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Chat agent to HTTP API to safely, quickly and stably add, view, edit or remove data in tables, forms or charts together with A2UI.
AI generate UI once, API repeat everytime safely, quickly and stably.

Agent-to-API protocol and MVP demo: generate a simple task UI, tune an HTTP API request until it works, then let users change filters, sort, and paging from the UI — which directly calls HTTP API
without going through the LLM again, no more token cost.

No SQL execution path. Sensitive writes (default: delete) wait in the Admin approval queue; other writes auto-execute and leave an auto_approved audit record on the server.

• Node.js 18+
• Local APIJSONBoot-MultiDataSource (or compatible) at http://localhost:8080

cd ~/a2api
cp .env.example .env
npm install
npm test
npm run build
npm run dev

• Client (Vite): http://localhost:5173

• Admin (config approvals): npm run dev:admin → http://localhost:5174

  • Tables Apply + Call: run apps/admin/sql/sys_Apply.sql and sys_Call.sql, reload Access/Request. If Call logs say GET denied for LOGIN, run apps/admin/sql/patch_Call_access.sql (Access id 9003; 9002 is Apply).
  • Ordinary CRUD hits APIJSON HTTP directly; admin server only runs approve → Access/Request/Document/Chain
  • Admin tabs: Apply · Call logs · Stats

• API (Hono): http://localhost:3000

Open the client URL. Use Login (top-right) to open the account menu and set AI Model / Base URL / API Key (APIAuto-style). Try chips such as List the latest 3 moments with authors, then change sort/page and click Query / Refresh — the right panel shows usedLlm: false and the exact APIJSON body.

Curated chat examples live in conversations/; project Agent skills in .cursor/skills/.

Optional: set OPENAI_API_KEY in .env to refine bootstrap with an LLM. Without it, built-in intent rules for User / Moment / Comment still work (English and Chinese phrases).

Envelopes: { "version": "0.1", "<type>": { ... } }

• proposeRequest — candidate APIJSON call
• reviseRequest / decision — edit / approve|reject
• bindRequest — after code == 200, template + paramMap for UI-driven calls
• requestResult / status — outcomes

Read methods auto-execute. Non-sensitive post / put auto-execute with an audit row. Sensitive methods (default delete, override SENSITIVE_METHODS) wait for Admin Approve/Reject.

1. Bootstrap (chat / AI or rules) — generate UI + propose APIJSON → validate → execute until success → emit bindRequest
2. Steady-state (no LLM) — filter/sort/page → BoundExecutor merges paramMap into bodyTemplate → POST {baseUrl}/{method}

Top tabs:

• UI — chat bootstrap + bound table/detail/charts
• Data — APIAuto-style HTTP debugger
• Admin — sensitive approval queue + audit trail (auto_approved / approved / rejected)

Also:

• Embed APIAuto — iframe http://localhost:8080/api/index.html?send=true&type=JSON&url=...&json=... (share-link auto fill + send)
• Open APIAuto in new window — same share URL in a new tab

Agent / console automation:

a2apiAgent.switchTab("data")
a2apiAgent.debug({
  url: "http://localhost:8080/get",
  json: { User: { id: 38710 } },
  send: true,          // builtin send
  // useApiAuto: true, // or load iframe + auto send
})

export APIJSON_BASE_URL=http://localhost:8080
# or edit .env

Ensure the Demo schema (User / Moment / Comment) is available on that server.

Writes (POST/PUT/DELETE): the Demo often requires a logged-in session (@role OWNER/LOGIN). The MVP still generates the request and shows the HITL Approve/Reject UI; if APIJSON returns "not logged in", log in via your Demo/APIAuto session cookies or relax Access for local testing. Reads work out of the box against the public Demo data.

npm test          # protocol + runtime unit tests
npm run build     # compile packages + demo
npm run dev       # API :3000 + Vite :5173
npm run typecheck

Versioned snapshots (reuse / auto-adjust / manual-adjust), local-first store, cross-device sync via APIJSON tables or file import/export — see the design plan.