FastAPI chatbot backend
Input → normalize → model → output. Matches a typical POST /chat body with a single LLM call.
Workflows
Workflow runtime
Design and run controlled AI workflows with policies, knowledge, tools, and evaluations attached—runtime graphs your control plane executes and traces.
Backend-oriented starters
Pre-wired graphs that mirror how teams ship FastAPI, Node, or .NET services: RAG, guardrails, approvals, and simple chat pipelines. Opens in the editor with the production mapping panel.
Input → normalize → model → output. Matches a typical POST /chat body with a single LLM call.
Retrieval → model → answer with sources. Like FastAPI RAG: embed/search then generate.
Policy check before and after model — like middleware + post-validation in .NET Minimal APIs.
Policy gate on student-facing prompts — align with FERPA-style handling before generation.
Model proposes → human approves in Quantlix → response released. Like a manual gate in Temporal.
Pick an organization in Create workflow below so templates know which org to use.
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