IMA Video AI — Video Generator#

For complete API documentation, security details, all parameters, and Python examples, read SKILL-DETAIL.md. ⚠️ MANDATORY: You MUST read("SKILL-DETAIL.md") (full file — do NOT pass limit parameter) before your first video generation call. It contains the full API payload structure, error handling tables, and UX protocol that this summary omits. Skipping it or reading only part of it causes parameter errors and poor user experience.

Model ID Reference (CRITICAL)#

Use exact model_id from this table. Do NOT infer from friendly names.

Friendly Namemodel_id (t2v)model_id (i2v)NotesWan 2.6wan2.6-t2v``wan2.6-i2v⚠️ -t2v/-i2v suffixKling O1kling-video-o1``kling-video-o1⚠️ video- prefixKling 2.6kling-v2-6``kling-v2-6⚠️ v prefixHailuo 2.3MiniMax-Hailuo-2.3``MiniMax-Hailuo-2.3⚠️ MiniMax- prefixHailuo 2.0MiniMax-Hailuo-02``MiniMax-Hailuo-02⚠️ 02 not 2.0Vidu Q2viduq2``viduq2-pro⚠️ Different for t2v/i2vGoogle Veo 3.1veo-3.1-generate-preview``veo-3.1-generate-preview⚠️ -generate-preview suffixSora 2 Prosora-2-pro``sora-2-pro✅ StraightforwardPixverse V5.5pixverse``pixverse✅ Same as friendly nameSeeDance 1.5 Prodoubao-seedance-1.5-pro``doubao-seedance-1.5-pro⚠️ doubao- prefix

User input aliases: 万/Wan → wan2.6-* · 可灵/Kling → kling-video-o1 · 海螺/Hailuo → MiniMax-Hailuo-2.3 · Veo/Google Veo → veo-3.1-generate-preview

Video Generation Modes#

User intenttask_typeWhen to useText only, no imagetext_to_video"生成一段…视频" / "text to video"Image as first frameimage_to_video"把这张图动起来" / "图生视频"Image as visual reference (not first frame)reference_image_to_video"参考这张图生成" / "像这张风格"Two images (start + end)first_last_frame_to_video"首帧+尾帧" / "从A过渡到B"

Visual Consistency (IMPORTANT)#

If user mentions "same character", "series", "multi-shot", or continues from a previous generation:

• Do NOT use text_to_video (will produce different-looking results)
• Use image_to_video or reference_image_to_video with previous result as reference
• Read ima-knowledge-ai/references/visual-consistency.md if available

Pre-Check: Knowledge Base#

If ima-knowledge-ai is installed, read before generating:

1. ima-knowledge-ai/references/video-modes.md — understand mode differences
2. ima-knowledge-ai/references/visual-consistency.md — if multi-shot or character continuity needed

If not installed: use this SKILL's model table and defaults.

Model Selection Priority#

1. User preference (if explicitly stated) → highest priority
2. ima-knowledge-ai recommendation (if installed)
3. Fallback defaults:

TaskDefault Modelmodel_idCosttext_to_videoWan 2.6wan2.6-t2v25 ptstext_to_video (premium)Hailuo 2.3MiniMax-Hailuo-2.338 ptstext_to_video (budget)Vidu Q2viduq25 ptsimage_to_videoWan 2.6wan2.6-i2v25 ptsfirst_last_frameKling O1kling-video-o148 ptsreference_imageKling O1kling-video-o148 pts

User Input Parsing#

Duration: 5秒→5 · 10秒→10 · 15秒→15 · 1分钟→use max (tell user "当前最长15秒") Aspect ratio: 横屏/16:9→16:9 · 竖屏/9:16→9:16 · 方形/1:1→1:1 Resolution: 720P/1080P/4K (if model supports) Budget: 最便宜→Vidu Q2 (5pts) · 最好→Kling O1 or Veo 3.1

Script Usage#

bash

# Text to video
python3 {baseDir}/scripts/ima_video_create.py \
  --api-key $IMA_API_KEY \
  --task-type text_to_video \
  --model-id wan2.6-t2v \
  --prompt "a puppy runs across a sunny meadow" \
  --user-id {user_id} \
  --output-json

# Image to video (accepts URLs and local file paths)
python3 {baseDir}/scripts/ima_video_create.py \
  --api-key $IMA_API_KEY \
  --task-type image_to_video \
  --model-id wan2.6-i2v \
  --prompt "camera slowly zooms in" \
  --input-images https://example.com/photo.jpg \
  --user-id {user_id} \
  --output-json

# First-last frame (exactly 2 images required)
python3 {baseDir}/scripts/ima_video_create.py \
  --api-key $IMA_API_KEY \
  --task-type first_last_frame_to_video \
  --model-id kling-video-o1 \
  --prompt "smooth transition" \
  --input-images first.jpg last.jpg \
  --user-id {user_id} \
  --output-json

Sending Results to User#

python

# ✅ CORRECT: Use remote URL directly for inline video playback
message(action="send", media=video_url, caption="✅ 视频生成成功！\n• 模型：[Name]\n• 耗时：[X]s\n• 积分：[N pts]")

# Then send link for copying
message(action="send", message=f"🔗 视频链接：\n{video_url}")

# ❌ WRONG: Never download to local file (shows as attachment, not playable)

UX Protocol (Brief)#

1. Pre-generation: "🎬 开始生成视频… 模型：[Name]，预计[X~Y]秒，消耗[N]积分"
2. Progress: Every 30-60s: "⏳ 视频生成中… [P]%" (cap at 95% until API returns success)
3. Success: Send video via media=video_url + send link text for sharing
4. Failure: Natural language error + suggest alternative models. Never show technical errors to users. See SKILL-DETAIL.md for full error translation table.

Never say to users: script names, API endpoints, attribute_id, technical parameter names. Only: model name · time · credits · result · status.

Sora 2 Pro Content Policy#

Sora has strict OpenAI content safety: ❌ people, celebrities, IP assets. ✅ landscapes, abstract, animals, nature. If rejected, suggest Wan 2.6 or Kling O1.

Environment#

Base URL: https://api.imastudio.com Headers: Authorization: Bearer $IMA_API_KEY · x-app-source: ima_skills · x_app_language: en

Core Flow#

1. GET /open/v1/product/list?app=ima&platform=web&category=<task_type> → get attribute_id, credit, model_version, form_config
2. [Image tasks only] Upload images or pass local paths to script
3. POST /open/v1/tasks/create → get task_id
4. POST /open/v1/tasks/detail → poll every 8s until resource_status==1

MANDATORY: Always query product list first. attribute_id is required — if 0 or missing, task fails.

User Preference Memory#

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

• Save when user explicitly says "用XXX" / "默认用XXX" / "always use XXX"
• Clear when user says "用最好的" / "推荐一个" / "自动选择"
• Never save auto-selected or fallback models as preferences

Pixverse Special Case (v1.0.7+)#

Pixverse V5.5/V5/V4 lack model in form_config. Script auto-infers from model_name (e.g. "Pixverse V5.5" → model: "v5.5"). No manual action needed.

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⚠️ REMINDER: read("SKILL-DETAIL.md") (full file, no limit) is required before generating video. This file is a summary — SKILL-DETAIL.md has the complete API reference, error translation table, and UX protocol you need for correct execution.