Step-by-step tutorials on building voice and chat AI agents using OpenAI Agents SDK, Realtime API, function calling, multi-agent orchestration, and production deployment patterns.
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Learn how to build a robust SQL validation layer that prevents injection attacks, enforces read-only access, limits query complexity, and ensures AI-generated queries cannot damage your database.
Explore multi-agent reinforcement learning (MARL) concepts including reward shaping, cooperative versus competitive strategies, and policy gradient methods for agent teams with practical Python implementations.
Understand when to use Microsoft UFO for Windows desktop automation versus browser tools like Playwright or Selenium, with use cases for legacy apps, native software, and hybrid approaches.
Master the art of schema representation for text-to-SQL systems. Learn how to format CREATE TABLE statements, add column descriptions, encode foreign key relationships, and provide sample data for maximum query accuracy.
Compare open-source text-to-SQL models including SQLCoder, NSQL, and DeFog SQLCoder. Learn how to deploy them locally, fine-tune on your schema, and evaluate accuracy against commercial alternatives.
Design robust communication protocols for multi-agent systems including message schemas, capability advertisement, negotiation protocols, and service discovery mechanisms with practical Python implementations.
Build a text-to-SQL system with automatic error detection, self-correction loops, and intelligent retry strategies that fix query mistakes without user intervention.
Build a complete text-to-SQL agent using GPT-4 that extracts database schemas, generates SQL queries from natural language, executes them safely, and formats results for end users.
