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Functional Agents and ReAct Agents

 Let’s dive into the world of Functional Agents and ReAct Agents in the context of Retrieval-Augmented Generation (RAG). 🦙🌟

Functional Agents:

What are Functional Agents?

Imagine a llama that can perform specific tasks based on predefined functions.

Functional agents are designed to execute specific actions or operations.

Think of them as the llama ranch hands—each with a specific job!

Examples with Llama Magic:

Date Calculator (Tool_Date):

You want to calculate the start date based on a relative time frame (e.g., “past 6 months”).

The llama (Functional Agent) uses a Python function to subtract the time frame from today’s date.

Example: “What was the start date 6 months ago?” 📅🦙

Search Engine (Tool_Search):

You need to find relevant documents related to a specific query.

The llama (Functional Agent) uses a search engine tool to retrieve a list of relevant documents.

Example: “Show me articles about llama grooming.” 🔍🦙

ReAct Agents:

What are ReAct Agents?

ReAct agents take the llama ranch hand concept further.

They break down complex queries into actionable sub-tasks and follow through step by step.

Think of them as the llama project managers—orchestrating a sequence of actions!

Examples with Llama Magic:

Multi-Hop Question Answering:

You ask a complex question: “Has there been an increase in flavor concerns in the past 1 month?”

The llama (ReAct Agent) systematically performs the following steps:

Calculate the start date based on “past 1 month.”

Fetch queries mentioning flavor issues for the start date.

Count the queries.

Fetch queries mentioning flavor issues for the end date.

Count the queries.

Calculate the percentage increase/decrease.

Example: “Flavor concerns increased by 20% in the past month.” 📊🦙

Why Functional Agents and ReAct Agents Matter?

🚀 Efficiency: They break down complex tasks into manageable steps.

🌐 Systematic Reasoning: They use language models to plan and execute actions.

🦙 Llama Power: Functional and ReAct agents make RAG systems smarter and more reliable!

So next time you encounter a llama-powered RAG system, appreciate the magic of functional and ReAct agents! 🦙✨

!Functional and ReAct Agents

For more llama-approved insights, check out this Medium article. Happy llama-linguistics! 🗣️🦙🔍

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