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llava

Analyze images for visual question answering and multi-turn multimodal chat.

Updated May 4, 2026
Search Tags:#multimodal#multi-turn chat#vision-language#visual question answering#llava#image captioning
One-click install
npx skills add https://github.com/Supporter09/Face_Anti_Spoofing_Biometric --skill llava-supporter09
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: llava
Source: https://github.com/Supporter09/Face_Anti_Spoofing_Biometric/tree/main/.claude/skills/llava
Command: npx skills add https://github.com/Supporter09/Face_Anti_Spoofing_Biometric --skill llava-supporter09

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

LLaVA solves the challenge of understanding images through natural language, letting you ask questions, request descriptions, and hold multi-turn conversations about visual content without switching tools.

Core Features & Use Cases

  • Visual Question Answering: Ask direct questions about an image and receive grounded responses.
  • Image Captioning and Scene Understanding: Generate detailed descriptions, identify objects, and interpret what is happening in a scene.
  • Multi-turn Image Chat: Keep context across several follow-up questions about the same image or document.
  • Use Case: A team can upload a product screenshot, ask what elements are visible, then refine the conversation to inspect labels, layout, or missing UI details.

Quick Start

Ask the LLaVA skill to analyze an attached image and answer a specific visual question in one conversational turn.

Frequently Asked Questions about llava

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I do visual question answering with an image in a conversational chat?▼

Visual question answering lets you ask direct questions about an image and receive grounded responses. You can upload an image and use multi-turn chat to inspect specific visual elements like objects or layout.

Can I generate image captions and identify objects in a scene automatically?▼

Image captioning and scene understanding automatically generate detailed descriptions and identify objects within an image. This interprets what is visually happening in a scene without manual inspection.

Does multi-turn multimodal chat keep context across follow-up questions about the same image?▼

Multi-turn multimodal chat maintains context across several follow-up questions about the same image or document. This allows refining the conversation to inspect specific labels, layout, or missing UI details progressively.

What language model and vision encoder do I need for image token processing?▼

Image token processing requires a CLIP-based vision encoder and a Vicuna or LLaMA language model. This setup provides GPU-oriented inference support for visual understanding workflows.

What is the best way to analyze a product screenshot for missing UI details?▼

Analyzing a product screenshot for missing UI details is best handled by uploading the image and asking what elements are visible. You can then refine the conversation to inspect specific labels or layout configurations.

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