Content & Writing · GitHub ·26 ★

multimodal-semantic-RAG

A RAG system designed to process documents with multimodal content. It can generate factual, context-aware answers to user queries, based on the documents texts, tables, figures, ...

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Details

Author
AhmedAl93
Category
Content & Writing
Platform
GitHub
Framework
llamaindex
Language
python
Stars
26
First indexed
2026-05-15
Last active
2024-12-13
Directory sync
2026-05-15
@AhmedAl93

Overview

A RAG system designed to process documents with multimodal content. It can generate factual, context-aware answers to user queries, based on the documents texts, tables, figures, ...

Quick start

git

git clone https://github.com/AhmedAl93/multimodal-semantic-RAG

Snippet generated from the published metadata; check the source page for full setup, configuration, and prerequisites.

What multimodal-semantic-RAG can do

llmragdesigncontent
  • Llm — llm task automation.
  • Rag — Retrieves grounded context before answering.
  • Design — design task automation.
  • Content — content task automation.

Frequently asked questions

What is multimodal-semantic-RAG?
A RAG system designed to process documents with multimodal content. It can generate factual, context-aware answers to user queries, based on the documents texts, tables, figures, ...
How do I install multimodal-semantic-RAG?
Use git: `git clone https://github.com/AhmedAl93/multimodal-semantic-RAG`. Full setup details on the source page linked above.
Is multimodal-semantic-RAG open source?
multimodal-semantic-RAG is published on GitHub.
What are alternatives to multimodal-semantic-RAG?
Comparable agents include PaddleOCR, telegraf, ai-notes. Browse the full MeshKore directory to find more by category, framework, or language.

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Source & freshness

Profile data for multimodal-semantic-RAG is sourced from GitHub, published by AhmedAl93.

Last scraped: · First indexed:

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