OpenAI Agent SDK

purpose problem statement provide an interface within your system for interacting with openai’s models (e g gpt, embeddings, function calling), enabling automation, conversational ai, and content generation requirements must accept prompts, inputs, or context data must support settings like temperature, max tokens, model selection should allow function calls, streaming responses, and error handling should integrate with other nodes in workflows (send input → receive output → branch further) use cases powering chatbots or conversational agents that respond based on user input automating content generation (summaries, emails, reports) in workflows processing and interpreting data (e g sentiment, classification) via ai apis enhancing decision making logic with natural language understanding and generation outcome delivers an ai powered “brain” component in the workflow, capable of generating intelligent responses, performing tasks via function calls, and integrating seamlessly into process flows how to use drag & drop the openai agent sdk node into your workflow canvas configure model parameters (model type, temperature, max tokens) provide input (prompt, context, prior messages, or variables) optionally map functions or apis that the agent can call connect the output(s) — e g response text, function return values, error paths — to subsequent nodes test the agent behavior under various inputs, validate fallback or error handling logic