Agentic Loop

• Agents combine the models with tools
• Agents reason about tasks, decide which tools to use and work towards a solution
• https://docs.langchain.com/oss/python/langchain/agents

• The langchain.agents.create_agent function build a graph-based agent runtime using LangGraph
• It consists of nodes (steps) and edges (connections) that defines how your agent processes information

Evolution of the Agentic Loop

1. ReAct Prompt with AgentExecutor (2022~mid-2023)

   • create_react_agent & AgentExecutor
   • Prompt with the reasoning format (Thought/Action/Observation), tool descriptions and output instructions
   • The AgentExecutor ran the loop: call LLM, parse output, tool calls, append observations, repeat

2. Tool Calling with AgentExecutor (mid-2023~2024)

   • create_tool_calling_agent & AgentExecutor
   • OpenAI introduced function calling (June 2023)
   • Use the function calling functionality of LLMs (made available in June 2023) that also support the structured output
   • AgentExecutor still orchestrated the loop

3. Tool Calling with LangGraph

   • create_agent (langchain 1.0)
   • LangGraph allowed agents with graphs/state machines, not hidden loops