({ action: "deploy.update", deployed_model: deployedModel, body }, format);
+      emitResult({ action: "deploy.update", deployed_model: deployedModel, body }, "json");
       return;
     }
 
     const response = await updateDeployment(ctx.client, deployedModel, body);
-    const deployment = response.output ?? response.data;
 
     if (settings.quiet) {
       emitBare(deployedModel);
-    } else if (format === "text") {
-      const parts: string[] = [];
-      if (deployment?.rpm_limit !== undefined) parts.push(`rpm_limit=${deployment.rpm_limit}`);
-      if (deployment?.tpm_limit !== undefined) parts.push(`tpm_limit=${deployment.tpm_limit}`);
-      const summary = parts.length ? ` (${parts.join(", ")})` : "";
-      emitBare(`Updated ${deployedModel}${summary}.`);
-      emitRequestId(response.request_id, settings.quiet);
     } else {
-      emitResult(response, format);
+      emitResult(response, "json");
     }
   },
 });

packages/commands/src/commands/finetune/cancel.ts

@@ -1,5 +1,5 @@
-import { defineCommand, detectOutputFormat, cancelFineTune, type FlagsDef } from "bailian-cli-core";
-import { emitResult, emitBare, emitRequestId } from "bailian-cli-runtime";
+import { defineCommand, cancelFineTune, type FlagsDef } from "bailian-cli-core";
+import { emitResult, emitBare } from "bailian-cli-runtime";
 
 const CANCEL_FLAGS = {
   jobId: {
@@ -23,24 +23,18 @@ export default defineCommand({
   async run(ctx) {
     const { settings, flags } = ctx;
     const jobId = flags.jobId;
-    const format = detectOutputFormat(settings.output);
 
     if (settings.dryRun) {
-      emitResult({ action: "finetune.cancel", job_id: jobId }, format);
+      emitResult({ action: "finetune.cancel", job_id: jobId }, "json");
       return;
     }
 
     const response = await cancelFineTune(ctx.client, jobId);
-    const job = response.output ?? response.data;
 
     if (settings.quiet) {
       emitBare(jobId);
-    } else if (format === "text") {
-      const status = job?.status ? ` (status=${job.status})` : "";
-      emitBare(`Cancelled ${jobId}${status}.`);
-      emitRequestId(response.request_id, settings.quiet);
     } else {
-      emitResult(response, format);
+      emitResult(response, "json");
     }
   },
 });

packages/commands/src/commands/finetune/capability.ts

@@ -1,6 +1,5 @@
 import {
   defineCommand,
-  detectOutputFormat,
   fetchModelListAll,
   fetchModelCapability,
   listSupportedTrainingTypes,
@@ -27,19 +26,8 @@ async function fetchAllFoundationModels(settings: Settings): Promise<ModelCapabi
   return all as ModelCapability[];
 }
 
-const VARIANT_LABEL: Record<string, string> = {
-  full: "full-parameter",
-  lora: "LoRA",
-};
-
-function describeTrainingType(value: string): string {
-  if (!isTrainingTypeCli(value)) return value;
-  const { method, variant } = trainingTypeMethodVariant(value);
-  return `${VARIANT_LABEL[variant] ?? variant} ${method.toUpperCase()}`;
-}
-
 const CAPABILITY_FLAGS = {
-  model: {
+  baseModel: {
     type: "string",
     valueHint: "<m>",
     description: "List training types supported by this base model.",
@@ -55,31 +43,31 @@ export default defineCommand({
   description:
     "Query fine-tune training capability — by model (which training types it supports) or by training type (which models support it)",
   auth: "none",
-  usageArgs: "--model <m> | --training-type <t>",
+  usageArgs: "--base-model <m> | --training-type <t>",
   flags: CAPABILITY_FLAGS,
   exampleArgs: [
-    "--model qwen3-8b",
+    "--base-model qwen3-8b",
     "--training-type sft-lora",
     "--training-type cpt --output json",
     "--training-type sft --quiet",
   ],
   notes: [
-    "Exactly one of --model / --training-type is required.",
+    "Exactly one of --base-model / --training-type is required.",
     "Training-type values use the `<method>` / `<method>-lora` convention:",
     "sft | sft-lora | dpo | dpo-lora | cpt. (cpt has no -lora variant server-side.)",
     "Queries listFoundationModels, a public API — no console login needed.",
   ],
   validate: (f) => {
-    if (f.model && f.trainingType)
-      return "--model and --training-type are mutually exclusive; pass one.";
-    if (!f.model && !f.trainingType) return "one of --model / --training-type is required.";
+    if (f.baseModel && f.trainingType)
+      return "--base-model and --training-type are mutually exclusive; pass one.";
+    if (!f.baseModel && !f.trainingType)
+      return "one of --base-model / --training-type is required.";
     return undefined;
   },
   async run(ctx) {
     const { settings, flags } = ctx;
-    const model = flags.model || undefined;
+    const model = flags.baseModel || undefined;
     const trainingType = flags.trainingType || undefined;
-    const format = detectOutputFormat(settings.output);
 
     if (settings.dryRun) {
       emitResult(
@@ -88,7 +76,7 @@ export default defineCommand({
           model,
           training_type: trainingType,
         },
-        format,
+        "json",
       );
       return;
     }
@@ -97,7 +85,7 @@ export default defineCommand({
     if (model) {
       const capability = await fetchModelCapability(settings, model);
       if (!capability) {
-        emitBare(`No foundation model found matching "${model}".`);
+        emitResult({ model, error: `No foundation model found matching "${model}".` }, "json");
         return;
       }
       const supported = listSupportedTrainingTypes(capability);
@@ -105,23 +93,15 @@ export default defineCommand({
         for (const value of supported) emitBare(value);
         return;
       }
-      if (format !== "text") {
-        emitResult(
-          {
-            model: capability.model ?? model,
-            supported,
-            supports: capability.supports,
-            trainingTypes: capability.trainingTypes,
-          },
-          format,
-        );
-        return;
-      }
-      emitBare(`${capability.model ?? model}`);
-      emitBare(supported.length ? "Supported training types:" : "No supported training types.");
-      for (const value of supported) {
-        emitBare(`  ${value.padEnd(10)} ${describeTrainingType(value)}`);
-      }
+      emitResult(
+        {
+          model: capability.model ?? model,
+          supported,
+          supports: capability.supports,
+          trainingTypes: capability.trainingTypes,
+        },
+        "json",
+      );
       return;
     }
 
@@ -146,20 +126,15 @@ export default defineCommand({
       for (const entry of matched) emitBare(entry.model);
       return;
     }
-    if (format !== "text") {
-      emitResult(
-        {
-          training_type: trainingType,
-          method,
-          variant,
-          count: matched.length,
-          models: matched,
-        },
-        format,
-      );
-      return;
-    }
-    emitBare(`Models supporting ${trainingType} (${method} / ${variant}): ${matched.length}`);
-    for (const entry of matched) emitBare(`  ${entry.model}`);
+    emitResult(
+      {
+        training_type: trainingType,
+        method,
+        variant,
+        count: matched.length,
+        models: matched,
+      },
+      "json",
+    );
   },
 });

packages/commands/src/commands/finetune/checkpoints.ts

@@ -1,10 +1,5 @@
-import {
-  defineCommand,
-  detectOutputFormat,
-  listCheckpoints,
-  type FlagsDef,
-} from "bailian-cli-core";
-import { emitResult, emitBare, emitRequestId, formatTable } from "bailian-cli-runtime";
+import { defineCommand, listCheckpoints, type FlagsDef } from "bailian-cli-core";
+import { emitResult } from "bailian-cli-runtime";
 
 const CHECKPOINTS_FLAGS = {
   jobId: {
@@ -15,6 +10,8 @@ const CHECKPOINTS_FLAGS = {
   },
 } satisfies FlagsDef;
 
+const EXPIRY_WARN_THRESHOLD_MS = 72 * 60 * 60 * 1000; // 72 hours
+
 export default defineCommand({
   description: "List checkpoints produced by a fine-tune job",
   auth: "apiKey",
@@ -22,16 +19,15 @@ export default defineCommand({
   flags: CHECKPOINTS_FLAGS,
   exampleArgs: ["--job-id ft-xxx", "--job-id ft-xxx --output json"],
   notes: [
-    "Use the returned `checkpoint` value with `finetune export` to publish",
-    "a deployable model.",
+    "`model_name` (shown for SUCCEEDED checkpoints) is the direct input for `deploy create --model-name`.",
+    "Checkpoints expire ~15 days after creation; `expire_time` shows the deadline. Export or deploy before expiry.",
   ],
   async run(ctx) {
     const { settings, flags } = ctx;
     const jobId = flags.jobId;
-    const format = detectOutputFormat(settings.output);
 
     if (settings.dryRun) {
-      emitResult({ action: "finetune.checkpoints", job_id: jobId }, format);
+      emitResult({ action: "finetune.checkpoints", job_id: jobId }, "json");
       return;
     }
 
@@ -44,22 +40,26 @@ export default defineCommand({
       checkpoint: item.checkpoint ?? item.checkpoint_id ?? "",
       step: item.step !== undefined ? String(item.step) : "",
       status: item.status ?? "",
+      model_name: item.model_name ?? "",
+      expire_time: item.expire_time ?? "",
     }));
 
-    if (format === "json") {
-      emitResult({ items, total, request_id: response.request_id }, format);
-      return;
-    }
+    emitResult({ items, total, request_id: response.request_id }, "json");
 
-    // text / quiet
-    if (items.length === 0) {
-      emitBare("No checkpoints found.");
-      return;
+    // Near-expiry warning: check if any non-expired checkpoint is within 72h of expiry.
+    const now = Date.now();
+    const expiringSoon = items.filter((item) => {
+      if (!item.expire_time) return false;
+      const deadline = new Date(item.expire_time).getTime();
+      if (Number.isNaN(deadline)) return false;
+      const remaining = deadline - now;
+      return remaining > 0 && remaining < EXPIRY_WARN_THRESHOLD_MS;
+    });
+    if (expiringSoon.length > 0) {
+      process.stderr.write(
+        `\n[warning] ${expiringSoon.length} checkpoint(s) will expire within 72 hours. ` +
+          "Export or deploy before expiry to avoid losing the model artifact.\n",
+      );
     }
-    const headers = ["CHECKPOINT", "STEP", "STATUS"];
-    const rows = items.map((i) => [i.checkpoint, i.step, i.status]);
-    for (const line of formatTable(headers, rows)) emitBare(line);
-    emitBare(`\nTotal: ${total}`);
-    emitRequestId(response.request_id, settings.quiet);
   },
 });

packages/commands/src/commands/finetune/create.ts

@@ -1,6 +1,5 @@
 import {
   defineCommand,
-  detectOutputFormat,
   createFineTune,
   getDataset,
   uploadDataset,
@@ -27,7 +26,7 @@ import {
 } from "bailian-cli-core";
 import { existsSync, statSync } from "fs";
 import { basename } from "path";
-import { emitResult, emitBare, emitRequestId } from "bailian-cli-runtime";
+import { emitResult, emitBare } from "bailian-cli-runtime";
 
 /**
  * A `--datasets` / `--validations` token is treated as a local file to upload
@@ -208,7 +207,7 @@ async function uploadResolvedLocal(
 }
 
 /** The modality a `finetune <modality> create` subcommand is bound to. */
-type CommandModality = "text" | "audio" | "image";
+type CommandModality = "text" | "audio" | "image" | "video";
 
 /**
  * Flags shared by every `finetune <modality> create` subcommand: what to train
@@ -216,10 +215,10 @@ type CommandModality = "text" | "audio" | "image";
  * output. Every modality's model consumes these.
  */
 const COMMON_FLAGS = {
-  model: {
+  baseModel: {
     type: "string",
     valueHint: "<model>",
-    description: "Base model to fine-tune",
+    description: "Base model to fine-tune (e.g. qwen3-8b; not the output model name)",
     required: true,
   },
   datasets: {
@@ -317,13 +316,41 @@ const IMAGE_FLAGS = {
 } satisfies FlagsDef;
 
 const TEXT_USAGE =
-  "--model <model> --datasets <id|path,...> [--validations <id|path,...>] [--model-name <name>] [--suffix <text>] [--n-epochs <n>] [--batch-size <n>] [--learning-rate <str>] [--max-length <n>] [--training-type <sft|sft-lora|dpo|dpo-lora|cpt>]";
+  "--base-model <model> --datasets <id|path,...> [--validations <id|path,...>] [--model-name <name>] [--suffix <text>] [--n-epochs <n>] [--batch-size <n>] [--learning-rate <str>] [--max-length <n>] [--training-type <sft|sft-lora|dpo|dpo-lora|cpt>]";
 
 const AUDIO_USAGE =
-  "--model <model> --datasets <id|path> [--validations <id|path>] [--model-name <name>] [--suffix <text>]";
+  "--base-model <model> --datasets <id|path> [--validations <id|path>] [--model-name <name>] [--suffix <text>]";
 
 const IMAGE_USAGE =
-  "--model <model> --datasets <id|path> [--validations <id|path>] [--model-name <name>] [--suffix <text>] [--generation-type <t2i|i2i>] [--learning-rate <str>]";
+  "--base-model <model> --datasets <id|path> [--validations <id|path>] [--model-name <name>] [--suffix <text>] [--generation-type <t2i|i2i>] [--learning-rate <str>]";
+
+/**
+ * Video (Wan i2v/kf2v) flags: exposes the three hyper-parameters that the
+ * video API supports and users may want to override. Defaults are model-specific
+ * (resolved by the sft-lora profile: wan2.7 → batch_size 1 / max_pixels 102400,
+ * wan2.5 → 4 / 36864, wan2.2 → 4 / 262144).
+ */
+const VIDEO_FLAGS = {
+  ...COMMON_FLAGS,
+  nEpochs: {
+    type: "number",
+    valueHint: "<n>",
+    description: "Training epochs (default: 50)",
+  },
+  batchSize: {
+    type: "number",
+    valueHint: "<n>",
+    description: "Batch size (default: model-specific, 1 for wan2.7, 4 for wan2.5/2.2)",
+  },
+  learningRate: {
+    type: "string",
+    valueHint: "<str>",
+    description: 'Learning rate as a string to preserve precision (default: "2e-5")',
+  },
+} satisfies FlagsDef;
+
+const VIDEO_USAGE =
+  "--base-model <model> --datasets <id|path> [--validations <id|path>] [--model-name <name>] [--suffix <text>] [--n-epochs <n>] [--batch-size <n>] [--learning-rate <str>]";
 
 const COMMON_NOTES = [
   "Creating a job uploads any local datasets and consumes training quota.",
@@ -383,7 +410,7 @@ async function runCreate<F extends FlagsDef>(
 ): Promise<void> {
   const { identity, settings } = ctx;
   const flags = ctx.flags as Record<string, unknown>;
-  const model = flags.model as string;
+  const model = flags.baseModel as string;
   const datasetsRaw = flags.datasets as string;
 
   // CosyVoice audio fine-tuning accepts exactly one training file
@@ -441,6 +468,10 @@ async function runCreate<F extends FlagsDef>(
       if (detected === "image-i2i") modality = "image-i2i";
     }
   }
+  if (commandModality === "video" && firstLocalPath && !settings.dryRun) {
+    const detected = await detectModality(firstLocalPath);
+    if (detected === "video-kf2v") modality = "video-kf2v";
+  }
 
   const training = await analyzeDatasetTokens(
     settings,
@@ -606,8 +637,6 @@ async function runCreate<F extends FlagsDef>(
   if (modelName) body.model_name = modelName;
   if (suffix) body.finetuned_output_suffix = suffix;
 
-  const format = detectOutputFormat(settings.output);
-
   if (settings.dryRun) {
     const pending = [
       ...training.localPaths.map((path) => ({ field: "datasets", path })),
@@ -617,7 +646,7 @@ async function runCreate<F extends FlagsDef>(
       pending.length > 0
         ? { action: "finetune.create", body, pending_uploads: pending }
         : { action: "finetune.create", body },
-      format,
+      "json",
     );
     return;
   }
@@ -627,16 +656,8 @@ async function runCreate<F extends FlagsDef>(
 
   if (settings.quiet) {
     if (job?.job_id) emitBare(job.job_id);
-  } else if (format === "text") {
-    if (job?.job_id) {
-      emitBare(`Created fine-tune job: ${job.job_id}`);
-      if (job.status) emitBare(`Status: ${job.status}`);
-      emitRequestId(response.request_id, settings.quiet);
-    } else {
-      emitResult(response, format);
-    }
   } else {
-    emitResult(response, format);
+    emitResult(response, "json");
   }
 }
 
@@ -647,14 +668,14 @@ export const finetuneTextCreate = defineCommand({
   usageArgs: TEXT_USAGE,
   flags: TEXT_FLAGS,
   exampleArgs: [
-    "--model qwen3-8b --datasets file-xxx",
-    "--model qwen3-8b --datasets ./train.jsonl",
-    "--model qwen3-8b --datasets ./train.jsonl --validations ./eval.jsonl",
-    "--model qwen3-8b --datasets file-aaa,./extra.jsonl",
-    "--model qwen3-8b --datasets ./train.jsonl --training-type sft",
-    '--model qwen3-8b --datasets file-xxx --learning-rate "1.6e-5" --n-epochs 4',
-    "--model qwen3-8b --datasets file-xxx --output json",
-    "--model qwen3-8b --datasets file-xxx --dry-run",
+    "--base-model qwen3-8b --datasets file-xxx",
+    "--base-model qwen3-8b --datasets ./train.jsonl",
+    "--base-model qwen3-8b --datasets ./train.jsonl --validations ./eval.jsonl",
+    "--base-model qwen3-8b --datasets file-aaa,./extra.jsonl",
+    "--base-model qwen3-8b --datasets ./train.jsonl --training-type sft",
+    '--base-model qwen3-8b --datasets file-xxx --learning-rate "1.6e-5" --n-epochs 4',
+    "--base-model qwen3-8b --datasets file-xxx --output json",
+    "--base-model qwen3-8b --datasets file-xxx --dry-run",
   ],
   notes: TEXT_NOTES,
   run: (ctx) => runCreate("text", ctx),
@@ -667,11 +688,11 @@ export const finetuneAudioCreate = defineCommand({
   usageArgs: AUDIO_USAGE,
   flags: AUDIO_FLAGS,
   exampleArgs: [
-    "--model cosyvoice-v3-flash --datasets ./audio.zip",
-    "--model cosyvoice-v3-flash --datasets file-xxx",
-    "--model cosyvoice-v3-flash --datasets ./audio.zip --model-name my-tts",
-    "--model cosyvoice-v3-flash --datasets file-xxx --output json",
-    "--model cosyvoice-v3-flash --datasets ./audio.zip --dry-run",
+    "--base-model cosyvoice-v3-flash --datasets ./audio.zip",
+    "--base-model cosyvoice-v3-flash --datasets file-xxx",
+    "--base-model cosyvoice-v3-flash --datasets ./audio.zip --model-name my-tts",
+    "--base-model cosyvoice-v3-flash --datasets file-xxx --output json",
+    "--base-model cosyvoice-v3-flash --datasets ./audio.zip --dry-run",
   ],
   notes: AUDIO_NOTES,
   run: (ctx) => runCreate("audio", ctx),
@@ -684,13 +705,38 @@ export const finetuneImageCreate = defineCommand({
   usageArgs: IMAGE_USAGE,
   flags: IMAGE_FLAGS,
   exampleArgs: [
-    "--model wan2.7-image-pro --datasets ./images.zip",
-    "--model wan2.7-image-pro --datasets file-xxx",
-    "--model wan2.7-image-pro --datasets file-xxx --generation-type i2i",
-    "--model wan2.7-image-pro --datasets ./images.zip --model-name my-wan",
-    "--model wan2.7-image-pro --datasets file-xxx --output json",
-    "--model wan2.7-image-pro --datasets ./images.zip --dry-run",
+    "--base-model wan2.7-image-pro --datasets ./images.zip",
+    "--base-model wan2.7-image-pro --datasets file-xxx",
+    "--base-model wan2.7-image-pro --datasets file-xxx --generation-type i2i",
+    "--base-model wan2.7-image-pro --datasets ./images.zip --model-name my-wan",
+    "--base-model wan2.7-image-pro --datasets file-xxx --output json",
+    "--base-model wan2.7-image-pro --datasets ./images.zip --dry-run",
   ],
   notes: IMAGE_NOTES,
   run: (ctx) => runCreate("image", ctx),
 });
+
+const VIDEO_NOTES = [
+  ...COMMON_NOTES,
+  "Video generation training (Wan i2v/kf2v) runs efficient_sft with model-",
+  "specific defaults: wan2.7 (batch_size=1, max_pixels=102400), wan2.5/2.2",
+  "(batch_size=4, max_pixels per model). Override with --batch-size/--n-epochs.",
+  "Datasets are .zip archives with data.jsonl + frame images + videos.",
+  "Recommended: ≥10 training samples, 20-100 for stable results.",
+];
+
+/** `bl finetune video create` — fine-tune a video generation model. Datasets are `.zip`. */
+export const finetuneVideoCreate = defineCommand({
+  description: "Create a video generation model fine-tune job (Wan i2v/kf2v, efficient_sft)",
+  auth: "apiKey",
+  usageArgs: VIDEO_USAGE,
+  flags: VIDEO_FLAGS,
+  exampleArgs: [
+    "--base-model wan2.7-i2v --datasets file-xxx",
+    "--base-model wan2.7-i2v --datasets ./i2v-data.zip",
+    "--base-model wan2.2-kf2v-flash --datasets file-xxx --n-epochs 100",
+    "--base-model wan2.7-i2v --datasets file-xxx --dry-run",
+  ],
+  notes: VIDEO_NOTES,
+  run: (ctx) => runCreate("video", ctx),
+});

packages/commands/src/commands/finetune/delete.ts

@@ -1,5 +1,5 @@
-import { defineCommand, detectOutputFormat, deleteFineTune, type FlagsDef } from "bailian-cli-core";
-import { emitResult, emitBare, emitRequestId } from "bailian-cli-runtime";
+import { defineCommand, deleteFineTune, type FlagsDef } from "bailian-cli-core";
+import { emitResult, emitBare } from "bailian-cli-runtime";
 
 const DELETE_FLAGS = {
   jobId: {
@@ -23,10 +23,9 @@ export default defineCommand({
   async run(ctx) {
     const { settings, flags } = ctx;
     const jobId = flags.jobId;
-    const format = detectOutputFormat(settings.output);
 
     if (settings.dryRun) {
-      emitResult({ action: "finetune.delete", job_id: jobId }, format);
+      emitResult({ action: "finetune.delete", job_id: jobId }, "json");
       return;
     }
 
@@ -34,11 +33,8 @@ export default defineCommand({
 
     if (settings.quiet) {
       emitBare(jobId);
-    } else if (format === "text") {
-      emitBare(`Deleted ${jobId}.`);
-      emitRequestId(response.request_id, settings.quiet);
     } else {
-      emitResult(response, format);
+      emitResult(response, "json");
     }
   },
 });

packages/commands/src/commands/finetune/export.ts

@@ -1,10 +1,5 @@
-import {
-  defineCommand,
-  detectOutputFormat,
-  exportCheckpoint,
-  type FlagsDef,
-} from "bailian-cli-core";
-import { emitResult, emitBare, emitRequestId } from "bailian-cli-runtime";
+import { defineCommand, exportCheckpoint, type FlagsDef } from "bailian-cli-core";
+import { emitResult, emitBare } from "bailian-cli-runtime";
 
 const EXPORT_FLAGS = {
   jobId: {
@@ -39,11 +34,10 @@ export default defineCommand({
     "explicit export is the canonical path for non-best checkpoints.",
   ],
   async run(ctx) {
-    const { identity, settings, flags } = ctx;
+    const { settings, flags } = ctx;
     const jobId = flags.jobId;
     const checkpoint = flags.checkpoint;
     const modelName = flags.modelName;
-    const format = detectOutputFormat(settings.output);
 
     if (settings.dryRun) {
       emitResult(
@@ -53,7 +47,7 @@ export default defineCommand({
           checkpoint,
           model_name: modelName,
         },
-        format,
+        "json",
       );
       return;
     }
@@ -64,14 +58,8 @@ export default defineCommand({
 
     if (settings.quiet) {
       emitBare(exported);
-    } else if (format === "text") {
-      emitBare(`Exported ${jobId} / ${checkpoint} → model_name=${exported}`);
-      emitBare(
-        `Next: ${identity.binName} deploy text create --model ${exported} --name <display-name>`,
-      );
-      emitRequestId(response.request_id, settings.quiet);
     } else {
-      emitResult(response, format);
+      emitResult(response, "json");
     }
   },
 });

packages/commands/src/commands/finetune/fee.ts

@@ -0,0 +1,105 @@
+/**
+ * Best-effort actual training fee calculation using the model catalog's
+ * "ft" (fine-tune) price entry. Pure API-key domain — no console auth needed.
+ *
+ * The model catalog (`listFoundationModels` via public gateway) returns a
+ * `prices[]` array **only when `queryPrice: true` is passed** (the same flag
+ * `fetchModelDetail` uses). Combined with the job's `output.usage` (actual
+ * consumed tokens, present on SUCCEEDED / CANCELED), this gives the exact
+ * training cost without any console-domain login.
+ */
+import {
+  callConsoleGateway,
+  effectiveConsoleGatewayConfig,
+  unwrapResponse,
+  MODEL_LIST_API,
+  type Settings,
+  type ModelPriceInfo,
+} from "bailian-cli-core";
+
+export interface ActualFee {
+  cost: number;
+  unitPrice: number;
+  priceUnit: string;
+}
+
+/**
+ * Fetch the model's training price from the public catalog gateway.
+ * Uses the same anonymous gateway path as `fetchModelCapability` (no console
+ * token required), but adds `queryPrice: true` to include the prices array.
+ */
+async function fetchTrainingPrice(
+  settings: Settings,
+  model: string,
+): Promise<ModelPriceInfo | null> {
+  const eff = effectiveConsoleGatewayConfig(settings);
+  const result = await callConsoleGateway(
+    { region: eff.consoleRegion, site: eff.consoleSite, switchAgent: eff.consoleSwitchAgent },
+    settings.timeout,
+    {
+      api: MODEL_LIST_API,
+      data: {
+        input: {
+          pageNo: 1,
+          pageSize: 10,
+          group: true,
+          model,
+          queryPrice: true,
+          querySampleCode: false,
+          queryGroupByModel: true,
+          queryQuota: false,
+          queryQpmInfo: false,
+          queryApplyStatus: false,
+          queryPermissions: false,
+          queryActivationStatus: false,
+        },
+      },
+    },
+  );
+  const responseData = unwrapResponse(result as Record<string, unknown>);
+  const list = (responseData.list as Record<string, unknown>[]) ?? [];
+  // The response is grouped; find the exact model in items.
+  for (const group of list) {
+    const items = (group.items as Record<string, unknown>[]) ?? [];
+    for (const item of items) {
+      if (item.model === model) {
+        const prices = (item.prices as ModelPriceInfo[]) ?? [];
+        return prices.find((entry) => entry.type === "ft") ?? null;
+      }
+    }
+    // Flat response fallback (no items nesting).
+    if (group.model === model) {
+      const prices = (group.prices as ModelPriceInfo[]) ?? [];
+      return prices.find((entry) => entry.type === "ft") ?? null;
+    }
+  }
+  return null;
+}
+
+/**
+ * Compute the actual training fee from the model catalog's "ft" price entry.
+ * Returns null when the price is unavailable (network error, model not in
+ * catalog, or no "ft" entry). Never throws.
+ *
+ * Only uses the public model catalog (model metadata) — does NOT call
+ * console-domain pricing APIs (modelCenter.getModelPrice). Models whose
+ * catalog entry lacks a "ft" price (e.g. CosyVoice) will simply omit the
+ * training_cost field until the platform adds it to the catalog.
+ */
+export async function computeActualFee(
+  settings: Settings,
+  model: string,
+  usageTokens: number,
+): Promise<ActualFee | null> {
+  try {
+    const ftEntry = await fetchTrainingPrice(settings, model);
+    const unitPrice = Number(ftEntry?.price);
+    if (!Number.isFinite(unitPrice) || unitPrice <= 0) return null;
+    const priceUnit = ftEntry?.priceUnit ?? "每百万tokens";
+    // Catalog price is yuan per million tokens.
+    const cost = (usageTokens / 1_000_000) * unitPrice;
+    return { cost: Number(cost.toFixed(4)), unitPrice, priceUnit };
+  } catch {
+    return null;
+  }
+}

packages/commands/src/commands/finetune/get.ts

@@ -1,5 +1,6 @@
-import { defineCommand, detectOutputFormat, getFineTune, type FlagsDef } from "bailian-cli-core";
-import { emitResult, emitBare, emitRequestId } from "bailian-cli-runtime";
+import { defineCommand, getFineTune, type FlagsDef } from "bailian-cli-core";
+import { emitResult } from "bailian-cli-runtime";
+import { computeActualFee } from "./fee.ts";
 
 const GET_FLAGS = {
   jobId: {
@@ -17,12 +18,11 @@ export default defineCommand({
   flags: GET_FLAGS,
   exampleArgs: ["--job-id ft-xxx", "--job-id ft-xxx --output json"],
   async run(ctx) {
-    const { identity, settings, flags } = ctx;
+    const { settings, flags } = ctx;
     const jobId = flags.jobId;
-    const format = detectOutputFormat(settings.output);
 
     if (settings.dryRun) {
-      emitResult({ action: "finetune.get", job_id: jobId }, format);
+      emitResult({ action: "finetune.get", job_id: jobId }, "json");
       return;
     }
 
@@ -30,18 +30,24 @@ export default defineCommand({
     const job = response.output ?? response.data;
 
     if (!job) {
-      emitBare(`No data returned for ${jobId}`);
+      emitResult({ job_id: jobId, error: "No data returned" }, "json");
       return;
     }
 
-    const hp = job.hyper_parameters;
+    const hyperParameters = job.hyper_parameters;
     const hyperParts: string[] = [];
-    if (hp?.n_epochs !== undefined) hyperParts.push(`n_epochs=${hp.n_epochs}`);
-    if (hp?.batch_size !== undefined) hyperParts.push(`batch_size=${hp.batch_size}`);
-    if (hp?.learning_rate !== undefined) hyperParts.push(`learning_rate=${hp.learning_rate}`);
-    if (hp?.max_length !== undefined) hyperParts.push(`max_length=${hp.max_length}`);
+    if (hyperParameters?.n_epochs !== undefined)
+      hyperParts.push(`n_epochs=${hyperParameters.n_epochs}`);
+    if (hyperParameters?.batch_size !== undefined)
+      hyperParts.push(`batch_size=${hyperParameters.batch_size}`);
+    if (hyperParameters?.learning_rate !== undefined)
+      hyperParts.push(`learning_rate=${hyperParameters.learning_rate}`);
+    if (hyperParameters?.max_length !== undefined)
+      hyperParts.push(`max_length=${hyperParameters.max_length}`);
 
-    const item = {
+    const usageTokens = typeof job.usage === "number" ? job.usage : undefined;
+
+    const item: Record<string, unknown> = {
       job_id: job.job_id ?? jobId,
       base_model: job.model ?? "",
       status: job.status ?? "",
@@ -53,29 +59,20 @@ export default defineCommand({
       model_name: job.model_name ?? "",
       created_at: job.create_time ?? job.gmt_create ?? "",
       updated_at: job.end_time ?? job.gmt_modified ?? "",
+      usage_tokens: usageTokens ?? "",
+      charge_type: typeof job.charge_type === "string" ? job.charge_type : "",
     };
 
-    if (format === "json") {
-      emitResult({ ...item, request_id: response.request_id }, format);
-      return;
+    // Actual fee: only when the platform reports a concrete token count
+    // (SUCCEEDED / CANCELED). Best-effort — silently omitted on lookup failure.
+    if (usageTokens !== undefined && usageTokens > 0 && job.model) {
+      const fee = await computeActualFee(settings, job.model, usageTokens);
+      if (fee) {
+        item.training_cost = fee.cost;
+        item.cost_basis = `${fee.unitPrice} 元/${fee.priceUnit}`;
+      }
     }
 
-    // text / quiet
-    emitBare(`job_id:           ${item.job_id}`);
-    if (item.base_model) emitBare(`base_model:       ${item.base_model}`);
-    if (item.status) emitBare(`status:           ${item.status}`);
-    if (item.training_type) emitBare(`training_type:    ${item.training_type}`);
-    if (item.training_files.length) emitBare(`training_files:   ${item.training_files.join(", ")}`);
-    if (item.validation_files.length)
-      emitBare(`validation_files: ${item.validation_files.join(", ")}`);
-    if (item.hyper_params) emitBare(`hyper_params:     ${item.hyper_params}`);
-    if (item.output_model)
-      emitBare(
-        `output_model:     ${item.output_model}  (→ ${identity.binName} deploy text create --model)`,
-      );
-    if (item.model_name) emitBare(`model_name:       ${item.model_name}`);
-    if (item.created_at) emitBare(`created_at:       ${item.created_at}`);
-    if (item.updated_at) emitBare(`updated_at:       ${item.updated_at}`);
-    emitRequestId(response.request_id, settings.quiet);
+    emitResult({ ...item, request_id: response.request_id }, "json");
   },
 });

packages/commands/src/commands/finetune/list.ts

@@ -1,5 +1,5 @@
-import { defineCommand, detectOutputFormat, listFineTunes, type FlagsDef } from "bailian-cli-core";
-import { emitResult, emitBare, emitRequestId, formatTable } from "bailian-cli-runtime";
+import { defineCommand, listFineTunes, type FlagsDef } from "bailian-cli-core";
+import { emitResult } from "bailian-cli-runtime";
 
 const LIST_FLAGS = {
   page: { type: "number", valueHint: "<n>", description: "Page number (default: 1)" },
@@ -13,71 +13,48 @@ const LIST_FLAGS = {
     valueHint: "<s>",
     description: "Filter by status (PENDING / RUNNING / SUCCEEDED / FAILED / CANCELED)",
   },
+  baseModel: {
+    type: "string",
+    valueHint: "<model>",
+    description: "Filter by base model ID (server-side)",
+  },
 } satisfies FlagsDef;
 
 export default defineCommand({
   description: "List fine-tune jobs",
   auth: "apiKey",
-  usageArgs: "[--page <n>] [--page-size <n>] [--status <s>]",
+  usageArgs: "[--page <n>] [--page-size <n>] [--status <s>] [--base-model <model>]",
   flags: LIST_FLAGS,
-  exampleArgs: ["", "--status RUNNING", "--page-size 20 --output json"],
+  exampleArgs: ["", "--status RUNNING", "--base-model qwen3-8b", "--page-size 20"],
   async run(ctx) {
-    const { identity, settings, flags } = ctx;
-    const format = detectOutputFormat(settings.output);
+    const { settings, flags } = ctx;
     const pageNo = flags.page;
     const pageSize = flags.pageSize;
     const status = flags.status || undefined;
+    const model = flags.baseModel || undefined;
 
     if (settings.dryRun) {
-      emitResult({ action: "finetune.list", page: pageNo, page_size: pageSize, status }, format);
+      emitResult(
+        { action: "finetune.list", page: pageNo, page_size: pageSize, status, model },
+        "json",
+      );
       return;
     }
 
-    const response = await listFineTunes(ctx.client, { pageNo, pageSize, status });
+    const response = await listFineTunes(ctx.client, { pageNo, pageSize, status, model });
     const payload = response.output ?? response.data;
     const jobs = payload?.jobs ?? [];
     const total = payload?.total;
 
-    const items = jobs.map((item) => ({
-      job_id: item.job_id ?? "",
-      base_model: item.model ?? "",
-      status: item.status ?? "",
-      training_type: item.training_type ?? "",
-      output_model: item.finetuned_output ?? "",
-      created_at: item.create_time ?? item.gmt_create ?? "",
+    const items = jobs.map((job) => ({
+      job_id: job.job_id ?? "",
+      base_model: job.model ?? "",
+      status: job.status ?? "",
+      training_type: job.training_type ?? "",
+      output_model: job.finetuned_output ?? "",
+      created_at: job.create_time ?? job.gmt_create ?? "",
     }));
 
-    if (format === "json") {
-      emitResult({ items, total, request_id: response.request_id }, format);
-      return;
-    }
-
-    // text / quiet
-    if (items.length === 0) {
-      emitBare("No fine-tune jobs found.");
-      return;
-    }
-    const headers = [
-      "JOB_ID",
-      "BASE_MODEL",
-      "STATUS",
-      "TRAINING_TYPE",
-      "OUTPUT_MODEL",
-      "CREATED_AT",
-    ];
-    const rows = items.map((i) => [
-      i.job_id,
-      i.base_model,
-      i.status,
-      i.training_type,
-      i.output_model,
-      i.created_at,
-    ]);
-    for (const line of formatTable(headers, rows)) emitBare(line);
-    if (total !== undefined) emitBare(`\nTotal: ${total}`);
-    emitBare(
-      `Tip: OUTPUT_MODEL is the input for \`${identity.binName} deploy text create --model\``,
-    );
-    emitRequestId(response.request_id, settings.quiet);
+    emitResult({ items, total, request_id: response.request_id }, "json");
   },
 });

packages/commands/src/commands/finetune/logs.ts

@@ -1,25 +1,24 @@
 import {
   defineCommand,
-  detectOutputFormat,
   getFineTuneLogs,
   type Client,
   type FineTuneLogEntry,
   type FlagsDef,
 } from "bailian-cli-core";
-import { emitResult, emitBare, emitRequestId } from "bailian-cli-runtime";
+import { emitResult } from "bailian-cli-runtime";
 
 /**
- * Render a single log entry as a single line (mirrors the flatten logic used
- * for non-search text output: prefer common fields, fall back to JSON).
+ * Render a single log entry as a single line (used for search matching:
+ * prefer common fields, fall back to JSON).
  */
 function renderEntry(entry: FineTuneLogEntry | string): string {
   if (typeof entry === "string") return entry;
   const record = entry as Record<string, unknown>;
-  const ts = (record.timestamp ?? record.time ?? record.create_time ?? "") as string;
+  const timestamp = (record.timestamp ?? record.time ?? record.create_time ?? "") as string;
   const level = (record.level ?? "") as string;
-  const msg = (record.message ?? record.msg ?? record.log ?? "") as string;
-  if (msg || ts || level) {
-    return [ts, level, msg].filter(Boolean).join("\t");
+  const message = (record.message ?? record.msg ?? record.log ?? "") as string;
+  if (message || timestamp || level) {
+    return [timestamp, level, message].filter(Boolean).join("\t");
   }
   return JSON.stringify(entry);
 }
@@ -48,16 +47,16 @@ async function fetchAllLogs(
   let total = 0;
   // Hard cap to avoid an unbounded loop if the server misreports `total`.
   const maxPages = 200;
-  for (let i = 0; i < maxPages; i++) {
+  for (let page = 0; page < maxPages; page++) {
     const response = await getFineTuneLogs(client, jobId, { pageNo, pageSize });
     const payload = response.output ?? response.data;
-    const page = payload?.logs ?? [];
+    const logs = payload?.logs ?? [];
     total = payload?.total ?? total;
-    if (page.length === 0) break;
-    entries.push(...page);
+    if (logs.length === 0) break;
+    entries.push(...logs);
     // Stop once we've collected everything the server claims exists.
     if (total && entries.length >= total) break;
-    if (page.length < pageSize) break;
+    if (logs.length < pageSize) break;
     pageNo++;
   }
   return { entries, total };
@@ -110,7 +109,6 @@ export default defineCommand({
     const pageSize = flags.pageSize;
     const search = flags.search || undefined;
     const tail = flags.tail;
-    const format = detectOutputFormat(settings.output);
 
     if (settings.dryRun) {
       emitResult(
@@ -122,7 +120,7 @@ export default defineCommand({
           search,
           tail,
         },
-        format,
+        "json",
       );
       return;
     }
@@ -147,18 +145,6 @@ export default defineCommand({
       const result =
         tailApplied !== undefined ? scanned.slice(scanned.length - tailApplied) : scanned;
 
-      if (settings.quiet || format === "text") {
-        if (result.length === 0) {
-          emitBare(search ? `No logs matched "${search}".` : "No logs returned.");
-          return;
-        }
-        for (const entry of result) emitBare(renderEntry(entry));
-        const parts: string[] = [`${result.length} shown`];
-        if (matched !== undefined) parts.push(`matched ${matched}`);
-        parts.push(`of ${entries.length}` + (total ? ` (total ${total})` : ""));
-        emitBare(`\n${parts.join(", ")}`);
-        return;
-      }
       emitResult(
         {
           ...(matched !== undefined ? { matched } : {}),
@@ -168,28 +154,13 @@ export default defineCommand({
           ...(tailApplied !== undefined ? { tail: tailApplied } : {}),
           logs: result,
         },
-        format,
+        "json",
       );
       return;
     }
 
     // Default: single page, verbatim response.
     const response = await getFineTuneLogs(ctx.client, jobId, { pageNo, pageSize });
-    const payload = response.output ?? response.data;
-    const logs = payload?.logs ?? [];
-
-    if (settings.quiet || format === "text") {
-      if (logs.length === 0) {
-        emitBare("No logs returned.");
-        return;
-      }
-      for (const entry of logs) {
-        emitBare(renderEntry(entry));
-      }
-      if (payload?.total !== undefined) emitBare(`\nTotal: ${payload.total}`);
-      emitRequestId(response.request_id, settings.quiet);
-    } else {
-      emitResult(response, format);
-    }
+    emitResult(response, "json");
   },
 });

packages/commands/src/commands/finetune/price.ts

@@ -0,0 +1,139 @@
+import {
+  defineCommand,
+  fetchTrainingModelPrice,
+  estimateSftDpoTokens,
+  estimateCptTokens,
+  BailianError,
+  ExitCode,
+  type FlagsDef,
+} from "bailian-cli-core";
+import { emitResult } from "bailian-cli-runtime";
+
+const PRICE_FLAGS = {
+  baseModel: {
+    type: "string",
+    valueHint: "<model>",
+    description: "Base model to fine-tune (e.g. qwen3-8b; not the output model name)",
+    required: true,
+  },
+  datasets: {
+    type: "string",
+    valueHint: "<ids>",
+    description: "Training dataset file IDs, comma-separated (required)",
+    required: true,
+  },
+  trainingType: {
+    type: "string",
+    valueHint: "<type>",
+    description: "Training type: sft | dpo | cpt (default: sft)",
+  },
+  nEpochs: {
+    type: "number",
+    valueHint: "<n>",
+    description: "Number of training epochs (default: 3)",
+  },
+} satisfies FlagsDef;
+
+const SUPPORTED_TRAINING_TYPES = ["sft", "dpo", "cpt"];
+
+// Fixed hyper-parameters used for estimation. Only n_epochs materially affects
+// the estimate; the rest are held at representative defaults (not exposed as
+// flags to keep the command surface minimal).
+const ESTIMATE_BATCH_SIZE = 16;
+const ESTIMATE_MAX_LENGTH = 8192;
+const DEFAULT_N_EPOCHS = 3;
+
+export default defineCommand({
+  description: "Estimate the training cost for a fine-tune job (token billing)",
+  auth: "console",
+  usageArgs: "--base-model <model> --datasets <ids> [--training-type <type>] [--n-epochs <n>]",
+  flags: PRICE_FLAGS,
+  exampleArgs: [
+    "--base-model qwen3-8b --datasets file-ft-xxx",
+    "--base-model qwen3-8b --datasets file-ft-xxx,file-ft-yyy --n-epochs 2",
+    "--base-model qwen3-8b --datasets file-ft-xxx --training-type cpt",
+  ],
+  notes: [
+    "Estimate only — the server computes token usage from the datasets; final cost is subject to the bill.",
+    "Covers token billing for sft / dpo / cpt. Training-unit (MTU) billing is not supported by this command.",
+    "Hyper-parameters other than --n-epochs are fixed at representative defaults for estimation.",
+  ],
+  async run(ctx) {
+    const { settings, flags } = ctx;
+    const model = flags.baseModel;
+    const datasetIds = flags.datasets
+      .split(",")
+      .map((datasetId) => datasetId.trim())
+      .filter(Boolean);
+    const trainingType = (flags.trainingType ?? "sft").toLowerCase();
+    const nEpochs = flags.nEpochs ?? DEFAULT_N_EPOCHS;
+
+    if (!SUPPORTED_TRAINING_TYPES.includes(trainingType)) {
+      throw new BailianError(
+        `Unsupported training type "${trainingType}". Supported: ${SUPPORTED_TRAINING_TYPES.join(", ")}.`,
+        ExitCode.USAGE,
+      );
+    }
+    if (datasetIds.length === 0) {
+      throw new BailianError("--datasets must contain at least one file ID.", ExitCode.USAGE);
+    }
+
+    if (settings.dryRun) {
+      emitResult(
+        { action: "finetune.price", model, datasets: datasetIds, trainingType, nEpochs },
+        "json",
+      );
+      return;
+    }
+
+    // Unit price (yuan per 千Token).
+    const priceInfo = await fetchTrainingModelPrice(ctx.client, model);
+    const unitPrice = Number(priceInfo.price);
+    if (!Number.isFinite(unitPrice)) {
+      throw new BailianError(
+        `No training price found for model "${model}".`,
+        ExitCode.GENERAL,
+        undefined,
+        { rawResponse: JSON.stringify(priceInfo) },
+      );
+    }
+
+    // Per-epoch token estimate (min/max range).
+    const estimate =
+      trainingType === "cpt"
+        ? await estimateCptTokens(ctx.client, model, datasetIds.join(","), nEpochs)
+        : await estimateSftDpoTokens(ctx.client, datasetIds, {
+            nEpochs,
+            batchSize: ESTIMATE_BATCH_SIZE,
+            maxLength: ESTIMATE_MAX_LENGTH,
+          });
+
+    const minPerEpoch = estimate.estimatedDatasetConsumedTokensMinPerEpoch ?? 0;
+    const maxPerEpoch = estimate.estimatedDatasetConsumedTokensMaxPerEpoch ?? 0;
+    const mixedMinPerEpoch = estimate.estimatedMixedConsumedTokensMinPerEpoch ?? 0;
+    const mixedMaxPerEpoch = estimate.estimatedMixedConsumedTokensMaxPerEpoch ?? 0;
+
+    const minTokens = (minPerEpoch + mixedMinPerEpoch) * nEpochs;
+    const maxTokens = (maxPerEpoch + mixedMaxPerEpoch) * nEpochs;
+    // price is yuan per 1000 tokens.
+    const minFee = (minTokens / 1000) * unitPrice;
+    const maxFee = (maxTokens / 1000) * unitPrice;
+
+    emitResult(
+      {
+        model,
+        training_type: trainingType,
+        n_epochs: nEpochs,
+        unit_price: unitPrice,
+        price_unit: priceInfo.priceUnit ?? "千Token",
+        estimated_tokens: { min: minTokens, max: maxTokens },
+        estimated_fee_yuan: {
+          min: Number(minFee.toFixed(4)),
+          max: Number(maxFee.toFixed(4)),
+        },
+        disclaimer: "Server-side estimate; final cost is subject to the bill.",
+      },
+      "json",
+    );
+  },
+});

packages/commands/src/commands/finetune/watch.ts

@@ -1,12 +1,12 @@
 import {
   defineCommand,
-  detectOutputFormat,
   getFineTune,
   BailianError,
   ExitCode,
   type FlagsDef,
 } from "bailian-cli-core";
-import { emitResult, emitBare, emitRequestId } from "bailian-cli-runtime";
+import { emitResult, emitBare } from "bailian-cli-runtime";
+import { computeActualFee } from "./fee.ts";
 
 const DEFAULT_INTERVAL_SEC = 10;
 const MIN_INTERVAL_SEC = 1;
@@ -103,7 +103,6 @@ export default defineCommand({
     const follow = flags.follow;
     const intervalSec = Math.max(MIN_INTERVAL_SEC, flags.interval ?? DEFAULT_INTERVAL_SEC);
     const pollTimeoutSec = flags.pollTimeout;
-    const format = detectOutputFormat(settings.output);
 
     if (settings.dryRun) {
       emitResult(
@@ -114,7 +113,7 @@ export default defineCommand({
           interval: intervalSec,
           timeout: pollTimeoutSec,
         },
-        format,
+        "json",
       );
       return;
     }
@@ -132,16 +131,24 @@ export default defineCommand({
       if (settings.quiet) {
         // Just the status word — ideal for `status=$(... finetune watch ... --quiet)`.
         emitBare(status || "UNKNOWN");
-      } else if (format === "text") {
-        emitBare(`${nowStamp()}  ${jobId}  ${status || "UNKNOWN"}`);
-        if (status === "SUCCEEDED") emitBare(`✓ ${jobId}  ${status}`);
-        emitRequestId(response.request_id, settings.quiet);
       } else {
-        // json: a compact, purpose-built status probe.
-        emitResult(
-          { job_id: jobId, status: status || "UNKNOWN", terminal, request_id: response.request_id },
-          format,
-        );
+        const output: Record<string, unknown> = {
+          job_id: jobId,
+          status: status || "UNKNOWN",
+          terminal,
+          request_id: response.request_id,
+        };
+        // Enrich terminal output with actual fee when usage is reported.
+        const usageTokens = typeof job?.usage === "number" ? job.usage : undefined;
+        if (terminal && usageTokens && usageTokens > 0 && job?.model) {
+          output.usage_tokens = usageTokens;
+          const fee = await computeActualFee(settings, job.model as string, usageTokens);
+          if (fee) {
+            output.training_cost = fee.cost;
+            output.cost_basis = `${fee.unitPrice} 元/${fee.priceUnit}`;
+          }
+        }
+        emitResult(output, "json");
       }
 
       if (terminal && status !== "SUCCEEDED") {
@@ -168,18 +175,28 @@ export default defineCommand({
         const job = response.output ?? response.data;
         const status = String(job?.status ?? "").toUpperCase();
 
-        if (format === "text" && !settings.quiet && status !== lastStatus) {
-          emitBare(`${nowStamp()}  ${jobId}  ${status || "UNKNOWN"}`);
+        if (!settings.quiet && status !== lastStatus) {
+          process.stderr.write(`${nowStamp()}  ${jobId}  ${status || "UNKNOWN"}\n`);
           lastStatus = status;
         }
 
         if (TERMINAL_STATUSES.has(status)) {
           const elapsed = Date.now() - startedAt;
-          if (format !== "text" || settings.quiet) {
-            emitResult(response, format);
-          } else if (status === "SUCCEEDED") {
-            emitBare(`\n✓ ${jobId}  ${status}  (elapsed ${formatElapsed(elapsed)})`);
-            emitRequestId(response.request_id, settings.quiet);
+          if (settings.quiet) {
+            emitBare(status || "UNKNOWN");
+          } else {
+            // Enrich the raw response with actual fee when usage is available.
+            const usageTokens = typeof job?.usage === "number" ? job.usage : undefined;
+            const enriched: Record<string, unknown> = { ...response };
+            if (usageTokens && usageTokens > 0 && job?.model) {
+              const fee = await computeActualFee(settings, job.model as string, usageTokens);
+              if (fee) {
+                enriched.training_cost = fee.cost;
+                enriched.usage_tokens = usageTokens;
+                enriched.cost_basis = `${fee.unitPrice} 元/${fee.priceUnit}`;
+              }
+            }
+            emitResult(enriched, "json");
           }
           if (status !== "SUCCEEDED") {
             throw new BailianError(
@@ -205,7 +222,7 @@ export default defineCommand({
       // Any other error (including the BailianError thrown above) propagates to
       // the central handler.
       if (controller.signal.aborted) {
-        emitBare("\nInterrupted.");
+        process.stderr.write("\nInterrupted.\n");
         return;
       }
       throw error;

packages/commands/src/commands/skill/init.ts

@@ -4,21 +4,12 @@ import {
   defineCommand,
   detectInstalledAgents,
   fetchSkillsIndex,
-  getSkillRegistryBaseUrl,
   installSkillWithFanout,
   readSkillLock,
   runWithConcurrency,
   writeSkillLock,
 } from "bailian-cli-core";
-import { emitBare, emitResult, formatTable } from "bailian-cli-runtime";
-
-interface InitOutcome {
-  name: string;
-  status: "installed" | "failed";
-  publishedAt?: string;
-  agents?: string[];
-  reason?: string;
-}
+import { emitBare, emitResult } from "bailian-cli-runtime";
 
 /** Prefix used to identify first-party Bailian skills in the registry. */
 const BAILIAN_PREFIX = "bailian-";
@@ -26,6 +17,22 @@ const BAILIAN_PREFIX = "bailian-";
 /** Max number of skills downloading/installing at the same time. */
 const INIT_CONCURRENCY = 3;
 
+/** Default output format when user does not pass --output explicitly. */
+const DEFAULT_FORMAT = "json";
+
+/** All status values used by skill init (per-skill outcome + aggregate result). */
+const STATUS = {
+  success: "success",
+  partial: "partial",
+  failed: "failed",
+} as const;
+
+interface InitOutcome {
+  name: string;
+  status: typeof STATUS.success | typeof STATUS.failed;
+  reason?: string;
+}
+
 export default defineCommand({
   description: "Install all bailian-* skills (one-shot bootstrap for new environments)",
   auth: "none",
@@ -36,7 +43,7 @@ export default defineCommand({
     "Equivalent to: bl skill add --all (filtered to bailian-* skills)",
   ],
   async run(ctx) {
-    const format = ctx.settings.outputExplicit ? ctx.settings.output : "json";
+    const format = ctx.settings.outputExplicit ? ctx.settings.output : DEFAULT_FORMAT;
     const index = await fetchSkillsIndex();
 
     // Discover all bailian-* skills from the live registry index
@@ -55,16 +62,11 @@ export default defineCommand({
           lock.skills[name]?.links ?? [],
         );
         lock.skills[name] = record.lockEntry;
-        return {
-          name,
-          status: "installed",
-          publishedAt: entry.publishedAt,
-          agents: record.linkedAgents,
-        };
+        return { name, status: STATUS.success };
       } catch (err) {
         return {
           name,
-          status: "failed",
+          status: STATUS.failed,
           reason: err instanceof Error ? err.message : String(err),
         };
       }
@@ -72,30 +74,46 @@ export default defineCommand({
     const results = await runWithConcurrency(tasks, INIT_CONCURRENCY);
     writeSkillLock(lock);
 
-    if (format === "json") {
-      emitResult(
-        {
-          registry: getSkillRegistryBaseUrl(),
-          agents: agents.map((agent) => agent.id),
-          skills: results,
-        },
-        format,
-      );
+    const installed = results.filter((result) => result.status === STATUS.success);
+    const failed = results.filter((result) => result.status === STATUS.failed);
+
+    const status =
+      failed.length === 0
+        ? STATUS.success
+        : installed.length === 0
+          ? STATUS.failed
+          : STATUS.partial;
+
+    if (format === DEFAULT_FORMAT) {
+      const agentIds = agents.map((agent) => agent.id);
+      const payload: Record<string, unknown> = {
+        status,
+        skills: installed.map((result) => result.name),
+      };
+      if (failed.length > 0) {
+        payload.failed = failed.map((result) => ({
+          name: result.name,
+          reason: result.reason,
+          agents: agentIds,
+        }));
+      }
+      emitResult(payload, format);
     } else if (results.length === 0) {
       emitBare("No bailian-* skills found in the registry.");
     } else {
-      const rows = results.map((result) => [
-        result.name,
-        result.status,
-        result.publishedAt ? result.publishedAt.slice(0, 10) : "-",
-        result.status === "installed" ? result.agents?.join(", ") || "-" : (result.reason ?? "-"),
-      ]);
-      for (const line of formatTable(["NAME", "STATUS", "PUBLISHED", "AGENTS / REASON"], rows)) {
-        emitBare(line);
+      emitBare(
+        status === STATUS.success
+          ? `Installed ${installed.length} bailian-* skills.`
+          : `Installed ${installed.length}/${results.length} bailian-* skills.`,
+      );
+      if (failed.length > 0) {
+        emitBare("Failed:");
+        for (const item of failed) {
+          emitBare(`  ${item.name}: ${item.reason}`);
+        }
       }
     }
 
-    const failed = results.filter((result) => result.status === "failed");
     if (failed.length > 0) {
       throw new BailianError(
         `${failed.length}/${results.length} skill(s) failed to install`,

packages/commands/src/commands/video/generate.ts

@@ -1,6 +1,7 @@
 import {
   defineCommand,
   videoGeneratePath,
+  image2videoPath,
   taskPath,
   detectOutputFormat,
   type DashScopeVideoRequest,
@@ -43,6 +44,11 @@ export default defineCommand({
       valueHint: "<url>",
       description: "Input image URL for image-to-video generation",
     },
+    lastFrame: {
+      type: "string",
+      valueHint: "<url>",
+      description: "Last frame image URL (with --image, enables kf2v first+last frame mode)",
+    },
     negativePrompt: {
       type: "string",
       valueHint: "<text>",
@@ -110,12 +116,20 @@ export default defineCommand({
     const format = detectOutputFormat(settings.output);
 
     const imageUrl = flags.image;
+    const lastFrameUrl = flags.lastFrame as string | undefined;
 
     // Auto-upload local image file for i2v
     let resolvedImageUrl: string | undefined;
     if (imageUrl) {
       resolvedImageUrl = await ctx.client.resolveImageInput(imageUrl, model);
     }
+    let resolvedLastFrameUrl: string | undefined;
+    if (lastFrameUrl) {
+      resolvedLastFrameUrl = await ctx.client.resolveImageInput(lastFrameUrl, model);
+    }
+
+    // kf2v mode: both --image and --last-frame provided.
+    const isKf2v = Boolean(resolvedImageUrl && resolvedLastFrameUrl);
 
     const watermark = resolveWatermark(flags.watermark);
     const promptExtend = resolveBooleanFlag(flags.promptExtend, undefined, "prompt-extend");
@@ -125,10 +139,16 @@ export default defineCommand({
       input: {
         prompt: prompt,
         negative_prompt: flags.negativePrompt || undefined,
-        // i2v models (happyhorse-1.1-i2v) require input.media with type 'first_frame'
-        ...(resolvedImageUrl
-          ? { media: [{ type: "first_frame" as const, url: resolvedImageUrl }] }
-          : {}),
+        // kf2v: first+last frame flat fields via image2video endpoint.
+        // wan2.1~2.6 i2v: flat img_url via video-generation endpoint.
+        // wan2.7+ / happyhorse i2v: media[] via video-generation endpoint.
+        ...(isKf2v
+          ? { first_frame_url: resolvedImageUrl, last_frame_url: resolvedLastFrameUrl }
+          : resolvedImageUrl
+            ? /wan[x]?2\.[1-6]/i.test(model)
+              ? { img_url: resolvedImageUrl }
+              : { media: [{ type: "first_frame" as const, url: resolvedImageUrl }] }
+            : {}),
       },
       parameters: {
         resolution: flags.resolution || undefined,
@@ -141,15 +161,28 @@ export default defineCommand({
     };
 
     if (settings.dryRun) {
-      const previewBody = resolvedImageUrl
-        ? {
-            ...body,
-            input: {
-              ...body.input,
-              media: [{ type: "first_frame" as const, url: redactDataUri(resolvedImageUrl) }],
-            },
-          }
-        : body;
+      let previewBody = body;
+      if (isKf2v) {
+        previewBody = {
+          ...body,
+          input: {
+            ...body.input,
+            first_frame_url: redactDataUri(resolvedImageUrl ?? ""),
+            last_frame_url: redactDataUri(resolvedLastFrameUrl ?? ""),
+          },
+        };
+      } else if (resolvedImageUrl) {
+        const redactedUrl = redactDataUri(resolvedImageUrl);
+        previewBody = {
+          ...body,
+          input: {
+            ...body.input,
+            ...(/wan[x]?2\.[1-6]/i.test(model)
+              ? { img_url: redactedUrl }
+              : { media: [{ type: "first_frame" as const, url: redactedUrl }] }),
+          },
+        };
+      }
       emitResult({ request: previewBody }, format);
       return;
     }
@@ -162,7 +195,7 @@ export default defineCommand({
       settings,
       () =>
         ctx.client.requestJson<DashScopeAsyncResponse>({
-          path: videoGeneratePath(),
+          path: isKf2v ? image2videoPath() : videoGeneratePath(),
           method: "POST",
           body,
           async: true,

packages/commands/src/index.ts

@@ -71,6 +71,7 @@ export {
   finetuneTextCreate,
   finetuneAudioCreate,
   finetuneImageCreate,
+  finetuneVideoCreate,
 } from "./commands/finetune/create.ts";
 export { default as finetuneList } from "./commands/finetune/list.ts";
 export { default as finetuneGet } from "./commands/finetune/get.ts";
@@ -81,6 +82,7 @@ export { default as finetuneCheckpoints } from "./commands/finetune/checkpoints.
 export { default as finetuneExport } from "./commands/finetune/export.ts";
 export { default as finetuneWatch } from "./commands/finetune/watch.ts";
 export { default as finetuneCapability } from "./commands/finetune/capability.ts";
+export { default as finetunePrice } from "./commands/finetune/price.ts";
 export {
   deployTextCreate,
   deployAudioCreate,
@@ -92,6 +94,8 @@ export { default as deployModels } from "./commands/deploy/models.ts";
 export { default as deployScale } from "./commands/deploy/scale.ts";
 export { default as deployUpdate } from "./commands/deploy/update.ts";
 export { default as deployDelete } from "./commands/deploy/delete.ts";
+export { default as deployPause } from "./commands/deploy/pause.ts";
+export { default as deployResume } from "./commands/deploy/resume.ts";
 export { default as tokenPlanListSeats } from "./commands/token-plan/list-seats.ts";
 export { default as tokenPlanCreateKey } from "./commands/token-plan/create-key.ts";
 export { default as tokenPlanAssignSeats } from "./commands/token-plan/assign-seats.ts";

packages/commands/tests/e2e/deploy.e2e.test.ts

@@ -30,7 +30,7 @@ describe.skipIf(!isDashScopeE2EReady())("e2e: deploy (offline)", () => {
       "--help",
     ]);
     expect(exitCode, stderr).toBe(0);
-    expect(stderr).toMatch(/--model|--name/i);
+    expect(stderr).toMatch(/--model-name|--display-name/i);
   });
 
   test("deploy create --dry-run 构造 lora 部署请求体", async () => {
@@ -38,9 +38,9 @@ describe.skipIf(!isDashScopeE2EReady())("e2e: deploy (offline)", () => {
       "deploy",
       "text",
       "create",
-      "--model",
+      "--model-name",
       "qwen-plus-2025-12-01",
-      "--name",
+      "--display-name",
       "my-qwen-plus",
       "--dry-run",
       "--output",
@@ -68,9 +68,9 @@ describe.skipIf(!isDashScopeE2EReady())("e2e: deploy (offline)", () => {
       "deploy",
       "text",
       "create",
-      "--model",
+      "--model-name",
       "qwen3-8b",
-      "--name",
+      "--display-name",
       "my-qwen3-mu",
       "--plan",
       "mu",
@@ -102,9 +102,9 @@ describe.skipIf(!isDashScopeE2EReady())("e2e: deploy (offline)", () => {
       "deploy",
       "audio",
       "create",
-      "--model",
+      "--model-name",
       "my-cosyvoice-ft",
-      "--name",
+      "--display-name",
       "my-tts",
       "--dry-run",
       "--output",

packages/commands/tests/e2e/finetune.e2e.test.ts

@@ -31,7 +31,7 @@ describe.skipIf(!isDashScopeE2EReady())("e2e: finetune (offline)", () => {
       "--help",
     ]);
     expect(exitCode, stderr).toBe(0);
-    expect(stderr).toMatch(/--model|--datasets/i);
+    expect(stderr).toMatch(/--base-model|--datasets/i);
   });
 
   test("finetune create --dry-run 构造 SFT 默认请求体", async () => {
@@ -39,7 +39,7 @@ describe.skipIf(!isDashScopeE2EReady())("e2e: finetune (offline)", () => {
       "finetune",
       "text",
       "create",
-      "--model",
+      "--base-model",
       "qwen3-8b",
       "--datasets",
       "file-aaa,file-bbb",
@@ -73,7 +73,7 @@ describe.skipIf(!isDashScopeE2EReady())("e2e: finetune (offline)", () => {
       "finetune",
       "text",
       "create",
-      "--model",
+      "--base-model",
       "qwen3-8b",
       "--datasets",
       "file-aaa",
@@ -135,7 +135,7 @@ describe.skipIf(!isDashScopeE2EReady())("e2e: finetune (offline)", () => {
         "finetune",
         "text",
         "create",
-        "--model",
+        "--base-model",
         "qwen3-8b",
         "--datasets",
         "file-aaa",
@@ -157,7 +157,7 @@ describe.skipIf(!isDashScopeE2EReady())("e2e: finetune (offline)", () => {
       "finetune",
       "text",
       "create",
-      "--model",
+      "--base-model",
       "qwen3-8b",
       "--datasets",
       "file-aaa",
@@ -176,7 +176,7 @@ describe.skipIf(!isDashScopeE2EReady())("e2e: finetune (offline)", () => {
       "finetune",
       "text",
       "create",
-      "--model",
+      "--base-model",
       "qwen3-8b",
       "--datasets",
       `${localPath},file-bbb`,
@@ -207,7 +207,7 @@ describe.skipIf(!isDashScopeE2EReady())("e2e: finetune (offline)", () => {
       "finetune",
       "text",
       "create",
-      "--model",
+      "--base-model",
       "qwen3-8b",
       "--datasets",
       " , ",
@@ -228,7 +228,7 @@ describe.skipIf(!isDashScopeE2EReady())("e2e: finetune (offline)", () => {
       "finetune",
       "text",
       "create",
-      "--model",
+      "--base-model",
       "qwen3-8b",
       "--datasets",
       localPath,
@@ -250,7 +250,7 @@ describe.skipIf(!isDashScopeE2EReady())("e2e: finetune (offline)", () => {
       "finetune",
       "text",
       "create",
-      "--model",
+      "--base-model",
       "qwen3-8b",
       "--datasets",
       localPath,
@@ -272,7 +272,7 @@ describe.skipIf(!isDashScopeE2EReady())("e2e: finetune (offline)", () => {
     ["cancel", ["--job-id", "ft-xxx"]],
     ["delete", ["--job-id", "ft-xxx"]],
     ["watch", ["--job-id", "ft-xxx"]],
-    ["capability", ["--model", "qwen3-8b"]],
+    ["capability", ["--base-model", "qwen3-8b"]],
   ])("finetune %s --dry-run 发出结构化动作", async (sub, extra) => {
     const { stdout, stderr, exitCode } = await runCommandE2e(FINETUNE_ROUTES, [
       "finetune",
@@ -292,7 +292,7 @@ describe.skipIf(!isDashScopeE2EReady())("e2e: finetune (offline)", () => {
       "finetune",
       "text",
       "create",
-      "--model",
+      "--base-model",
       "qwen3-8b",
       "--datasets",
       " file-a , ,file-b ",
@@ -314,7 +314,7 @@ describe.skipIf(!isDashScopeE2EReady())("e2e: finetune (offline)", () => {
       "finetune",
       "audio",
       "create",
-      "--model",
+      "--base-model",
       "cosyvoice-v3-flash",
       "--datasets",
       "file-audio",
@@ -343,7 +343,7 @@ describe.skipIf(!isDashScopeE2EReady())("e2e: finetune (offline)", () => {
       "--help",
     ]);
     expect(exitCode, stderr).toBe(0);
-    expect(stderr).toMatch(/--model|--datasets/i);
+    expect(stderr).toMatch(/--base-model|--datasets/i);
     expect(stderr).not.toMatch(/--training-type|--n-epochs|--batch-size|--max-length/);
   });
 
@@ -352,7 +352,7 @@ describe.skipIf(!isDashScopeE2EReady())("e2e: finetune (offline)", () => {
       "finetune",
       "image",
       "create",
-      "--model",
+      "--base-model",
       "wan2.7-image-pro",
       "--datasets",
       "file-image",
@@ -365,6 +365,104 @@ describe.skipIf(!isDashScopeE2EReady())("e2e: finetune (offline)", () => {
     expect(data.action).toBe("finetune.create");
     expect(data.body.training_type).toBe("efficient_sft");
   });
+
+  test("finetune video create --help 暴露视频超参且不含文本超参", async () => {
+    // Video exposes --n-epochs / --batch-size / --learning-rate; the text-only
+    // --training-type / --max-length surface is not offered.
+    const { stderr, exitCode } = await runCommandE2e(FINETUNE_ROUTES, [
+      "finetune",
+      "video",
+      "create",
+      "--help",
+    ]);
+    expect(exitCode, stderr).toBe(0);
+    expect(stderr).toMatch(/--base-model/);
+    expect(stderr).toMatch(/--n-epochs/);
+    expect(stderr).toMatch(/--batch-size/);
+    expect(stderr).toMatch(/--learning-rate/);
+    expect(stderr).not.toMatch(/--training-type|--max-length/);
+  });
+
+  test("finetune video create --datasets 缺失时退出为用法错误 (2)", async () => {
+    const { stderr, exitCode } = await runCommandE2e(FINETUNE_ROUTES, [
+      "finetune",
+      "video",
+      "create",
+      "--base-model",
+      "wan2.7-i2v",
+      "--quiet",
+    ]);
+    expect(exitCode).toBe(2);
+    expect(stderr).toMatch(/--datasets|Missing required/i);
+  });
+
+  test.each([
+    // Model-family-specific defaults resolved by the sft-lora video profile.
+    ["wan2.7-i2v", 1, 102400],
+    ["wan2.5-i2v-preview", 4, 36864],
+    ["wan2.2-kf2v-flash", 4, 262144],
+  ])(
+    "finetune video create --dry-run %s 解析 batch_size=%i / max_pixels=%i",
+    async (baseModel, batchSize, maxPixels) => {
+      const { stdout, stderr, exitCode } = await runCommandE2e(FINETUNE_ROUTES, [
+        "finetune",
+        "video",
+        "create",
+        "--base-model",
+        baseModel,
+        "--datasets",
+        "file-video",
+        "--dry-run",
+        "--output",
+        "json",
+      ]);
+      expect(exitCode, stderr).toBe(0);
+      const data = parseStdoutJson<{
+        action: string;
+        body: {
+          model: string;
+          training_type: string;
+          hyper_parameters: Record<string, unknown>;
+        };
+      }>(stdout);
+      expect(data.action).toBe("finetune.create");
+      expect(data.body.model).toBe(baseModel);
+      expect(data.body.training_type).toBe("efficient_sft");
+      expect(data.body.hyper_parameters.batch_size).toBe(batchSize);
+      expect(data.body.hyper_parameters.max_pixels).toBe(maxPixels);
+      expect(data.body.hyper_parameters.learning_rate).toBe("2e-5");
+      expect(data.body.hyper_parameters.lora_rank).toBe(32);
+    },
+  );
+
+  test("finetune video create --dry-run 转发超参覆盖且不做 clamp", async () => {
+    const { stdout, stderr, exitCode } = await runCommandE2e(FINETUNE_ROUTES, [
+      "finetune",
+      "video",
+      "create",
+      "--base-model",
+      "wan2.7-i2v",
+      "--datasets",
+      "file-video",
+      "--n-epochs",
+      "100",
+      "--batch-size",
+      "2",
+      "--learning-rate",
+      "1e-5",
+      "--dry-run",
+      "--output",
+      "json",
+    ]);
+    expect(exitCode, stderr).toBe(0);
+    const data = parseStdoutJson<{
+      body: { hyper_parameters: Record<string, unknown> };
+    }>(stdout);
+    // Video overrides are forwarded verbatim (no [8, 1024] text clamp).
+    expect(data.body.hyper_parameters.n_epochs).toBe(100);
+    expect(data.body.hyper_parameters.batch_size).toBe(2);
+    expect(data.body.hyper_parameters.learning_rate).toBe("1e-5");
+  });
 });
 
 describe.skipIf(!isDashScopeE2EReady())("e2e: finetune (DashScope)", () => {

packages/commands/tests/e2e/topic-routes.ts

@@ -145,6 +145,7 @@ export const FINETUNE_ROUTES: E2eRouteExports = {
   "finetune text create": "finetuneTextCreate",
   "finetune audio create": "finetuneAudioCreate",
   "finetune image create": "finetuneImageCreate",
+  "finetune video create": "finetuneVideoCreate",
   "finetune list": "finetuneList",
   "finetune get": "finetuneGet",
   "finetune cancel": "finetuneCancel",

packages/commands/tests/e2e/video-generate-i2v.e2e.test.ts

@@ -112,6 +112,62 @@ describe("e2e: video generate (i2v)", () => {
     }>(stdout);
     expect(data.request?.input?.media?.[0]?.url).toBe("data:image/png;base64,<omitted>");
   });
+
+  test.each([
+    // wan2.1~2.6 (legacy) use flat img_url; wan2.7+ and happyhorse use media[].
+    ["wan2.5-i2v-preview", "img_url"],
+    ["wan2.6-i2v", "img_url"],
+    ["wan2.7-i2v", "media"],
+    ["happyhorse-1.1-i2v", "media"],
+  ])("video generate --dry-run %s 首帧走 %s 字段", async (model, field) => {
+    const configDir = makeE2eOutputDir(`video-i2v-input-shape-${model}`);
+    writeFileSync(
+      join(configDir, "config.json"),
+      JSON.stringify({
+        "token-plan": {
+          api_key: "sk-sp-e2e-placeholder",
+          base_url: "https://token-plan.cn-beijing.maas.aliyuncs.com",
+        },
+      }),
+    );
+
+    const { stdout, stderr, exitCode } = await runCommandE2e(
+      VIDEO_ROUTES,
+      [
+        "video",
+        "generate",
+        "--config",
+        "token-plan",
+        "--dry-run",
+        "--model",
+        model,
+        "--image",
+        "https://example.com/placeholder.png",
+        "--prompt",
+        "干跑校验",
+        "--output",
+        "json",
+      ],
+      {
+        BAILIAN_CONFIG_DIR: configDir,
+        DASHSCOPE_API_KEY: "",
+        DASHSCOPE_BASE_URL: "",
+      },
+    );
+    expect(exitCode, stderr).toBe(0);
+    const data = parseStdoutJson<{
+      request?: {
+        input?: { img_url?: string; media?: Array<{ type?: string; url?: string }> };
+      };
+    }>(stdout);
+    if (field === "img_url") {
+      expect(data.request?.input?.img_url).toBe("https://example.com/placeholder.png");
+      expect(data.request?.input?.media).toBeUndefined();
+    } else {
+      expect(data.request?.input?.media?.[0]?.type).toBe("first_frame");
+      expect(data.request?.input?.img_url).toBeUndefined();
+    }
+  });
 });
 
 describe.skipIf(!isBailianE2EVideoEnabled() || !isDashScopeE2EReady())(

packages/core/package.json

@@ -1,6 +1,6 @@
 {
   "name": "bailian-cli-core",
-  "version": "1.15.0",
+  "version": "1.15.1",
   "description": "Core SDK for bailian-cli. See https://www.npmjs.com/package/bailian-cli for usage.",
   "homepage": "https://bailian.console.aliyun.com/cli",
   "bugs": {

packages/core/src/client/endpoints.ts

@@ -37,6 +37,11 @@ export function videoGeneratePath(): string {
   return "/api/v1/services/aigc/video-generation/video-synthesis";
 }
 
+/** POST /api/v1/services/aigc/image2video/video-synthesis — kf2v (first+last frame). */
+export function image2videoPath(): string {
+  return "/api/v1/services/aigc/image2video/video-synthesis";
+}
+
 // ---- Async Task Query ----
 export function taskPath(taskId: string): string {
   return `/api/v1/tasks/${encodeURIComponent(taskId)}`;

packages/core/src/client/index.ts

@@ -22,6 +22,7 @@ export {
   taskPath,
   userProfilePath,
   videoGeneratePath,
+  image2videoPath,
 } from "./endpoints.ts";
 export {
   isLegacyImage2ImageModel,

packages/core/src/dataset/index.ts

@@ -7,6 +7,7 @@ export {
   registerValidator,
   listSupportedFormats,
   MAX_DATASET_BYTES,
+  MAX_CPT_BYTES,
   MAX_MEDIA_ZIP_BYTES,
   parseDatasetSchemaFlag,
   formatIssue,

packages/core/src/dataset/validate/common.ts

@@ -12,18 +12,24 @@ import { ExitCode } from "../../errors/codes.ts";
 import type { DatasetSchema, ValidationIssue, ValidationStats } from "./types.ts";
 
 /**
- * The platform caps dataset uploads at 300MB per file. `bl dataset upload`
- * enforces this client-side so users learn early. Update if the platform
- * raises the cap or differentiates per-purpose limits.
+ * The platform caps SFT/DPO text dataset uploads at 200MB per file.
+ * `bl dataset upload` enforces this client-side so users learn early.
+ * CPT uses 300MB (see MAX_CPT_BYTES); API general upload is also 300MB.
  */
-export const MAX_DATASET_BYTES = 300 * 1024 * 1024;
+export const MAX_DATASET_BYTES = 200 * 1024 * 1024;
 
 /**
- * Image / video ZIP size cap — 1 GB per the platform docs (vs 300 MB for
- * text / audio). Used by `bl dataset upload` for media schemas and by the
- * `sft-lora` training profile for image / video validation.
+ * CPT text dataset size cap — 300 MB per the platform docs.
+ * CPT requires at least 50M tokens; larger files are expected.
  */
-export const MAX_MEDIA_ZIP_BYTES = 1024 * 1024 * 1024;
+export const MAX_CPT_BYTES = 300 * 1024 * 1024;
+
+/**
+ * Image / video ZIP size cap — 2 GB per the platform docs. Used by
+ * `bl dataset upload` for media schemas and by the `sft-lora` training
+ * profile for image / video validation.
+ */
+export const MAX_MEDIA_ZIP_BYTES = 2 * 1024 * 1024 * 1024;
 
 export interface PreflightResult {
   bytes: number;

packages/core/src/dataset/validate/index.ts

@@ -4,7 +4,12 @@ export {
   registerValidator,
   listSupportedFormats,
 } from "./registry.ts";
-export { MAX_DATASET_BYTES, MAX_MEDIA_ZIP_BYTES, parseDatasetSchemaFlag } from "./common.ts";
+export {
+  MAX_DATASET_BYTES,
+  MAX_CPT_BYTES,
+  MAX_MEDIA_ZIP_BYTES,
+  parseDatasetSchemaFlag,
+} from "./common.ts";
 export { formatIssue } from "./format.ts";
 export type {
   ValidatorSpec,

packages/core/src/dataset/validate/schemas/chatml.ts

@@ -5,12 +5,281 @@
  * and no more specific schema matches, ChatML is selected. `inspectMessageObject`
  * lives here because it is the canonical per-message check; the DPO schema
  * imports it to validate `chosen` / `rejected` preference messages.
+ *
+ * Content format: supports both legacy plain-string content (`"content": "…"`)
+ * and the current platform array format (`"content": [{"text": "…"}, …]`).
+ * The array format may also carry `image` / `video` items for VL multimodal
+ * understanding data.
+ *
+ * Tool calling: supports `role: "tool"` messages with `tool_call_id`, and
+ * `assistant.tool_calls` arrays. Validates id correspondence.
  */
 import { makeIssue } from "../common.ts";
 import type { ValidationIssue } from "../types.ts";
 import type { RecordSchemaSpec } from "./types.ts";
 
-const VALID_ROLES = new Set(["system", "user", "assistant"]);
+const VALID_ROLES = new Set(["system", "user", "assistant", "tool"]);
+
+/** Platform bounds for video sampling rate params (`fps` / `sample_fps`). */
+const VIDEO_FPS_MIN = 0.1;
+const VIDEO_FPS_MAX = 10;
+
+/**
+ * Validate the sampling/clipping params carried by a video content item.
+ * Mode rules (platform spec):
+ *  - path mode (video: string): `fps`, `video_start`, `video_end` allowed; `sample_fps` is not
+ *  - frame-list mode (video: string[]): `sample_fps` allowed; `fps` / `video_start` / `video_end` are not
+ * `fps` / `sample_fps` must be numbers within [0.1, 10] when present.
+ */
+function inspectVideoParams(
+  item: Record<string, unknown>,
+  isFrameList: boolean,
+  lineNo: number,
+  itemPath: string,
+): ValidationIssue[] {
+  const out: ValidationIssue[] = [];
+  const checkFpsRange = (field: "fps" | "sample_fps"): void => {
+    if (!(field in item)) return;
+    const value = item[field];
+    if (typeof value !== "number" || value < VIDEO_FPS_MIN || value > VIDEO_FPS_MAX) {
+      out.push(
+        makeIssue(
+          "error",
+          "INVALID_VIDEO_FPS",
+          `"${field}" must be a number between ${VIDEO_FPS_MIN} and ${VIDEO_FPS_MAX} (got ${JSON.stringify(value)}).`,
+          { line: lineNo, path: `${itemPath}.${field}` },
+        ),
+      );
+    }
+  };
+  checkFpsRange("fps");
+  checkFpsRange("sample_fps");
+
+  const wrongModeFields = isFrameList ? ["fps", "video_start", "video_end"] : ["sample_fps"];
+  const modeName = isFrameList ? "frame-list" : "file-path";
+  for (const field of wrongModeFields) {
+    if (field in item) {
+      out.push(
+        makeIssue(
+          "warning",
+          "VIDEO_PARAM_MODE_MISMATCH",
+          `"${field}" does not apply to ${modeName} video mode and will be ignored by the platform.`,
+          { line: lineNo, path: `${itemPath}.${field}` },
+        ),
+      );
+    }
+  }
+
+  for (const field of ["video_start", "video_end"] as const) {
+    if (field in item && !isFrameList && typeof item[field] !== "number") {
+      out.push(
+        makeIssue("error", "INVALID_VIDEO_CLIP_TIME", `"${field}" must be a number (seconds).`, {
+          line: lineNo,
+          path: `${itemPath}.${field}`,
+        }),
+      );
+    }
+  }
+  return out;
+}
+
+/**
+ * Validate a content field that may be:
+ *  - A plain string (legacy format)
+ *  - An array of content items: `[{text: "…"}, {image: "…"}, {video: "…"|"…"}, …]`
+ *
+ * Returns issues found. `path` scopes the location for error reporting.
+ */
+export function inspectContentField(
+  content: unknown,
+  lineNo: number,
+  path: string,
+): ValidationIssue[] {
+  const out: ValidationIssue[] = [];
+  if (typeof content === "string") {
+    // Legacy string format — always valid.
+    return out;
+  }
+  if (!Array.isArray(content)) {
+    out.push(
+      makeIssue(
+        "error",
+        "INVALID_CONTENT",
+        `"content" must be a string or an array of content items (got ${typeof content}).`,
+        { line: lineNo, path },
+      ),
+    );
+    return out;
+  }
+  if (content.length === 0) {
+    out.push(
+      makeIssue("error", "EMPTY_CONTENT_ARRAY", `"content" array must not be empty.`, {
+        line: lineNo,
+        path,
+      }),
+    );
+    return out;
+  }
+  for (let idx = 0; idx < content.length; idx++) {
+    const item = content[idx];
+    const itemPath = `${path}[${idx}]`;
+    if (item === null || typeof item !== "object" || Array.isArray(item)) {
+      out.push(
+        makeIssue("error", "INVALID_CONTENT_ITEM", `Content item must be an object.`, {
+          line: lineNo,
+          path: itemPath,
+        }),
+      );
+      continue;
+    }
+    const obj = item as Record<string, unknown>;
+    const hasText = "text" in obj;
+    const hasImage = "image" in obj;
+    const hasVideo = "video" in obj;
+    if (!hasText && !hasImage && !hasVideo) {
+      out.push(
+        makeIssue(
+          "error",
+          "CONTENT_ITEM_NO_KNOWN_FIELD",
+          `Content item must contain at least one of: "text", "image", "video".`,
+          { line: lineNo, path: itemPath },
+        ),
+      );
+      continue;
+    }
+    if (hasText && typeof obj.text !== "string") {
+      out.push(
+        makeIssue("error", "INVALID_CONTENT_TEXT", `"text" in content item must be a string.`, {
+          line: lineNo,
+          path: `${itemPath}.text`,
+        }),
+      );
+    }
+    if (hasImage && typeof obj.image !== "string") {
+      out.push(
+        makeIssue("error", "INVALID_CONTENT_IMAGE", `"image" in content item must be a string.`, {
+          line: lineNo,
+          path: `${itemPath}.image`,
+        }),
+      );
+    }
+    if (hasVideo) {
+      // video can be a string (file path) or an array of strings (frame list)
+      const video = obj.video;
+      if (typeof video !== "string" && !Array.isArray(video)) {
+        out.push(
+          makeIssue(
+            "error",
+            "INVALID_CONTENT_VIDEO",
+            `"video" in content item must be a string (file path) or an array of strings (frame list).`,
+            { line: lineNo, path: `${itemPath}.video` },
+          ),
+        );
+      } else {
+        if (Array.isArray(video)) {
+          for (let frameIdx = 0; frameIdx < video.length; frameIdx++) {
+            if (typeof video[frameIdx] !== "string") {
+              out.push(
+                makeIssue(
+                  "error",
+                  "INVALID_VIDEO_FRAME",
+                  `Video frame list item at index ${frameIdx} must be a string.`,
+                  { line: lineNo, path: `${itemPath}.video[${frameIdx}]` },
+                ),
+              );
+            }
+          }
+        }
+        out.push(...inspectVideoParams(obj, Array.isArray(video), lineNo, itemPath));
+      }
+    }
+  }
+  return out;
+}
+
+/**
+ * Validate `tool_calls` array on an assistant message.
+ * Each entry: `{id: string, type: "function", function: {name: string, arguments: string}}`.
+ */
+function inspectToolCalls(toolCalls: unknown, lineNo: number, path: string): ValidationIssue[] {
+  const out: ValidationIssue[] = [];
+  if (!Array.isArray(toolCalls)) {
+    out.push(
+      makeIssue("error", "INVALID_TOOL_CALLS", `"tool_calls" must be an array.`, {
+        line: lineNo,
+        path,
+      }),
+    );
+    return out;
+  }
+  for (let idx = 0; idx < toolCalls.length; idx++) {
+    const call = toolCalls[idx];
+    const callPath = `${path}[${idx}]`;
+    if (call === null || typeof call !== "object" || Array.isArray(call)) {
+      out.push(
+        makeIssue("error", "INVALID_TOOL_CALL", `tool_calls item must be an object.`, {
+          line: lineNo,
+          path: callPath,
+        }),
+      );
+      continue;
+    }
+    const obj = call as Record<string, unknown>;
+    if (typeof obj.id !== "string" || obj.id.length === 0) {
+      out.push(
+        makeIssue("error", "TOOL_CALL_MISSING_ID", `tool_calls item must have a non-empty "id".`, {
+          line: lineNo,
+          path: `${callPath}.id`,
+        }),
+      );
+    }
+    if (obj.type !== "function") {
+      out.push(
+        makeIssue(
+          "warning",
+          "TOOL_CALL_TYPE_NOT_FUNCTION",
+          `tool_calls item "type" should be "function" (got "${String(obj.type)}").`,
+          { line: lineNo, path: `${callPath}.type` },
+        ),
+      );
+    }
+    const fn = obj.function;
+    if (fn === null || typeof fn !== "object" || Array.isArray(fn)) {
+      out.push(
+        makeIssue(
+          "error",
+          "TOOL_CALL_MISSING_FUNCTION",
+          `tool_calls item must have a "function" object.`,
+          {
+            line: lineNo,
+            path: `${callPath}.function`,
+          },
+        ),
+      );
+    } else {
+      const fnObj = fn as Record<string, unknown>;
+      if (typeof fnObj.name !== "string" || fnObj.name.length === 0) {
+        out.push(
+          makeIssue("error", "TOOL_CALL_FN_NO_NAME", `tool_calls function must have a "name".`, {
+            line: lineNo,
+            path: `${callPath}.function.name`,
+          }),
+        );
+      }
+      if (typeof fnObj.arguments !== "string") {
+        out.push(
+          makeIssue(
+            "error",
+            "TOOL_CALL_FN_ARGS_NOT_STRING",
+            `tool_calls function "arguments" must be a JSON string.`,
+            { line: lineNo, path: `${callPath}.function.arguments` },
+          ),
+        );
+      }
+    }
+  }
+  return out;
+}
 
 /**
  * Structural checks for a single message object `{role, content}`. Shared by
@@ -35,25 +304,74 @@ export function inspectMessageObject(
   }
   const record = msg as Record<string, unknown>;
   const role = record.role;
-  const content = record.content;
   if (typeof role !== "string" || !VALID_ROLES.has(role)) {
     out.push(
       makeIssue(
         "error",
         "INVALID_ROLE",
-        `Invalid role "${String(role)}". Expected one of: system, user, assistant.`,
+        `Invalid role "${String(role)}". Expected one of: system, user, assistant, tool.`,
         { line: lineNo, path: `${path}.role` },
       ),
     );
   }
-  if (typeof content !== "string") {
+
+  // tool role: must have tool_call_id
+  if (role === "tool") {
+    if (typeof record.tool_call_id !== "string" || record.tool_call_id.length === 0) {
+      out.push(
+        makeIssue(
+          "error",
+          "TOOL_MISSING_CALL_ID",
+          `A "tool" role message must have a non-empty "tool_call_id".`,
+          { line: lineNo, path: `${path}.tool_call_id` },
+        ),
+      );
+    }
+  }
+
+  // content validation: string or array format
+  if (!("content" in record)) {
+    // assistant messages with tool_calls may omit content
+    if (role !== "assistant" || !("tool_calls" in record)) {
+      out.push(
+        makeIssue("error", "MISSING_CONTENT", `"content" field is missing.`, {
+          line: lineNo,
+          path: `${path}.content`,
+        }),
+      );
+    }
+  } else {
+    out.push(...inspectContentField(record.content, lineNo, `${path}.content`));
+  }
+
+  // tool_calls on assistant
+  if ("tool_calls" in record) {
+    out.push(...inspectToolCalls(record.tool_calls, lineNo, `${path}.tool_calls`));
+  }
+
+  // OpenAI migration guard: the platform rejects data carrying name / weight
+  if ("name" in record) {
     out.push(
-      makeIssue("error", "INVALID_CONTENT", `"content" must be a string (got ${typeof content}).`, {
-        line: lineNo,
-        path: `${path}.content`,
-      }),
+      makeIssue(
+        "error",
+        "UNSUPPORTED_FIELD_NAME",
+        `Field "name" is not supported by Bailian and must be removed when migrating from OpenAI/Azure.`,
+        { line: lineNo, path: `${path}.name` },
+      ),
     );
   }
+  if ("weight" in record) {
+    out.push(
+      makeIssue(
+        "error",
+        "UNSUPPORTED_FIELD_WEIGHT",
+        `Field "weight" is not supported by Bailian and must be removed when migrating from OpenAI/Azure. ` +
+          `All assistant outputs are trained; per-line importance uses "loss_weight" (invite-only).`,
+        { line: lineNo, path: `${path}.weight` },
+      ),
+    );
+  }
+
   return out;
 }
 
@@ -91,19 +409,24 @@ export function inspectChatMLRecord(
 
   let sawSystem = false;
   let lastRole: string | undefined;
-  for (let i = 0; i < messages.length; i++) {
-    const msg = messages[i];
-    const path = `messages[${i}]`;
+  let lastAssistantIdx = -1;
+  const toolCallIds = new Set<string>();
+  const toolResponseIds = new Set<string>();
+
+  for (let idx = 0; idx < messages.length; idx++) {
+    const msg = messages[idx];
+    const path = `messages[${idx}]`;
     out.push(...inspectMessageObject(msg, lineNo, path));
-    const role = (msg as Record<string, unknown> | null)?.role;
+    const msgObj = msg as Record<string, unknown> | null;
+    const role = msgObj?.role;
 
     if (role === "system") {
-      if (i !== 0) {
+      if (idx !== 0) {
         out.push(
           makeIssue(
             "warning",
             "SYSTEM_NOT_FIRST",
-            `"system" message should appear at index 0; found at index ${i}.`,
+            `"system" message should appear at index 0; found at index ${idx}.`,
             { line: lineNo, path: `${path}.role` },
           ),
         );
@@ -111,6 +434,27 @@ export function inspectChatMLRecord(
       sawSystem = true;
     }
 
+    if (role === "assistant") {
+      lastAssistantIdx = idx;
+      // Collect tool_calls ids
+      if (msgObj && Array.isArray(msgObj.tool_calls)) {
+        for (const call of msgObj.tool_calls) {
+          const callObj = call as Record<string, unknown> | null;
+          if (callObj && typeof callObj.id === "string") {
+            toolCallIds.add(callObj.id);
+          }
+        }
+      }
+    }
+
+    if (role === "tool") {
+      const callId = msgObj?.tool_call_id;
+      if (typeof callId === "string" && callId.length > 0) {
+        toolResponseIds.add(callId);
+      }
+    }
+
+    // Consecutive same-role warning (skip tool — multiple tool responses are normal)
     if (lastRole === role && (role === "user" || role === "assistant")) {
       out.push(
         makeIssue(
@@ -123,6 +467,7 @@ export function inspectChatMLRecord(
     }
     if (typeof role === "string") lastRole = role;
   }
+
   // Soft check: messages without any user role almost certainly indicate a bug.
   if (!messages.some((m) => (m as Record<string, unknown>).role === "user")) {
     out.push(
@@ -140,9 +485,132 @@ export function inspectChatMLRecord(
       }),
     );
   }
+
+  // tool_call_id correspondence must be one-to-one (platform spec):
+  // every tool response must reference a known call id (hard error), and every
+  // tool_call should receive a response (advisory — trailing calls are dubious
+  // in training data but we cannot rule out platform-side tolerance).
+  for (const responseId of toolResponseIds) {
+    if (!toolCallIds.has(responseId)) {
+      out.push(
+        makeIssue(
+          "error",
+          "TOOL_CALL_ID_UNMATCHED",
+          `tool message references tool_call_id "${responseId}" which does not match any assistant tool_calls[].id.`,
+          { line: lineNo, path: "messages" },
+        ),
+      );
+    }
+  }
+  for (const callId of toolCallIds) {
+    if (!toolResponseIds.has(callId)) {
+      out.push(
+        makeIssue(
+          "warning",
+          "TOOL_CALL_NO_RESPONSE",
+          `assistant tool_calls[].id "${callId}" has no matching tool response message.`,
+          { line: lineNo, path: "messages" },
+        ),
+      );
+    }
+  }
+
+  // thinking tag check: <think>…</think> should only appear in the last
+  // assistant message. Exemption (platform spec, tool+thinking combo): an
+  // assistant that carries tool_calls may legitimately hold a <think> block
+  // even when it is not the last assistant message.
+  if (lastAssistantIdx >= 0) {
+    for (let idx = 0; idx < messages.length; idx++) {
+      if (idx === lastAssistantIdx) continue;
+      const msg = messages[idx] as Record<string, unknown> | null;
+      if (msg?.role !== "assistant") continue;
+      if (msg && Array.isArray(msg.tool_calls)) continue;
+      const content = msg?.content;
+      if (contentHasThinkTag(content)) {
+        out.push(
+          makeIssue(
+            "warning",
+            "THINK_TAG_NOT_LAST",
+            `Thinking tags (<think>…</think>) should only appear in the last assistant message ` +
+              `(or an assistant message carrying tool_calls), found at messages[${idx}].`,
+            { line: lineNo, path: `messages[${idx}].content` },
+          ),
+        );
+      }
+    }
+  }
+
+  // loss_weight validation (invite-only parameter).
+  // Range is enforced wherever the field appears (record level and message
+  // level); placement follows the spec: only the LAST assistant message line
+  // supports loss_weight — misplaced occurrences are advisory (invite-only
+  // semantics are account-specific, so we do not hard-fail).
+  const checkLossWeightRange = (value: unknown, path: string): void => {
+    if (typeof value !== "number" || value < 0 || value > 1) {
+      out.push(
+        makeIssue(
+          "error",
+          "INVALID_LOSS_WEIGHT",
+          `"loss_weight" must be a number between 0.0 and 1.0 (got ${JSON.stringify(value)}).`,
+          { line: lineNo, path },
+        ),
+      );
+    }
+  };
+  if ("loss_weight" in record) {
+    checkLossWeightRange(record.loss_weight, "loss_weight");
+  }
+  for (let idx = 0; idx < messages.length; idx++) {
+    const msg = messages[idx] as Record<string, unknown> | null;
+    if (!msg || !("loss_weight" in msg)) continue;
+    checkLossWeightRange(msg.loss_weight, `messages[${idx}].loss_weight`);
+    if (!(msg.role === "assistant" && idx === lastAssistantIdx)) {
+      out.push(
+        makeIssue(
+          "warning",
+          "LOSS_WEIGHT_PLACEMENT",
+          `"loss_weight" is only supported on the last assistant message; found at messages[${idx}] (role "${String(msg.role)}").`,
+          { line: lineNo, path: `messages[${idx}].loss_weight` },
+        ),
+      );
+    }
+  }
+
+  // OpenAI migration guard at record level (message-level occurrences are
+  // handled by inspectMessageObject above)
+  if ("weight" in record) {
+    out.push(
+      makeIssue(
+        "error",
+        "UNSUPPORTED_FIELD_WEIGHT",
+        `Record-level field "weight" is not supported by Bailian and must be removed when migrating from OpenAI/Azure.`,
+        { line: lineNo, path: "weight" },
+      ),
+    );
+  }
+
   return out;
 }
 
+/** Check whether content (string or array) contains a <think> tag. */
+function contentHasThinkTag(content: unknown): boolean {
+  if (typeof content === "string") {
+    return content.includes("<think>");
+  }
+  if (Array.isArray(content)) {
+    return content.some((item) => {
+      if (item && typeof item === "object" && "text" in item) {
+        return (
+          typeof (item as Record<string, unknown>).text === "string" &&
+          ((item as Record<string, unknown>).text as string).includes("<think>")
+        );
+      }
+      return false;
+    });
+  }
+  return false;
+}
+
 /**
  * ChatML / SFT schema. The auto-detect predicate is `true` so it acts as the
  * registry fallback — any record that isn't picked up by a more specific

packages/core/src/dataset/validate/schemas/dpo.ts

@@ -18,6 +18,76 @@ function inspectDPORecord(record: Record<string, unknown>, lineNo: number): Vali
   const messages = record.messages;
   if (!Array.isArray(messages) || messages.length === 0) return out;
 
+  /** image / video content items are outside the DPO support matrix */
+  const mediaIssues = (content: unknown, basePath: string): ValidationIssue[] => {
+    if (!Array.isArray(content)) return [];
+    const found: ValidationIssue[] = [];
+    for (let itemIdx = 0; itemIdx < content.length; itemIdx++) {
+      const item = content[itemIdx] as Record<string, unknown> | null;
+      if (!item || typeof item !== "object") continue;
+      for (const mediaField of ["image", "video"] as const) {
+        if (mediaField in item) {
+          found.push(
+            makeIssue(
+              "error",
+              "DPO_UNSUPPORTED_ELEMENT",
+              `DPO training data does not support ${mediaField} inputs; found at ${basePath}.content[${itemIdx}].`,
+              { line: lineNo, path: `${basePath}.content[${itemIdx}].${mediaField}` },
+            ),
+          );
+        }
+      }
+    }
+    return found;
+  };
+
+  // Support matrix (platform spec): DPO is text + thinking ONLY — no image /
+  // video inputs and no tool calling. Reject multimodal items and tool fields
+  // that the SFT-oriented ChatML inspector would otherwise accept.
+  if ("tools" in record) {
+    out.push(
+      makeIssue(
+        "error",
+        "DPO_UNSUPPORTED_ELEMENT",
+        `DPO training data does not support tool calling; remove the "tools" definition.`,
+        { line: lineNo, path: "tools" },
+      ),
+    );
+  }
+  for (let idx = 0; idx < messages.length; idx++) {
+    const msg = messages[idx] as Record<string, unknown> | null;
+    if (!msg) continue;
+    const msgPath = `messages[${idx}]`;
+    if (msg.role === "tool" || "tool_calls" in msg) {
+      out.push(
+        makeIssue(
+          "error",
+          "DPO_UNSUPPORTED_ELEMENT",
+          `DPO training data does not support tool calling; found ${
+            msg.role === "tool" ? `role "tool"` : `"tool_calls"`
+          } at ${msgPath}.`,
+          { line: lineNo, path: msgPath },
+        ),
+      );
+    }
+    out.push(...mediaIssues(msg.content, msgPath));
+  }
+
+  // DPO trains the preference for the LAST user input — messages ending with
+  // any other role make the chosen/rejected pair semantically meaningless.
+  const lastMsg = messages[messages.length - 1] as Record<string, unknown> | null;
+  if (lastMsg && lastMsg.role !== "user") {
+    out.push(
+      makeIssue(
+        "error",
+        "DPO_LAST_MSG_NOT_USER",
+        `DPO "messages" must end with a "user" message (the prompt for chosen/rejected). ` +
+          `Got "${String(lastMsg.role)}" as the last message.`,
+        { line: lineNo, path: `messages[${messages.length - 1}].role` },
+      ),
+    );
+  }
+
   const hasChosen = "chosen" in record;
   const hasRejected = "rejected" in record;
 
@@ -39,6 +109,7 @@ function inspectDPORecord(record: Record<string, unknown>, lineNo: number): Vali
   }
   if (hasChosen) {
     out.push(...inspectMessageObject(record.chosen, lineNo, "chosen"));
+    out.push(...mediaIssues((record.chosen as Record<string, unknown> | null)?.content, "chosen"));
     const role = (record.chosen as Record<string, unknown> | null)?.role;
     if (typeof role === "string" && role !== "assistant") {
       out.push(
@@ -53,6 +124,9 @@ function inspectDPORecord(record: Record<string, unknown>, lineNo: number): Vali
   }
   if (hasRejected) {
     out.push(...inspectMessageObject(record.rejected, lineNo, "rejected"));
+    out.push(
+      ...mediaIssues((record.rejected as Record<string, unknown> | null)?.content, "rejected"),
+    );
     const role = (record.rejected as Record<string, unknown> | null)?.role;
     if (typeof role === "string" && role !== "assistant") {
       out.push(

packages/core/src/dataset/validate/schemas/image.ts

@@ -16,7 +16,15 @@ import type { ValidationIssue } from "../types.ts";
 import type { RecordSchemaSpec } from "./types.ts";
 
 /** Accepted image file extensions (lower-case, with dot). */
-export const IMAGE_EXTENSIONS = new Set([".png", ".jpg", ".jpeg", ".bmp", ".webp", ".tiff"]);
+export const IMAGE_EXTENSIONS = new Set([
+  ".png",
+  ".jpg",
+  ".jpeg",
+  ".bmp",
+  ".tif",
+  ".tiff",
+  ".webp",
+]);
 
 /**
  * Check that a path string ends with an accepted image extension.

packages/core/src/dataset/validate/zip.ts

@@ -3,14 +3,15 @@
  *
  * A training data ZIP must have:
  *   - `data.jsonl` at the root — the manifest mapping media files to labels.
- *   - A `train/` subfolder (or media files at the root) referenced by the
- *     manifest entries.
+ *     The platform requires data.jsonl to be directly visible when opening the
+ *     ZIP (no wrapping folder).
+ *   - Media files referenced by the manifest entries.
  *
  * This validator owns the **ZIP-level structural checks** (entries present,
- * references resolve). The **per-record JSONL content validation** is delegated
- * to the existing `jsonlValidator` — we extract `data.jsonl` to a temp file,
- * run the full pipeline (quickScan + deepCheck + schema dispatch), and stitch
- * the results together.
+ * references resolve, filename constraints). The **per-record JSONL content
+ * validation** is delegated to the existing `jsonlValidator` — we extract
+ * `data.jsonl` to a temp file, run the full pipeline (quickScan + deepCheck +
+ * schema dispatch), and stitch the results together.
  *
  * The schema for `data.jsonl` records is passed via `opts.schema` (typically
  * `"tts"` for audio). The profile layer decides which schema to use based on
@@ -92,6 +93,139 @@ function collectZipEntries(zipPath: string): Promise<string[]> {
   });
 }
 
+/**
+ * Platform filename constraints:
+ * - Allowed charset: ASCII letters (a-z, A-Z), digits (0-9), underscore (_), hyphen (-)
+ * - Filename (without extension) ≤ 120 characters
+ * - Filenames must be globally unique (ignoring extension)
+ */
+const FILENAME_CHARSET_RE = /^[a-zA-Z0-9_-]+$/;
+const MAX_FILENAME_BASE_LENGTH = 120;
+
+/** Extract the base name (no extension) from a path segment. */
+function basenameNoExt(segment: string): string {
+  const dot = segment.lastIndexOf(".");
+  return dot > 0 ? segment.slice(0, dot) : segment;
+}
+
+/**
+ * macOS Finder/zip metadata entries (`__MACOSX/` resource forks, `.DS_Store`,
+ * AppleDouble `._*` files). They are packaging noise, not training data:
+ * exclude them from filename constraints and media counting so Mac-created
+ * archives don't fail on artifacts the user never sees.
+ */
+function isZipMetadataEntry(entry: string): boolean {
+  if (entry === "__MACOSX" || entry.startsWith("__MACOSX/")) return true;
+  const lastSegment =
+    entry
+      .split("/")
+      .filter((segment) => segment.length > 0)
+      .pop() ?? "";
+  return lastSegment === ".DS_Store" || lastSegment.startsWith("._");
+}
+
+/**
+ * Validate ZIP entry filenames against platform constraints.
+ * Returns issues for charset violations, over-length names, and duplicates.
+ * Exported for direct unit testing (not re-exported by the barrel).
+ */
+export function validateZipFilenames(entries: string[]): ValidationIssue[] {
+  const out: ValidationIssue[] = [];
+  const seenBasenames = new Map<string, string>(); // basename (no ext) → first full path
+  const MAX_REPORTED = 10;
+
+  for (const entry of entries) {
+    // Skip directory entries and macOS packaging metadata
+    if (entry.endsWith("/")) continue;
+    if (isZipMetadataEntry(entry)) continue;
+
+    // Check each path segment (folder names + file name)
+    const segments = entry.split("/").filter((s) => s.length > 0);
+    for (const segment of segments) {
+      // Strip extension for the charset check on the base part
+      const base = basenameNoExt(segment);
+      const ext = segment.slice(base.length); // includes dot, e.g. ".jpg"
+
+      // Charset check on base name (extension checked separately)
+      if (base.length > 0 && !FILENAME_CHARSET_RE.test(base)) {
+        if (out.length < MAX_REPORTED) {
+          out.push(
+            makeIssue(
+              "error",
+              "INVALID_FILENAME_CHARSET",
+              `File/folder name "${segment}" contains invalid characters. ` +
+                `Only a-z, A-Z, 0-9, underscore (_), and hyphen (-) are allowed.`,
+              { path: entry },
+            ),
+          );
+        }
+      }
+
+      // Extension charset (allow dot + alphanumeric)
+      if (ext.length > 0 && !/^\.[a-zA-Z0-9]+$/.test(ext)) {
+        if (out.length < MAX_REPORTED) {
+          out.push(
+            makeIssue(
+              "error",
+              "INVALID_FILENAME_CHARSET",
+              `File extension "${ext}" in "${segment}" contains invalid characters.`,
+              { path: entry },
+            ),
+          );
+        }
+      }
+    }
+
+    // Filename length check (base name without extension)
+    const fileName = segments[segments.length - 1] ?? "";
+    const baseName = basenameNoExt(fileName);
+    if (baseName.length > MAX_FILENAME_BASE_LENGTH) {
+      if (out.length < MAX_REPORTED) {
+        out.push(
+          makeIssue(
+            "error",
+            "FILENAME_TOO_LONG",
+            `Filename "${fileName}" (without extension) exceeds ${MAX_FILENAME_BASE_LENGTH} characters ` +
+              `(got ${baseName.length}). Shorten the name and re-upload.`,
+            { path: entry },
+          ),
+        );
+      }
+    }
+
+    // Global uniqueness check (ignoring extension, case-sensitive)
+    if (baseName.length > 0) {
+      const existing = seenBasenames.get(baseName);
+      if (existing !== undefined) {
+        if (out.length < MAX_REPORTED) {
+          out.push(
+            makeIssue(
+              "error",
+              "DUPLICATE_FILENAME",
+              `Filename "${fileName}" conflicts with "${existing}" — names must be globally unique ` +
+                `(ignoring extension) even across different folders.`,
+              { path: entry },
+            ),
+          );
+        }
+      } else {
+        seenBasenames.set(baseName, entry);
+      }
+    }
+  }
+
+  if (out.length >= MAX_REPORTED) {
+    out.push(
+      makeIssue(
+        "warning",
+        "FILENAME_ISSUES_TRUNCATED",
+        `More filename issues exist but reporting is capped at ${MAX_REPORTED}.`,
+      ),
+    );
+  }
+  return out;
+}
+
 /**
  * Extract a single entry from a ZIP archive to a destination path.
  */
@@ -201,19 +335,37 @@ export const zipValidator: ValidatorSpec = {
       };
     }
 
-    // --- 2. Check for data.jsonl ---
-    const hasDataJsonl = entries.some(
-      (entry) => entry === "data.jsonl" || entry.endsWith("/data.jsonl"),
-    );
-    if (!hasDataJsonl) {
-      errors.push(
-        makeIssue(
-          "error",
-          "MISSING_DATA_JSONL",
-          `ZIP archive must contain "data.jsonl" at the root. ` +
-            `This file maps media files (e.g. .wav) to their labels.`,
-        ),
-      );
+    // --- 2. Check for data.jsonl (must be at ZIP root) ---
+    const hasRootDataJsonl = entries.some((entry) => entry === "data.jsonl");
+    const nestedDataJsonl =
+      !hasRootDataJsonl && entries.find((entry) => entry.endsWith("/data.jsonl"));
+    if (!hasRootDataJsonl) {
+      if (nestedDataJsonl) {
+        errors.push(
+          makeIssue(
+            "error",
+            "DATA_JSONL_NOT_AT_ROOT",
+            `"data.jsonl" must be at the ZIP root (found "${nestedDataJsonl}"). ` +
+              `Re-package so that opening the ZIP shows data.jsonl directly, without a wrapping folder.`,
+          ),
+        );
+      } else {
+        errors.push(
+          makeIssue(
+            "error",
+            "MISSING_DATA_JSONL",
+            `ZIP archive must contain "data.jsonl" at the root. ` +
+              `This file maps media files (e.g. .wav, .jpg) to their labels.`,
+          ),
+        );
+      }
+    }
+
+    // --- 2b. Filename constraints (charset, length, uniqueness) ---
+    const filenameIssues = validateZipFilenames(entries);
+    for (const issue of filenameIssues) {
+      if (issue.severity === "error") errors.push(issue);
+      else warnings.push(issue);
     }
 
     // --- 3. Check for train/ directory (modality-aware) ---
@@ -249,6 +401,7 @@ export const zipValidator: ValidatorSpec = {
       const imageFiles = entries.filter((entry) => {
         if (entry === "data.jsonl" || entry.endsWith("/data.jsonl")) return false;
         if (entry.endsWith("/")) return false; // directory entries
+        if (isZipMetadataEntry(entry)) return false; // __MACOSX/._x.jpg is not an image
         const dot = entry.lastIndexOf(".");
         const ext = dot >= 0 ? entry.slice(dot).toLowerCase() : "";
         return IMAGE_EXTENSIONS.has(ext);
@@ -265,8 +418,8 @@ export const zipValidator: ValidatorSpec = {
       }
     }
 
-    // If data.jsonl is missing, we can't do JSONL content validation.
-    if (!hasDataJsonl) {
+    // If data.jsonl is missing entirely, we can't do JSONL content validation.
+    if (!hasRootDataJsonl && !nestedDataJsonl) {
       return {
         valid: false,
         format: "zip",
@@ -278,9 +431,11 @@ export const zipValidator: ValidatorSpec = {
     }
 
     // --- 4. Extract data.jsonl to a temp file and run jsonlValidator ---
-    const dataJsonlEntry = entries.find(
-      (entry) => entry === "data.jsonl" || entry.endsWith("/data.jsonl"),
-    )!;
+    // Prefer root data.jsonl; fall back to nested for content validation even
+    // though we already reported the root-placement error above.
+    const dataJsonlEntry = hasRootDataJsonl
+      ? "data.jsonl"
+      : entries.find((entry) => entry.endsWith("/data.jsonl"))!;
     const tmpDir = join(tmpdir(), `bl-zip-${randomBytes(6).toString("hex")}`);
     mkdirSync(tmpDir, { recursive: true });
     const tmpJsonl = join(tmpDir, "data.jsonl");

packages/core/src/deploy/index.ts

@@ -2,3 +2,4 @@ export * from "./api.ts";
 export * from "./types.ts";
 export * from "./constants.ts";
 export * from "./plans.ts";
+export * from "./lifecycle.ts";

packages/core/src/deploy/lifecycle.ts

@@ -0,0 +1,99 @@
+/**
+ * Deployment lifecycle operations via the **console gateway**.
+ *
+ * Unlike the DashScope REST endpoints in `api.ts`, start/stop/list-independent
+ * are console-domain APIs (`zeldaEasy.broadscope-platform.modelInstance.*`).
+ * Commands using these must declare `auth: "console"`.
+ */
+import type { Client } from "../client/client.ts";
+import { unwrapResponse } from "../console/models.ts";
+
+// ---------------------------------------------------------------------------
+// API names
+// ---------------------------------------------------------------------------
+
+export const DEPLOY_START_API = "zeldaEasy.broadscope-platform.modelInstance.startModelService";
+export const DEPLOY_STOP_API = "zeldaEasy.broadscope-platform.modelInstance.stopModelService";
+export const DEPLOY_LIST_INDEPENDENT_API =
+  "zeldaEasy.broadscope-platform.modelInstance.listIndependentDeployedModel";
+
+// ---------------------------------------------------------------------------
+// Types
+// ---------------------------------------------------------------------------
+
+export interface ModelServiceEntry {
+  modelServiceId?: string;
+  deployedModel?: string;
+  deployed_model?: string;
+  status?: string;
+  modelName?: string;
+  model_name?: string;
+  plan?: string;
+  [key: string]: unknown;
+}
+
+// ---------------------------------------------------------------------------
+// API wrappers
+// ---------------------------------------------------------------------------
+
+/** Start (bring online) a stopped deployment. */
+export async function startModelService(
+  client: Client,
+  modelServiceId: string,
+): Promise<Record<string, unknown>> {
+  const raw = await client.console<Record<string, unknown>>(DEPLOY_START_API, {
+    input: { modelServiceId },
+  });
+  return unwrapResponse(raw);
+}
+
+/** Stop (take offline) a running deployment. Stops billing for mu/ptu plans. */
+export async function stopModelService(
+  client: Client,
+  modelServiceId: string,
+): Promise<Record<string, unknown>> {
+  const raw = await client.console<Record<string, unknown>>(DEPLOY_STOP_API, {
+    input: { modelServiceId },
+  });
+  return unwrapResponse(raw);
+}
+
+/**
+ * List independently deployed models (console domain).
+ * Used for precheck status verification and ID mapping.
+ * Paginates internally to return all entries.
+ */
+export async function listIndependentDeployedModels(client: Client): Promise<ModelServiceEntry[]> {
+  const allEntries: ModelServiceEntry[] = [];
+  let page = 1;
+
+  while (true) {
+    const raw = await client.console<Record<string, unknown>>(DEPLOY_LIST_INDEPENDENT_API, {
+      input: { pageNo: page, pageSize: 50 },
+    });
+    const resp = unwrapResponse(raw);
+    const records = (resp.records ?? []) as ModelServiceEntry[];
+    allEntries.push(...records);
+    const pageCount = (resp.pageCount as number) ?? 1;
+    if (page >= pageCount || records.length === 0) break;
+    page++;
+  }
+
+  return allEntries;
+}
+
+/**
+ * Find a deployment entry by its identifier in the console-domain list.
+ * Matches against `modelServiceId`, `deployedModel`, or `deployed_model`.
+ */
+export function findDeploymentEntry(
+  entries: ModelServiceEntry[],
+  deployedModel: string,
+): ModelServiceEntry | undefined {
+  return entries.find(
+    (entry) =>
+      entry.modelServiceId === deployedModel ||
+      entry.deployedModel === deployedModel ||
+      entry.deployed_model === deployedModel,
+  );
+}

packages/core/src/finetune/api.ts

@@ -43,6 +43,8 @@ export interface ListFineTunesParams {
   pageNo?: number;
   pageSize?: number;
   status?: string;
+  /** Filter by base model ID (server-side). */
+  model?: string;
   signal?: AbortSignal;
 }
 
@@ -55,6 +57,7 @@ export async function listFineTunes(
   if (params.pageNo !== undefined) qs.set("page_no", String(params.pageNo));
   if (params.pageSize !== undefined) qs.set("page_size", String(params.pageSize));
   if (params.status) qs.set("status", params.status);
+  if (params.model) qs.set("model", params.model);
   const base = finetuneJobsPath();
   const path = qs.toString() ? `${base}?${qs.toString()}` : base;
   return client.requestJson<ListFineTunesResponse>({

packages/core/src/finetune/index.ts

@@ -3,3 +3,4 @@ export * from "./api.ts";
 export * from "./capability.ts";
 export * from "./preflight.ts";
 export * from "./profiles/index.ts";
+export * from "./price.ts";

packages/core/src/finetune/price.ts

@@ -0,0 +1,121 @@
+/**
+ * Training price estimation via the **console gateway**.
+ *
+ * These are console-domain APIs (`zeldaEasy.broadscope-platform.*`); commands
+ * using them must declare `auth: "console"`. Two different argument wrappers
+ * exist: `getModelPrice` takes a top-level `query`, while the token-estimation
+ * APIs take a top-level `input`.
+ */
+import type { Client } from "../client/client.ts";
+import { unwrapResponse } from "../console/models.ts";
+
+// ---------------------------------------------------------------------------
+// API names
+// ---------------------------------------------------------------------------
+
+export const TRAINING_MODEL_PRICE_API = "zeldaEasy.broadscope-platform.modelCenter.getModelPrice";
+export const CALC_DATASETS_TOKENS_API =
+  "zeldaEasy.broadscope-platform.modelInstance.calculateDatasetsTotalTokens";
+export const ESTIMATE_FINETUNE_TOKENS_API =
+  "zeldaEasy.broadscope-platform.modelInstance.estimateFinetuneTokens";
+
+// ---------------------------------------------------------------------------
+// Types
+// ---------------------------------------------------------------------------
+
+export interface TrainingModelPrice {
+  price?: string;
+  priceUnit?: string;
+  modelId?: string;
+  [key: string]: unknown;
+}
+
+export interface TokenEstimate {
+  estimatedDatasetConsumedTokensMinPerEpoch?: number;
+  estimatedDatasetConsumedTokensMaxPerEpoch?: number;
+  estimatedMixedConsumedTokensMinPerEpoch?: number;
+  estimatedMixedConsumedTokensMaxPerEpoch?: number;
+  [key: string]: unknown;
+}
+
+// ---------------------------------------------------------------------------
+// API wrappers
+// ---------------------------------------------------------------------------
+
+/**
+ * Training unit price for a model. `price` is denominated in `priceUnit`
+ * (typically "千Token" — yuan per 1000 tokens).
+ */
+export async function fetchTrainingModelPrice(
+  client: Client,
+  modelId: string,
+): Promise<TrainingModelPrice> {
+  const raw = await client.console<Record<string, unknown>>(TRAINING_MODEL_PRICE_API, {
+    query: { type: 0, modelId },
+  });
+  return unwrapResponse(raw) as TrainingModelPrice;
+}
+
+/**
+ * Estimate training tokens for SFT / DPO jobs.
+ * Returns a per-epoch min/max range; multiply by `n_epochs` for the total.
+ */
+export async function estimateSftDpoTokens(
+  client: Client,
+  datasetIds: string[],
+  hyperParams: { nEpochs: number; batchSize: number; maxLength: number },
+): Promise<TokenEstimate> {
+  const raw = await client.console<Record<string, unknown>>(CALC_DATASETS_TOKENS_API, {
+    input: { trainDatasetIds: datasetIds, hyperParams },
+  });
+  return unwrapResponse(raw) as TokenEstimate;
+}
+
+/**
+ * Estimate training tokens for CPT jobs.
+ *
+ * The console API requires `hyperParams` as a **JSON string** with a full
+ * `userDefinedObj` payload (captured from the console frontend), plus several
+ * top-level fields (`algorithmType`, `bizType`, `priority`, …). Only
+ * `n_epochs` / `max_length` materially affect the estimate; the remaining
+ * hyper-parameters are fixed defaults.
+ */
+export async function estimateCptTokens(
+  client: Client,
+  model: string,
+  datasetIdsCsv: string,
+  nEpochs: number,
+): Promise<TokenEstimate> {
+  const userDefinedObj = {
+    batch_size: 16,
+    eval_steps: 50,
+    learning_rate: "7e-6",
+    lr_scheduler_type: "linear",
+    max_length: 8192,
+    n_epochs: nEpochs,
+    split: 0.9,
+    save_total_limit: "3",
+    resume_from_checkpoint: false,
+    save_strategy: "epoch",
+  };
+  const hyperParams = JSON.stringify({
+    useDefault: false,
+    userDefinedObj,
+    useQwenMixedStrategy: false,
+  });
+  const raw = await client.console<Record<string, unknown>>(ESTIMATE_FINETUNE_TOKENS_API, {
+    input: {
+      trainingType: "cpt",
+      instanceName: `${model}_cli_estimate`,
+      algorithmType: 100,
+      bizType: 100,
+      trainDatasetIds: datasetIdsCsv,
+      hyperParams,
+      bailianTrainModel: model,
+      validationDatasetIds: "",
+      jobName: `${model}_cli_estimate`,
+      priority: "L0",
+    },
+  });
+  return unwrapResponse(raw) as TokenEstimate;
+}

packages/core/src/finetune/profiles/cpt.ts

@@ -1,7 +1,39 @@
 /**
  * `cpt` profile — Continual Pre-Training (full-parameter).
  * Maps to the server's `cpt` training type. CPT record schema.
+ * CPT allows larger files (300 MB) compared to SFT/DPO (200 MB).
  */
-import { textProfile } from "./common.ts";
+import type { TrainingProfile, DataModality } from "./types.ts";
+import type { ValidateOpts, ValidationResult } from "../../dataset/validate/types.ts";
+import { validateDataset } from "../../dataset/validate/registry.ts";
+import { resolveTextHyperParameters } from "./common.ts";
+import { MAX_CPT_BYTES } from "../../dataset/validate/common.ts";
 
-export const cptProfile = textProfile("cpt", "cpt", "cpt");
+export const cptProfile: TrainingProfile = {
+  clientTrainingType: "cpt",
+  serverTrainingType: "cpt",
+  acceptedExtensions: [".jsonl"],
+
+  async validate(
+    filePath: string,
+    _modality: DataModality,
+    opts: ValidateOpts,
+  ): Promise<ValidationResult> {
+    return validateDataset(filePath, { ...opts, schema: "cpt", maxBytes: MAX_CPT_BYTES });
+  },
+
+  resolveHyperParameters(
+    _modality: DataModality,
+    flags: Record<string, unknown>,
+  ): Record<string, unknown> {
+    return resolveTextHyperParameters(flags);
+  },
+
+  shouldSkipGate(_gate: string, _modality: DataModality): boolean {
+    return false;
+  },
+
+  shouldSkipCapabilityCheck(_modality: DataModality): boolean {
+    return false;
+  },
+};

packages/core/src/finetune/profiles/sft-lora.ts

@@ -75,20 +75,24 @@ const IMAGE_HYPER_PARAMS_I2I: Record<string, unknown> = {
  *
  * Shared across all video models; `batch_size` and `max_pixels` differ by model
  * family (resolved per model in `resolveHyperParameters`):
- *   - wan2.5 (e.g. wan2.5-i2v-preview): batch_size 2, max_pixels 36864
- *   - wan2.2 (i2v-flash / kf2v-flash):  batch_size 4, max_pixels 262144
+ *   - wan2.7 (e.g. wan2.7-i2v):           batch_size 1, max_pixels 102400
+ *   - wan2.5 (e.g. wan2.5-i2v-preview):   batch_size 4, max_pixels 36864
+ *   - wan2.2 (i2v-flash / kf2v-flash):    batch_size 4, max_pixels 262144
  *
  * `learning_rate` is a string to avoid JSON-number precision loss (consistent
  * with the image defaults). `split` (0.9) + `max_split_val_dataset_sample`
  * (5) drive the automatic train/validation split when no explicit
  * validation_file_ids are provided.
+ *
+ * Values aligned with the official user guide (2026-07):
+ *   n_epochs 50, eval_epochs 20 (≥ n_epochs/10).
  */
 const VIDEO_HYPER_PARAMS_BASE: Record<string, unknown> = {
-  n_epochs: 400,
+  n_epochs: 50,
   learning_rate: "2e-5",
-  split: 0.9,
+  split: 0.5,
   max_split_val_dataset_sample: 5,
-  eval_epochs: 50,
+  eval_epochs: 20,
   save_total_limit: 10,
   lora_rank: 32,
   lora_alpha: 32,
@@ -109,6 +113,11 @@ function isWan25(model: string | undefined): boolean {
   return typeof model === "string" && /wan2\.5/i.test(model);
 }
 
+/** wan2.7 family uses batch_size 1 and max_pixels 102400. */
+function isWan27(model: string | undefined): boolean {
+  return typeof model === "string" && /wan2\.7/i.test(model);
+}
+
 export const sftLoraProfile: TrainingProfile = {
   clientTrainingType: "sft-lora",
   serverTrainingType: "efficient_sft",
@@ -195,15 +204,18 @@ export const sftLoraProfile: TrainingProfile = {
     }
     if (isVideo(modality)) {
       // Video: shared defaults + model-family-specific batch_size / max_pixels.
-      // wan2.5 uses batch_size 2 / max_pixels 36864; wan2.2 uses 4 / 262144.
-      const wan25 = isWan25(flags.model as string | undefined);
+      //   wan2.7: batch_size 1, max_pixels 102400
+      //   wan2.5: batch_size 4, max_pixels 36864
+      //   wan2.2: batch_size 4, max_pixels 262144
+      const model = (flags.model ?? flags.baseModel) as string | undefined;
       const hp: Record<string, unknown> = {
         ...VIDEO_HYPER_PARAMS_BASE,
-        batch_size: 4,
-        max_pixels: wan25 ? 36864 : 262144,
+        batch_size: isWan27(model) ? 1 : 4,
+        max_pixels: isWan27(model) ? 102400 : isWan25(model) ? 36864 : 262144,
       };
       // Optional overrides (no clamping — video batch_size is intentionally small).
       if (flags.nEpochs !== undefined) hp.n_epochs = flags.nEpochs as number;
+      if (flags.batchSize !== undefined) hp.batch_size = flags.batchSize as number;
       if (flags.learningRate !== undefined) hp.learning_rate = flags.learningRate as string;
       return hp;
     }

packages/core/src/skills/agents.ts

@@ -285,6 +285,21 @@ function isRecordedCopy(linkPath: string, recordedLinks: string[]): boolean {
   }
 }
 
+/**
+ * Whether linkPath is a real directory containing a SKILL.md — indicating it is a
+ * skill artifact installed by another tool (e.g. `npx skills add`) or an older
+ * version predating bl's symlink management. These are safe to replace: they are
+ * not arbitrary user content but the same kind of artifact we manage.
+ */
+function isForeignSkillDir(linkPath: string): boolean {
+  try {
+    if (!lstatSync(linkPath).isDirectory()) return false;
+    return existsSync(join(linkPath, "SKILL.md"));
+  } catch {
+    return false;
+  }
+}
+
 export interface LinkResult {
   agent: string;
   path: string;
@@ -326,6 +341,11 @@ export function linkSkillToAgents(
           // Copy-fallback artifact from a previous install → replace so updates
           // reach agents that have no symlink permission
           rmSync(linkPath, { recursive: true, force: true });
+        } else if (isForeignSkillDir(linkPath)) {
+          // A real directory containing SKILL.md — a skill installed by another
+          // tool (e.g. `npx skills add`) or predating bl's symlink management.
+          // Replace with our symlink so future updates propagate automatically.
+          rmSync(linkPath, { recursive: true, force: true });
         } else {
           results.push({
             agent: agent.id,

packages/core/src/types/api.ts

@@ -206,6 +206,8 @@ export interface DashScopeVideoRequest {
     prompt: string;
     negative_prompt?: string;
     img_url?: string;
+    first_frame_url?: string;
+    last_frame_url?: string;
     media?: Array<{
       type: "image" | "video" | "first_frame" | "last_frame" | "driving_audio" | "first_clip";
       url: string;

packages/core/tests/dataset-validate.test.ts

@@ -56,8 +56,6 @@ describe("validateDataset — DPO schema", () => {
   });
 
   test('schema "dpo" requires both chosen and rejected on every record', async () => {
-    // A record with neither chosen nor rejected is SFT-shaped; under --schema dpo
-    // it must be flagged as missing both preferences.
     const p = file("sft_under_dpo.jsonl", [SFT_OK]);
     const r = await validateDataset(p, { fullValidate: true, schema: "dpo" });
     expect(r.valid).toBe(false);
@@ -107,6 +105,43 @@ describe("validateDataset — DPO schema", () => {
     const r = await validateDataset(p, { fullValidate: true, schema: "dpo" });
     expect(r.valid).toBe(true);
   });
+
+  test("DPO messages ending with assistant → DPO_LAST_MSG_NOT_USER error", async () => {
+    const p = file("dpo_last_asst.jsonl", [
+      '{"messages":[{"role":"user","content":"hi"},{"role":"assistant","content":"yo"}],"chosen":{"role":"assistant","content":"good"},"rejected":{"role":"assistant","content":"bad"}}',
+    ]);
+    const r = await validateDataset(p, { fullValidate: true, schema: "dpo" });
+    expect(r.valid).toBe(false);
+    expect(codes(r).errors).toContain("DPO_LAST_MSG_NOT_USER");
+  });
+
+  test("DPO with image content item → DPO_UNSUPPORTED_ELEMENT error", async () => {
+    const p = file("dpo_image.jsonl", [
+      '{"messages":[{"role":"user","content":[{"text":"look"},{"image":"a.jpg"}]}],"chosen":{"role":"assistant","content":[{"text":"good"}]},"rejected":{"role":"assistant","content":[{"text":"bad"}]}}',
+    ]);
+    const r = await validateDataset(p, { fullValidate: true, schema: "dpo" });
+    expect(r.valid).toBe(false);
+    expect(codes(r).errors).toContain("DPO_UNSUPPORTED_ELEMENT");
+  });
+
+  test("DPO with tools / tool_calls → DPO_UNSUPPORTED_ELEMENT error", async () => {
+    const p = file("dpo_tools.jsonl", [
+      '{"tools":[{"type":"function","function":{"name":"f","parameters":{}}}],"messages":[{"role":"user","content":"hi"}],"chosen":{"role":"assistant","content":"good"},"rejected":{"role":"assistant","content":"bad"}}',
+    ]);
+    const r = await validateDataset(p, { fullValidate: true, schema: "dpo" });
+    expect(r.valid).toBe(false);
+    expect(codes(r).errors).toContain("DPO_UNSUPPORTED_ELEMENT");
+  });
+
+  test("DPO chosen carrying an image item → DPO_UNSUPPORTED_ELEMENT error", async () => {
+    const p = file("dpo_chosen_image.jsonl", [
+      '{"messages":[{"role":"user","content":"hi"}],"chosen":{"role":"assistant","content":[{"text":"good"},{"image":"x.png"}]},"rejected":{"role":"assistant","content":"bad"}}',
+    ]);
+    const r = await validateDataset(p, { fullValidate: true, schema: "dpo" });
+    expect(r.valid).toBe(false);
+    const err = r.errors.find((e) => e.code === "DPO_UNSUPPORTED_ELEMENT");
+    expect(err?.path).toContain("chosen");
+  });
 });
 
 describe("validateDataset — CPT schema", () => {
@@ -142,8 +177,6 @@ describe("validateDataset — CPT schema", () => {
   });
 
   test("auto-detect routes a {text} record to CPT, not ChatML", async () => {
-    // A CPT record has no `messages`; under auto-detect it must NOT produce a
-    // ChatML MISSING_MESSAGES error — it should be validated as CPT and pass.
     const p = file("cpt_auto.jsonl", [CPT_OK]);
     const r = await validateDataset(p, { fullValidate: true });
     expect(r.valid).toBe(true);
@@ -151,8 +184,6 @@ describe("validateDataset — CPT schema", () => {
   });
 
   test("SFT record with a stray text field still routes to ChatML", async () => {
-    // {messages, text} is ambiguous; CPT detect requires text AND no messages,
-    // so this falls through to ChatML and validates as SFT (text ignored).
     const p = file("mixed.jsonl", [
       '{"messages":[{"role":"user","content":"hi"},{"role":"assistant","content":"yo"}],"text":"noise"}',
     ]);
@@ -162,6 +193,400 @@ describe("validateDataset — CPT schema", () => {
   });
 });
 
+describe("validateDataset — content array format", () => {
+  test("content as [{text}] array passes validation", async () => {
+    const p = file("content_arr.jsonl", [
+      '{"messages":[{"role":"system","content":[{"text":"sys"}]},{"role":"user","content":[{"text":"hi"}]},{"role":"assistant","content":[{"text":"hello"}]}]}',
+    ]);
+    const r = await validateDataset(p, { fullValidate: true });
+    expect(r.valid).toBe(true);
+    expect(codes(r).errors).toEqual([]);
+  });
+
+  test("content as plain string still passes (legacy format)", async () => {
+    const p = file("content_str.jsonl", [SFT_OK]);
+    const r = await validateDataset(p, { fullValidate: true });
+    expect(r.valid).toBe(true);
+  });
+
+  test("content array with image item passes (VL multimodal)", async () => {
+    const p = file("content_img.jsonl", [
+      '{"messages":[{"role":"user","content":[{"text":"describe"},{"image":"img1.jpg"}]},{"role":"assistant","content":[{"text":"a cat"}]}]}',
+    ]);
+    const r = await validateDataset(p, { fullValidate: true });
+    expect(r.valid).toBe(true);
+  });
+
+  test("content array with video string item passes", async () => {
+    const p = file("content_vid.jsonl", [
+      '{"messages":[{"role":"user","content":[{"text":"describe"},{"video":"vid1.mp4"}]},{"role":"assistant","content":[{"text":"a car"}]}]}',
+    ]);
+    const r = await validateDataset(p, { fullValidate: true });
+    expect(r.valid).toBe(true);
+  });
+
+  test("content array with video frame list passes", async () => {
+    const p = file("content_frames.jsonl", [
+      '{"messages":[{"role":"user","content":[{"text":"describe"},{"video":["0.jpg","1.jpg","2.jpg"]}]},{"role":"assistant","content":[{"text":"frames"}]}]}',
+    ]);
+    const r = await validateDataset(p, { fullValidate: true });
+    expect(r.valid).toBe(true);
+  });
+
+  test("content array with invalid item (no text/image/video) → error", async () => {
+    const p = file("content_bad_item.jsonl", [
+      '{"messages":[{"role":"user","content":[{"foo":"bar"}]},{"role":"assistant","content":"ok"}]}',
+    ]);
+    const r = await validateDataset(p, { fullValidate: true });
+    expect(r.valid).toBe(false);
+    expect(codes(r).errors).toContain("CONTENT_ITEM_NO_KNOWN_FIELD");
+  });
+
+  test("content as number → INVALID_CONTENT error", async () => {
+    const p = file("content_num.jsonl", [
+      '{"messages":[{"role":"user","content":42},{"role":"assistant","content":"ok"}]}',
+    ]);
+    const r = await validateDataset(p, { fullValidate: true });
+    expect(r.valid).toBe(false);
+    expect(codes(r).errors).toContain("INVALID_CONTENT");
+  });
+
+  test("empty content array → EMPTY_CONTENT_ARRAY error", async () => {
+    const p = file("content_empty_arr.jsonl", [
+      '{"messages":[{"role":"user","content":[]},{"role":"assistant","content":"ok"}]}',
+    ]);
+    const r = await validateDataset(p, { fullValidate: true });
+    expect(r.valid).toBe(false);
+    expect(codes(r).errors).toContain("EMPTY_CONTENT_ARRAY");
+  });
+
+  test("DPO with content array format passes", async () => {
+    const p = file("dpo_arr.jsonl", [
+      '{"messages":[{"role":"user","content":[{"text":"hi"}]}],"chosen":{"role":"assistant","content":[{"text":"good"}]},"rejected":{"role":"assistant","content":[{"text":"bad"}]}}',
+    ]);
+    const r = await validateDataset(p, { fullValidate: true, schema: "dpo" });
+    expect(r.valid).toBe(true);
+  });
+});
+
+describe("validateDataset — tool calling (function calling)", () => {
+  const TOOL_OK = JSON.stringify({
+    tools: [
+      {
+        type: "function",
+        function: {
+          name: "get_weather",
+          description: "get weather",
+          parameters: {
+            type: "object",
+            properties: { city: { type: "string" } },
+            required: ["city"],
+          },
+        },
+      },
+    ],
+    messages: [
+      { role: "user", content: [{ text: "weather in Beijing" }] },
+      {
+        role: "assistant",
+        content: [{ text: "let me check" }],
+        tool_calls: [
+          {
+            id: "call_1",
+            type: "function",
+            function: { name: "get_weather", arguments: '{"city":"Beijing"}' },
+          },
+        ],
+      },
+      { role: "tool", tool_call_id: "call_1", content: [{ text: '{"weather":"sunny"}' }] },
+      { role: "assistant", content: [{ text: "It is sunny." }] },
+    ],
+  });
+
+  test("valid tool calling record passes", async () => {
+    const p = file("tool_ok.jsonl", [TOOL_OK]);
+    const r = await validateDataset(p, { fullValidate: true });
+    expect(r.valid).toBe(true);
+    expect(codes(r).errors).toEqual([]);
+  });
+
+  test("tool role is accepted (no INVALID_ROLE)", async () => {
+    const p = file("tool_role.jsonl", [TOOL_OK]);
+    const r = await validateDataset(p, { fullValidate: true });
+    expect(codes(r).errors).not.toContain("INVALID_ROLE");
+  });
+
+  test("tool message without tool_call_id → TOOL_MISSING_CALL_ID", async () => {
+    const p = file("tool_no_id.jsonl", [
+      '{"messages":[{"role":"user","content":"hi"},{"role":"assistant","content":"","tool_calls":[{"id":"c1","type":"function","function":{"name":"f","arguments":"{}"}}]},{"role":"tool","content":"result"},{"role":"assistant","content":"done"}]}',
+    ]);
+    const r = await validateDataset(p, { fullValidate: true });
+    expect(r.valid).toBe(false);
+    expect(codes(r).errors).toContain("TOOL_MISSING_CALL_ID");
+  });
+
+  test("tool_call_id unmatched → TOOL_CALL_ID_UNMATCHED error", async () => {
+    const p = file("tool_unmatched.jsonl", [
+      '{"messages":[{"role":"user","content":"hi"},{"role":"assistant","content":"","tool_calls":[{"id":"c1","type":"function","function":{"name":"f","arguments":"{}"}}]},{"role":"tool","tool_call_id":"WRONG_ID","content":"result"},{"role":"assistant","content":"done"}]}',
+    ]);
+    const r = await validateDataset(p, { fullValidate: true });
+    expect(r.valid).toBe(false);
+    expect(codes(r).errors).toContain("TOOL_CALL_ID_UNMATCHED");
+    // The orphaned call side is advisory
+    expect(codes(r).warnings).toContain("TOOL_CALL_NO_RESPONSE");
+  });
+
+  test("tool_calls without a tool response → TOOL_CALL_NO_RESPONSE warning", async () => {
+    const p = file("tool_no_resp.jsonl", [
+      '{"messages":[{"role":"user","content":"hi"},{"role":"assistant","content":"","tool_calls":[{"id":"c1","type":"function","function":{"name":"f","arguments":"{}"}}]},{"role":"assistant","content":"done"}]}',
+    ]);
+    const r = await validateDataset(p, { fullValidate: true });
+    expect(codes(r).warnings).toContain("TOOL_CALL_NO_RESPONSE");
+  });
+
+  test("tool_calls with missing function name → TOOL_CALL_FN_NO_NAME", async () => {
+    const p = file("tool_no_fn_name.jsonl", [
+      '{"messages":[{"role":"user","content":"hi"},{"role":"assistant","content":"","tool_calls":[{"id":"c1","type":"function","function":{"arguments":"{}"}}]},{"role":"tool","tool_call_id":"c1","content":"r"},{"role":"assistant","content":"ok"}]}',
+    ]);
+    const r = await validateDataset(p, { fullValidate: true });
+    expect(r.valid).toBe(false);
+    expect(codes(r).errors).toContain("TOOL_CALL_FN_NO_NAME");
+  });
+
+  test("assistant with tool_calls but no content is valid", async () => {
+    const p = file("tool_no_content.jsonl", [
+      '{"messages":[{"role":"user","content":"hi"},{"role":"assistant","tool_calls":[{"id":"c1","type":"function","function":{"name":"f","arguments":"{}"}}]},{"role":"tool","tool_call_id":"c1","content":"r"},{"role":"assistant","content":"ok"}]}',
+    ]);
+    const r = await validateDataset(p, { fullValidate: true });
+    expect(r.valid).toBe(true);
+    expect(codes(r).errors).not.toContain("MISSING_CONTENT");
+  });
+});
+
+describe("validateDataset — thinking tags", () => {
+  test("think tag in last assistant is valid", async () => {
+    const p = file("think_ok.jsonl", [
+      '{"messages":[{"role":"user","content":"hi"},{"role":"assistant","content":"<think>\\nreasoning\\n</think>\\n\\nanswer"}]}',
+    ]);
+    const r = await validateDataset(p, { fullValidate: true });
+    expect(r.valid).toBe(true);
+    expect(codes(r).warnings).not.toContain("THINK_TAG_NOT_LAST");
+  });
+
+  test("think tag in non-last assistant → THINK_TAG_NOT_LAST warning", async () => {
+    const p = file("think_mid.jsonl", [
+      '{"messages":[{"role":"user","content":"hi"},{"role":"assistant","content":"<think>\\nearly\\n</think>\\n\\nmid"},{"role":"user","content":"more"},{"role":"assistant","content":"final"}]}',
+    ]);
+    const r = await validateDataset(p, { fullValidate: true });
+    expect(r.valid).toBe(true);
+    expect(codes(r).warnings).toContain("THINK_TAG_NOT_LAST");
+  });
+
+  test("think tag in content array format detected", async () => {
+    const p = file("think_arr.jsonl", [
+      '{"messages":[{"role":"user","content":[{"text":"hi"}]},{"role":"assistant","content":[{"text":"<think>\\nreason\\n</think>\\n\\nans"}]},{"role":"user","content":[{"text":"more"}]},{"role":"assistant","content":[{"text":"final"}]}]}',
+    ]);
+    const r = await validateDataset(p, { fullValidate: true });
+    expect(r.valid).toBe(true);
+    expect(codes(r).warnings).toContain("THINK_TAG_NOT_LAST");
+  });
+
+  test("official tool+thinking combo: think in non-last assistant WITH tool_calls is exempt", async () => {
+    // Mirrors the platform spec's 工具与思考组合 example: the assistant that
+    // issues tool_calls carries the <think> block, the final assistant answers.
+    const p = file("think_tool_combo.jsonl", [
+      JSON.stringify({
+        tools: [
+          {
+            type: "function",
+            function: { name: "get_weather", description: "d", parameters: { type: "object" } },
+          },
+        ],
+        messages: [
+          { role: "user", content: [{ text: "weather in Beijing?" }] },
+          {
+            role: "assistant",
+            content: [{ text: "<think>\nneed the weather tool\n</think>\n" }],
+            tool_calls: [
+              {
+                id: "call_1",
+                type: "function",
+                function: { name: "get_weather", arguments: '{"city":"Beijing"}' },
+              },
+            ],
+          },
+          { role: "tool", tool_call_id: "call_1", content: [{ text: '{"weather":"sunny"}' }] },
+          { role: "assistant", content: [{ text: "It is sunny in Beijing." }] },
+        ],
+      }),
+    ]);
+    const r = await validateDataset(p, { fullValidate: true });
+    expect(r.valid).toBe(true);
+    expect(codes(r).warnings).not.toContain("THINK_TAG_NOT_LAST");
+  });
+});
+
+describe("validateDataset — OpenAI migration guards", () => {
+  test("message-level name field → UNSUPPORTED_FIELD_NAME error", async () => {
+    const p = file("openai_name.jsonl", [
+      '{"messages":[{"role":"user","content":"hi","name":"alice"},{"role":"assistant","content":"hello"}]}',
+    ]);
+    const r = await validateDataset(p, { fullValidate: true });
+    expect(r.valid).toBe(false);
+    expect(codes(r).errors).toContain("UNSUPPORTED_FIELD_NAME");
+  });
+
+  test("message-level weight field → UNSUPPORTED_FIELD_WEIGHT error", async () => {
+    const p = file("openai_weight.jsonl", [
+      '{"messages":[{"role":"user","content":"hi"},{"role":"assistant","content":"hello","weight":0.5}]}',
+    ]);
+    const r = await validateDataset(p, { fullValidate: true });
+    expect(r.valid).toBe(false);
+    expect(codes(r).errors).toContain("UNSUPPORTED_FIELD_WEIGHT");
+  });
+
+  test("record-level weight field → UNSUPPORTED_FIELD_WEIGHT error", async () => {
+    const p = file("record_weight.jsonl", [
+      '{"messages":[{"role":"user","content":"hi"},{"role":"assistant","content":"hello"}],"weight":1}',
+    ]);
+    const r = await validateDataset(p, { fullValidate: true });
+    expect(r.valid).toBe(false);
+    expect(codes(r).errors).toContain("UNSUPPORTED_FIELD_WEIGHT");
+  });
+});
+
+describe("validateDataset — loss_weight", () => {
+  test("valid loss_weight (0.5) passes", async () => {
+    const p = file("lw_ok.jsonl", [
+      '{"messages":[{"role":"user","content":"hi"},{"role":"assistant","content":"hello"}],"loss_weight":0.5}',
+    ]);
+    const r = await validateDataset(p, { fullValidate: true });
+    expect(r.valid).toBe(true);
+    expect(codes(r).errors).not.toContain("INVALID_LOSS_WEIGHT");
+  });
+
+  test("loss_weight out of range (1.5) → INVALID_LOSS_WEIGHT", async () => {
+    const p = file("lw_bad.jsonl", [
+      '{"messages":[{"role":"user","content":"hi"},{"role":"assistant","content":"hello"}],"loss_weight":1.5}',
+    ]);
+    const r = await validateDataset(p, { fullValidate: true });
+    expect(r.valid).toBe(false);
+    expect(codes(r).errors).toContain("INVALID_LOSS_WEIGHT");
+  });
+
+  test("loss_weight negative → INVALID_LOSS_WEIGHT", async () => {
+    const p = file("lw_neg.jsonl", [
+      '{"messages":[{"role":"user","content":"hi"},{"role":"assistant","content":"hello"}],"loss_weight":-0.1}',
+    ]);
+    const r = await validateDataset(p, { fullValidate: true });
+    expect(r.valid).toBe(false);
+    expect(codes(r).errors).toContain("INVALID_LOSS_WEIGHT");
+  });
+
+  test("loss_weight non-number → INVALID_LOSS_WEIGHT", async () => {
+    const p = file("lw_str.jsonl", [
+      '{"messages":[{"role":"user","content":"hi"},{"role":"assistant","content":"hello"}],"loss_weight":"high"}',
+    ]);
+    const r = await validateDataset(p, { fullValidate: true });
+    expect(r.valid).toBe(false);
+    expect(codes(r).errors).toContain("INVALID_LOSS_WEIGHT");
+  });
+
+  test("loss_weight boundary values 0 and 1 pass", async () => {
+    const p = file("lw_boundary.jsonl", [
+      '{"messages":[{"role":"user","content":"a"},{"role":"assistant","content":"b"}],"loss_weight":0}',
+      '{"messages":[{"role":"user","content":"c"},{"role":"assistant","content":"d"}],"loss_weight":1}',
+    ]);
+    const r = await validateDataset(p, { fullValidate: true });
+    expect(r.valid).toBe(true);
+  });
+
+  test("message-level loss_weight on the LAST assistant passes without warning", async () => {
+    const p = file("lw_msg_last.jsonl", [
+      '{"messages":[{"role":"user","content":"hi"},{"role":"assistant","content":"hello","loss_weight":0.8}]}',
+    ]);
+    const r = await validateDataset(p, { fullValidate: true });
+    expect(r.valid).toBe(true);
+    expect(codes(r).warnings).not.toContain("LOSS_WEIGHT_PLACEMENT");
+  });
+
+  test("message-level loss_weight on a non-last assistant → LOSS_WEIGHT_PLACEMENT warning", async () => {
+    const p = file("lw_msg_mid.jsonl", [
+      '{"messages":[{"role":"user","content":"a"},{"role":"assistant","content":"b","loss_weight":0.8},{"role":"user","content":"c"},{"role":"assistant","content":"d"}]}',
+    ]);
+    const r = await validateDataset(p, { fullValidate: true });
+    expect(codes(r).warnings).toContain("LOSS_WEIGHT_PLACEMENT");
+  });
+
+  test("message-level loss_weight out of range → INVALID_LOSS_WEIGHT", async () => {
+    const p = file("lw_msg_range.jsonl", [
+      '{"messages":[{"role":"user","content":"hi"},{"role":"assistant","content":"hello","loss_weight":2}]}',
+    ]);
+    const r = await validateDataset(p, { fullValidate: true });
+    expect(r.valid).toBe(false);
+    expect(codes(r).errors).toContain("INVALID_LOSS_WEIGHT");
+  });
+});
+
+describe("validateDataset — video content params", () => {
+  test("path-mode video with in-range fps and clip times passes", async () => {
+    const p = file("video_path_ok.jsonl", [
+      '{"messages":[{"role":"user","content":[{"text":"desc"},{"video":"v.mp4","fps":3.0,"video_start":0.0,"video_end":3.0}]},{"role":"assistant","content":[{"text":"ok"}]}]}',
+    ]);
+    const r = await validateDataset(p, { fullValidate: true });
+    expect(r.valid).toBe(true);
+    expect(codes(r).warnings).not.toContain("VIDEO_PARAM_MODE_MISMATCH");
+  });
+
+  test("fps out of [0.1, 10] → INVALID_VIDEO_FPS error", async () => {
+    const p = file("video_fps_bad.jsonl", [
+      '{"messages":[{"role":"user","content":[{"text":"desc"},{"video":"v.mp4","fps":30}]},{"role":"assistant","content":[{"text":"ok"}]}]}',
+    ]);
+    const r = await validateDataset(p, { fullValidate: true });
+    expect(r.valid).toBe(false);
+    expect(codes(r).errors).toContain("INVALID_VIDEO_FPS");
+  });
+
+  test("sample_fps on path-mode video → VIDEO_PARAM_MODE_MISMATCH warning", async () => {
+    const p = file("video_mode_mix.jsonl", [
+      '{"messages":[{"role":"user","content":[{"text":"desc"},{"video":"v.mp4","sample_fps":2.0}]},{"role":"assistant","content":[{"text":"ok"}]}]}',
+    ]);
+    const r = await validateDataset(p, { fullValidate: true });
+    expect(codes(r).warnings).toContain("VIDEO_PARAM_MODE_MISMATCH");
+  });
+
+  test("frame-list video with sample_fps passes; fps there is flagged", async () => {
+    const p = file("video_frames.jsonl", [
+      '{"messages":[{"role":"user","content":[{"text":"desc"},{"video":["0.jpg","1.jpg"],"sample_fps":5.0}]},{"role":"assistant","content":[{"text":"ok"}]}]}',
+      '{"messages":[{"role":"user","content":[{"text":"desc"},{"video":["0.jpg"],"fps":2.0}]},{"role":"assistant","content":[{"text":"ok"}]}]}',
+    ]);
+    const r = await validateDataset(p, { fullValidate: true });
+    expect(r.valid).toBe(true);
+    expect(codes(r).warnings).toContain("VIDEO_PARAM_MODE_MISMATCH");
+  });
+});
+
+describe("validateZipFilenames — macOS metadata entries", () => {
+  test("__MACOSX / .DS_Store / ._resource-fork entries are ignored", async () => {
+    const { validateZipFilenames } = await import("../src/dataset/validate/zip.ts");
+    const issues = validateZipFilenames([
+      "data.jsonl",
+      "image_1.jpg",
+      "__MACOSX/._image_1.jpg",
+      "__MACOSX/",
+      ".DS_Store",
+      "train/._clip.wav",
+    ]);
+    expect(issues).toEqual([]);
+  });
+
+  test("real charset violations are still reported", async () => {
+    const { validateZipFilenames } = await import("../src/dataset/validate/zip.ts");
+    const issues = validateZipFilenames(["data.jsonl", "图片1.jpg"]);
+    expect(issues.map((issue) => issue.code)).toContain("INVALID_FILENAME_CHARSET");
+  });
+});
+
 describe("parseDatasetSchemaFlag", () => {
   test("undefined / empty → undefined (auto)", () => {
     expect(parseDatasetSchemaFlag(undefined)).toBeUndefined();

packages/core/tests/skills-agents.test.ts

@@ -293,21 +293,52 @@ test("agents: Amp-style XDG config dir lights up the universal-xdg shared target
   });
 });
 
-test("agents: recorded copy-fallback artifact is replaced; unrecorded dir stays skipped", async () => {
+test("agents: foreign skill dir (contains SKILL.md) is replaced even without lock record", async () => {
   await inFakeHome(async (home) => {
     mkdirSync(join(home, ".claude"), { recursive: true });
     const canonical = seedCanonicalSkill("demo");
     const copyPath = join(home, ".claude", "skills", "demo");
 
-    // Simulate a previous install that fell back to copy (no symlink permission, e.g. Windows)
+    // Simulate a skill installed by another tool (e.g. `npx skills add`) — a real
+    // directory containing SKILL.md, not recorded in our lock.
+    mkdirSync(copyPath, { recursive: true });
+    writeFileSync(join(copyPath, "SKILL.md"), "stale copy from another tool");
+
+    // New behavior: contains SKILL.md → recognized as a skill artifact → replaced
+    const result = linkSkillToAgents("demo");
+    expect(result[0]).toMatchObject({ agent: "claude-code", mode: "symlink" });
+    expect(lstatSync(copyPath).isSymbolicLink()).toBe(true);
+    expect(readlinkSync(copyPath)).toBe(canonical);
+  });
+});
+
+test("agents: foreign non-skill dir (no SKILL.md) stays skipped", async () => {
+  await inFakeHome(async (home) => {
+    mkdirSync(join(home, ".claude"), { recursive: true });
+    seedCanonicalSkill("demo");
+    const foreignPath = join(home, ".claude", "skills", "demo");
+
+    // A user's own directory that happens to share the skill name but has no SKILL.md
+    mkdirSync(foreignPath, { recursive: true });
+    writeFileSync(join(foreignPath, "my-notes.txt"), "user content");
+
+    const result = linkSkillToAgents("demo");
+    expect(result[0].mode).toBe("skipped");
+    // User content untouched
+    expect(readFileSync(join(foreignPath, "my-notes.txt"), "utf-8")).toBe("user content");
+  });
+});
+
+test("agents: recorded copy-fallback artifact is replaced with symlink", async () => {
+  await inFakeHome(async (home) => {
+    mkdirSync(join(home, ".claude"), { recursive: true });
+    const canonical = seedCanonicalSkill("demo");
+    const copyPath = join(home, ".claude", "skills", "demo");
+
+    // Simulate a previous install that fell back to copy (no symlink permission)
     mkdirSync(copyPath, { recursive: true });
     writeFileSync(join(copyPath, "SKILL.md"), "stale copy");
 
-    // Without a lock record the dir is foreign → skipped, content untouched
-    const unrecorded = linkSkillToAgents("demo");
-    expect(unrecorded[0].mode).toBe("skipped");
-    expect(readFileSync(join(copyPath, "SKILL.md"), "utf-8")).toBe("stale copy");
-
     // With the recorded link the artifact is rebuilt and points at canonical again
     const recorded = linkSkillToAgents("demo", detectInstalledAgents(), [copyPath]);
     expect(recorded[0]).toMatchObject({ agent: "claude-code", mode: "symlink" });

packages/kscli/package.json

@@ -1,6 +1,6 @@
 {
   "name": "knowledge-studio-cli",
-  "version": "1.15.0",
+  "version": "1.15.1",
   "description": "Lightweight RAG CLI for Aliyun Model Studio — focused on knowledge-base retrieval.",
   "keywords": [
     "alibaba-cloud",

packages/runtime/package.json

@@ -1,6 +1,6 @@
 {
   "name": "bailian-cli-runtime",
-  "version": "1.15.0",
+  "version": "1.15.1",
   "description": "Runtime framework for bailian-cli (createCli, registry, args, output, pipeline). See https://www.npmjs.com/package/bailian-cli for usage.",
   "homepage": "https://bailian.console.aliyun.com/cli",
   "bugs": {

skills/bailian-cli/SKILL.md

@@ -1,7 +1,7 @@
 ---
 name: bailian-cli
 metadata:
-  version: "1.15.0"
+  version: "1.15.1"
   requires:
     bins: ["bl"]
 description: >-

skills/bailian-finetune/SKILL.md

@@ -1,7 +1,7 @@
 ---
 name: bailian-finetune
 metadata:
-  version: "1.15.0"
+  version: "1.15.1"
   requires:
     bins: ["bl"]
 description: >-
@@ -23,14 +23,14 @@ description: >-
 ```
 1. Validate data   bl dataset validate --file train.jsonl [--schema chatml|dpo|cpt|tts|image]
 2. Upload data     bl dataset upload --file train.jsonl          # returns a file-id
-3. Create job      bl finetune text|audio|image create --model <base> --datasets <file-id|path>
+3. Create job      bl finetune text|audio|image create --base-model <base> --datasets <file-id|path>
 4. Watch progress  bl finetune watch --job-id ft-xxx             # or get / logs
 5. Pick artifact   bl finetune checkpoints --job-id ft-xxx
 6. Export model    bl finetune export --job-id ft-xxx --checkpoint ckpt-N --model-name my-model
-7. Deploy service  bl deploy text|audio|image create --model my-model --name my-svc
+7. Deploy service  bl deploy text|audio|image create --model-name my-model --display-name my-svc
 ```
 
-- Unsure which training methods a base model supports → `bl finetune capability --model <base>` or `--training-type sft|sft-lora|dpo|cpt`.
+- Unsure which training methods a base model supports → `bl finetune capability --base-model <base>` or `--training-type sft|sft-lora|dpo|cpt`.
 - Text `--training-type` values: `sft` / `sft-lora` / `dpo` / `dpo-lora` / `cpt`. Audio bases include `cosyvoice-v3-flash`; image bases include `wan2.7-image-pro`.
 - Deployment plans: audio defaults to `--plan mu`; text/image default to `lora`.
 - Preview write operations (create / delete / cancel / scale) with `--dry-run` first, and confirm with the user before deleting a job or dataset.
@@ -55,10 +55,10 @@ Flags, usage, and examples: see [`reference/`](reference/index.md) or `bl <comma
 ```bash
 bl dataset validate --file train.jsonl
 bl dataset upload --file train.jsonl
-bl finetune text create --model qwen3-8b --training-type sft-lora --datasets file-xxx
+bl finetune text create --base-model qwen3-8b --training-type sft-lora --datasets file-xxx
 bl finetune watch --job-id ft-xxx
 bl finetune export --job-id ft-xxx --checkpoint ckpt-3 --model-name my-qwen-sft
-bl deploy text create --model my-qwen-sft --name my-svc
+bl deploy text create --model-name my-qwen-sft --display-name my-svc
 ```
 
 ## Common hand-offs

skills/bailian-finetune/reference/dataset.md

@@ -110,35 +110,36 @@ bl dataset list --output json
 
 ### `bl dataset upload`
 
-| Field              | Value                                                                                                                            |
-| ------------------ | -------------------------------------------------------------------------------------------------------------------------------- |
-| **Name**           | `dataset upload`                                                                                                                 |
-| **Description**    | Upload a dataset file (.jsonl or .zip) to Bailian                                                                                |
-| **Authentication** | API Key                                                                                                                          |
-| **Usage**          | `bl dataset upload --file <path> [--purpose <name>] [--schema <chatml\|dpo\|cpt\|tts\|image>] [--no-validate] [--full-validate]` |
+| Field              | Value                                                                                                                                   |
+| ------------------ | --------------------------------------------------------------------------------------------------------------------------------------- |
+| **Name**           | `dataset upload`                                                                                                                        |
+| **Description**    | Upload a dataset file (.jsonl or .zip) to Bailian                                                                                       |
+| **Authentication** | API Key                                                                                                                                 |
+| **Usage**          | `bl dataset upload --file <path> [--purpose <name>] [--schema <chatml\|dpo\|cpt\|tts\|image\|video>] [--no-validate] [--full-validate]` |
 
 #### Flags
 
-| Flag               | Type   | Required | Description                                                                                                                                              |
-| ------------------ | ------ | -------- | -------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `--file <path>`    | string | yes      | Local dataset file (.jsonl or .zip; ≤300MB text, ≤1GB image)                                                                                             |
-| `--purpose <name>` | string | no       | Dataset purpose tag (default: "fine-tune"; e.g. "evaluation")                                                                                            |
-| `--schema <s>`     | string | no       | Record schema: "chatml" (SFT), "dpo" (chosen/rejected), "cpt" (raw text), "tts" (audio), or "image" (image generation). Default auto-detects per record. |
-| `--no-validate`    | switch | no       | Skip the local JSONL pre-flight check (not recommended)                                                                                                  |
-| `--full-validate`  | switch | no       | JSON.parse every line instead of sampling (slower)                                                                                                       |
-| `--api-key <key>`  | string | no       | API key                                                                                                                                                  |
-| `--base-url <url>` | string | no       | API base URL                                                                                                                                             |
+| Flag               | Type   | Required | Description                                                                                                                                                                          |
+| ------------------ | ------ | -------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
+| `--file <path>`    | string | yes      | Local dataset file (.jsonl or .zip; ≤200MB SFT/DPO, ≤300MB CPT, ≤2GB media zip)                                                                                                      |
+| `--purpose <name>` | string | no       | Dataset purpose tag (default: "fine-tune"; e.g. "evaluation")                                                                                                                        |
+| `--schema <s>`     | string | no       | Record schema: "chatml" (SFT), "dpo" (chosen/rejected), "cpt" (raw text), "tts" (audio), "image" (image generation), or "video" (video generation). Default auto-detects per record. |
+| `--no-validate`    | switch | no       | Skip the local JSONL pre-flight check (not recommended)                                                                                                                              |
+| `--full-validate`  | switch | no       | JSON.parse every line instead of sampling (slower)                                                                                                                                   |
+| `--api-key <key>`  | string | no       | API key                                                                                                                                                                              |
+| `--base-url <url>` | string | no       | API base URL                                                                                                                                                                         |
 
 #### Notes
 
 - Supports .jsonl (text) and .zip (audio/image archives with a data.jsonl
-- manifest). Five record schemas are recognized: chatml = {messages:[...]}
+- manifest). Six record schemas are recognized: chatml = {messages:[...]}
 - (SFT); dpo = {messages:[...], chosen, rejected}; cpt = {text:"..."}
 - (continual pre-training, raw text); tts = {wav_fn:"train/xxx.wav",
 - text:"..."} (audio fine-tuning); image = {img_path:"..."} (image
-- generation). With no --schema, a record carrying wav_fn is validated as
-- TTS, img_path as image, chosen/rejected as DPO, text (no messages) as CPT,
-- otherwise ChatML. Upload cap: 300MB text, 1GB image. Upload uses the
+- generation); video = {first_frame_path:...} (video generation). With no
+- --schema, a record carrying wav_fn is validated as TTS, img_path as image,
+- chosen/rejected as DPO, text (no messages) as CPT, otherwise ChatML.
+- Upload cap: 200MB SFT/DPO text, 300MB CPT, 2GB media zip. Upload uses the
 - OpenAI-compatible /compatible-mode/v1/files endpoint so the purpose tag is
 - persisted (the DashScope-native /api/v1/files drops it).
 
@@ -174,20 +175,20 @@ bl dataset upload --file train.jsonl --no-validate
 
 ### `bl dataset validate`
 
-| Field              | Value                                                                                           |
-| ------------------ | ----------------------------------------------------------------------------------------------- |
-| **Name**           | `dataset validate`                                                                              |
-| **Description**    | Locally validate a dataset file (.jsonl or .zip) without uploading                              |
-| **Authentication** | No Auth                                                                                         |
-| **Usage**          | `bl dataset validate --file <path> [--full-validate] [--schema <chatml\|dpo\|cpt\|tts\|image>]` |
+| Field              | Value                                                                                                  |
+| ------------------ | ------------------------------------------------------------------------------------------------------ |
+| **Name**           | `dataset validate`                                                                                     |
+| **Description**    | Locally validate a dataset file (.jsonl or .zip) without uploading                                     |
+| **Authentication** | No Auth                                                                                                |
+| **Usage**          | `bl dataset validate --file <path> [--full-validate] [--schema <chatml\|dpo\|cpt\|tts\|image\|video>]` |
 
 #### Flags
 
-| Flag              | Type   | Required | Description                                                                                                                                              |
-| ----------------- | ------ | -------- | -------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `--file <path>`   | string | yes      | Local dataset file (.jsonl or .zip)                                                                                                                      |
-| `--full-validate` | switch | no       | JSON.parse every line instead of sampling (slower)                                                                                                       |
-| `--schema <s>`    | string | no       | Record schema: "chatml" (SFT), "dpo" (chosen/rejected), "cpt" (raw text), "tts" (audio), or "image" (image generation). Default auto-detects per record. |
+| Flag              | Type   | Required | Description                                                                                                                                                                          |
+| ----------------- | ------ | -------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
+| `--file <path>`   | string | yes      | Local dataset file (.jsonl or .zip)                                                                                                                                                  |
+| `--full-validate` | switch | no       | JSON.parse every line instead of sampling (slower)                                                                                                                                   |
+| `--schema <s>`    | string | no       | Record schema: "chatml" (SFT), "dpo" (chosen/rejected), "cpt" (raw text), "tts" (audio), "image" (image generation), or "video" (video generation). Default auto-detects per record. |
 
 #### Notes
 
@@ -196,13 +197,15 @@ bl dataset upload --file train.jsonl --no-validate
 - Schemas: chatml = {messages:[...]} (SFT); dpo = {messages:[...], chosen,
 - rejected}; cpt = {text:"..."} (continual pre-training, raw text);
 - tts = {wav_fn:"train/xxx.wav", text:"..."} (audio fine-tuning);
-- image = {img_path:"..."} (image generation). With no --schema, a record
-- carrying wav_fn is validated as TTS, img_path as image, chosen/rejected
-- as DPO, text (no messages) as CPT, otherwise ChatML. Pass --schema to
-- require a specific shape on every record. ZIP archives (.zip) are
-- validated structurally (data.jsonl present, media references resolve) in
-- addition to per-record content checks. Use --full-validate to JSON.parse
-- every line.
+- image = {img_path:"..."} (image generation);
+- video = {first_frame_path:"...", video_path:"..."} (video generation,
+- i2v first-frame or kf2v first+last-frame with last_frame_path). With no
+- --schema, a record carrying wav_fn is validated as TTS, img_path as image,
+- first_frame_path/video_path as video, chosen/rejected as DPO, text (no
+- messages) as CPT, otherwise ChatML. Pass --schema to require a specific
+- shape on every record. ZIP archives (.zip) are validated structurally
+- (data.jsonl present, media references resolve) in addition to per-record
+- content checks. Use --full-validate to JSON.parse every line.
 
 #### Examples
 
@@ -222,6 +225,10 @@ bl dataset validate --file cpt.jsonl --schema cpt
 bl dataset validate --file audio.zip --schema tts
 ```
 
+```bash
+bl dataset validate --file wan-i2v-training-dataset.zip --schema video
+```
+
 ```bash
 bl dataset validate --file eval.jsonl --full-validate
 ```

skills/bailian-finetune/reference/deploy.md

@@ -7,44 +7,46 @@ Index: [index.md](index.md)
 
 ## Commands in this group
 
-| Command                  | Authentication | Description                                               |
-| ------------------------ | -------------- | --------------------------------------------------------- |
-| `bl deploy audio create` | API Key        | Create an audio (TTS) model deployment                    |
-| `bl deploy delete`       | API Key        | Delete a model deployment (must be STOPPED or FAILED)     |
-| `bl deploy get`          | API Key        | Get details of a single model deployment                  |
-| `bl deploy image create` | API Key        | Create an image generation model deployment               |
-| `bl deploy list`         | API Key        | List model deployments                                    |
-| `bl deploy models`       | API Key        | List models available for deployment                      |
-| `bl deploy scale`        | API Key        | Scale a deployment's capacity                             |
-| `bl deploy text create`  | API Key        | Create a text model deployment                            |
-| `bl deploy update`       | API Key        | Update a deployment's rate limits (rpm_limit / tpm_limit) |
+| Command                  | Authentication | Description                                                   |
+| ------------------------ | -------------- | ------------------------------------------------------------- |
+| `bl deploy audio create` | API Key        | Create an audio (TTS) model deployment                        |
+| `bl deploy delete`       | API Key        | Delete a model deployment (must be STOPPED or FAILED)         |
+| `bl deploy get`          | API Key        | Get details of a single model deployment                      |
+| `bl deploy image create` | API Key        | Create an image generation model deployment                   |
+| `bl deploy list`         | API Key        | List model deployments                                        |
+| `bl deploy models`       | API Key        | List models available for deployment                          |
+| `bl deploy pause`        | Console        | Pause a running model deployment (stops billing for mu/ptu)   |
+| `bl deploy resume`       | Console        | Resume a paused model deployment (brings service back online) |
+| `bl deploy scale`        | API Key        | Scale a deployment's capacity                                 |
+| `bl deploy text create`  | API Key        | Create a text model deployment                                |
+| `bl deploy update`       | API Key        | Update a deployment's rate limits (rpm_limit / tpm_limit)     |
 
 ## Command details
 
 ### `bl deploy audio create`
 
-| Field              | Value                                                                                                                                                                                                             |
-| ------------------ | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| **Name**           | `deploy audio create`                                                                                                                                                                                             |
-| **Description**    | Create an audio (TTS) model deployment                                                                                                                                                                            |
-| **Authentication** | API Key                                                                                                                                                                                                           |
-| **Usage**          | `bl deploy audio create --model <model_name> --name <display_name> [--plan <plan>] [--deploy-spec <id>] [--capacity <n>] [--billing-method <m>] [--input-tpm <n>] [--output-tpm <n>] [--thinking-output-tpm <n>]` |
+| Field              | Value                                                                                                                                                                                                                          |
+| ------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
+| **Name**           | `deploy audio create`                                                                                                                                                                                                          |
+| **Description**    | Create an audio (TTS) model deployment                                                                                                                                                                                         |
+| **Authentication** | API Key                                                                                                                                                                                                                        |
+| **Usage**          | `bl deploy audio create --model-name <model_name> --display-name <display_name> [--plan <plan>] [--deploy-spec <id>] [--capacity <n>] [--billing-method <m>] [--input-tpm <n>] [--output-tpm <n>] [--thinking-output-tpm <n>]` |
 
 #### Flags
 
-| Flag                        | Type   | Required | Description                                                                     |
-| --------------------------- | ------ | -------- | ------------------------------------------------------------------------------- |
-| `--model <name>`            | string | yes      | Model name (catalog model or fine-tuned output) (required)                      |
-| `--name <display_name>`     | string | yes      | Console display name for the deployment (required)                              |
-| `--plan <plan>`             | string | no       | Billing plan: lora (default, Token-billed) \| ptu (Token-billed) \| mu          |
-| `--deploy-spec <id>`        | string | no       | Deploy spec (only used by plan=mu; auto-picked if omitted)                      |
-| `--capacity <n>`            | number | no       | Resource units (plan=mu only; required by API; defaults to the template's unit) |
-| `--billing-method <m>`      | string | no       | Billing method (plan=mu only; default "POST_PAY", the only supported value)     |
-| `--input-tpm <n>`           | number | no       | PTU max input tokens/min (required for plan=ptu)                                |
-| `--output-tpm <n>`          | number | no       | PTU max output tokens/min (required for plan=ptu)                               |
-| `--thinking-output-tpm <n>` | number | no       | PTU max thinking-output tokens/min (optional, some models)                      |
-| `--api-key <key>`           | string | no       | API key                                                                         |
-| `--base-url <url>`          | string | no       | API base URL                                                                    |
+| Flag                            | Type   | Required | Description                                                                     |
+| ------------------------------- | ------ | -------- | ------------------------------------------------------------------------------- |
+| `--model-name <model_name>`     | string | yes      | Model to deploy — fine-tuned output name or catalog model (required)            |
+| `--display-name <display_name>` | string | yes      | Console display name for the deployment (required)                              |
+| `--plan <plan>`                 | string | no       | Billing plan: lora (default, Token-billed) \| ptu (Token-billed) \| mu          |
+| `--deploy-spec <id>`            | string | no       | Deploy spec (only used by plan=mu; auto-picked if omitted)                      |
+| `--capacity <n>`                | number | no       | Resource units (plan=mu only; required by API; defaults to the template's unit) |
+| `--billing-method <m>`          | string | no       | Billing method (plan=mu only; default "POST_PAY", the only supported value)     |
+| `--input-tpm <n>`               | number | no       | PTU max input tokens/min (required for plan=ptu)                                |
+| `--output-tpm <n>`              | number | no       | PTU max output tokens/min (required for plan=ptu)                               |
+| `--thinking-output-tpm <n>`     | number | no       | PTU max thinking-output tokens/min (optional, some models)                      |
+| `--api-key <key>`               | string | no       | API key                                                                         |
+| `--base-url <url>`              | string | no       | API base URL                                                                    |
 
 #### Notes
 
@@ -59,27 +61,24 @@ Index: [index.md](index.md)
 - Use `bl deploy models --source base` to inspect available templates.
 - After creation, status starts at PENDING and transitions to RUNNING.
 - Invoke the deployed model with: bl text chat --model <deployed_model>
-- WARNING: --model is overloaded across commands and refers to DIFFERENT
-- values. `bl deploy <modality> create --model` takes the exported model_name
-- (e.g. `qwen3-8b-ft-...`), but the create response also returns a
-- `deployed_model` field (the deployment instance id, e.g.
-- `qwen3-8b-5ecb5f068d79`). The inference call `bl text chat --model` must use
-- the `deployed_model` from the create response — NOT the `model_name` you
-- passed to `deploy <modality> create`. Do not reuse the value across the two
-- commands.
+- NOTE: --model-name is the model being deployed (e.g. `qwen3-8b-ft-...`).
+- The create response also returns a `deployed_model` field — the deployment
+- instance id (e.g. `qwen3-8b-5ecb5f068d79`). Use that id for inference
+- (`bl text chat --model <deployed_model>`) and lifecycle commands
+- (`deploy get/scale/pause/resume/delete --deployed-model <id>`).
 
 #### Examples
 
 ```bash
-bl deploy audio create --model my-cosyvoice-ft --name my-tts
+bl deploy audio create --model-name my-cosyvoice-ft --display-name my-tts
 ```
 
 ```bash
-bl deploy audio create --model my-cosyvoice-ft --name my-tts --deploy-spec dps-xxxx --capacity 1
+bl deploy audio create --model-name my-cosyvoice-ft --display-name my-tts --deploy-spec dps-xxxx --capacity 1
 ```
 
 ```bash
-bl deploy audio create --model my-cosyvoice-ft --name my-tts --dry-run
+bl deploy audio create --model-name my-cosyvoice-ft --display-name my-tts --dry-run
 ```
 
 ### `bl deploy delete`
@@ -139,28 +138,28 @@ bl deploy get --deployed-model qwen-plus-2025-12-01-b6d61c71 --output json
 
 ### `bl deploy image create`
 
-| Field              | Value                                                                                                                                                                                                             |
-| ------------------ | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| **Name**           | `deploy image create`                                                                                                                                                                                             |
-| **Description**    | Create an image generation model deployment                                                                                                                                                                       |
-| **Authentication** | API Key                                                                                                                                                                                                           |
-| **Usage**          | `bl deploy image create --model <model_name> --name <display_name> [--plan <plan>] [--deploy-spec <id>] [--capacity <n>] [--billing-method <m>] [--input-tpm <n>] [--output-tpm <n>] [--thinking-output-tpm <n>]` |
+| Field              | Value                                                                                                                                                                                                                          |
+| ------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
+| **Name**           | `deploy image create`                                                                                                                                                                                                          |
+| **Description**    | Create an image generation model deployment                                                                                                                                                                                    |
+| **Authentication** | API Key                                                                                                                                                                                                                        |
+| **Usage**          | `bl deploy image create --model-name <model_name> --display-name <display_name> [--plan <plan>] [--deploy-spec <id>] [--capacity <n>] [--billing-method <m>] [--input-tpm <n>] [--output-tpm <n>] [--thinking-output-tpm <n>]` |
 
 #### Flags
 
-| Flag                        | Type   | Required | Description                                                                     |
-| --------------------------- | ------ | -------- | ------------------------------------------------------------------------------- |
-| `--model <name>`            | string | yes      | Model name (catalog model or fine-tuned output) (required)                      |
-| `--name <display_name>`     | string | yes      | Console display name for the deployment (required)                              |
-| `--plan <plan>`             | string | no       | Billing plan: lora (default, Token-billed) \| ptu (Token-billed) \| mu          |
-| `--deploy-spec <id>`        | string | no       | Deploy spec (only used by plan=mu; auto-picked if omitted)                      |
-| `--capacity <n>`            | number | no       | Resource units (plan=mu only; required by API; defaults to the template's unit) |
-| `--billing-method <m>`      | string | no       | Billing method (plan=mu only; default "POST_PAY", the only supported value)     |
-| `--input-tpm <n>`           | number | no       | PTU max input tokens/min (required for plan=ptu)                                |
-| `--output-tpm <n>`          | number | no       | PTU max output tokens/min (required for plan=ptu)                               |
-| `--thinking-output-tpm <n>` | number | no       | PTU max thinking-output tokens/min (optional, some models)                      |
-| `--api-key <key>`           | string | no       | API key                                                                         |
-| `--base-url <url>`          | string | no       | API base URL                                                                    |
+| Flag                            | Type   | Required | Description                                                                     |
+| ------------------------------- | ------ | -------- | ------------------------------------------------------------------------------- |
+| `--model-name <model_name>`     | string | yes      | Model to deploy — fine-tuned output name or catalog model (required)            |
+| `--display-name <display_name>` | string | yes      | Console display name for the deployment (required)                              |
+| `--plan <plan>`                 | string | no       | Billing plan: lora (default, Token-billed) \| ptu (Token-billed) \| mu          |
+| `--deploy-spec <id>`            | string | no       | Deploy spec (only used by plan=mu; auto-picked if omitted)                      |
+| `--capacity <n>`                | number | no       | Resource units (plan=mu only; required by API; defaults to the template's unit) |
+| `--billing-method <m>`          | string | no       | Billing method (plan=mu only; default "POST_PAY", the only supported value)     |
+| `--input-tpm <n>`               | number | no       | PTU max input tokens/min (required for plan=ptu)                                |
+| `--output-tpm <n>`              | number | no       | PTU max output tokens/min (required for plan=ptu)                               |
+| `--thinking-output-tpm <n>`     | number | no       | PTU max thinking-output tokens/min (optional, some models)                      |
+| `--api-key <key>`               | string | no       | API key                                                                         |
+| `--base-url <url>`              | string | no       | API base URL                                                                    |
 
 #### Notes
 
@@ -175,27 +174,24 @@ bl deploy get --deployed-model qwen-plus-2025-12-01-b6d61c71 --output json
 - Use `bl deploy models --source base` to inspect available templates.
 - After creation, status starts at PENDING and transitions to RUNNING.
 - Invoke the deployed model with: bl text chat --model <deployed_model>
-- WARNING: --model is overloaded across commands and refers to DIFFERENT
-- values. `bl deploy <modality> create --model` takes the exported model_name
-- (e.g. `qwen3-8b-ft-...`), but the create response also returns a
-- `deployed_model` field (the deployment instance id, e.g.
-- `qwen3-8b-5ecb5f068d79`). The inference call `bl text chat --model` must use
-- the `deployed_model` from the create response — NOT the `model_name` you
-- passed to `deploy <modality> create`. Do not reuse the value across the two
-- commands.
+- NOTE: --model-name is the model being deployed (e.g. `qwen3-8b-ft-...`).
+- The create response also returns a `deployed_model` field — the deployment
+- instance id (e.g. `qwen3-8b-5ecb5f068d79`). Use that id for inference
+- (`bl text chat --model <deployed_model>`) and lifecycle commands
+- (`deploy get/scale/pause/resume/delete --deployed-model <id>`).
 
 #### Examples
 
 ```bash
-bl deploy image create --model my-wan-ft --name my-wan
+bl deploy image create --model-name my-wan-ft --display-name my-wan
 ```
 
 ```bash
-bl deploy image create --model my-wan-ft --name my-wan-mu --plan mu
+bl deploy image create --model-name my-wan-ft --display-name my-wan-mu --plan mu
 ```
 
 ```bash
-bl deploy image create --model my-wan-ft --name my-wan --dry-run
+bl deploy image create --model-name my-wan-ft --display-name my-wan --dry-run
 ```
 
 ### `bl deploy list`
@@ -269,6 +265,84 @@ bl deploy models --source custom --page-size 50
 bl deploy models --catalog-version v1.0 --output json
 ```
 
+### `bl deploy pause`
+
+| Field              | Value                                                       |
+| ------------------ | ----------------------------------------------------------- |
+| **Name**           | `deploy pause`                                              |
+| **Description**    | Pause a running model deployment (stops billing for mu/ptu) |
+| **Authentication** | Console                                                     |
+| **Usage**          | `bl deploy pause --deployed-model <id> [--skip-precheck]`   |
+
+#### Flags
+
+| Flag                           | Type   | Required | Description                                              |
+| ------------------------------ | ------ | -------- | -------------------------------------------------------- |
+| `--deployed-model <id>`        | string | yes      | Deployed model identifier (required)                     |
+| `--skip-precheck`              | switch | no       | Skip the local RUNNING/PENDING status precheck           |
+| `--console-region <region>`    | string | no       | Console gateway region (e.g. cn-beijing, ap-southeast-1) |
+| `--console-site <site>`        | string | no       | Console site: domestic, international                    |
+| `--console-switch-agent <uid>` | number | no       | Switch agent UID for delegated access                    |
+| `--workspace-id <id>`          | string | no       | Workspace ID (env: BAILIAN_WORKSPACE_ID)                 |
+
+#### Notes
+
+- While paused, billing ceases for mu/ptu plans. Use `deploy resume` to bring it back online or `deploy delete` to remove.
+- Precheck verifies status is RUNNING/PENDING before issuing the pause; pass --skip-precheck to bypass.
+
+#### Examples
+
+```bash
+bl deploy pause --deployed-model dep-...
+```
+
+```bash
+bl deploy pause --deployed-model dep-... --skip-precheck
+```
+
+```bash
+bl deploy pause --deployed-model dep-... --dry-run
+```
+
+### `bl deploy resume`
+
+| Field              | Value                                                         |
+| ------------------ | ------------------------------------------------------------- |
+| **Name**           | `deploy resume`                                               |
+| **Description**    | Resume a paused model deployment (brings service back online) |
+| **Authentication** | Console                                                       |
+| **Usage**          | `bl deploy resume --deployed-model <id> [--skip-precheck]`    |
+
+#### Flags
+
+| Flag                           | Type   | Required | Description                                              |
+| ------------------------------ | ------ | -------- | -------------------------------------------------------- |
+| `--deployed-model <id>`        | string | yes      | Deployed model identifier (required)                     |
+| `--skip-precheck`              | switch | no       | Skip the local STOPPED status precheck                   |
+| `--console-region <region>`    | string | no       | Console gateway region (e.g. cn-beijing, ap-southeast-1) |
+| `--console-site <site>`        | string | no       | Console site: domestic, international                    |
+| `--console-switch-agent <uid>` | number | no       | Switch agent UID for delegated access                    |
+| `--workspace-id <id>`          | string | no       | Workspace ID (env: BAILIAN_WORKSPACE_ID)                 |
+
+#### Notes
+
+- Precheck verifies status is STOPPED before issuing the resume; pass --skip-precheck to bypass.
+- For mu/ptu plans, billing resumes once the service is back online.
+
+#### Examples
+
+```bash
+bl deploy resume --deployed-model dep-...
+```
+
+```bash
+bl deploy resume --deployed-model dep-... --skip-precheck
+```
+
+```bash
+bl deploy resume --deployed-model dep-... --dry-run
+```
+
 ### `bl deploy scale`
 
 | Field              | Value                                                                                       |
@@ -301,28 +375,28 @@ bl deploy scale --deployed-model dep-... --capacity 2
 
 ### `bl deploy text create`
 
-| Field              | Value                                                                                                                                                                                                            |
-| ------------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| **Name**           | `deploy text create`                                                                                                                                                                                             |
-| **Description**    | Create a text model deployment                                                                                                                                                                                   |
-| **Authentication** | API Key                                                                                                                                                                                                          |
-| **Usage**          | `bl deploy text create --model <model_name> --name <display_name> [--plan <plan>] [--deploy-spec <id>] [--capacity <n>] [--billing-method <m>] [--input-tpm <n>] [--output-tpm <n>] [--thinking-output-tpm <n>]` |
+| Field              | Value                                                                                                                                                                                                                         |
+| ------------------ | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| **Name**           | `deploy text create`                                                                                                                                                                                                          |
+| **Description**    | Create a text model deployment                                                                                                                                                                                                |
+| **Authentication** | API Key                                                                                                                                                                                                                       |
+| **Usage**          | `bl deploy text create --model-name <model_name> --display-name <display_name> [--plan <plan>] [--deploy-spec <id>] [--capacity <n>] [--billing-method <m>] [--input-tpm <n>] [--output-tpm <n>] [--thinking-output-tpm <n>]` |
 
 #### Flags
 
-| Flag                        | Type   | Required | Description                                                                     |
-| --------------------------- | ------ | -------- | ------------------------------------------------------------------------------- |
-| `--model <name>`            | string | yes      | Model name (catalog model or fine-tuned output) (required)                      |
-| `--name <display_name>`     | string | yes      | Console display name for the deployment (required)                              |
-| `--plan <plan>`             | string | no       | Billing plan: lora (default, Token-billed) \| ptu (Token-billed) \| mu          |
-| `--deploy-spec <id>`        | string | no       | Deploy spec (only used by plan=mu; auto-picked if omitted)                      |
-| `--capacity <n>`            | number | no       | Resource units (plan=mu only; required by API; defaults to the template's unit) |
-| `--billing-method <m>`      | string | no       | Billing method (plan=mu only; default "POST_PAY", the only supported value)     |
-| `--input-tpm <n>`           | number | no       | PTU max input tokens/min (required for plan=ptu)                                |
-| `--output-tpm <n>`          | number | no       | PTU max output tokens/min (required for plan=ptu)                               |
-| `--thinking-output-tpm <n>` | number | no       | PTU max thinking-output tokens/min (optional, some models)                      |
-| `--api-key <key>`           | string | no       | API key                                                                         |
-| `--base-url <url>`          | string | no       | API base URL                                                                    |
+| Flag                            | Type   | Required | Description                                                                     |
+| ------------------------------- | ------ | -------- | ------------------------------------------------------------------------------- |
+| `--model-name <model_name>`     | string | yes      | Model to deploy — fine-tuned output name or catalog model (required)            |
+| `--display-name <display_name>` | string | yes      | Console display name for the deployment (required)                              |
+| `--plan <plan>`                 | string | no       | Billing plan: lora (default, Token-billed) \| ptu (Token-billed) \| mu          |
+| `--deploy-spec <id>`            | string | no       | Deploy spec (only used by plan=mu; auto-picked if omitted)                      |
+| `--capacity <n>`                | number | no       | Resource units (plan=mu only; required by API; defaults to the template's unit) |
+| `--billing-method <m>`          | string | no       | Billing method (plan=mu only; default "POST_PAY", the only supported value)     |
+| `--input-tpm <n>`               | number | no       | PTU max input tokens/min (required for plan=ptu)                                |
+| `--output-tpm <n>`              | number | no       | PTU max output tokens/min (required for plan=ptu)                               |
+| `--thinking-output-tpm <n>`     | number | no       | PTU max thinking-output tokens/min (optional, some models)                      |
+| `--api-key <key>`               | string | no       | API key                                                                         |
+| `--base-url <url>`              | string | no       | API base URL                                                                    |
 
 #### Notes
 
@@ -337,31 +411,28 @@ bl deploy scale --deployed-model dep-... --capacity 2
 - Use `bl deploy models --source base` to inspect available templates.
 - After creation, status starts at PENDING and transitions to RUNNING.
 - Invoke the deployed model with: bl text chat --model <deployed_model>
-- WARNING: --model is overloaded across commands and refers to DIFFERENT
-- values. `bl deploy <modality> create --model` takes the exported model_name
-- (e.g. `qwen3-8b-ft-...`), but the create response also returns a
-- `deployed_model` field (the deployment instance id, e.g.
-- `qwen3-8b-5ecb5f068d79`). The inference call `bl text chat --model` must use
-- the `deployed_model` from the create response — NOT the `model_name` you
-- passed to `deploy <modality> create`. Do not reuse the value across the two
-- commands.
+- NOTE: --model-name is the model being deployed (e.g. `qwen3-8b-ft-...`).
+- The create response also returns a `deployed_model` field — the deployment
+- instance id (e.g. `qwen3-8b-5ecb5f068d79`). Use that id for inference
+- (`bl text chat --model <deployed_model>`) and lifecycle commands
+- (`deploy get/scale/pause/resume/delete --deployed-model <id>`).
 
 #### Examples
 
 ```bash
-bl deploy text create --model my-qwen-sft --name my-sft-test
+bl deploy text create --model-name my-qwen-sft --display-name my-sft-test
 ```
 
 ```bash
-bl deploy text create --model qwen3.6-flash-2026-04-16 --name my-flash --plan ptu --input-tpm 10000 --output-tpm 1000
+bl deploy text create --model-name qwen3.6-flash-2026-04-16 --display-name my-flash --plan ptu --input-tpm 10000 --output-tpm 1000
 ```
 
 ```bash
-bl deploy text create --model qwen3-8b --name my-qwen3-mu --plan mu
+bl deploy text create --model-name qwen3-8b --display-name my-qwen3-mu --plan mu
 ```
 
 ```bash
-bl deploy text create --model qwen3-8b --name my-qwen3 --plan mu --deploy-spec MU1 --capacity 2
+bl deploy text create --model-name qwen3-8b --display-name my-qwen3 --plan mu --deploy-spec MU1 --capacity 2
 ```
 
 ### `bl deploy update`

skills/bailian-finetune/reference/finetune.md

@@ -19,25 +19,27 @@ Index: [index.md](index.md)
 | `bl finetune image create` | API Key        | Create an image generation model fine-tune job (sft-lora)                                                                       |
 | `bl finetune list`         | API Key        | List fine-tune jobs                                                                                                             |
 | `bl finetune logs`         | API Key        | Fetch training logs for a fine-tune job                                                                                         |
+| `bl finetune price`        | Console        | Estimate the training cost for a fine-tune job (token billing)                                                                  |
 | `bl finetune text create`  | API Key        | Create a text model fine-tune job (sft \| sft-lora \| dpo \| dpo-lora \| cpt)                                                   |
+| `bl finetune video create` | API Key        | Create a video generation model fine-tune job (Wan i2v/kf2v, efficient_sft)                                                     |
 | `bl finetune watch`        | API Key        | Probe a fine-tune job's status (default: single non-blocking fetch). Pass --follow to poll until terminal.                      |
 
 ## Command details
 
 ### `bl finetune audio create`
 
-| Field              | Value                                                                                                                               |
-| ------------------ | ----------------------------------------------------------------------------------------------------------------------------------- |
-| **Name**           | `finetune audio create`                                                                                                             |
-| **Description**    | Create an audio TTS model fine-tune job (sft-lora)                                                                                  |
-| **Authentication** | API Key                                                                                                                             |
-| **Usage**          | `bl finetune audio create --model <model> --datasets <id\|path> [--validations <id\|path>] [--model-name <name>] [--suffix <text>]` |
+| Field              | Value                                                                                                                                    |
+| ------------------ | ---------------------------------------------------------------------------------------------------------------------------------------- |
+| **Name**           | `finetune audio create`                                                                                                                  |
+| **Description**    | Create an audio TTS model fine-tune job (sft-lora)                                                                                       |
+| **Authentication** | API Key                                                                                                                                  |
+| **Usage**          | `bl finetune audio create --base-model <model> --datasets <id\|path> [--validations <id\|path>] [--model-name <name>] [--suffix <text>]` |
 
 #### Flags
 
 | Flag                         | Type   | Required | Description                                                                                                                                                        |
 | ---------------------------- | ------ | -------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
-| `--model <model>`            | string | yes      | Base model to fine-tune                                                                                                                                            |
+| `--base-model <model>`       | string | yes      | Base model to fine-tune (e.g. qwen3-8b; not the output model name)                                                                                                 |
 | `--datasets <ids\|paths>`    | string | yes      | Comma-separated dataset file IDs or local paths (.jsonl for text, .zip for audio/image). Local paths are uploaded (validated) first, then their file-ids are used. |
 | `--validations <ids\|paths>` | string | no       | Comma-separated validation dataset file IDs or local paths (auto-uploaded like --datasets).                                                                        |
 | `--model-name <name>`        | string | no       | Output model name (after training)                                                                                                                                 |
@@ -59,23 +61,23 @@ Index: [index.md](index.md)
 #### Examples
 
 ```bash
-bl finetune audio create --model cosyvoice-v3-flash --datasets ./audio.zip
+bl finetune audio create --base-model cosyvoice-v3-flash --datasets ./audio.zip
 ```
 
 ```bash
-bl finetune audio create --model cosyvoice-v3-flash --datasets file-xxx
+bl finetune audio create --base-model cosyvoice-v3-flash --datasets file-xxx
 ```
 
 ```bash
-bl finetune audio create --model cosyvoice-v3-flash --datasets ./audio.zip --model-name my-tts
+bl finetune audio create --base-model cosyvoice-v3-flash --datasets ./audio.zip --model-name my-tts
 ```
 
 ```bash
-bl finetune audio create --model cosyvoice-v3-flash --datasets file-xxx --output json
+bl finetune audio create --base-model cosyvoice-v3-flash --datasets file-xxx --output json
 ```
 
 ```bash
-bl finetune audio create --model cosyvoice-v3-flash --datasets ./audio.zip --dry-run
+bl finetune audio create --base-model cosyvoice-v3-flash --datasets ./audio.zip --dry-run
 ```
 
 ### `bl finetune cancel`
@@ -117,18 +119,18 @@ bl finetune cancel --job-id ft-xxx --dry-run
 | **Name**           | `finetune capability`                                                                                                           |
 | **Description**    | Query fine-tune training capability — by model (which training types it supports) or by training type (which models support it) |
 | **Authentication** | No Auth                                                                                                                         |
-| **Usage**          | `bl finetune capability --model <m> \| --training-type <t>`                                                                     |
+| **Usage**          | `bl finetune capability --base-model <m> \| --training-type <t>`                                                                |
 
 #### Flags
 
 | Flag                  | Type   | Required | Description                                                                           |
 | --------------------- | ------ | -------- | ------------------------------------------------------------------------------------- |
-| `--model <m>`         | string | no       | List training types supported by this base model.                                     |
+| `--base-model <m>`    | string | no       | List training types supported by this base model.                                     |
 | `--training-type <t>` | string | no       | List models supporting this training type: sft \| sft-lora \| dpo \| dpo-lora \| cpt. |
 
 #### Notes
 
-- Exactly one of --model / --training-type is required.
+- Exactly one of --base-model / --training-type is required.
 - Training-type values use the `<method>` / `<method>-lora` convention:
 - sft | sft-lora | dpo | dpo-lora | cpt. (cpt has no -lora variant server-side.)
 - Queries listFoundationModels, a public API — no console login needed.
@@ -136,7 +138,7 @@ bl finetune cancel --job-id ft-xxx --dry-run
 #### Examples
 
 ```bash
-bl finetune capability --model qwen3-8b
+bl finetune capability --base-model qwen3-8b
 ```
 
 ```bash
@@ -170,8 +172,8 @@ bl finetune capability --training-type sft --quiet
 
 #### Notes
 
-- Use the returned `checkpoint` value with `finetune export` to publish
-- a deployable model.
+- `model_name` (shown for SUCCEEDED checkpoints) is the direct input for `deploy create --model-name`.
+- Checkpoints expire ~15 days after creation; `expire_time` shows the deadline. Export or deploy before expiry.
 
 #### Examples
 
@@ -275,18 +277,18 @@ bl finetune get --job-id ft-xxx --output json
 
 ### `bl finetune image create`
 
-| Field              | Value                                                                                                                                                                                      |
-| ------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
-| **Name**           | `finetune image create`                                                                                                                                                                    |
-| **Description**    | Create an image generation model fine-tune job (sft-lora)                                                                                                                                  |
-| **Authentication** | API Key                                                                                                                                                                                    |
-| **Usage**          | `bl finetune image create --model <model> --datasets <id\|path> [--validations <id\|path>] [--model-name <name>] [--suffix <text>] [--generation-type <t2i\|i2i>] [--learning-rate <str>]` |
+| Field              | Value                                                                                                                                                                                           |
+| ------------------ | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| **Name**           | `finetune image create`                                                                                                                                                                         |
+| **Description**    | Create an image generation model fine-tune job (sft-lora)                                                                                                                                       |
+| **Authentication** | API Key                                                                                                                                                                                         |
+| **Usage**          | `bl finetune image create --base-model <model> --datasets <id\|path> [--validations <id\|path>] [--model-name <name>] [--suffix <text>] [--generation-type <t2i\|i2i>] [--learning-rate <str>]` |
 
 #### Flags
 
 | Flag                           | Type   | Required | Description                                                                                                                                                         |
 | ------------------------------ | ------ | -------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `--model <model>`              | string | yes      | Base model to fine-tune                                                                                                                                             |
+| `--base-model <model>`         | string | yes      | Base model to fine-tune (e.g. qwen3-8b; not the output model name)                                                                                                  |
 | `--datasets <ids\|paths>`      | string | yes      | Comma-separated dataset file IDs or local paths (.jsonl for text, .zip for audio/image). Local paths are uploaded (validated) first, then their file-ids are used.  |
 | `--validations <ids\|paths>`   | string | no       | Comma-separated validation dataset file IDs or local paths (auto-uploaded like --datasets).                                                                         |
 | `--model-name <name>`          | string | no       | Output model name (after training)                                                                                                                                  |
@@ -312,47 +314,48 @@ bl finetune get --job-id ft-xxx --output json
 #### Examples
 
 ```bash
-bl finetune image create --model wan2.7-image-pro --datasets ./images.zip
+bl finetune image create --base-model wan2.7-image-pro --datasets ./images.zip
 ```
 
 ```bash
-bl finetune image create --model wan2.7-image-pro --datasets file-xxx
+bl finetune image create --base-model wan2.7-image-pro --datasets file-xxx
 ```
 
 ```bash
-bl finetune image create --model wan2.7-image-pro --datasets file-xxx --generation-type i2i
+bl finetune image create --base-model wan2.7-image-pro --datasets file-xxx --generation-type i2i
 ```
 
 ```bash
-bl finetune image create --model wan2.7-image-pro --datasets ./images.zip --model-name my-wan
+bl finetune image create --base-model wan2.7-image-pro --datasets ./images.zip --model-name my-wan
 ```
 
 ```bash
-bl finetune image create --model wan2.7-image-pro --datasets file-xxx --output json
+bl finetune image create --base-model wan2.7-image-pro --datasets file-xxx --output json
 ```
 
 ```bash
-bl finetune image create --model wan2.7-image-pro --datasets ./images.zip --dry-run
+bl finetune image create --base-model wan2.7-image-pro --datasets ./images.zip --dry-run
 ```
 
 ### `bl finetune list`
 
-| Field              | Value                                                            |
-| ------------------ | ---------------------------------------------------------------- |
-| **Name**           | `finetune list`                                                  |
-| **Description**    | List fine-tune jobs                                              |
-| **Authentication** | API Key                                                          |
-| **Usage**          | `bl finetune list [--page <n>] [--page-size <n>] [--status <s>]` |
+| Field              | Value                                                                                   |
+| ------------------ | --------------------------------------------------------------------------------------- |
+| **Name**           | `finetune list`                                                                         |
+| **Description**    | List fine-tune jobs                                                                     |
+| **Authentication** | API Key                                                                                 |
+| **Usage**          | `bl finetune list [--page <n>] [--page-size <n>] [--status <s>] [--base-model <model>]` |
 
 #### Flags
 
-| Flag               | Type   | Required | Description                                                          |
-| ------------------ | ------ | -------- | -------------------------------------------------------------------- |
-| `--page <n>`       | number | no       | Page number (default: 1)                                             |
-| `--page-size <n>`  | number | no       | Results per page (default: 10, max 100)                              |
-| `--status <s>`     | string | no       | Filter by status (PENDING / RUNNING / SUCCEEDED / FAILED / CANCELED) |
-| `--api-key <key>`  | string | no       | API key                                                              |
-| `--base-url <url>` | string | no       | API base URL                                                         |
+| Flag                   | Type   | Required | Description                                                          |
+| ---------------------- | ------ | -------- | -------------------------------------------------------------------- |
+| `--page <n>`           | number | no       | Page number (default: 1)                                             |
+| `--page-size <n>`      | number | no       | Results per page (default: 10, max 100)                              |
+| `--status <s>`         | string | no       | Filter by status (PENDING / RUNNING / SUCCEEDED / FAILED / CANCELED) |
+| `--base-model <model>` | string | no       | Filter by base model ID (server-side)                                |
+| `--api-key <key>`      | string | no       | API key                                                              |
+| `--base-url <url>`     | string | no       | API base URL                                                         |
 
 #### Examples
 
@@ -365,7 +368,11 @@ bl finetune list --status RUNNING
 ```
 
 ```bash
-bl finetune list --page-size 20 --output json
+bl finetune list --base-model qwen3-8b
+```
+
+```bash
+bl finetune list --page-size 20
 ```
 
 ### `bl finetune logs`
@@ -415,20 +422,62 @@ bl finetune logs --job-id ft-xxx --tail 20
 bl finetune logs --job-id ft-xxx --search checkpoint --tail 5
 ```
 
+### `bl finetune price`
+
+| Field              | Value                                                                                               |
+| ------------------ | --------------------------------------------------------------------------------------------------- |
+| **Name**           | `finetune price`                                                                                    |
+| **Description**    | Estimate the training cost for a fine-tune job (token billing)                                      |
+| **Authentication** | Console                                                                                             |
+| **Usage**          | `bl finetune price --base-model <model> --datasets <ids> [--training-type <type>] [--n-epochs <n>]` |
+
+#### Flags
+
+| Flag                           | Type   | Required | Description                                                        |
+| ------------------------------ | ------ | -------- | ------------------------------------------------------------------ |
+| `--base-model <model>`         | string | yes      | Base model to fine-tune (e.g. qwen3-8b; not the output model name) |
+| `--datasets <ids>`             | string | yes      | Training dataset file IDs, comma-separated (required)              |
+| `--training-type <type>`       | string | no       | Training type: sft \| dpo \| cpt (default: sft)                    |
+| `--n-epochs <n>`               | number | no       | Number of training epochs (default: 3)                             |
+| `--console-region <region>`    | string | no       | Console gateway region (e.g. cn-beijing, ap-southeast-1)           |
+| `--console-site <site>`        | string | no       | Console site: domestic, international                              |
+| `--console-switch-agent <uid>` | number | no       | Switch agent UID for delegated access                              |
+| `--workspace-id <id>`          | string | no       | Workspace ID (env: BAILIAN_WORKSPACE_ID)                           |
+
+#### Notes
+
+- Estimate only — the server computes token usage from the datasets; final cost is subject to the bill.
+- Covers token billing for sft / dpo / cpt. Training-unit (MTU) billing is not supported by this command.
+- Hyper-parameters other than --n-epochs are fixed at representative defaults for estimation.
+
+#### Examples
+
+```bash
+bl finetune price --base-model qwen3-8b --datasets file-ft-xxx
+```
+
+```bash
+bl finetune price --base-model qwen3-8b --datasets file-ft-xxx,file-ft-yyy --n-epochs 2
+```
+
+```bash
+bl finetune price --base-model qwen3-8b --datasets file-ft-xxx --training-type cpt
+```
+
 ### `bl finetune text create`
 
-| Field              | Value                                                                                                                                                                                                                                                                           |
-| ------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| **Name**           | `finetune text create`                                                                                                                                                                                                                                                          |
-| **Description**    | Create a text model fine-tune job (sft \| sft-lora \| dpo \| dpo-lora \| cpt)                                                                                                                                                                                                   |
-| **Authentication** | API Key                                                                                                                                                                                                                                                                         |
-| **Usage**          | `bl finetune text create --model <model> --datasets <id\|path,...> [--validations <id\|path,...>] [--model-name <name>] [--suffix <text>] [--n-epochs <n>] [--batch-size <n>] [--learning-rate <str>] [--max-length <n>] [--training-type <sft\|sft-lora\|dpo\|dpo-lora\|cpt>]` |
+| Field              | Value                                                                                                                                                                                                                                                                                |
+| ------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
+| **Name**           | `finetune text create`                                                                                                                                                                                                                                                               |
+| **Description**    | Create a text model fine-tune job (sft \| sft-lora \| dpo \| dpo-lora \| cpt)                                                                                                                                                                                                        |
+| **Authentication** | API Key                                                                                                                                                                                                                                                                              |
+| **Usage**          | `bl finetune text create --base-model <model> --datasets <id\|path,...> [--validations <id\|path,...>] [--model-name <name>] [--suffix <text>] [--n-epochs <n>] [--batch-size <n>] [--learning-rate <str>] [--max-length <n>] [--training-type <sft\|sft-lora\|dpo\|dpo-lora\|cpt>]` |
 
 #### Flags
 
 | Flag                         | Type   | Required | Description                                                                                                                                                                              |
 | ---------------------------- | ------ | -------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `--model <model>`            | string | yes      | Base model to fine-tune                                                                                                                                                                  |
+| `--base-model <model>`       | string | yes      | Base model to fine-tune (e.g. qwen3-8b; not the output model name)                                                                                                                       |
 | `--datasets <ids\|paths>`    | string | yes      | Comma-separated dataset file IDs or local paths (.jsonl for text, .zip for audio/image). Local paths are uploaded (validated) first, then their file-ids are used.                       |
 | `--validations <ids\|paths>` | string | no       | Comma-separated validation dataset file IDs or local paths (auto-uploaded like --datasets).                                                                                              |
 | `--model-name <name>`        | string | no       | Output model name (after training)                                                                                                                                                       |
@@ -464,35 +513,90 @@ bl finetune logs --job-id ft-xxx --search checkpoint --tail 5
 #### Examples
 
 ```bash
-bl finetune text create --model qwen3-8b --datasets file-xxx
+bl finetune text create --base-model qwen3-8b --datasets file-xxx
 ```
 
 ```bash
-bl finetune text create --model qwen3-8b --datasets ./train.jsonl
+bl finetune text create --base-model qwen3-8b --datasets ./train.jsonl
 ```
 
 ```bash
-bl finetune text create --model qwen3-8b --datasets ./train.jsonl --validations ./eval.jsonl
+bl finetune text create --base-model qwen3-8b --datasets ./train.jsonl --validations ./eval.jsonl
 ```
 
 ```bash
-bl finetune text create --model qwen3-8b --datasets file-aaa,./extra.jsonl
+bl finetune text create --base-model qwen3-8b --datasets file-aaa,./extra.jsonl
 ```
 
 ```bash
-bl finetune text create --model qwen3-8b --datasets ./train.jsonl --training-type sft
+bl finetune text create --base-model qwen3-8b --datasets ./train.jsonl --training-type sft
 ```
 
 ```bash
-bl finetune text create --model qwen3-8b --datasets file-xxx --learning-rate "1.6e-5" --n-epochs 4
+bl finetune text create --base-model qwen3-8b --datasets file-xxx --learning-rate "1.6e-5" --n-epochs 4
 ```
 
 ```bash
-bl finetune text create --model qwen3-8b --datasets file-xxx --output json
+bl finetune text create --base-model qwen3-8b --datasets file-xxx --output json
 ```
 
 ```bash
-bl finetune text create --model qwen3-8b --datasets file-xxx --dry-run
+bl finetune text create --base-model qwen3-8b --datasets file-xxx --dry-run
+```
+
+### `bl finetune video create`
+
+| Field              | Value                                                                                                                                                                                                |
+| ------------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| **Name**           | `finetune video create`                                                                                                                                                                              |
+| **Description**    | Create a video generation model fine-tune job (Wan i2v/kf2v, efficient_sft)                                                                                                                          |
+| **Authentication** | API Key                                                                                                                                                                                              |
+| **Usage**          | `bl finetune video create --base-model <model> --datasets <id\|path> [--validations <id\|path>] [--model-name <name>] [--suffix <text>] [--n-epochs <n>] [--batch-size <n>] [--learning-rate <str>]` |
+
+#### Flags
+
+| Flag                         | Type   | Required | Description                                                                                                                                                        |
+| ---------------------------- | ------ | -------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
+| `--base-model <model>`       | string | yes      | Base model to fine-tune (e.g. qwen3-8b; not the output model name)                                                                                                 |
+| `--datasets <ids\|paths>`    | string | yes      | Comma-separated dataset file IDs or local paths (.jsonl for text, .zip for audio/image). Local paths are uploaded (validated) first, then their file-ids are used. |
+| `--validations <ids\|paths>` | string | no       | Comma-separated validation dataset file IDs or local paths (auto-uploaded like --datasets).                                                                        |
+| `--model-name <name>`        | string | no       | Output model name (after training)                                                                                                                                 |
+| `--suffix <text>`            | string | no       | Output suffix appended by the platform (finetuned_output_suffix)                                                                                                   |
+| `--n-epochs <n>`             | number | no       | Training epochs (default: 50)                                                                                                                                      |
+| `--batch-size <n>`           | number | no       | Batch size (default: model-specific, 1 for wan2.7, 4 for wan2.5/2.2)                                                                                               |
+| `--learning-rate <str>`      | string | no       | Learning rate as a string to preserve precision (default: "2e-5")                                                                                                  |
+| `--api-key <key>`            | string | no       | API key                                                                                                                                                            |
+| `--base-url <url>`           | string | no       | API base URL                                                                                                                                                       |
+
+#### Notes
+
+- Creating a job uploads any local datasets and consumes training quota.
+- Use --dry-run to preview the request body without submitting.
+- --datasets / --validations accept either file-ids (from `dataset upload`)
+- or local paths. Local paths are validated and uploaded first, then their
+- file-ids are submitted — a one-step upload-and-train.
+- Video generation training (Wan i2v/kf2v) runs efficient_sft with model-
+- specific defaults: wan2.7 (batch_size=1, max_pixels=102400), wan2.5/2.2
+- (batch_size=4, max_pixels per model). Override with --batch-size/--n-epochs.
+- Datasets are .zip archives with data.jsonl + frame images + videos.
+- Recommended: ≥10 training samples, 20-100 for stable results.
+
+#### Examples
+
+```bash
+bl finetune video create --base-model wan2.7-i2v --datasets file-xxx
+```
+
+```bash
+bl finetune video create --base-model wan2.7-i2v --datasets ./i2v-data.zip
+```
+
+```bash
+bl finetune video create --base-model wan2.2-kf2v-flash --datasets file-xxx --n-epochs 100
+```
+
+```bash
+bl finetune video create --base-model wan2.7-i2v --datasets file-xxx --dry-run
 ```
 
 ### `bl finetune watch`

skills/bailian-finetune/reference/index.md

@@ -22,6 +22,8 @@ Use this index for the skill-scoped quick index and global flags.
 | `bl deploy image create`   | API Key        | Create an image generation model deployment                                                                                     | [deploy.md](deploy.md)     |
 | `bl deploy list`           | API Key        | List model deployments                                                                                                          | [deploy.md](deploy.md)     |
 | `bl deploy models`         | API Key        | List models available for deployment                                                                                            | [deploy.md](deploy.md)     |
+| `bl deploy pause`          | Console        | Pause a running model deployment (stops billing for mu/ptu)                                                                     | [deploy.md](deploy.md)     |
+| `bl deploy resume`         | Console        | Resume a paused model deployment (brings service back online)                                                                   | [deploy.md](deploy.md)     |
 | `bl deploy scale`          | API Key        | Scale a deployment's capacity                                                                                                   | [deploy.md](deploy.md)     |
 | `bl deploy text create`    | API Key        | Create a text model deployment                                                                                                  | [deploy.md](deploy.md)     |
 | `bl deploy update`         | API Key        | Update a deployment's rate limits (rpm_limit / tpm_limit)                                                                       | [deploy.md](deploy.md)     |
@@ -35,16 +37,18 @@ Use this index for the skill-scoped quick index and global flags.
 | `bl finetune image create` | API Key        | Create an image generation model fine-tune job (sft-lora)                                                                       | [finetune.md](finetune.md) |
 | `bl finetune list`         | API Key        | List fine-tune jobs                                                                                                             | [finetune.md](finetune.md) |
 | `bl finetune logs`         | API Key        | Fetch training logs for a fine-tune job                                                                                         | [finetune.md](finetune.md) |
+| `bl finetune price`        | Console        | Estimate the training cost for a fine-tune job (token billing)                                                                  | [finetune.md](finetune.md) |
 | `bl finetune text create`  | API Key        | Create a text model fine-tune job (sft \| sft-lora \| dpo \| dpo-lora \| cpt)                                                   | [finetune.md](finetune.md) |
+| `bl finetune video create` | API Key        | Create a video generation model fine-tune job (Wan i2v/kf2v, efficient_sft)                                                     | [finetune.md](finetune.md) |
 | `bl finetune watch`        | API Key        | Probe a fine-tune job's status (default: single non-blocking fetch). Pass --follow to poll until terminal.                      | [finetune.md](finetune.md) |
 
 ## By group
 
-| Group      | Commands                                                                                                                                 | Reference                  |
-| ---------- | ---------------------------------------------------------------------------------------------------------------------------------------- | -------------------------- |
-| `dataset`  | `delete`, `get`, `list`, `upload`, `validate`                                                                                            | [dataset.md](dataset.md)   |
-| `deploy`   | `audio create`, `delete`, `get`, `image create`, `list`, `models`, `scale`, `text create`, `update`                                      | [deploy.md](deploy.md)     |
-| `finetune` | `audio create`, `cancel`, `capability`, `checkpoints`, `delete`, `export`, `get`, `image create`, `list`, `logs`, `text create`, `watch` | [finetune.md](finetune.md) |
+| Group      | Commands                                                                                                                                                          | Reference                  |
+| ---------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------- |
+| `dataset`  | `delete`, `get`, `list`, `upload`, `validate`                                                                                                                     | [dataset.md](dataset.md)   |
+| `deploy`   | `audio create`, `delete`, `get`, `image create`, `list`, `models`, `pause`, `resume`, `scale`, `text create`, `update`                                            | [deploy.md](deploy.md)     |
+| `finetune` | `audio create`, `cancel`, `capability`, `checkpoints`, `delete`, `export`, `get`, `image create`, `list`, `logs`, `price`, `text create`, `video create`, `watch` | [finetune.md](finetune.md) |
 
 ## Global flags
 

skills/bailian-gen/SKILL.md

@@ -1,7 +1,7 @@
 ---
 name: bailian-gen
 metadata:
-  version: "1.15.0"
+  version: "1.15.1"
   requires:
     bins: ["bl"]
 description: >-

skills/bailian-gen/reference/video.md

@@ -111,6 +111,7 @@ bl video edit --video https://example.com/input.mp4 --prompt "Put clothes on the
 | `--model <model>`           | string  | no       | Model ID (default: happyhorse-1.1-t2v, or happyhorse-1.1-i2v with --image)              |
 | `--prompt <text>`           | string  | yes      | Video description                                                                       |
 | `--image <url>`             | string  | no       | Input image URL for image-to-video generation                                           |
+| `--last-frame <url>`        | string  | no       | Last frame image URL (with --image, enables kf2v first+last frame mode)                 |
 | `--negative-prompt <text>`  | string  | no       | Negative prompt to exclude unwanted content                                             |
 | `--resolution <res>`        | string  | no       | Resolution: 720P or 1080P (default: 1080P)                                              |
 | `--ratio <ratio>`           | string  | no       | Aspect ratio (e.g. 16:9, 9:16, 1:1)                                                     |

skills/bailian-managed-agent/SKILL.md

@@ -1,7 +1,7 @@
 ---
 name: bailian-managed-agent
 metadata:
-  version: "1.15.0"
+  version: "1.15.1"
   requires:
     bins: ["bl"]
 description: >-

skills/bailian-protocol/SKILL.md

@@ -1,7 +1,7 @@
 ---
 name: bailian-protocol
 metadata:
-  version: "1.15.0"
+  version: "1.15.1"
   requires:
     bins: ["bl"]
 description: >-