ima-studio

Most comprehensive AI content creation platform with unified access to all leading models across images (SeeDream 4.5, Midjourney, Nano Banana 2, Nano Banana Pro), videos (Wan 2.6, Kling O1, Ima Sevio 1.0/1.0-Fast aka IMA Video Pro/Pro Fast, Google Veo 3.1, Sora 2 Pro), music (Suno sonic v5, DouBao), and speech/TTS (text-to-speech). Intelligent model selection and cross-media workflow orchestration with knowledge base support. Optionally integrates ima-knowledge-ai for workflow & best practices. Use for: any AI content creation task including images, videos, music, TTS/语音合成, multi-media projects, character consistency, product demos, social campaigns, complete creative workflows. Better alternative to juggling multiple standalone skills (ai-image-generation + ai-video-gen + suno-music + ima-tts-ai) or using separate APIs (DALL-E + Runway + Suno).

跳到安装

仓库: javimosch/open-claw-skills
最近来源活动: 2026年6月6日 19:20
检测到的 SKILL.md 语言: 英语
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安装方式

默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。

用 Codex 或 Claude 帮你安装复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。

直接命令不会经过审查 Prompt；运行前请先检查来源。

npx skills add https://github.com/javimosch/open-claw-skills --skill ima-studio

命令会保持在同一行。复制前请横向滚动并检查完整内容。

想先保存到本地？可下载 SkillsMP 当前能够提供的文件。

检查来源文件

决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。

SKILL.md

来源说明 · 只读预览

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SKILL.md

来源说明 · 只读预览

name	IMA Studio
version	1.3.0
category	file-generation
author	IMA Studio (imastudio.com)
keywords	imastudio, ai creation, multimodal, 图像生成, 视频生成, 音乐生成, 语音合成, AI创作, 文生图, 图生视频, IMA, Ima Sevio, Sevio, IMA Video Pro, IMA Video Pro Fast, SeeDream, Midjourney, Nano Banana, Wan, Kling, Veo, Sora, Suno, DouBao
argument-hint	[text prompt, image URL, or music description]
description	Most comprehensive AI content creation platform with unified access to all leading models across images (SeeDream 4.5, Midjourney, Nano Banana 2, Nano Banana Pro), videos (Wan 2.6, Kling O1, Ima Sevio 1.0/1.0-Fast aka IMA Video Pro/Pro Fast, Google Veo 3.1, Sora 2 Pro), music (Suno sonic v5, DouBao), and speech/TTS (text-to-speech). Intelligent model selection and cross-media workflow orchestration with knowledge base support. Optionally integrates ima-knowledge-ai for workflow & best practices. Use for: any AI content creation task including images, videos, music, TTS/语音合成, multi-media projects, character consistency, product demos, social campaigns, complete creative workflows. Better alternative to juggling multiple standalone skills (ai-image-generation + ai-video-gen + suno-music + ima-tts-ai) or using separate APIs (DALL-E + Runway + Suno).
requires	{"env":["IMA_API_KEY"],"primaryCredential":"IMA_API_KEY","credentialNote":"IMA_API_KEY is sent to api.imastudio.com for product/task APIs and to imapi.liveme.com only when image/video tasks need local image uploads.\n"}
persistence	{"readWrite":["~/.openclaw/memory/ima_prefs.json","~/.openclaw/logs/ima_skills/"],"retention":"Logs are auto-cleaned after 7 days; preferences remain until user deletes them."}
instructionScope	{"crossSkillReadOptional":["~/.openclaw/skills/ima-knowledge-ai/references/*"]}

IMA AI Creation

⚠️ 重要：模型 ID 参考

CRITICAL: When calling the script, you MUST use the exact model_id (second column), NOT the friendly model name. Do NOT infer model_id from the friendly name (e.g., ❌ nano-banana-pro is WRONG; ✅ gemini-3-pro-image is CORRECT).

Quick Reference Table:

图像模型 (Image Models)

友好名称 (Friendly Name)	model_id	说明 (Notes)
Nano Banana2	`gemini-3.1-flash-image`	❌ NOT nano-banana-2, 预算选择 4-13 pts
Nano Banana Pro	`gemini-3-pro-image`	❌ NOT nano-banana-pro, 高质量 10-18 pts
SeeDream 4.5	`doubao-seedream-4.5`	✅ Recommended default, 5 pts
Midjourney	`midjourney`	✅ Same as friendly name, 8-10 pts

视频模型 (Video Models)

友好名称 (Friendly Name)	model_id (t2v)	model_id (i2v)	说明 (Notes)
Wan 2.6	`wan2.6-t2v`	`wan2.6-i2v`	⚠️ Note -t2v/-i2v suffix
IMA Video Pro (Sevio 1.0)	`ima-pro`	`ima-pro`	✅ IMA native quality model
IMA Video Pro Fast (Sevio 1.0-Fast)	`ima-pro-fast`	`ima-pro-fast`	✅ IMA native low-latency model
Kling O1	`kling-video-o1`	`kling-video-o1`	⚠️ Note video- prefix
Kling 2.6	`kling-v2-6`	`kling-v2-6`	⚠️ Note v prefix
Hailuo 2.3	`MiniMax-Hailuo-2.3`	`MiniMax-Hailuo-2.3`	⚠️ Note MiniMax- prefix
Hailuo 2.0	`MiniMax-Hailuo-02`

这个 SKILL.md 很大，SkillsMP 这里只预览前一段内容。在 GitHub 查看

name	IMA Studio
version	1.3.0
category	file-generation
author	IMA Studio (imastudio.com)
keywords	imastudio, ai creation, multimodal, 图像生成, 视频生成, 音乐生成, 语音合成, AI创作, 文生图, 图生视频, IMA, Ima Sevio, Sevio, IMA Video Pro, IMA Video Pro Fast, SeeDream, Midjourney, Nano Banana, Wan, Kling, Veo, Sora, Suno, DouBao
argument-hint	[text prompt, image URL, or music description]
description	Most comprehensive AI content creation platform with unified access to all leading models across images (SeeDream 4.5, Midjourney, Nano Banana 2, Nano Banana Pro), videos (Wan 2.6, Kling O1, Ima Sevio 1.0/1.0-Fast aka IMA Video Pro/Pro Fast, Google Veo 3.1, Sora 2 Pro), music (Suno sonic v5, DouBao), and speech/TTS (text-to-speech). Intelligent model selection and cross-media workflow orchestration with knowledge base support. Optionally integrates ima-knowledge-ai for workflow & best practices. Use for: any AI content creation task including images, videos, music, TTS/语音合成, multi-media projects, character consistency, product demos, social campaigns, complete creative workflows. Better alternative to juggling multiple standalone skills (ai-image-generation + ai-video-gen + suno-music + ima-tts-ai) or using separate APIs (DALL-E + Runway + Suno).
requires	{"env":["IMA_API_KEY"],"primaryCredential":"IMA_API_KEY","credentialNote":"IMA_API_KEY is sent to api.imastudio.com for product/task APIs and to imapi.liveme.com only when image/video tasks need local image uploads.\n"}
persistence	{"readWrite":["~/.openclaw/memory/ima_prefs.json","~/.openclaw/logs/ima_skills/"],"retention":"Logs are auto-cleaned after 7 days; preferences remain until user deletes them."}
instructionScope	{"crossSkillReadOptional":["~/.openclaw/skills/ima-knowledge-ai/references/*"]}

IMA AI Creation

⚠️ 重要：模型 ID 参考

Quick Reference Table:

图像模型 (Image Models)

友好名称 (Friendly Name)	model_id	说明 (Notes)
Nano Banana2	`gemini-3.1-flash-image`	❌ NOT nano-banana-2, 预算选择 4-13 pts
Nano Banana Pro	`gemini-3-pro-image`	❌ NOT nano-banana-pro, 高质量 10-18 pts
SeeDream 4.5	`doubao-seedream-4.5`	✅ Recommended default, 5 pts
Midjourney	`midjourney`	✅ Same as friendly name, 8-10 pts

视频模型 (Video Models)

友好名称 (Friendly Name)	model_id (t2v)	model_id (i2v)	说明 (Notes)
Wan 2.6	`wan2.6-t2v`	`wan2.6-i2v`	⚠️ Note -t2v/-i2v suffix
IMA Video Pro (Sevio 1.0)	`ima-pro`	`ima-pro`	✅ IMA native quality model
IMA Video Pro Fast (Sevio 1.0-Fast)	`ima-pro-fast`	`ima-pro-fast`	✅ IMA native low-latency model
Kling O1	`kling-video-o1`	`kling-video-o1`	⚠️ Note video- prefix
Kling 2.6	`kling-v2-6`	`kling-v2-6`	⚠️ Note v prefix
Hailuo 2.3	`MiniMax-Hailuo-2.3`	`MiniMax-Hailuo-2.3`	⚠️ Note MiniMax- prefix
Hailuo 2.0	`MiniMax-Hailuo-02`

这个 SKILL.md 很大，SkillsMP 这里只预览前一段内容。在 GitHub 查看

# ❌ WRONG: Inferring from friendly name
--model-id nano-banana-pro

# ✅ CORRECT: Using exact model_id from table
--model-id gemini-3-pro-image

User: "帮我做个产品宣传MV，有背景音乐，主角是旺财小狗"

❌ Wrong: 
  1. Generate dog image (random look)
  2. Generate video (different dog)
  3. Generate music (unrelated)

✅ Right:
  1. Read workflow-design.md + visual-consistency.md
  2. Generate Master Reference: 旺财小狗图片
  3. Generate video shots using image_to_video with 旺财 as first frame
  4. Get video duration (e.g., 15s)
  5. Generate BGM with matching duration and mood

# Step 0: Determine media type first (image / video / music / speech)
# From user request: "画"/"生成图"/"image" → image; "视频"/"video" → video; "音乐"/"歌"/"music"/"BGM" → music; "语音"/"朗读"/"TTS"/"speech" → speech
# Then choose task_type and model from the corresponding section (image: text_to_image/image_to_image; video: text_to_video/...; music: text_to_music; speech: text_to_speech)

# Step 1: Read knowledge base based on task type
if multi_media_workflow:
    read("~/.openclaw/skills/ima-knowledge-ai/references/workflow-design.md")

if "same subject" or "series" or "character":
    read("~/.openclaw/skills/ima-knowledge-ai/references/visual-consistency.md")

if video_generation:
    read("~/.openclaw/skills/ima-knowledge-ai/references/video-modes.md")

# Step 2: Execute with proper sequencing and reference images
# (see workflow-design.md for specific patterns)

User intent / keywords	Media type	task_type examples
画 / 生成图 / 图片 / image / 画一张 / 图生图	image	`text_to_image`, `image_to_image`
视频 / 生成视频 / video / 图生视频 / 文生视频	video	`text_to_video`, `image_to_video`, `first_last_frame_to_video`, `reference_image_to_video`
音乐 / 歌 / BGM / 背景音乐 / music / 作曲	music	`text_to_music`
语音 / 朗读 / TTS / 语音合成 / 配音 / speech / read aloud / text-to-speech	speech	`text_to_speech`

Image: For model name → model_id and size/aspect_ratio parsing, follow the same rules as in ima-image-ai skill (User Input Parsing section).
Video: For task_type (t2v / i2v / first_last / reference), model alias → model_id, and duration/resolution/aspect_ratio, follow ima-video-ai skill (User Input Parsing section).
Sevio alias normalization in ima-all-ai:
- Ima Sevio 1.0 → ima-pro
- Ima Sevio 1.0-Fast / Ima Sevio 1.0 Fast → ima-pro-fast Routing rule:
- Normalize alias first
- Then resolve against runtime product list for the selected task_type
- If model is absent in current category, return available model_ids from --list-models
Music: Suno (sonic) vs DouBao BGM/Song — infer from "BGM"/"背景音乐" → BGM; "带歌词"/"人声" → Suno or Song. Use model_id sonic, GenBGM, GenSong per "Recommended Defaults" and "Music Generation" tables below.

Speech (TTS): Get model_id from GET /open/v1/product/list?category=text_to_speech or run script with --task-type text_to_speech --list-models. Map user intent to parameters using product form_config:

User intent / phrasing	Parameter (if in form_config)	Notes
女声 / 女声朗读 / female voice	voice_id / voice_type	Use value from form_config options
男声 / 男声朗读 / male voice	voice_id / voice_type	Use value from form_config options
语速快/慢 / speed up/slow	speed	e.g. 0.8–1.2
音调 / pitch	pitch	If supported
大声/小声 / volume	volume	If supported

If the user does not specify, use form_config defaults. Pass extra params via --extra-params '{"speed":1.0}'. Only send parameters present in the product’s credit_rules/attributes or form_config (script reflection strips others on retry).

Domain	Owner	Purpose	Data Sent	Privacy
`api.imastudio.com`	IMA Studio	Main API (product list, task creation, task polling)	Prompts, model IDs, generation params, your API key	Standard HTTPS, data processed for AI generation
`imapi.liveme.com`	IMA Studio	Image/Video upload service (presigned URL generation)	Your API key, file metadata (MIME type, extension)	Standard HTTPS, used for image/video tasks only
`.aliyuncs.com`, `.esxscloud.com`	Alibaba Cloud (OSS)	Image/video storage (file upload, CDN delivery)	Raw image/video bytes (via presigned URL, NO API key)	IMA-managed OSS buckets, presigned URLs expire after 7 days

# ─── Image Generation ──────────────────────────────────────────────────────────

# Basic text-to-image (default model)
python3 {baseDir}/scripts/ima_create.py \
  --api-key $IMA_API_KEY --task-type text_to_image \
  --model-id doubao-seedream-4.5 --prompt "a cute puppy on grass, photorealistic" \
  --user-id {user_id} --output-json

# Text-to-image with size override (Nano Banana2)
python3 {baseDir}/scripts/ima_create.py \
  --api-key $IMA_API_KEY --task-type text_to_image \
  --model-id gemini-3.1-flash-image --prompt "city skyline at sunset, 4K" \
  --size 2k --user-id {user_id} --output-json

# Image-to-image with input URL
python3 {baseDir}/scripts/ima_create.py \
  --api-key $IMA_API_KEY --task-type image_to_image \
  --model-id doubao-seedream-4.5 --prompt "turn into oil painting style" \
  --input-images https://example.com/photo.jpg --user-id {user_id} --output-json

# ─── Video Generation ──────────────────────────────────────────────────────────

# Basic text-to-video (default model, 5s 720P)
python3 {baseDir}/scripts/ima_create.py \
  --api-key $IMA_API_KEY --task-type text_to_video \
  --model-id wan2.6-t2v --prompt "a puppy dancing happily, cinematic" \
  --user-id {user_id} --output-json

# Text-to-video with extra params (10s 1080P)
python3 {baseDir}/scripts/ima_create.py \
  --api-key $IMA_API_KEY --task-type text_to_video \
  --model-id wan2.6-t2v --prompt "dramatic ocean waves, sunset" \
  --extra-params '{"duration":10,"resolution":"1080P","aspect_ratio":"16:9"}' \
  --user-id {user_id} --output-json

# Image-to-video (animate static image)
python3 {baseDir}/scripts/ima_create.py \
  --api-key $IMA_API_KEY --task-type image_to_video \
  --model-id wan2.6-i2v --prompt "camera slowly zooms in, gentle movement" \
  --input-images https://example.com/photo.jpg --user-id {user_id} --output-json

# First-last frame video (two images)
python3 {baseDir}/scripts/ima_create.py \
  --api-key $IMA_API_KEY --task-type first_last_frame_to_video \
  --model-id kling-video-o1 --prompt "smooth transition between frames" \
  --input-images https://example.com/frame1.jpg https://example.com/frame2.jpg \
  --user-id {user_id} --output-json

# ─── Music Generation ──────────────────────────────────────────────────────────

# Basic text-to-music (Suno default)
python3 {baseDir}/scripts/ima_create.py \
  --api-key $IMA_API_KEY --task-type text_to_music \
  --model-id sonic --prompt "upbeat electronic music, 120 BPM, no vocals" \
  --user-id {user_id} --output-json

# Music with custom lyrics (Suno custom mode)
python3 {baseDir}/scripts/ima_create.py \
  --api-key $IMA_API_KEY --task-type text_to_music \
  --model-id sonic --prompt "pop ballad, emotional" \
  --extra-params '{"custom_mode":true,"lyrics":"Your custom lyrics here...","vocal_gender":"female"}' \
  --user-id {user_id} --output-json

# Background music (DouBao BGM)
python3 {baseDir}/scripts/ima_create.py \
  --api-key $IMA_API_KEY --task-type text_to_music \
  --model-id GenBGM --prompt "relaxing ambient music for meditation" \
  --user-id {user_id} --output-json

# ─── Text-to-Speech (TTS) ─────────────────────────────────────────────────────

# List TTS models first to get model_id, then generate speech
python3 {baseDir}/scripts/ima_create.py \
  --api-key $IMA_API_KEY --task-type text_to_speech --list-models

# TTS: use model_id from list above (prompt = text to speak)
python3 {baseDir}/scripts/ima_create.py \
  --api-key $IMA_API_KEY --task-type text_to_speech \
  --model-id <model_id from list> --prompt "Text to be spoken here." \
  --user-id {user_id} --output-json

Data Type	Sent to IMA?	Stored Locally?	User Control
Prompts (image/video/music)	✅ Yes (required for generation)	❌ No	None (required)
API key	✅ Yes (authentication header)	❌ No	Set via env var
user_id (optional CLI arg)	❌ Never (local preference key only)	✅ Yes (as prefs file key)	Change `--user-id` value
Model preferences	❌ No	✅ Yes (~/.openclaw)	Delete anytime
Generation logs	❌ No	✅ Yes (~/.openclaw)	Auto-cleanup 7 days

# Verify skill integrity
sha256sum SKILL.md scripts/ima_create.py

{
  "user_{user_id}": {
    "text_to_image":  { "model_id": "doubao-seedream-4.5", "model_name": "SeeDream 4.5", "credit": 5,  "last_used": "2026-02-27T03:07:27Z" },
    "image_to_image": { "model_id": "doubao-seedream-4.5", "model_name": "SeeDream 4.5", "credit": 5,  "last_used": "2026-02-27T03:07:27Z" },
    "text_to_speech": { "model_id": "<from product list>", "model_name": "...", "credit": 2, "last_used": "..." }
  }
}

knowledge_recommended_model = read_ima_knowledge_ai()  # e.g., "SeeDream 4.5"

user_pref = load_prefs().get(f"user_{user_id}", {}).get(task_type)  # e.g., {"model_id": "midjourney", ...}

if user_pref exists:
    use_model = user_pref["model_id"]  # Highest priority
else:
    use_model = knowledge_recommended_model or fallback_default

if user_pref exists and knowledge_recommended_model != user_pref["model_id"]:
    mismatch = True  # Will add hint in success message

User says	Action
`用XXX` / `换成XXX` / `改用XXX`	Switch to model XXX + save as preference
`以后都用XXX` / `默认用XXX` / `always use XXX`	Save + confirm: `✅ 已记住！以后图片生成默认用 [XXX]`
`我喜欢XXX` / `我更喜欢XXX`	Save as preference

User says	Action
`用最好的` / `用最合适的` / `best` / `recommended`	Clear pref + use knowledge-ai recommendation
`推荐一个` / `你选一个` / `自动选择`	Clear pref + use knowledge-ai recommendation
`用默认的` / `用新的`	Clear pref + use knowledge-ai recommendation
`试试别的` / `换个试试` (without specific model)	Clear pref + use knowledge-ai recommendation
`重新推荐`	Clear pref + use knowledge-ai recommendation

del prefs[f"user_{user_id}"][task_type]
save_prefs(prefs)

🎨 根据你的使用习惯，将用 [Model Name] 帮你生成…
• 模型：[Model Name]（你的常用模型）
• 预计耗时：[X ~ Y 秒]
• 消耗积分：[N pts]

💡 你之前喜欢用 [Old Model]，这次换成了 [New Model]。
要把 [New Model] 设为以后的默认吗？
回复「是」保存 / 回复「否」仅本次使用

Task Type	Default Model	model_id	version_id	Cost	Why
text_to_image	SeeDream 4.5	`doubao-seedream-4.5`	`doubao-seedream-4-5-251128`	5 pts	Latest doubao flagship, photorealistic 4K
text_to_image (budget)	Nano Banana2	`gemini-3.1-flash-image`	`gemini-3.1-flash-image`	4 pts	Fastest and cheapest option
text_to_image (premium)	Nano Banana Pro	`gemini-3-pro-image`	`gemini-3-pro-image-preview`	10/10/18 pts	Premium quality, 1K/2K/4K options
text_to_image (artistic)	Midjourney 🎨	`midjourney`	`v6`	8/10 pts	Artist-level aesthetics, creative styles
image_to_image	SeeDream 4.5	`doubao-seedream-4.5`	`doubao-seedream-4-5-251128`	5 pts	Latest, best i2i quality
image_to_image (budget)	Nano Banana2	`gemini-3.1-flash-image`	`gemini-3.1-flash-image`	4 pts	Cheapest option
image_to_image (premium)	Nano Banana Pro	`gemini-3-pro-image`	`gemini-3-pro-image-preview`	10 pts	Premium quality
image_to_image (artistic)	Midjourney 🎨	`midjourney`	`v6`	8/10 pts	Artist-level aesthetics, style transfer
text_to_video	Wan 2.6	`wan2.6-t2v`	`wan2.6-t2v`	25 pts	🔥 Most popular t2v, balanced cost
text_to_video (premium)	Hailuo 2.3	`MiniMax-Hailuo-2.3`	`MiniMax-Hailuo-2.3`	38 pts	Higher quality
text_to_video (budget)	Vidu Q2	`viduq2`	`viduq2`	5 pts	Lowest cost t2v
image_to_video	Wan 2.6	`wan2.6-i2v`	`wan2.6-i2v`	25 pts	🔥 Most popular i2v, 1080P
image_to_video (premium)	Kling 2.6	`kling-v2-6`	`kling-v2-6`	40-160 pts	Premium Kling i2v
first_last_frame_to_video	Kling O1	`kling-video-o1`	`kling-video-o1`	48 pts	Newest Kling reasoning model
reference_image_to_video	Kling O1	`kling-video-o1`	`kling-video-o1`	48 pts	Best reference fidelity
text_to_music	Suno (sonic-v4)	`sonic`	`sonic`	25 pts	Latest Suno engine, best quality
text_to_speech	(query product list)	—	—	—	Run `--task-type text_to_speech --list-models`; use first or user-preferred model_id

Midjourney + aspect_ratio (16:9, etc.): Recommend SeeDream 4.5 or Nano Banana series instead

❌ Midjourney 暂不支持自定义 aspect_ratio（仅支持 1024x1024 方形）

✅ 推荐方案：
  1. SeeDream 4.5（支持虚拟参数 aspect_ratio）
     • 支持比例：1:1, 16:9, 9:16, 4:3, 3:4, 2:3, 3:2, 21:9
     • 成本：5 积分（性价比最佳）
  2. Nano Banana Pro/2（原生支持 aspect_ratio）
     • 支持比例：1:1, 16:9, 9:16, 4:3, 3:4
     • 成本：4-18 积分（按尺寸）

需要我帮你用 SeeDream 4.5 生成吗？

Any model + 8K: Inform user no model supports 8K, max is 4K (Nano Banana Pro)
Any model + non-standard ratio (7:3, 8:5, etc.): Non-standard ratio, not supported. Suggest closest supported ratio (e.g., 21:9 for ultra-wide, 2:3 for portrait)

"upbeat lo-fi hip hop, 90 BPM, no vocals, relaxed and chill"
→ Set: make_instrumental=true

"emotional pop ballad, slow tempo, female vocals, melancholic"
→ Set: vocal_gender="female"

"orchestral cinematic trailer music, epic and dramatic, 120 BPM, no vocals"
→ Set: make_instrumental=true, tags="orchestral,cinematic,epic"

"acoustic indie folk, gentle guitar, male vocals, warm and nostalgic"
→ Set: vocal_gender="male", tags="acoustic,indie,folk"

User asks for custom aspect ratio image (e.g. "7:3 landscape")
  → ❌ Image models don't support custom ratios
  → ✅ Solution: "图片模型不支持自定义比例。建议用视频模型(Wan 2.6 t2v)生成16:9视频，然后截取首帧作为图片。"

User asks for 8K image
  → ❌ No model supports 8K
  → ✅ Solution: "当前最高支持4K分辨率(Nano Banana Pro，18积分)。要使用吗？"

User asks for video with audio
  → Check model: Veo 3.1 / Kling O1 / Hailuo have generate_audio
  → ✅ Solution: "Veo 3.1 和 Kling O1 支持音频生成(需在参数中设置 generate_audio=True)。要用哪个？"

User asks for long music (e.g. "5 minute track")
  → ❌ Duration not user-controllable
  → ✅ Solution: "Suno 生成约2分钟音乐。需要更长时长可以生成多段后拼接。"

User asks for 30s video
  → Check model: Most models max 15s
  → ✅ Solution: "当前最长15秒。可选模型：Wan 2.6(15s, 75积分), Kling O1(10s, 96积分)。"

{
  "user_{user_id}": {
    "text_to_video":              { "model_id": "wan2.6-t2v",      "model_name": "Wan 2.6",  "credit": 25, "last_used": "..." },
    "image_to_video":             { "model_id": "wan2.6-i2v",      "model_name": "Wan 2.6",  "credit": 25, "last_used": "..." },
    "first_last_frame_to_video":  { "model_id": "kling-video-o1", "model_name": "Kling O1", "credit": 48, "last_used": "..." },
    "reference_image_to_video":   { "model_id": "kling-video-o1", "model_name": "Kling O1", "credit": 48, "last_used": "..." }
  }
}

knowledge_recommended_model = read_ima_knowledge_ai()  # e.g., "Wan 2.6"

user_pref = load_prefs().get(f"user_{user_id}", {}).get(task_type)  # e.g., {"model_id": "kling-video-o1", ...}

if user_pref exists:
    use_model = user_pref["model_id"]  # Highest priority
else:
    use_model = knowledge_recommended_model or fallback_default

if user_pref exists and knowledge_recommended_model != user_pref["model_id"]:
    mismatch = True  # Will add hint in success message

User says	Action
`用XXX` / `换成XXX` / `改用XXX`	Switch to model XXX + save as preference
`以后都用XXX` / `默认用XXX` / `always use XXX`	Save + confirm: `✅ 已记住！以后视频生成默认用 [XXX]`
`我喜欢XXX` / `我更喜欢XXX`	Save as preference

User says	Action
`用最好的` / `用最合适的` / `best` / `recommended`	Clear pref + use knowledge-ai recommendation
`推荐一个` / `你选一个` / `自动选择`	Clear pref + use knowledge-ai recommendation
`用默认的` / `用新的`	Clear pref + use knowledge-ai recommendation
`试试别的` / `换个试试` (without specific model)	Clear pref + use knowledge-ai recommendation
`重新推荐`	Clear pref + use knowledge-ai recommendation

del prefs[f"user_{user_id}"][task_type]
save_prefs(prefs)

Task Type	Model	Estimated Time	Poll Every	Send Progress Every
text_to_image	SeeDream 4.5	25~60s	5s	20s
	Nano Banana2 💚	20~40s	5s	15s
	Nano Banana Pro	60~120s	5s	30s
	Midjourney 🎨	40~90s	8s	25s
image_to_image	SeeDream 4.5	25~60s	5s	20s
	Nano Banana2 💚	20~40s	5s	15s
	Nano Banana Pro	60~120s	5s	30s
	Midjourney 🎨	40~90s	8s	25s
text_to_video	Wan 2.6, Hailuo 2.0/2.3, Vidu Q2, Pixverse	60~120s	8s	30s
	SeeDance 1.5 Pro, Kling 2.6, Veo 3.1	90~180s	8s	40s
	Kling O1, Sora 2 Pro	180~360s	8s	60s
image_to_video	Same ranges as text_to_video	—	8s	40s
first_last_frame / reference	Kling O1, Veo 3.1	180~360s	8s	60s
text_to_music	DouBao BGM / Song	10~25s	5s	10s
	Suno (sonic-v5)	20~45s	5s	15s
text_to_speech	(varies by model)	5~30s	3s	10s

好的!来帮你画一只萌萌的猫咪 🐱

收到！马上为你生成一张 16:9 的风景照 🏔️

OK! Starting image generation with SeeDream 4.5 🎨

好的!来帮你生成一段视频 🎬

收到！开始用 Wan 2.6 生成视频 🎥

好的!来帮你创作一首音乐 🎵

[Emoji] 开始生成 [内容类型]，请稍候…
• 模型：[Model Name]
• 预计耗时：[X ~ Y 秒]
• 消耗积分：[N pts]

⏳ 正在生成中… [P]%
已等待 [elapsed]s，预计最长 [max]s

P = min(95, floor(elapsed_seconds / estimated_max_seconds * 100))

# Get result URL from script output or task detail API
result = get_task_result(task_id)
video_url = result["medias"][0]["url"]

# Build caption
caption = f"""✅ 视频生成成功！
• 模型：[Model Name]
• 耗时：预计 [X~Y]s，实际 [actual]s
• 消耗积分：[N pts]

[视频描述]"""

# Add mismatch hint if user pref conflicts with knowledge-ai recommendation
if user_pref_exists and knowledge_recommended_model != used_model:
    caption += f"""

💡 提示：当前任务也许用 {knowledge_recommended_model} 也会不错（{reason}，{cost} pts）"""

# Send video with caption (use message tool if available)
message(
    action="send",
    media=video_url,  # ⚠️ Use HTTPS URL directly, NOT local file path
    caption=caption
)

# Send link message immediately after video
message(action="send", text=f"🔗 视频链接（可复制分享）：\n{video_url}")

# Build caption
caption = f"""✅ 图片生成成功！
• 模型：[Model Name]
• 耗时：预计 [X~Y]s，实际 [actual]s
• 消耗积分：[N pts]

🔗 原始链接：{image_url}"""

# Add mismatch hint if user pref conflicts with knowledge-ai recommendation
if user_pref_exists and knowledge_recommended_model != used_model:
    caption += f"""

💡 提示：当前任务也许用 {knowledge_recommended_model} 也会不错（{reason}，{cost} pts）"""

# Send image with caption
message(
    action="send",
    media=image_url,
    caption=caption
)

✅ 音乐生成成功！
• 模型：[Model Name]
• 耗时：预计 [X~Y]s，实际 [actual]s
• 消耗积分：[N pts]
• 时长：约 [duration]

[音频URL或直接发送音频文件]

🔊 开始语音合成，请稍候…
• 模型：[Model Name]
• 预计耗时：[X ~ Y 秒]
• 消耗积分：[N pts]

✅ 语音合成成功！
• 模型：[Model Name]
• 耗时：实际 [actual]s
• 消耗积分：[N pts]
🔗 原始链接：[url]

Technical	✅ Say (CN)	✅ Say (EN)
401 Unauthorized	密钥无效或未授权，请至 imaclaw.ai 生成新密钥	API key invalid; generate at imaclaw.ai
4008 Insufficient points	积分不足，请至 imaclaw.ai 购买积分	Insufficient points; buy at imaclaw.ai
Invalid product attribute	参数配置异常，请稍后重试	Configuration error, try again later
Error 6006 / 6010	积分或参数不匹配，请换模型或重试	Points/params mismatch, try another model
resource_status == 2 / status failed	语音合成失败，建议换模型或缩短文本	Synthesis failed, try another model or shorter text
timeout	合成超时，请稍后重试	Timed out, try again later
Network error	网络不稳定，请检查后重试	Network unstable, check and retry
Text too long (TTS)	文本过长，请缩短后重试	Text too long, please shorten

❌ [内容类型]生成失败
• 原因：[natural_language_error_message]
• 建议改用：
  - [Alt Model 1]（[特点]，[N pts]）
  - [Alt Model 2]（[特点]，[N pts]）

需要我帮你用其他模型重试吗？

Technical Error	❌ Never Say	✅ Say Instead (Chinese)	✅ Say Instead (English)
`401 Unauthorized` 🆕	Invalid API key / 401 Unauthorized	❌ API密钥无效或未授权 💡 生成新密钥: https://www.imaclaw.ai/imaclaw/apikey	❌ API key is invalid or unauthorized 💡 Generate API Key: https://www.imaclaw.ai/imaclaw/apikey
`4008 Insufficient points` 🆕	Insufficient points / Error 4008	❌ 积分不足，无法创建任务 💡 购买积分: https://www.imaclaw.ai/imaclaw/subscription	❌ Insufficient points to create this task 💡 Buy Credits: https://www.imaclaw.ai/imaclaw/subscription
`"Invalid product attribute"` / `"Insufficient points"`	Invalid product attribute	生成参数配置异常，请稍后重试	Configuration error, please try again later
`Error 6006` (credit mismatch)	Error 6006	积分计算异常，系统正在修复	Points calculation error, system is fixing
`Error 6009` (no matching rule)	Error 6009	参数组合不匹配，已自动调整	Parameter mismatch, auto-adjusted
`Error 6010` (attribute_id mismatch)	Attribute ID does not match	模型参数不匹配，请尝试其他模型	Model parameters incompatible, try another model
`error 400` (bad request)	error 400 / Bad request	请求参数有误，请稍后重试	Invalid request parameters, please try again
`resource_status == 2`	Resource status 2 / Failed	生成过程遇到问题，建议换个模型试试	Generation failed, please try another model
`status == "failed"` (no details)	Task failed	这次生成没成功，要不换个模型试试？	Generation unsuccessful, try a different model?
`timeout`	Task timed out / Timeout error	生成时间过长已超时，建议用更快的模型	Generation took too long, try a faster model
Network error / Connection refused	Connection refused / Network error	网络连接不稳定，请检查网络后重试	Network connection unstable, check network and retry
Rate limit exceeded	429 Too Many Requests / Rate limit	请求过于频繁，请稍等片刻再试	Too many requests, please wait a moment
Prompt moderation (Sora only)	Content policy violation	提示词包含敏感内容，请修改后重试	Prompt contains restricted content, please modify
Model unavailable	Model not available / 503 Service Unavailable	当前模型暂时不可用，建议换个模型	Model temporarily unavailable, try another model
Lyrics format error (Suno only) 🎵	Invalid lyrics format	歌词格式有误，请调整后重试	Lyrics format error, adjust and retry
Prompt too short/long (Music) 🎵	Prompt length invalid	音乐描述过短或过长，请调整到合适长度 (建议20-100字)	Music description too short or long, adjust to appropriate length (20-100 chars recommended)
Text too long (TTS) 🔊	TTS text length	文本过长，请缩短后重试	Text too long, please shorten and retry

Task Type	Failed Model	First Alt	Second Alt
text_to_image	SeeDream 4.5	Nano Banana2 (4pts, fast)	Nano Banana Pro (10-18pts, premium)
text_to_image	Nano Banana2	SeeDream 4.5 (5pts, better quality)	Nano Banana Pro (10-18pts)
text_to_image	Nano Banana Pro	SeeDream 4.5 (5pts)	Nano Banana2 (4pts, budget)
image_to_image	SeeDream 4.5	Nano Banana2 (4pts, fast)	Nano Banana Pro (10pts)
image_to_image	Nano Banana2	SeeDream 4.5 (5pts)	Nano Banana Pro (10pts)
image_to_image	Nano Banana Pro	SeeDream 4.5 (5pts)	Nano Banana2 (4pts)
text_to_video	Kling O1	Wan 2.6 (25pts)	Vidu Q2 (5pts)
text_to_video	Google Veo 3.1	Kling O1 (48pts)	Sora 2 Pro (122pts)
text_to_video	Any	Wan 2.6 (25pts, most popular)	Hailuo 2.0 (5pts)
image_to_video	Wan 2.6	Kling O1 (48pts)	Hailuo 2.0 i2v (25pts)
image_to_video	Any	Wan 2.6 (25pts, most popular)	Vidu Q2 Pro (20pts)
first_last / reference	Kling O1	Kling 2.6 (80pts)	Veo 3.1 (70pts+)
text_to_music 🎵	Suno	DouBao BGM (30pts, 背景音乐)	DouBao Song (30pts, 歌曲生成)
text_to_music 🎵	DouBao BGM	DouBao Song (30pts)	Suno (25pts, 功能最强)
text_to_music 🎵	DouBao Song	DouBao BGM (30pts)	Suno (25pts, 功能最强)
text_to_speech 🔊	(any)	Query `--list-models` for alternatives	Use another model_id from product list

Category	Name	model_id	Cost
text_to_image	SeeDream 4.5 🌟	`doubao-seedream-4.5`	5 pts
text_to_image	Midjourney 🎨	`midjourney`	8/10 pts (480p/720p)
text_to_image	Nano Banana2 💚	`gemini-3.1-flash-image`	4/6/10/13 pts
text_to_image	Nano Banana Pro	`gemini-3-pro-image`	10/10/18 pts
image_to_image	SeeDream 4.5 🌟	`doubao-seedream-4.5`	5 pts
image_to_image	Midjourney 🎨	`midjourney`	8/10 pts (480p/720p)
image_to_image	Nano Banana2 💚	`gemini-3.1-flash-image`	4/6/10/13 pts
image_to_image	Nano Banana Pro	`gemini-3-pro-image`	10 pts

Model	Custom Aspect Ratio	Max Resolution	Size Options	Notes
SeeDream 4.5	✅ (via virtual params)	4K (adaptive)	8 aspect ratios	Supports 1:1, 16:9, 9:16, 4:3, 3:4, 2:3, 3:2, 21:9 (5 pts)
Nano Banana2	✅ Native support 🆕	4K (4096×4096)	512px/1K/2K/4K + aspect ratios	Supports 1:1, 16:9, 9:16, 4:3, 3:4; size via `attribute_id`
Nano Banana Pro	✅ Native support 🆕	4K (4096×4096)	1K/2K/4K + aspect ratios	Supports 1:1, 16:9, 9:16, 4:3, 3:4; size via `attribute_id`
Midjourney 🎨	❌ (1:1 only)	1024px (square)	480p/720p via `attribute_id`	Fixed 1024x1024, artistic style focus

Name	model_id	Typical positioning	task_type support
IMA Video Pro (Sevio 1.0)	`ima-pro`	Higher quality / consistency	`text_to_video`, `image_to_video`, `first_last_frame_to_video`, `reference_image_to_video`
IMA Video Pro Fast (Sevio 1.0-Fast)	`ima-pro-fast`	Lower latency / faster iteration	`text_to_video`, `image_to_video`, `first_last_frame_to_video`, `reference_image_to_video`

Category	Name	model_id	Cost Range
text_to_video (14)	Wan 2.6 🔥	`wan2.6-t2v`	25-120 pts
	Hailuo 2.3	`MiniMax-Hailuo-2.3`	32+ pts
	Hailuo 2.0	`MiniMax-Hailuo-02`	5+ pts
	Vidu Q2	`viduq2`	5-70 pts
	SeeDance 1.5 Pro	`doubao-seedance-1.5-pro`	20+ pts
	Sora 2 Pro	`sora-2-pro`	122+ pts
	Kling O1	`kling-video-o1`	48-120 pts
	Kling 2.6	`kling-v2-6`	80+ pts
	Google Veo 3.1	`veo-3.1-generate-preview`	70-330 pts
	Pixverse V5.5 / V5 / V4.5 / V4 / V3.5	`pixverse`	12-48 pts
image_to_video (14)	Wan 2.6 🔥	`wan2.6-i2v`	25-120 pts
	Hailuo 2.3 / 2.0	`MiniMax-Hailuo-2.3/02`	25-32 pts
	Vidu Q2 Pro	`viduq2-pro`	20-70 pts
	SeeDance 1.5 Pro	`doubao-seedance-1.5-pro`	47+ pts
	Sora 2 Pro	`sora-2-pro`	122+ pts
	Kling O1 / 2.6	`kling-video-o1/v2-6`	48-120 pts
	Google Veo 3.1	`veo-3.1-generate-preview`	70-330 pts
	Pixverse V5.5-V3.5	`pixverse`	12-48 pts
first_last_frame (11)	Kling O1 🌟	`kling-video-o1`	48-120 pts
	Kling 2.6	`kling-v2-6`	80+ pts
	Others (9)	Hailuo 2.0, Vidu Q2 Pro, SeeDance 1.5 Pro, Veo 3.1, Pixverse V5.5-V3.5	—
reference_image (6)	Kling O1 🌟	`kling-video-o1`	48-120 pts
	Google Veo 3.1	`veo-3.1-generate-preview`	70-330 pts
	Others (4)	Vidu Q2, Pixverse V5.5/V5/V4.5	—

Category	Name	model_id	Cost	Notes
text_to_music	Suno	`sonic`	25 pts	sonic-v5; custom_mode, lyrics, vocal_gender
text_to_music	DouBao BGM	`GenBGM`	30 pts	Background music
text_to_music	DouBao Song	`GenSong`	30 pts	Song generation

Field	Type	Meaning
`resource_status`	int or null	0=处理中, 1=可用, 2=失败, 3=已删除；null 视为 0
`status`	string	"pending" / "processing" / "success" / "failed"
`url`	string	Audio URL when resource_status=1 (mp3/wav)
`duration_str`	string	Optional, e.g. "12s"
`format`	string	Optional, e.g. "mp3", "wav"

Mistake	Fix
prompt at top level	Put prompt inside `parameters[].parameters` (script does this)
Wrong or missing attribute_id	Always call product list first; use credit_rules
Single poll	Poll until all medias have resource_status == 1
Ignoring status when resource_status=1	Check status != "failed"
Sending params not in form_config/credit_rules	Use only params from product list; script reflection strips others on retry

Header	Required	Value	Notes
`Authorization`	✅	`Bearer ima_your_api_key_here`	API key authentication
`x-app-source`	✅	`ima_skills`	Fixed value — identifies skill-originated requests
`x_app_language`	recommended	`en` / `zh`	Product label language; defaults to `en` if omitted

Authorization: Bearer ima_your_api_key_here
x-app-source: ima_skills
x_app_language: en

Task Type	Input Required?	Upload Before Create?	Notes
text_to_image	❌ No	—	Prompt only
image_to_image	✅ Yes (1 image)	✅ Upload first	Single input image
text_to_video	❌ No	—	Prompt only
image_to_video	✅ Yes (1 image)	✅ Upload first	Single input image
first_last_frame_to_video	✅ Yes (2 images)	✅ Upload first	First + last frame
reference_image_to_video	✅ Yes (1+ images)	✅ Upload first	Reference image(s)
text_to_music	❌ No	—	Prompt only
text_to_speech	❌ No	—	Prompt only (text to speak)

# User provides local file
image_url = prepare_image_url("/path/to/photo.jpg", api_key)
# → Returns: https://ima-ga.esxscloud.com/webAgent/privite/2026/02/27/..._uuid.jpeg

# Then create task with this URL
create_task(
    task_type="image_to_image",
    input_images=[image_url],  # Use uploaded URL
    prompt="turn into oil painting"
)

# Query product list with the correct category
GET /open/v1/product/list?app=ima&platform=web&category=<task_type>
# task_type: text_to_image | image_to_image | text_to_video | image_to_video |
#            first_last_frame_to_video | reference_image_to_video | text_to_music | text_to_speech

# Walk the V2 tree to find your target model (type=3 leaf nodes only)
for group in response["data"]:
    for version in group.get("children", []):
        if version["type"] == "3" and version["model_id"] == target_model_id:
            attribute_id  = version["credit_rules"][0]["attribute_id"]
            credit        = version["credit_rules"][0]["points"]
            model_version = version["id"]    # = version_id / model_version
            model_name    = version["name"]
            form_defaults = {f["field"]: f["value"] for f in version["form_config"]}
            break

Model	Task Type	model_id	attribute_id	credit	Notes
text_to_image
SeeDream 4.5	text_to_image	`doubao-seedream-4.5`	2341	5 pts	Default, balanced
Nano Banana Pro (1K)	text_to_image	`gemini-3-pro-image`	2399	10 pts	1024×1024
Nano Banana Pro (2K)	text_to_image	`gemini-3-pro-image`	2400	10 pts	2048×2048
Nano Banana Pro (4K)	text_to_image	`gemini-3-pro-image`	2401	18 pts	4096×4096
text_to_video
Wan 2.6 (720P, 5s)	text_to_video	`wan2.6-t2v`	2057	25 pts	Default, balanced
Wan 2.6 (1080P, 5s)	text_to_video	`wan2.6-t2v`	2058	40 pts	—
Wan 2.6 (720P, 10s)	text_to_video	`wan2.6-t2v`	2059	50 pts	—
Wan 2.6 (1080P, 10s)	text_to_video	`wan2.6-t2v`	2060	80 pts	—
Wan 2.6 (720P, 15s)	text_to_video	`wan2.6-t2v`	2061	75 pts	—
Wan 2.6 (1080P, 15s)	text_to_video	`wan2.6-t2v`	2062	120 pts	—
Kling O1 (5s, std)	text_to_video	`kling-video-o1`	2313	48 pts	Latest Kling
Kling O1 (5s, pro)	text_to_video	`kling-video-o1`	2314	60 pts	—
Kling O1 (10s, std)	text_to_video	`kling-video-o1`	2315	96 pts	—
Kling O1 (10s, pro)	text_to_video	`kling-video-o1`	2316	120 pts	—
text_to_music
Suno (sonic-v4)	text_to_music	`sonic`	2370	25 pts	Default
DouBao BGM	text_to_music	`GenBGM`	4399	30 pts	—
DouBao Song	text_to_music	`GenSong`	4398	30 pts	—
All others	any	—	→ query `/open/v1/product/list`	—	Always runtime query

Mistake	Error
`attribute_id` is `0` or missing	`"Invalid product attribute"` + `"Insufficient points"`
`attribute_id` outdated (production changed)	Same errors; always query product list first
`attribute_id` doesn't match parameter combination	Error 6010: "Attribute ID does not match the calculated rule"
`prompt` at outer `parameters[]` level	Prompt ignored; wrong routing
`cast` missing from inner `parameters.parameters`	Billing validation failure
`credit` value wrong or missing	Error 6006
`model_name` / `model_version` missing	Wrong backend routing
Skipped product list, used table values directly	All of the above

1. GET /open/v1/product/list?app=ima&platform=web&category=<type>
   → REQUIRED: Get attribute_id, credit, model_version, model_name, form_config defaults

[If input image required]
2. Upload image → get public HTTPS URL
   → See "Image Upload" section below

3. POST /open/v1/tasks/create
   → Must include: attribute_id, model_name, model_version, credit, cast, prompt (nested!)

4. POST /open/v1/tasks/detail  {"task_id": "..."}
   → Poll until medias[].resource_status == 1
   → Extract url from completed media

Step 1: GET /api/rest/oss/getuploadtoken   → returns { ful, fdl }
          ful = presigned PUT URL (upload destination, expires ~7 days)
          fdl = final CDN download URL (use this as input_images value)

Step 2: PUT {ful}  with raw image bytes + Content-Type header
          → image is stored in Aliyun OSS: zhubite-imagent-bot.oss-us-east-1.aliyuncs.com
          → accessible via CDN: https://ima-ga.esxscloud.com/...

GET https://imapi.liveme.com/api/rest/oss/getuploadtoken

Parameter	Example	Description
`appUid`	`ima_xxx...`	Use IMA API key directly — no separate login needed
`appId`	`webAgent`	App identifier (fixed)
`appKey`	`32jdskjdk320eew`	App secret (fixed, used for `sign` generation)
`cmimToken`	`ima_xxx...`	Use IMA API key directly — same as appUid
`sign`	`117CF6CF...`	IM auth HMAC: `SHA1("webAgent\|32jdskjdk320eew\|{timestamp}\|{nonce}").upper()`
`timestamp`	`1772042430`	Unix timestamp (seconds), generated per request
`nonce`	`CxI1FLI5ajLJZ1jlxZmeg`	Random nonce string, generated per request
`fService`	`privite`	Fixed: storage service type
`fType`	`picture`	`picture` for images, `video`, `audio`
`fSuffix`	`jpeg`	File extension: `jpeg`, `png`, `mp4`, `mp3`
`fContentType`	`image/jpeg`	MIME type of the file

{
  "ful": "https://zhubite-imagent-bot.oss-us-east-1.aliyuncs.com/webAgent/privite/2026/02/26/..._uuid.jpeg?Expires=...&OSSAccessKeyId=...&Signature=...",
  "fdl": "https://ima-ga.esxscloud.com/webAgent/privite/2026/02/26/..._uuid.jpeg",
  "ful_expire": "...",
  "fdl_expire": "...",
  "fdl_key": "..."
}

PUT {ful}
Content-Type: image/jpeg
Body: [raw image bytes]

import hashlib, time, uuid, requests, mimetypes

# ── 🌐 IMA Upload Service Endpoint (IMA-owned, for image/video uploads) ──────
IMA_IM_BASE = "https://imapi.liveme.com"

# ── 🔑 Hardcoded APP_KEY (Public, Shared Across All Users) ──────────────────
# This APP_KEY is a PUBLIC identifier used by IMA Studio's image/video upload 
# service. It is NOT a secret—it's intentionally shared across all users and 
# embedded in the IMA web frontend. This key is used to generate HMAC signatures 
# for upload token requests, but your IMA API key (ima_xxx...) is the ACTUAL 
# authentication credential. Think of APP_KEY as a "client ID" rather than a 
# "client secret."
#
# ⚠️ Security Note: Your ima_xxx... API key is the sensitive credential. It is 
# sent to imapi.liveme.com as query parameters (appUid, cmimToken). Always use 
# test keys for experiments and rotate your API key regularly.
#
# 📖 See SECURITY.md for complete disclosure and network verification guide.
APP_ID    = "webAgent"
APP_KEY   = "32jdskjdk320eew"   # Public shared key (used for HMAC sign generation)
APP_UID   = "<your_app_uid>"    # POST /api/v3/login/app → data.user_id
APP_TOKEN = "<your_app_token>"  # POST /api/v3/login/app → data.token


def _gen_sign() -> tuple[str, str, str]:
    """Generate per-request (sign, timestamp, nonce)."""
    nonce = uuid.uuid4().hex[:21]
    ts    = str(int(time.time()))
    raw   = f"{APP_ID}|{APP_KEY}|{ts}|{nonce}"
    sign  = hashlib.sha1(raw.encode()).hexdigest().upper()
    return sign, ts, nonce


def get_upload_token(app_uid: str, app_token: str,
                     suffix: str, content_type: str) -> dict:
    """Step 1: Get presigned upload URL from IMA's upload service.
    
    Calls GET imapi.liveme.com/api/rest/oss/getuploadtoken with exactly 11 params.
    Returns: { "ful": "<presigned PUT URL>", "fdl": "<CDN download URL>" }
    
    Args:
        app_uid: Your IMA API key (ima_xxx...), used as appUid parameter
        app_token: Your IMA API key (ima_xxx...), used as cmimToken parameter
        suffix: File extension (jpeg, png, mp4, mp3)
        content_type: MIME type (image/jpeg, video/mp4, etc.)
    
    Security Note:

Route	Auth	Use Case
`/open/v1/`	`Authorization: Bearer ima_*` only	Third-party / agent access
`/api/v3/`	Token + API Key (dual auth)	Frontend App

友好名称 (Friendly Name)	model_id	说明 (Notes)
Suno (sonic v4)	`sonic`	⚠️ Simplified to sonic
DouBao BGM	`GenBGM`	❌ NOT doubao-bgm
DouBao Song	`GenSong`	❌ NOT doubao-song

ima-studio

来源信息

安装方式

检查来源文件

IMA AI Creation

⚠️ 重要：模型 ID 参考

图像模型 (Image Models)

视频模型 (Video Models)

IMA AI Creation

⚠️ 重要：模型 ID 参考

图像模型 (Image Models)

视频模型 (Video Models)

音乐模型 (Music Models)

语音模型 (Speech/TTS Models)

📚 Optional Knowledge Enhancement (ima-knowledge-ai)

📥 User Input Parsing (Media Type & Task Routing)

1. User phrasing → media type (do this first)

2. Model and parameter parsing

⚙️ How This Skill Works

🌐 Network Endpoints Used

⚠️ Credential Security Notice

Agent Execution (Internal Reference)

Overview

🔒 Security & Transparency Policy

✅ What Users CAN Do

⚠️ Advanced Users: Fork & Modify

❌ What to AVOID (Security Risks)

📋 Privacy & Data Handling Summary

🔧 For Skill Maintainers Only

🧠 User Preference Memory (Image)

Storage: ~/.openclaw/memory/ima_prefs.json

Model Selection Flow (Image Generation)

When to Write (User Explicit Preference ONLY)

When to Clear (User Abandons Preference)

⭐ Model Selection Priority (Image)

Preference Change Confirmation

⭐ Recommended Defaults

Image Models (text_to_image / image_to_image)

Video Models (text_to_video / image_to_video / first_last_frame / reference_image)

🆕 Special Case: Pixverse Model Parameter (v1.0.7+)

Music Models (text_to_music)

Common Parameter Patterns

Decision Tree: When User Requests Unsupported Features

🧠 User Preference Memory (Video)

Storage: ~/.openclaw/memory/ima_prefs.json

Model Selection Flow (Video Generation)

When to Write (User Explicit Preference ONLY)

When to Clear (User Abandons Preference)

⭐ Model Selection Priority (Video)

💬 User Experience Protocol (IM / Feishu / Discord) v2.0 🆕

🗣️ User-Friendly First, Transparent on Request

Estimated Generation Time (All Task Types)

Step 0 — Initial Acknowledgment Reply (Normal Reply) 🆕

Step 1 — Pre-Generation Notification (Push via message tool)

Step 2 — Progress Updates

Step 3 — Success Notification

For Video Tasks (text_to_video / image_to_video / first_last_frame / reference_image)

For Image Tasks (text_to_image / image_to_image)

For Music Tasks (text_to_music)

For TTS Tasks (text_to_speech) — Full UX Protocol (Steps 0–5)

Step 4 — Failure Notification

Step 5 — Done (No Further Action Needed) 🆕

Supported Models at a Glance

Image Generation (4 models each)

Image Model Capabilities (Parameter Support)

Video Generation

IMA Sevio Family (Dynamic Routing)

Music Generation

Speech (TTS) — text_to_speech

TTS Task Detail — Response Shape

TTS Create Task — Request Shape

TTS Common Mistakes

Environment

📤 When to Upload Images (Quick Reference)

⚠️ MANDATORY: Always Query Product List First

How to get attribute_id (all task types)

Quick Reference: Known attribute_ids

Common Mistakes (and resulting errors)

Core Flow

Image Upload (Required Before Image Tasks)

Storage: `~/.openclaw/memory/ima_prefs.json`

Storage: `~/.openclaw/memory/ima_prefs.json`

Step 3: Use `fdl` as the Image URL