AI agents LangChain

AI agents LangChain are systems that use LLMs as reasoning engines to determine which actions to take and the inputs necessary to perform the action. After executing actions, the results can be fed back into the LLM to determine whether more actions are needed. These agents leverage the ReAct Framework which combines reasoning and action elements in large language models, enabling LLMs to reason and act according to the situation. The LangChain ReAct agent helps initiate multiple search actions, such as calling external tools, to resolve complex tasks such as multi-hop reasoning questions. The ReAct agent allows you to specify a description for each tool and then automatically selects the appropriate tool based on the description. LangChain makes it easier to develop large language models-powered applications through its extensive set of tools and abstractions, allowing developers to design powerful AI agents with complicated reasoning, task execution, and interaction with external systems.