Uni Vision Engine (v1.2.0)

This skill leverages a local jimeng-api Docker service. It allows AI agents to fully control high-quality image-to-video and text-to-video generation using a valid sessionid.

🌟 Core Feature: Native Chat Image Interception (Best Practice)

With this skill, the AI Assistant can automatically intercept clothing/character images sent by the user in the chat interface and seamlessly pass them to the generation model—no manual web uploads required!

<agent_instruction> When a user sends a "character/outfit" photo in the chat and intends to animate it (e.g., showing off the clothing, turning around), you MUST execute the following steps:

1. Intercept the Image Payload: Use the read tool or native execution flow to extract the base64 content or cache path of this image from the chat context. Save it as a local temporary file (e.g., /tmp/target.jpg).
2. Never use text-based URLs or JSON format for image uploads. You MUST use Node.js multipart/form-data to submit the physical file stream.
3. Initiate the Video Generation Task using the core script:

node {baseDir}/scripts/generate.js --prompt "The model naturally turns around, fully showcasing the gloss of the fabric, extremely high quality, natural sunlight..." --image /tmp/target.jpg

4. Monitor the Output: Generation usually takes 60-310 seconds. Monitor the Docker logs to retrieve the direct MP4 link and return it to the user. </agent_instruction>