Function Calling

A comprehensive technical guide for developers on integrating DeepSeek-V3-0324, covering MoE architecture, OpenAI-compatible API usage, function calling, and self-hosting strategies.

Discover Ecom-RLVE, a groundbreaking framework that leverages Reinforcement Learning from Verifiable Environments to build reliable, hallucination-free e-commerce AI agents using high-performance LLM APIs.

Discover how to leverage ChatGPT's new app integrations to streamline your workflow with Spotify, Canva, Expedia, and more. This guide covers setup, technical implementation, and developer best practices.

A comprehensive guide to implementing xAI's Grok API, covering chat completions, image/video generation, function calling, and advanced web search techniques.

OpenAI's latest plugin integration transforms the Codex model from a specialized code generator into a versatile agent capable of executing complex real-world actions through third-party APIs.

OpenAI unveils GPT-5.4 mini and nano, two lightweight models optimized for coding, tool use, and multimodal reasoning, offering unprecedented speed and cost-efficiency for developers using n1n.ai.

Discover why vector search fails for complex LLM tool-calling workflows and how a graph-based retrieval approach can boost accuracy from 12% to 82% while slashing token costs.

A comprehensive technical guide on utilizing ChatGPT's latest app integrations like Spotify, Canva, and DoorDash, and how developers can leverage these capabilities via n1n.ai.

Move beyond simple chat interfaces to build robust AI products. This guide covers implementing Tool Use, Retrieval-Augmented Generation (RAG), and advanced workflow patterns using the Claude API for enterprise-ready applications.

A comprehensive guide to the Model Context Protocol (MCP), explaining its architecture, benefits for developers, and how it standardizes tool integration for LLMs.

A deep dive into OpenAI's function calling feature, comparing it with traditional prompt engineering and exploring its integration with modern LLM aggregators like n1n.ai.

A deep dive into the Model Context Protocol (MCP), explaining how Large Language Models discover and execute external tools through a standardized architecture.