ReAct Agent LLM

Agent that uses the ReAct (Reasoning and Acting) logic to decide what action to take, optimized to be used with Non Chat Models.

ReAct Agent LLM Functionality

This agent implements the ReAct (Reason + Act) framework, which allows it to alternate between reasoning about a problem and taking actions to solve it. It’s designed to work seamlessly with chat models, making it particularly effective for interactive, multi-turn conversations that involve complex problem-solving.

The ReactAgentLLM is the core agent that implements the ReAct paradigm, allowing LLMs to reason through problems and invoke tools/functions step-by-step based on intermediate observations.

Inputs

The ReAct Agent LLM requires the following inputs to function effectively:

Required Parameters

• Allowed Tools: External capabilities the agent can use to complete tasks, such as web search, document reading, web scraping, file writing, API access, etc.
• Chat Model: language model that is specifically trained and optimized for multi-turn, conversational interactions (e.g., GPT-4 vs Claude 3).
• Memory: the memory input provides the agent with long-term context across multiple user interactions. It helps the agent remember previous messages, questions, and responses, allowing it to hold a coherent and natural multi-turn conversation.

Optional Parameters

• Input Moderation: Optional input that enables content moderation. This helps ensure that queries are appropriate and do not contain offensive or harmful content.

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