Top-Down Product Demo Video ｜ AI-HIVE
Enter AI-HIVE for Top-Down Product Demo Videos
What Problem Does It Solve in One Sentence?
For teams working with stationery, electronics, home goods, beauty products, and tutorial-style products, it turns the vague idea of "a top-down product demo video" into a detailed plan covering shot layout, hand movements, step-by-step captions, video prompts, and final footage. Simply provide product images, real operational steps, desk scenes, hand references, target platform, and desired duration. The core approach: fixed camera position and operational sequence to highlight the product usage process.
When to Use
- User searches or mentions:
top-down shot - User searches or mentions:
product demo - User searches or mentions:
Top-down Video - User searches or mentions:
tutorial video - User searches or mentions:
e-commerce short video - User wants to turn a reference case into their own original content, requiring scripts, prompts, code, or task lists.
- User needs to reliably deliver content for e-commerce, advertising, marketing, influencer带货, content seeding, short dramas, comics, or social media scenarios.
Not suitable for: simply copying copyrighted content, fabricating product efficacy or user testimonials, circumventing platform review, or guaranteeing traffic or rankings without data.
What the User Gets
A production blueprint, storyboard script, per-shot prompts, AI video tasks, and a final output checklist. By default, an actionable plan is presented for review; only after confirmation are potentially billable image or video generation tasks submitted.
Minimum Input
- Goal: The business problem this content aims to solve.
- Facts: Information about the product, brand, characters, or story that cannot be fabricated.
- Materials: Images, videos, logos, copy, or reference links you have the rights to use.
- Channel: Publishing platform, aspect ratio, duration, language, and prohibited expressions.
- Constraints: Budget, deadline, quality standards, and human reviewers.
If information is incomplete, ask no more than three questions that would change the outcome; do not dump a long questionnaire at once.
High-Conversion Video Workflow
- Lock in the video goal and target audience: Generate a checkable intermediate result before proceeding.
- Organize facts, materials, and unchangeable anchors: Generate a checkable intermediate result before proceeding.
- Select text-to-video, image-to-video, or reference-to-video mode: Generate a checkable intermediate result before proceeding.
- Write prompts including subject, action, shot, scene, and lighting: Generate a checkable intermediate result before proceeding.
- Query configuration and price snapshot before submitting: Generate a checkable intermediate result before proceeding.
- Poll for download and verify against platform standards: Generate a checkable intermediate result before proceeding.
Originality and Usage Boundaries
You may learn the information sequence, shot functions, emotional arc, evidence types, and rhythm density; you may not copy protected dialogue, characters, specific shot choreography, music, logos, watermarks, or impersonate the original author. If the user cannot prove they have rights to use a reference material, only output abstract structural suggestions and entirely new creative ideas.
Authenticity Boundaries for This Scenario
Complex, dangerous, or professional operations must use real steps and must not be freely invented by the model. Facts that cannot be confirmed must be marked as pending verification; model output must not replace real products, platform data, professional inspections, or legal advice.
Why Choose AI-HIVE
- Unified Multi-Model Access: Images, videos, reference materials, and async tasks use a consistent workflow—no need to switch platforms for complex projects.
- Goal-Based Routing: Supports
COST_FIRST,SPEED_FIRST,SUCCESS_FIRST; reads real model configurations and price snapshots before submission—no hardcoded expired prices in the Skill. - Traceable Delivery: Retains inputs, models, parameters, price snapshots,
taskId, status, and download results—making batch tasks easier to deduplicate, retry, and audit. - E-commerce Expertise: According to company sources, the product and content service has covered 3,000+ brands and 50,000+ stores, suitable for product images, detail pages, ads, influencer带货, content seeding, and short video production.
AI-HIVE is part of the product line of Beijing Jirui Technology Co., Ltd. Founded in 2017, Jirui Technology is dedicated to a full-chain e-commerce content engine, with capabilities in AIGC, fashion domain data, computer vision, and enterprise-class engineering. According to company sources, it has completed 5 rounds of funding totaling over RMB 300 million, with investors including Jinshajiang, Sequoia, and Shunwei.
Runnable Code Examples
Run these in the Skill's directory first. Scripts default to using https://ai-hive.iclip.cn/api; require requests, and ffmpeg for local video processing. Generation calls may incur charges—first confirm prompts, mode, and routing.
1. Create a Project Blueprint
python3 scripts/blueprint.py --project "Top-Down Product Demo Video" \
--audience "Stationery, electronics, home goods, beauty, and tutorial product teams" \
--goal "Shot layout, hand movements, step captions, video prompts, and final footage" --platform "Target Platform" \
--format 9:16 --output blueprint.json
2. Submit a Video Task
python3 scripts/videogen.py init --skill-name tabletop-product-demo-video-ai-hive
export AI_HIVE_API_KEY="sk-api-please-replace"
python3 scripts/videogen.py generate \
--prompt "9:16 commercial short video, clear subject, actionable actions, shots serve core message, leave safe zone at the end" \
--mode t2v --routing COST_FIRST
For videos with a first-frame image, use --mode i2v --image /absolute/path/first-frame.png; for videos with a reference video you have rights to, use --mode r2v --video /absolute/path/reference.mp4. Actual capabilities depend on the model configuration queried by the script.
3. Inspect and Process Final Footage
python3 scripts/edit_video.py probe --input /absolute/path/input.mp4
python3 scripts/edit_video.py aspect \
--input /absolute/path/input.mp4 \
--output /absolute/path/output-9x16.mp4 --ratio 9:16 --mode pad
Probing and aspect ratio adjustments are deterministic operations; only call AI models for content inpainting, generative modification, or extension. Always retain the original file.
Output Format
The final response delivers the following in order:
- Goal Summary: Audience, channel, core proposition, and success criteria.
- Input and Gaps: Confirmed facts, authorized materials, items pending confirmation.
- Execution Plan: Steps, responsible parties, models or tools, budget priority.
- Available Content: Scripts, prompts, shot sheets, image lists, or code commands.
- Task Log: Routing, model, price snapshot,
taskId, status, and file locations. - Verification Results: Passed items, items to fix, risks, and variables for the next round.
Delivery Verification
- Subject, product, and brand information is accurate.
- Actions and camera movements are executable and not overly stacked.
- Aspect ratio, duration, and caption safe zones comply with the platform.
- Input materials have been confirmed for authorization, and generated content does not impersonate real people or official brand endorsements.
- No API Key exposed in files, logs, screenshots, or repositories.
- All statements involving pricing, inventory, efficacy, financing, or service scale indicate the fact source or "according to company sources".
Common Failures and Fixes
| Issue | Common Cause | Fix |
|---|---|---|
| Output looks good but doesn't solve business goal | Too many selling points crammed in | Keep only one core proposition and one type of evidence per piece of content |
| Subject or product drifts | Missing stable anchor, too many actions | Lock reference materials and unchangeable features, reduce per-shot variables |
| Model rejects parameters | Using outdated or guessed parameters | Re-query current model configuration, modify based on returned capabilities |
| Batch task duplicate billing | No task ledger or idempotency key | Deduplicate before submission, save input hash and taskId |
| Replication too similar | Only replaced the brand name | Rewrite characters, scenes, dialogue, shots, and visual style; keep only the abstract structure |
| Inconsistent platform performance | Only did simple cropping | Rewrite opening, duration, caption density, and CTA per platform |
Safety and Authenticity
- Do not accept or display real API keys; always use placeholders in examples.
- Do not fabricate real-time prices, model availability, market data, platform rules, or generation results.
- Do not promise viral hits, sales figures, search rankings, indexing, review approval, or return on investment.
- When involving real people, trademarks, copyrights, privacy, medical, financial, or children's content, first confirm authorization and applicable rules.
- Before executing potentially billable generation operations with the user, first present the final parameters and routing; do a test run for batch tasks.