multimodal-rag

Answers questions about documents by combining text and visual context.

3|2|Updated Jan 29, 2026
One-click install
npx skills add https://github.com/zilliztech/milvus-marketplace --skill multimodal-rag
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: multimodal-rag
Source: https://github.com/zilliztech/milvus-marketplace/tree/main/plugins/multimodal-retrieval/skills/multimodal-rag
Command: npx skills add https://github.com/zilliztech/milvus-marketplace --skill multimodal-rag

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps users answer questions about documents that mix text and images, charts, or diagrams by combining textual and visual context.

Core Features & Use Cases

  • Multimodal RAG: Retrieve and reason over both text and image content from PDFs, manuals, reports, and presentations.
  • Visual Q&A: Answer questions about charts, diagrams, and figures embedded in documents.
  • Image-aware retrieval: Return relevant image captions or references alongside text results for richer context.

Quick Start

Example: Ask a question like "What does the revenue chart show on page 2 of the product manual?" and run multimodal reasoning across text and visuals.

Frequently Asked Questions about multimodal-rag

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

FAQPage Schema
How do I answer questions about images and text in PDF documents?▼

Multimodal RAG combines text embeddings and vision-enabled LLMs to index and retrieve both textual and visual content from PDFs, enabling you to ask questions about charts, diagrams, and mixed-media documents and receive answers grounded in both modalities.

Can I use vector search to find relevant images and text together in documents?▼

Yes. Image-aware retrieval returns both relevant image captions and text results alongside visual context, allowing vector-based search across multimodal document collections like manuals and reports containing diagrams or figures.

What document types does multimodal retrieval support?▼

Multimodal RAG processes PDFs, manuals, reports, and presentations that mix text with images, charts, or diagrams, enabling visual Q&A across diverse document structures.

How do I set up text and vision models for document question-answering?▼

Configure a text embedding model like text-embedding-3-small for indexing and a vision-enabled LLM like GPT-4o for reasoning over retrieved content, then build a retrieval pipeline indexed on Milvus or similar vector databases.

When should I use visual Q&A instead of text-only search?▼

Use visual Q&A when documents contain charts, diagrams, or figures that carry essential information—text-only search cannot extract meaning from images, so multimodal reasoning bridges that gap for comprehensive answers.