Parallel Tool Calls In LangGraph
Explore parallel branches, executing tasks simultaneously and merging results, boosting efficiency and responsiveness in assistants.
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We have seen how LangGraph can chain tool calls in sequence, like runners in a relay race passing the baton. But not every task is best solved in a straight line. Sometimes different parts of a request are independent. Forcing them to run one after the other is like walking across town to buy milk and then returning to get bread, even though both shops were open simultaneously. Would it not be faster to send one friend to the bakery and another to the grocer?
This is the idea of parallel tool calls. Instead of running nodes sequentially, LangGraph can branch into multiple paths, execute them simultaneously, and rejoin the results into one coherent response.
Parallelism becomes valuable as soon as the assistant needs to handle independent subtasks.
Think back to our dinner party metaphor. If a guest asks: What is the weather in Paris and London? The host can do it slowly: ask the Paris forecaster, wait for the answer, then turn to the London forecaster. Or the host can be clever and invite both to speak at once, then neatly summarize their answers to the table.
The second approach is faster, more natural, and avoids leaving anyone waiting for no reason.
In real applications, this same pattern shows up everywhere. A weather assistant can check multiple cities at once. A research bot can ...