Building the stategraph
Now we bring everything together. The StateGraph connects all our agents into a cohesive workflow with proper routing between them.
def create_text2sql_graph():
"""Create the LangGraph state graph for Text2SQL with visualization"""
workflow = StateGraph(AgentState)
# Add all agent nodes
workflow.add_node("guardrails_agent", guardrails_agent)
workflow.add_node("sql_agent", sql_agent)
workflow.add_node("execute_sql", execute_sql)
workflow.add_node("analysis_agent", analysis_agent)
workflow.add_node("error_agent", error_agent)
workflow.add_node("decide_graph_need", decide_graph_need)
workflow.add_node("viz_agent", viz_agent)
# Set the entry point - always start with guardrails
workflow.set_entry_point("guardrails_agent")
# Add conditional and regular edges (see next lesson)
# ...
return workflow.compile()
# Create the compiled graph at module load
text2sql_graph = create_text2sql_graph()The create_text2sql_graph function builds the complete workflow.
Full Multi-agent stategraph
The complete graph showing every agent node and how they connect through conditional and direct edges.
The graph structure itself never changes between requests. Building and compiling it once at startup means every incoming request can immediately execute the same graph without the overhead of construction. Think of it like compiling a program once and running it many times.
Ordering exercise: Order the graph construction steps
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Quiz: Quiz
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Fill in the blanks: Complete the stategraph setup
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The graph skeleton is built with all nodes connected. Next, we will add the intelligence: conditional routing that lets the graph make decisions at each branch point.