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 use OpenAI's Vision API to analyze images, send base64-encoded and URL-based images, build multi-modal prompts, and create practical image understanding applications.
Learn how to generate text embeddings with OpenAI's API, understand embedding dimensions, implement batch embedding, and build practical search and similarity applications.
Build automated CI/CD pipelines for AI agent services using GitHub Actions with prompt regression testing, integration tests, Docker image builds, and canary deployment strategies.
Master OpenAI's function calling feature to let language models invoke your Python functions, parse structured arguments, and build tool-augmented AI applications.
Learn how assigning specific roles and expertise to LLMs dramatically improves response quality. Covers proven persona patterns, role combinations, and techniques to minimize hallucination in role-based prompts.
Learn how to instrument AI agent systems with OpenTelemetry for end-to-end distributed tracing, including span creation, custom attributes for LLM calls, and trace context propagation across multi-agent pipelines.
Set up LangSmith for tracing LangChain runs, analyzing run trees, building evaluation datasets, running automated evaluations, and collecting feedback on LLM outputs.
Build resilient applications that gracefully handle OpenAI API errors with exponential backoff, rate limit management, circuit breakers, and fallback strategies.
