OmAgent

A multimodal intelligent agent framework for tackling complex tasks

CommonProductProgrammingMultimodalIntelligent Agent

OmAgent is a sophisticated multimodal intelligent agent system dedicated to leveraging multimodal large language models and other multimodal algorithms to accomplish compelling tasks. It encompasses a lightweight intelligent agent framework, omagent_core, meticulously designed to address multimodal challenges. OmAgent comprises three core components: Video2RAG, DnCLoop, and Rewinder Tool, respectively responsible for long video understanding, complex problem decomposition, and information retrieval.

Video2RAG: Transforms long video understanding into a multimodal RAG task
breaking the limitations of video length.
DnCLoop: Employs a divide-and-conquer algorithmic paradigm
recursively decomposing complex problems into task trees.
Rewinder Tool: A 'progress bar' tool designed to address the issue of video information loss
enabling the agent to autonomously rewind for details.
Supports custom configuration files for flexible task processing parameter settings.
Offers a quick start guide to simplify the task processing workflow.
Supports video understanding tasks
enhancing video feature retrieval through milvus vector databases and optional facial recognition algorithms.

OmAgent is designed for developers and researchers
particularly those interested in multimodal algorithms
large language models
and agent technology. It is suitable for professionals who work on complex tasks like long video understanding and analysis
helping them efficiently realize innovative ideas.

Construct a system using OmAgent that can automatically analyze and summarize the content of long videos.
Utilize the DnCLoop component to decompose a complex research project into manageable subtasks.
Leverage the Rewinder Tool to quickly locate and retrieve key information during video analysis.

Install a Python environment with a version of 3.10 or higher.
Navigate to the omagent-core directory and install omagent_core using pip.
Install any additional dependencies as needed
such as OpenAI GPT or other MLLMs.
Create a configuration file and set the necessary variables

Visit

OmAgent Visit Over Time

Monthly Visits

490881889

Bounce Rate

37.92%

Page per Visit

5.6

Visit Duration

00:06:18

OmAgent Visit Trend

OmAgent Visit Geography

OmAgent Traffic Sources

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OmAgent

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