Model interaction

Model interaction is the process of interacting with the model to get the desired output. It is the process of sending a prompt to the model and getting a response.

📄️ OpenAI-compatible API

An OpenAI-compatible API implements the same request and response formats as OpenAI's official API, allowing developers to switch between different models without changing existing code.

📄️ Anthropic-compatible API

An Anthropic-compatible API mirrors Anthropic's Messages API so Claude-based clients, SDKs, and agent tools can use another model or provider with minimal code changes.

📄️ Function calling

Learn what function calling is and its use case.

📄️ Structured outputs

Structured outputs are model responses in defined formats like JSON or XML, making AI-generated data predictable, machine-readable, and easy to integrate into applications and workflows.

📄️ Model Context Protocol

Learn what Model Context Protocol (MCP) is and its use case.

📄️ Prompt engineering

Understand prompt engineering for LLM inference. Learn system & user prompts, zero-shot & few-shot prompting, KV cache impact, token costs, and production best practices.

📄️ LLM inference parameters

LLM inference parameters are request-time settings that control randomness, output length, repetition, stopping behavior, reproducibility, and structured generation.

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