Leveraging LangGraph and AutoGen for Agentic AI Frameworks
Independent Publisher, USA.
World Journal of Advanced Engineering Technology and Sciences, 2023, 08(02), 402-411.
Article DOI: 10.30574/wjaets.2023.8.2.0068
Publication history:
Received on 28 January 2023; revised on 18 April 2023; accepted on 21 April 2023
Abstract:
This research examines how LangGraph and AutoGen improve Agentic AI models by enabling improved autonomous functioning in dynamic environments. Researchers examine LangGraph's language-based system and AutoGen's generative model as independently working tools for agent autonomous performance in intricate situations. Our study uses quality-benchmarking data and test simulations to examine modeling effects on AI agents' behavior and decision-making. The study shows that LangGraph boosts language understanding effectiveness while AutoGen improves the system's ability to adjust decisions swiftly in real-time. Our conclusion points to combined advancements enabling us to develop smarter AI systems that can operate autonomously under unpredictable real-world conditions.
Keywords:
Agentic AI; LangGraph Technology; AutoGen Framework; Natural Language; Generative Models; Decision-Making
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Copyright © 2023 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0