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Building Agentic RAG With Llamaindex L3 Building An Agent Reasoning Loop

Building Agentic RAG With Llamaindex L3 Building An Agent Reasoning Loop

llamaLlamaIndexAIvllmmachine-learning3p-integrationsdlai_agentic_ragllama2LLMllama-cookbookPythonfinetuningpytorchlangchain

Open In Colab

This notebook ports the DeepLearning.AI short course Building Agentic RAG with Llamaindex Lesson 3 Building an Agent Reasoning Loop to using Llama 3. It shows how to define a complete agent reasoning loop to reason over tools and multiple steps on a complex question the user asks about a single document while maintaining memory.

You should take the course before or after going through this notebook to have a deeper understanding.

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Load the data

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Setup the Query Tools

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Setup Llama and Agent

Note: The LlamaIndex's FunctionCallingAgentWorker API doesn't work correctly with Groq Llama, so we use ReActAgent here.

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Lower-Level: Debuggability and Control

Note: The LlamaIndex's FunctionCallingAgentWorker API doesn't work correctly with Groq Llama, so we use ReActAgent here.

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