WitUS Triage Agent

A LangGraph agent that reads incoming WitUS Inbox submissions, classifies them, enriches them with context, proposes an action, and waits for a human to approve before doing anything irreversible.

classify → enrich → propose → human approval → execute | log rejection

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TL;DR

WitUS Inbox collects form submissions from across a small ecosystem of products into one table. Reading every webhook by hand does not scale. This repo is the LangGraph agent that triages that traffic: typed graph state, schema-validated tools, and a human-in-the-loop interrupt that pauses the graph until an operator approves. It is production code with a real database, real auth, and real failure handling, not a demo.

It also runs on two LLM providers from one codebase: Gemini 2.5 Flash for development and CI, Claude Sonnet 4.6 for production. The provider is selected by environment, and an admin dashboard at /admin picks the model per graph node, so the same agent can be tested cheaply and tuned without a redeploy.

A 4-lesson curriculum under docs/lessons/ teaches the patterns this repo demonstrates.

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The problem

WitUS Inbox is a small internal tool that ingests signed webhooks from every product in the WitUS ecosystem (CentenarianOS, FlashLearnAI, Wanderlearn, Fly.WitUS, Work.WitUS, Tour Manager OS, witus.online) and lands them in one canonical submission table.

Without an agent, every submission, the obvious ones included, costs human attention. Most are resolvable in two clicks; a few are urgent; the rest are pattern-matchable noise. This agent sits between the webhook and the human. It does the read-and-propose. The human keeps the decision.

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Architecture

graph TD
    START([Webhook received]) --> CLASSIFY[Classify submission]
    CLASSIFY --> ENRICH[Enrich with past context]
    ENRICH --> PROPOSE[Propose action]
    PROPOSE --> APPROVAL{Human approval}
    APPROVAL -->|approved / edited| EXECUTE[Execute action]
    APPROVAL -->|rejected| LOG[Log + close]
    EXECUTE --> END([Done])
    LOG --> END

Six nodes. One durable approval interrupt. Five tools. One typed TriageState object that carries everything between steps. The graph is one small, readable file: agent/graph.ts.

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The three patterns

This repo demonstrates three LangGraph patterns; each has a companion lesson.

1. Typed graph state

Every node reads and writes one TriageState object, the contract between nodes. Each field is owned by exactly one producing node and is optional until that node runs.

export const TriageStateAnnotation = Annotation.Root({
  rawSubmission: Annotation<RawSubmission>,
  classification: Annotation<Classification | undefined>,
  enrichment: Annotation<Enrichment | undefined>,
  proposedAction: Annotation<ProposedAction | undefined>,
  approval: Annotation<Approval | undefined>,
  execution: Annotation<Execution | undefined>,
});

Full state: agent/state.ts · Schemas: agent/schemas.ts

2. Schema-validated tools

Each of the five tools is a tool() wrapper with a Zod input schema: the same schema documents the inputs, validates them, and (when bound to a model) becomes the JSON schema the model sees.

export const searchPastSubmissions = tool(runSearchPastSubmissions, {
  name: "search_past_submissions",
  description: "Find prior WitUS Inbox submissions from the same contact email.",
  schema: SearchPastSubmissionsInputSchema,
});

All five tools: agent/tools/

3. Human-in-the-loop interrupt

The graph pauses at human_approval via a real LangGraph interrupt(). A Postgres checkpointer persists the paused run, so the pause survives across HTTP requests and process restarts. The approval arrives on a separate request and resumes the exact same graph thread with new Command({ resume }). Execution is unreachable except through an approval. This is the pattern most agent demos skip and production systems need.

Nodes: agent/nodes/ · Checkpointer: agent/checkpointer.ts

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Quick start

You need Node 20+ and a Postgres 16 database (local, or Neon's free tier). This repo owns its own database. It does not connect to the live WitUS Inbox DB.

# 1. Install
npm install

# 2. Create a database
createdb witus_triage_agent

# 3. Configure
cp .env.example .env.local
#    Minimum to run the graph:
#      STORAGE_DATABASE_URL=postgresql://localhost:5432/witus_triage_agent
#      STORAGE_DATABASE_URL_UNPOOLED=postgresql://localhost:5432/witus_triage_agent
#      GEMINI_API_KEY=...        (testing — or ANTHROPIC_API_KEY for production)

# 4. Create the tables
npm run db:migrate

# 5. Seed the 25 hand-labeled fixture submissions
npm run db:seed

# 6. Run
npm run dev          # http://localhost:3000

npm test exercises the graph end to end (skipping live-LLM tests when no key is set). The PRD's target is clone-to-running in under 15 minutes. If it is slower for you, that is a real bug worth an issue.

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For operators (no code required)

If you just need to use the dashboard (review the queue, approve or reject), start with the operator guide, written in plain language with no setup steps:

• In the running app: /help (linked from the menu and footer; reachable without signing in).
• As markdown: docs/operator-guide/: getting started, the queue, reading a run, approving/rejecting, what the categories mean, and an FAQ.

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