This tutorial launches the Agent series by showing how to create a minimal, CLI‑driven entry point that wraps the model API in a Brain.chat() method, configures credentials via a .env file, handles errors gracefully, maintains multi‑turn conversation state, and outlines the project structure and next development steps.
This guide walks you through Claude Code model choices, secure API key handling, Python SDK setup, request construction, multi‑turn conversation management, system prompts, temperature tuning, response streaming, and extracting clean structured data such as JSON, all with practical code examples and diagrams.
This tutorial revisits LangChain basics, demonstrates how to add multi‑turn memory to a chatbot, shows streaming output via the stream method, and walks through creating a full‑stack web interface with Gradio, providing complete Python code examples for each step.
This article explores the architecture and components of Alibaba's Tmall Genie dialogue engine, detailing its bot, skill, domain, intent, entity concepts, NLU strategies—including deep‑learning and fuzzy approaches—skill execution methods, multi‑turn handling, screen‑based interactions, public intents, and the evolution of the platform.
The article reviews the inaugural global Task‑Oriented Multi‑Turn Dialogue Competition (JDDC), highlighting keynote speeches from JD.com executives, the competition’s dataset and evaluation methods, winning teams’ approaches, and future directions for AI‑driven conversational systems.
