agents.rag.llm_rag.example

Example usage of the LLM RAG Agent.

from typing import Any This script demonstrates how to: 1. Create and configure an LLM RAG agent 2. Run queries and access the results 3. Customize the agent’s behavior

Functions

compare_agent_configurations()	Compare different agent configurations side by side.
create_llm_rag_agent([use_relevance_checker, ...])	Creates and configures an LLM RAG agent.
main()	Main function to run the example.
run_example_queries(agent)	Run a set of example queries against the agent.

Module Contents

agents.rag.llm_rag.example.compare_agent_configurations()

Compare different agent configurations side by side.

Return type:

None

agents.rag.llm_rag.example.create_llm_rag_agent(use_relevance_checker=True, return_documents=3)

Creates and configures an LLM RAG agent.

Parameters:

• use_relevance_checker (bool) – Whether to include a relevance checking component

• return_documents (int) – Number of documents to retrieve

Returns:

Configured agent instance

Return type:

LLMRAGAgent

agents.rag.llm_rag.example.main()

Main function to run the example.

Return type:

None

agents.rag.llm_rag.example.run_example_queries(agent)

Run a set of example queries against the agent.

Parameters:

agent (Any) – The LLM RAG agent to query