Step-by-Step Guide: Building a Production Multi-Agent Graph with LangGraph & Redis

Practical Step-by-Step Walkthrough: Learn how to build, test, and deploy a stateful multi-agent execution graph with Redis checkpoint persistence, Pydantic schema validation, and reflection retry loops.

Step 1: Define the Shared Agent State Schema

In LangGraph, all agent nodes read from and write to a centralized state dictionary validated by Pydantic:

from pydantic import BaseModel, Field
from typing import List, Dict, Any, Optional

class AgentExecutionState(BaseModel):
    session_id: str
    user_query: str
    current_step: str = "planner"
    execution_plan: List[str] = Field(default_factory=list)
    intermediate_results: Dict[str, Any] = Field(default_factory=dict)
    error_log: List[str] = Field(default_factory=list)
    final_output: Optional[str] = None

Step 2: Build the Graph Execution Nodes

Create dedicated functions for the Planner Node, Tool Executor Node, and Reflection Evaluator Node.

Step 3: Wire Redis Checkpoint Persistence

Attach a RedisSaver instance to persist execution graphs across restarts:

from langgraph.checkpoint.redis import RedisSaver
import redis

redis_client = redis.Redis(host="localhost", port=6379, db=0)
checkpointer = RedisSaver(redis_client)
graph = builder.compile(checkpointer=checkpointer)

Step 4: Test & Verify Resilience

Simulate API timeouts to verify reflection loops automatically recover from execution errors.