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 rigorously benchmark vector databases with proper methodology — measuring latency, throughput, and recall under realistic conditions to make informed infrastructure decisions.
Learn how to expose AI agents through production-grade FastAPI REST endpoints with async request handling, Pydantic validation, structured error responses, and streaming support.
Design robust health check and readiness probe endpoints for AI agent services that verify dependencies, enable graceful startup and shutdown, and integrate with container orchestrators.
Understand when to use multiprocessing versus asyncio for AI agent workloads. Learn CPU-bound vs I/O-bound trade-offs, ProcessPoolExecutor, and hybrid patterns.
Implement the Observer pattern with an event bus for AI agent systems — enabling decoupled, publish-subscribe communication between agents for flexible coordination.
Understand what large language models are, how they evolved from simple neural networks to GPT-scale transformers, and why they can generate human-quality text.
Learn how to decompose complex AI tasks into sequential prompt chains — passing intermediate results between LLM calls, handling errors in pipelines, and building reliable multi-step workflows.
Learn how to use AsyncOpenAI with Python's asyncio to make concurrent API calls, implement connection pooling, and build high-throughput AI pipelines.
