Auto RAG Agent • AI Agent SDK

AutoRagAgent: Agent wrapper with automatic RAG retrieval decision.

AutoRagAgent

Defined in the Auto RAG Agent module.

AI Agent

Agent wrapper with automatic RAG retrieval decision.

Decides when to perform retrieval based on policy and heuristics, then composes RAG context with Agent chat.

This follows the same pattern as AutoAgents but for RAG:

• AutoAgents: auto-generates agent configs from instructions
• AutoRagAgent: auto-decides when to retrieve context

Constructor

agent · Agent · required

No description available.

rag · Optional

No description available.

config · Optional

No description available.

Methods

rag()

Lazy load RAG from agent if not provided.

name()

Delegate name to wrapped agent.

chat()

Chat with automatic RAG retrieval decision.

achat()

Async version of chat.

Usage

from praisonaiagents import Agent, AutoRagAgent
    
    agent = Agent(
        name="Research Assistant",
        knowledge=["docs/manual.pdf"],
    )
    
    auto_rag = AutoRagAgent(agent=agent)
    
    # Auto mode - decides based on query
    result = auto_rag.chat("What are the key findings?")
    
    # Force retrieval
    result = auto_rag.chat("Hello", force_retrieval=True)
    
    # Skip retrieval
    result = auto_rag.chat("What is 2+2?", skip_retrieval=True)

Source

View on GitHub

praisonaiagents/agents/auto_rag_agent.py at line 105

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Related Documentation

Agents Concept

Single Agent Guide

Multi-Agent Guide

Agent Configuration

Auto Agents