📄️ Team Collaborative Development with JitAi Desktop
Desktop Development Workflow (Recommended)
📄️ Developing and Debugging JitAi Applications with VSCode or PyCharm
This document guides developers on configuring a local development and debugging environment using the desktop version for efficient development and debugging.
📄️ AI Customer Service Agent
本文适合新手快速上手。通过对本文的学习，你将有以下收获：
📄️ AI-Powered Question Generation and Grading
行业背景
📄️ Agent Prompt Writing Techniques
This article is designed for developers who create systematic prompts for Agents in JitAi. Through "Poor Version vs. Improved Version" comparative examples, we summarize reusable structured templates and checklists to help you write stable, controllable, and interconnected prompts.
📄️ Business Entity Modeling and Data Analysis
Build a sales data analysis system that manages entities such as customers, stores, sales representatives, products, and orders. Support multi-database configuration (historical data archived to separate database instances), extended statistical fields in customer information, multi-dimensional aggregation analysis, and automated business rule processing when data changes.
📄️ Using Interceptors for Custom Request Authentication
When systems need to provide APIs for external partners, authentication is often required to restrict unauthorized access. JitAi's API authorization elements can implement exposing API interfaces to third parties (recommended approach), but this requires callers to use the client SDK provided by JitAi. When callers cannot use the SDK, you can use backend interceptors to implement custom authentication methods to accommodate different calling patterns. This document uses custom Bearer Token authentication as an example.
📄️ Application Layer Stability Guarantee
JitAi has the capability to support mainstream and leading application layer stability assurance measures in the industry.