Nodes & Edges

Separating 'what runs' (nodes) from 'what runs next' (edges) lets you compose complex agent logic without nesting callbacks or spaghetti if/else chains.

Nodes are kitchen stations (prep, grill, plate); edges are the rules for when an order moves to the next station or goes back for a redo.

Scenario

Node `search` → conditional edge checks `state['results_count']`: 0 routes to `rewrite_query`, >0 routes to `synthesize_answer`.

Solution

In Agent Frameworks, apply Nodes & Edges to this scenario: Node `search` → conditional edge checks `state['results_count']`: 0 routes to `rewrite_query`, >0 routes to `synthesize_answer`. Identify the inputs, run the technique, validate the output, and note one thing you would monitor in production.

Do this before moving to the next module — reading alone is not enough.

Open the Code Walkthrough below and run it locally. Change one parameter related to Nodes & Edges (e.g. model, temperature, top_k, or tool name), observe the difference in output, and write 2–3 sentences explaining what changed.

Highlighted lines show where Nodes & Edges happens in the code.

1def route(state):  # define a reusable function2    if state.get("needs_human"):3        return "human"  # return the result4    return "auto_reply"  # return the result5
6graph.add_conditional_edges("draft", route, {"human": "human_review", "auto_reply": "send"})  # key line for Nodes & Edges

• Treating Nodes & Edges as a black box without evaluation
• Ignoring cost and latency in production
• Skipping error handling for langgraph nodes edges

Quick recap — the most important points from this module.