awesome-repositories.com
Blog
MCP
awesome-repositories.com

Discover the best open-source repositories with AI-powered search.

ExploreCurated searchesOpen-source alternativesSelf-hosted softwareBlogSitemap
ProjectMCP serverAboutHow we rankPress
LegalPrivacyTerms
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
lyuchenyang avatar

lyuchenyang/Macaw-LLM

0
View on GitHub↗
1,590 stars·131 forks·Python·Apache-2.0·14 views

Macaw LLM

Macaw-LLM: Multi-Modal Language Modeling with Image, Video, Audio, and Text Integration

Features

  • Multimodal Agents - Integration of image, audio, video, and text.
  • Pre-training Datasets - Multi-turn dialogue dataset for multimodal integration.

Star history

Star history chart for lyuchenyang/macaw-llmStar history chart for lyuchenyang/macaw-llm

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

AI search

Explore more awesome repositories

Describe what you need in plain English — the AI ranks thousands of curated open-source projects by relevance.

Start searching with AI

Projects sharing features with Macaw LLM

These projects share indexed features with Macaw LLM. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • phellonchen/x-llmphellonchen avatar

    phellonchen/X-LLM

    318View on GitHub↗

    X-LLM: Bootstrapping Advanced Large Language Models by Treating Multi-Modalities as Foreign Languages

    Python
    View on GitHub↗318
  • othersideai/self-operating-computerOthersideAI avatar

    OthersideAI/self-operating-computer

    10,153View on GitHub↗

    This project is a computer control framework that uses multimodal vision models to simulate mouse and keyboard inputs for automating desktop tasks. It functions as an autonomous agent and vision-based orchestrator that interprets screen visuals to interact with user interfaces. The system employs vision language models and object detection to locate and click interface elements. It utilizes visual grounding to overlay numerical markers on UI components and uses optical character recognition to map on-screen text to precise pixel coordinates. The framework supports voice-controlled computing

    Pythonautomationopenaipyautogui
    View on GitHub↗10,153
  • 11cafe/jaaz11cafe avatar

    11cafe/jaaz

    6,384View on GitHub↗

    Jaaz is a self-hosted AI design suite and multimodal workspace used for generating and editing images and videos. It functions as a design workspace where users can produce visual content and assets through a combination of local and cloud-based AI models. The project features a hybrid model orchestrator that routes requests between local model runners and remote APIs to balance data privacy with processing performance. It utilizes an infinite canvas collaborative tool for organizing storyboards and assets, and includes an image prompt optimizer to translate rough ideas into detailed generati

    TypeScript
    View on GitHub↗6,384
  • qwenlm/qwen3-omniQwenLM avatar

    QwenLM/Qwen3-Omni

    3,843View on GitHub↗

    Qwen3-Omni is an omni-modal large language model designed to process and generate text, audio, images, and video within a single unified neural architecture. It functions as a real-time voice assistant and multimodal AI agent capable of reasoning across different media types and executing external tool-calling functions via APIs. The system supports low-latency conversational AI through autoregressive token streaming and natural turn-taking. It enables multilingual speech translation and generation across dozens of languages, featuring customizable speaker profiles and tones. The model's cap

    Jupyter Notebook
    View on GitHub↗3,843
Compare all 30 related projects→

Frequently asked questions

What does lyuchenyang/macaw-llm do?

Macaw-LLM: Multi-Modal Language Modeling with Image, Video, Audio, and Text Integration

What are the main features of lyuchenyang/macaw-llm?

The main features of lyuchenyang/macaw-llm are: Multimodal Agents, Pre-training Datasets.

Which projects share features with lyuchenyang/macaw-llm?

Projects with overlapping indexed features include: phellonchen/x-llm — X-LLM: Bootstrapping Advanced Large Language Models by Treating Multi-Modalities as Foreign Languages. simular-ai/agent-s — Agent-S is a multimodal AI agent and LLM desktop automation framework designed to control operating systems through… 11cafe/jaaz — Jaaz is a self-hosted AI design suite and multimodal workspace used for generating and editing images and videos. It… othersideai/self-operating-computer — This project is a computer control framework that uses multimodal vision models to simulate mouse and keyboard inputs… qwenlm/qwen3-omni — Qwen3-Omni is an omni-modal large language model designed to process and generate text, audio, images, and video… plexpt/chatgpt-corpus — This project provides a comprehensive Chinese language corpus designed to support the training and fine-tuning of…