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The Research Agent and Workflows share the same response model: a streaming sequence of typed events delivered over Server-Sent Events. The four guides in this section cover the cross-cutting protocol-level behavior that both services exhibit — streaming, grounding, errors, and conversation continuity. If you have not built against the Research Agent or Workflows before, work through these pages in order. They are self-contained, but each builds on the previous one’s vocabulary.
1

Streaming responses

Start here. Defines the SSE format, every public message type, the typical order of events in a request, and a canonical Python handler the rest of the docs build on. Read it
2

Grounding and citations

How GROUNDING references attribute spans of the answer to their source documents, the critical buffering rule for offset math, and a worked example that turns a streamed response into a Markdown answer with inline citations. Read it
3

Error handling

The difference between HTTP-level errors and in-stream errors, what each of ERROR, TOOL_ERROR, and LLM_RETRY means, and a retry/backoff pattern for 429 and 5xx responses. Read it
4

Conversation continuity

Resuming Research Agent conversations with chat_id and checkpoints, the persistence_mode switch, the "INITIAL" reset sentinel, and resuming Workflows by execution_id. Read it

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What each page covers

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Next steps

Once you are comfortable with the concepts, move on to the service-specific quickstarts and how-to guides.

Research Agent quickstart

Send your first Research Agent request end-to-end.

Workflows quickstart

Define and execute your first workflow, inline or by template id.

Non-streaming pattern

Consume the stream end-to-end and print the complete answer in one go.

Workflow templates

Anatomy of a workflow template, input placeholders, content filters, and research plans.