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Inside the portfolio

From question to answer.

A RAG flow with a model that can request four limited tools. Contact actions are never performed autonomously: the visitor must submit the form.

BrowserSite serverCloud AIData / external services

The model chooses whether to answer or use a tool. Select nodes for details; on mobile you can scroll and zoom the graph.

Conditional pathVisitor submission
__start__memoryShort memoryLast 5 completed exchangesknowledgeKnowledge baseResume · notes · artwork catalogentry_nodeQuestion and validationOrigin · format · limitsretrieveSemantic retrievalCloud embedding → local searchsystem_promptSystem promptIdentity · language · rulesprepare_contextRequest contextQuestion + memory + evidencegenerate_or_routeLLM modelAnswer or tool requesttool_nodeAvailable toolsrender_responseResponse / resourcesStreaming · text · resourcescontact_submitContact submissionForm → Telegram
Cloud AI

LLM model

OpenAI generates text or selects a tool based on intent. Vercel AI SDK orchestrates at most two steps, with store: false and streamed generation.

A short cycle, not an unlimited agent

The model receives descriptions of the four tools, can request their execution and receives the result. Orchestration stops within two steps. Informational questions normally receive text only.

Two paths, two treatments

AI calls receive question and context. The contact form uses a separate endpoint: its fields are never inserted into the prompt or history.

Limits and visitor control

You can stop streaming, open or download the resume and choose when to enter the exhibition or send a contact. RAG improves grounding in documents, but does not make answers or tool selection infallible.