Topic

Parallel & Multi-Step Tool Use

12 posts on parallel & multi-step tool use — part of api integration on the n4n AI blog.

When parallel function calling fails and how to recover

Practical guide to parallel function calling failure recovery: diagnose partial tool failures, isolate errors, retry, fallback, and aggregate results safely in LLM agents.

July 17, 20264 min read

API integrationComparison

Parallel vs sequential function calling: when to use each

Compare parallel vs sequential function calling on capabilities, cost, latency, ergonomics, and limits, with a clear verdict for building LLM tool integrations.

July 17, 20265 min read

API integrationHow-to

Parallel tool use with Claude's tool_choice parameter

Learn how to force Claude to call multiple tools in one turn using the tool_choice parameter, with runnable Python code for parallel execution.

July 17, 20263 min read

API integrationTutorial

Parallel function calling with GPT-4o: an example

Hands-on Python tutorial for parallel function calling with GPT-4o: define tools, trigger multiple calls, run them concurrently, and merge results.

July 17, 20262 min read

API integrationHow-to

Handling parallel tool call results in a single response

Learn how to execute multiple LLM tool calls concurrently and return all results in one response, with runnable Python code for OpenAI-compatible APIs.

July 17, 20263 min read

API integrationGuide

Designing agent loops for multi-step function calling

Practical guide to designing agent loops multi-step function calling: orchestration patterns, state management, parallelism, and failure handling.

July 17, 20264 min read

API integrationHow-to

Debugging race conditions in parallel LLM tool calls

Practical steps to diagnose and fix intermittent failures when LLM agents run multiple tool calls concurrently, with code and verification.

July 17, 20264 min read

API integrationGuide

Chaining tool calls across multiple turns in an agent loop

Practical guide to chaining tool calls agent loop turns: manage message state, run parallel tools, set termination, and handle errors in LLM agents.

July 17, 20263 min read

API integrationTutorial

Building a multi-step research agent with tool use

Hands-on tutorial for building a multi-step research agent with tool use: implement parallel tool calls, agent loop, and real search via OpenAI-compatible API.

July 17, 20264 min read

API integrationDefinition

Parallel function calling: running multiple tools at once

Parallel function calling multiple tools lets LLM agents invoke several functions in one turn. Learn how it works, why it matters, and common pitfalls.

July 16, 20266 min read

API integrationGuide

Multi-step tool use for autonomous LLM agents

Practical guide to building multi-step tool use autonomous agents: strict schemas, plan-execute loops, parallel steps, failure handling, and cost control.

July 16, 20264 min read

API integrationHow-to

How parallel tool calls work in the OpenAI API

Learn how parallel tool calls work in the OpenAI API with a step-by-step guide: define tools, send requests, run calls concurrently, and verify.

July 16, 20262 min read