om-ai-lab/OmAgent

Health v2 · maintenance only

Adoption not part of the score

2667 stars · 292 forks observed · 2026-09-24

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

OmAgent is a Python library for building multimodal language agents, wrapping worker orchestration, task queues, and graph-based workflow orchestration behind a simple interface. It natively supports VLM models, video processing, mobile device connections, and agent algorithms like ReAct and CoT, with both distributed and Lite deployment modes.

Use cases

• build a multimodal agent that reasons over video
• prototype a language agent with ReAct or CoT reasoning
• connect an agent to a mobile device for smart hardware control
• run a video understanding pipeline with a VLM
• deploy LLM agents locally with Ollama or LocalAI
• orchestrate a graph-based agent workflow with memory

When to choose

• you need multimodal inputs like image, video, or audio in your agent
• you want a lightweight agent framework without heavy middleware overhead
• you need distributed scaling or a middleware-free Lite mode
• you want reusable agent components and graph-based workflows in Python

When to avoid

• you only need simple text-only chatbot responses
• you prefer a mature ecosystem with extensive third-party integrations
• your project is not Python-based
• you need a no-code agent builder

Facets

framework · maturity active

agent-framework rag llm-inference video-processing workflow-automation chatbot artificial-intelligence large-language-models computer-vision python cross-platform multimodal-agents vlm video-understanding workflow-orchestration llm-agents distributed ai-agents multimodal natural-language-processing

Member repositories

For agents

markdown · JSON · MCP: product_card(name="om-ai-lab/OmAgent")