feat(chat): file attachments as chips, CoT closed, AI add-to-inventory

Chat fixes (#1/#6/#7):
- chat-input passes raw File[] up instead of inlining file text
- chat-panel sends files as FileUIPart and renders them with the
  ai-elements Attachments component (no more raw text dumps)
- backend extracts text-like file content for the model in routes/chat
- Chain-of-Thought now defaults to collapsed
- file upload works regardless of whether the input has text

AI add-to-inventory (#2):
- new proposeInventory tool (validates items, streams an approval card)
- system prompt distinguishes stocking inventory vs. billing a patient
- ActionPreviewCard commits inventory via POST /api/inventory

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
This commit is contained in:
Khalid Abdi
2026-06-15 18:27:43 +03:00
parent 3aa699aefe
commit 6e5598262e
7 changed files with 235 additions and 51 deletions
+51 -2
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@@ -33,6 +33,50 @@ export const chatRouter = Router();
chatRouter.use(requireAuth, requireOrg, requirePermission({ patient: ["read"] }));
// Text-like uploads (CSV/JSON/TXT/…) the model should read as parseable text
// rather than an opaque data URL. Images/PDFs are left as file parts so
// vision-capable providers read them directly.
const TEXT_LIKE_MEDIA = /^(text\/|application\/(json|xml|csv|x-ndjson))/i;
const TEXT_LIKE_EXT = /\.(csv|tsv|json|txt|md|xml|ndjson|tab)$/i;
function decodeDataUrl(url: string): string {
const comma = url.indexOf(",");
if (comma === -1) return "";
const meta = url.slice(0, comma);
const data = url.slice(comma + 1);
return meta.includes("base64")
? Buffer.from(data, "base64").toString("utf8")
: decodeURIComponent(data);
}
// Replace text-like file parts with a text part carrying the file's content
// (capped) so the agent can parse uploads (e.g. a medications list to add to
// inventory, or a database export to import). Display/storage are unaffected —
// this only shapes what the model sees.
function inlineTextFiles(messages: UIMessage[]): UIMessage[] {
return messages.map((message) => {
if (!Array.isArray(message.parts)) return message;
const parts = message.parts.flatMap((part) => {
if (
part.type === "file" &&
typeof part.url === "string" &&
(TEXT_LIKE_MEDIA.test(part.mediaType ?? "") ||
TEXT_LIKE_EXT.test(part.filename ?? ""))
) {
const content = decodeDataUrl(part.url).slice(0, 200_000);
return [
{
type: "text" as const,
text: `--- File: ${part.filename ?? "file"} ---\n${content}`,
},
];
}
return [part];
});
return { ...message, parts } as UIMessage;
});
}
function systemPrompt(veilActive: boolean, providerLabel: string): string {
return [
"You are temetro, a clinical assistant that helps clinicians retrieve,",
@@ -55,10 +99,15 @@ function systemPrompt(veilActive: boolean, providerLabel: string): string {
" asks to add/book/create one. They show an approval card; the record is only",
" written after the clinician clicks Add. NEVER say you added/booked/created",
" something — say you've drafted it for their approval.",
"- proposeInventory: when the clinician wants to ADD STOCK to the clinic's",
" inventory — e.g. they upload a list of medications/supplies with quantities",
" (and optionally prices) to stock. Parse it into items {name, form, strength,",
" unit, stockQuantity, reorderThreshold, expiresAt} and call proposeInventory.",
"- proposeInvoice: when the clinician wants to bill someone — e.g. they upload",
" a list of purchased medications/items. Parse it into line items",
" {description, quantity, unitPrice} (use the prices in the document) and call",
" proposeInvoice with the patient/client name.",
" proposeInvoice with the patient/client name. (Stocking inventory vs. billing a",
" patient are different — pick proposeInventory for the former.)",
"- previewImport: when the clinician wants to import/migrate an existing",
" patient database file, or add a single patient. Parse the uploaded content",
" into our patient shape and call previewImport.",
@@ -113,7 +162,7 @@ chatRouter.post("/", async (req, res, next) => {
},
};
const modelMessages = await convertToModelMessages(messages);
const modelMessages = await convertToModelMessages(inlineTextFiles(messages));
const system = systemPrompt(veil.active, resolved.providerLabel);
const stream = createUIMessageStream({
+72
View File
@@ -8,6 +8,7 @@ import { db } from "../../db/index.js";
import { organization } from "../../db/schema/auth.js";
import { appointmentInputSchema } from "../../lib/appointment-validation.js";
import { initialsFromName } from "../../lib/initials.js";
import { inventoryInputSchema } from "../../lib/inventory-validation.js";
import { invoiceInputSchema } from "../../lib/invoice-validation.js";
import { patientInputSchema } from "../../lib/patient-validation.js";
import { prescriptionInputSchema } from "../../lib/prescription-validation.js";
@@ -474,6 +475,77 @@ export function createChatTools(ctx: ToolContext) {
},
}),
proposeInventory: tool({
description:
"Propose adding one or more items to the clinic's inventory (medications/supplies) for the clinician to approve — e.g. parse an uploaded stock or purchase list into stock items. Does NOT save; it shows an approval card the clinician confirms. Each item needs a name; form/strength/unit/stockQuantity/reorderThreshold/location/expiresAt (YYYY-MM-DD)/notes are optional. Use this for STOCKING inventory; use proposeInvoice instead when billing a patient for purchased items.",
inputSchema: z.object({
items: z
.array(
z.object({
name: z.string().describe("Item / medication name"),
form: z
.string()
.optional()
.describe("Dosage form, e.g. Tablet, Capsule, Syrup"),
strength: z.string().optional().describe("e.g. 500mg"),
unit: z
.string()
.optional()
.describe("Dispensing unit, e.g. box, bottle"),
stockQuantity: z
.number()
.optional()
.describe("Units currently in stock"),
reorderThreshold: z
.number()
.optional()
.describe("Low-stock reorder level"),
location: z.string().optional().describe("Storage location"),
expiresAt: z
.string()
.nullish()
.describe("Expiry date, YYYY-MM-DD"),
notes: z.string().nullish(),
}),
)
.describe("Inventory items to add (prices/quantities from the document)"),
}),
execute: async ({ items }) => {
step(`Drafting ${items.length} inventory item(s)`);
// Inventory is non-PHI — no Veil resolution needed.
const validated: unknown[] = [];
const issues: string[] = [];
items.forEach((item, index) => {
const parsed = inventoryInputSchema.safeParse(item);
if (parsed.success) {
validated.push(parsed.data);
} else {
issues.push(
...parsed.error.issues.map(
(i) =>
`item ${index + 1} ${i.path.join(".") || "(root)"}: ${i.message}`,
),
);
}
});
writer.write({
type: "data-actionPreview",
data: {
token: `inventory-${stepSeq}`,
kind: "inventory" as const,
record: { items: validated.length ? validated : items },
issues,
},
});
return {
ok: issues.length === 0,
count: validated.length,
issues,
note: "Preview only — awaiting clinician approval before any write.",
};
},
}),
proposeInvoice: tool({
description:
"Propose a new invoice for the clinician to approve — e.g. parse an uploaded list of purchased medications into billable line items. Does NOT save; it shows an approval card the clinician confirms. Provide the patient/client name (a file number if known) and line items {description, quantity, unitPrice}; prices come from the uploaded document.",
@@ -2,6 +2,7 @@
import {
AlertTriangle,
Boxes,
CalendarPlus,
Check,
ClipboardList,
@@ -22,6 +23,7 @@ import {
type InvoiceInput,
type InvoiceLineItem,
} from "@/lib/invoices";
import { type InventoryInput, createInventory } from "@/lib/inventory";
import { type PrescriptionInput, createPrescription } from "@/lib/prescriptions";
import { type TaskInput, createTask } from "@/lib/tasks";
import { notify } from "@/lib/toast";
@@ -33,6 +35,7 @@ export const ACTION_ICONS = {
task: ClipboardList,
prescription: Pill,
invoice: Receipt,
inventory: Boxes,
} as const;
const ICONS = ACTION_ICONS;
@@ -61,6 +64,18 @@ export function summarize(data: ActionPreviewData): string[] {
`${items.length} item${items.length === 1 ? "" : "s"} · ${formatMoney(total)}`,
].filter(Boolean);
}
if (data.kind === "inventory") {
const items = (r.items as InventoryInput[] | undefined) ?? [];
return [
`${items.length} item${items.length === 1 ? "" : "s"}`,
items
.map((it) =>
[it.name, it.strength].filter(Boolean).join(" ") +
(it.stockQuantity ? ` ×${it.stockQuantity}` : ""),
)
.join(", "),
].filter(Boolean);
}
// prescription
return [
[r.medication, r.dose].filter(Boolean).join(" "),
@@ -81,6 +96,12 @@ export async function commitAction(data: ActionPreviewData): Promise<void> {
await createTask(data.record as TaskInput);
} else if (data.kind === "invoice") {
await createInvoice({ ...(data.record as InvoiceInput), source: "ai" });
} else if (data.kind === "inventory") {
const { items = [] } = data.record as { items?: InventoryInput[] };
// Commit each proposed stock item via the RBAC-gated create endpoint.
for (const item of items) {
await createInventory(item);
}
} else {
await createPrescription({
...(data.record as PrescriptionInput),
+7 -27
View File
@@ -17,7 +17,7 @@ import type { Effort } from "@/lib/ai-models";
import { cn } from "@/lib/utils";
type ChatInputProps = {
onSubmit: (text: string) => void;
onSubmit: (text: string, files: File[]) => void;
status: ChatStatus;
onStop?: () => void;
model: string;
@@ -55,36 +55,16 @@ export function ChatInput({
const canSend =
(value.trim().length > 0 || files.length > 0) && !isGenerating;
const submit = useCallback(async () => {
const submit = useCallback(() => {
const trimmed = value.trim();
// Allow submitting while generating — the panel queues it (Claude-style).
if (!trimmed && files.length === 0) {
return;
}
const parts: string[] = [];
if (trimmed) {
parts.push(trimmed);
}
// Include the text of attached files so the agent can parse them (e.g. a
// database export to import). Read text-like files; cap each so a huge file
// can't blow the context. Binary files are referenced by name only.
for (const file of files) {
const textLike =
/\.(csv|tsv|json|txt|md|xml|ndjson|tab)$/i.test(file.name) ||
file.type.startsWith("text/") ||
file.type === "application/json";
if (textLike) {
try {
const content = (await file.text()).slice(0, 200_000);
parts.push(`--- File: ${file.name} ---\n${content}`);
} catch {
parts.push(`[Attached: ${file.name}]`);
}
} else {
parts.push(`[Attached: ${file.name}]`);
}
}
onSubmit(parts.join("\n\n"));
// Hand the raw files to the panel; it sends them as proper attachment parts
// (rendered as chips, not raw inlined text) and the backend extracts any
// text-like content for the model.
onSubmit(trimmed, files);
setValue("");
setFiles([]);
}, [value, files, onSubmit]);
@@ -234,7 +214,7 @@ export function ChatInput({
<PatientFormDialog
key={addKey}
mode="create"
onCreated={(fileNumber) => onSubmit(`/patient ${fileNumber}`)}
onCreated={(fileNumber) => onSubmit(`/patient ${fileNumber}`, [])}
onOpenChange={setAddOpen}
open={addOpen}
/>
+75 -18
View File
@@ -1,13 +1,23 @@
"use client";
import { useChat } from "@ai-sdk/react";
import { DefaultChatTransport, type ToolUIPart } from "ai";
import {
DefaultChatTransport,
type FileUIPart,
type ToolUIPart,
} from "ai";
import { AlertTriangle, Brain, ChevronDown, ShieldCheck, X } from "lucide-react";
import { nanoid } from "nanoid";
import { useSearchParams } from "next/navigation";
import { useCallback, useEffect, useMemo, useRef, useState } from "react";
import { useTranslation } from "react-i18next";
import {
Attachment,
AttachmentInfo,
AttachmentPreview,
Attachments,
} from "@/components/ai-elements/attachments";
import {
ChainOfThought,
ChainOfThoughtContent,
@@ -83,6 +93,23 @@ import { getPatient } from "@/lib/patients";
// pulls records instantly without the LLM (also works offline).
const PATIENT_COMMAND = /^\/(?:patient\s+)?(\d+)$/i;
// Read a File into a FileUIPart (data URL). The backend extracts text-like
// content for the model; images/PDFs are read directly by vision providers.
function fileToPart(file: File): Promise<FileUIPart> {
return new Promise((resolve, reject) => {
const reader = new FileReader();
reader.onload = () =>
resolve({
type: "file",
mediaType: file.type || "application/octet-stream",
filename: file.name,
url: reader.result as string,
});
reader.onerror = () => reject(reader.error);
reader.readAsDataURL(file);
});
}
export function ChatPanel() {
const { t } = useTranslation();
const [model, setModel] = useState<string>(DEFAULT_MODEL_ID);
@@ -92,11 +119,14 @@ export function ChatPanel() {
// per session before the first such send — inline (no modal). `pendingConsent`
// holds the message text waiting on that one-time approval.
const [consented, setConsented] = useState(false);
const [pendingConsent, setPendingConsent] = useState<string | null>(null);
const [pendingConsent, setPendingConsent] = useState<{
text: string;
files: File[];
} | null>(null);
// Claude-style message queue: messages submitted while the assistant is busy
// (or waiting on the Veil gate) wait here and auto-send when it goes idle.
const [queued, setQueued] = useState<string[]>([]);
const [queued, setQueued] = useState<{ text: string; files: File[] }[]>([]);
// Persisted conversation: a client-owned thread id (a fresh one per new chat),
// saved to the server after each exchange so history survives reloads.
@@ -151,9 +181,10 @@ export function ChatPanel() {
// Run the LLM agent for a message (after any Veil gate) on a given model.
const runAgentWith = useCallback(
(text: string, modelId: string) => {
async (text: string, modelId: string, files: File[] = []) => {
const fileParts = await Promise.all(files.map(fileToPart));
sendMessage(
{ text },
{ text, files: fileParts },
{ body: { model: modelId, effort, threadId: threadIdRef.current } },
);
},
@@ -161,13 +192,13 @@ export function ChatPanel() {
);
const send = useCallback(
async (text: string) => {
async (text: string, files: File[] = []) => {
const trimmed = text.trim();
if (!trimmed) return;
if (!trimmed && files.length === 0) return;
// Busy or awaiting the Veil gate → queue and auto-send when idle.
if (status === "submitted" || status === "streaming" || pendingConsent) {
setQueued((q) => [...q, trimmed]);
setQueued((q) => [...q, { text: trimmed, files }]);
return;
}
@@ -206,10 +237,10 @@ export function ChatPanel() {
// Cloud model → inline Veil consent once before sending externally.
if (isCloudModel && !consented) {
setPendingConsent(trimmed);
setPendingConsent({ text: trimmed, files });
return;
}
runAgentWith(trimmed, model);
void runAgentWith(trimmed, model, files);
},
[
consented,
@@ -228,22 +259,22 @@ export function ChatPanel() {
if (status !== "ready" || pendingConsent || queued.length === 0) return;
const [next, ...rest] = queued;
setQueued(rest);
if (next) void send(next);
if (next) void send(next.text, next.files);
}, [status, pendingConsent, queued, send]);
// Veil gate actions.
const confirmConsent = useCallback(() => {
setConsented(true);
const text = pendingConsent;
const pending = pendingConsent;
setPendingConsent(null);
if (text) runAgentWith(text, model);
if (pending) void runAgentWith(pending.text, model, pending.files);
}, [pendingConsent, runAgentWith, model]);
const useLocalInstead = useCallback(() => {
setModel("ollama");
const text = pendingConsent;
const pending = pendingConsent;
setPendingConsent(null);
if (text) runAgentWith(text, "ollama");
if (pending) void runAgentWith(pending.text, "ollama", pending.files);
}, [pendingConsent, runAgentWith]);
const cancelConsent = useCallback(() => setPendingConsent(null), []);
@@ -381,10 +412,13 @@ export function ChatPanel() {
</span>
<QueueList>
{queued.map((q, i) => (
<QueueItem key={`${i}-${q}`}>
<QueueItem key={`${i}-${q.text}`}>
<div className="flex items-center gap-2">
<QueueItemIndicator />
<QueueItemContent>{q}</QueueItemContent>
<QueueItemContent>
{q.text ||
t("chat.queue.attachmentsOnly", { count: q.files.length })}
</QueueItemContent>
<QueueItemActions>
<QueueItemAction
aria-label={t("chat.queue.remove")}
@@ -415,13 +449,16 @@ export function ChatPanel() {
const firstActionPreviewIdx = message.parts.findIndex(
(p) => p.type === "data-actionPreview",
);
// Attachments the clinician uploaded — rendered once as a chip group.
const fileParts = message.parts.filter((p) => p.type === "file");
const firstFileIdx = message.parts.findIndex((p) => p.type === "file");
return (
<Message from={message.role} key={message.id}>
<MessageContent className="w-full">
{steps.length > 0 ? (
<ChainOfThought
className="mb-1"
defaultOpen={isLast && isWorking}
defaultOpen={false}
key={`${message.id}-cot`}
>
<ChainOfThoughtHeader>{t("chat.steps")}</ChainOfThoughtHeader>
@@ -478,6 +515,26 @@ export function ChatPanel() {
<MessageResponse key={key}>{part.text}</MessageResponse>
);
}
if (part.type === "file") {
// Render the whole message's files as one chip group, once.
if (i !== firstFileIdx) return null;
return (
<Attachments className="w-full" key={key} variant="inline">
{fileParts.map((fp, fi) => (
<Attachment
data={{
...(fp as FileUIPart),
id: `${message.id}-file-${fi}`,
}}
key={`${message.id}-file-${fi}`}
>
<AttachmentPreview />
<AttachmentInfo />
</Attachment>
))}
</Attachments>
);
}
if (part.type === "data-patientCard") {
return (
<PatientResult
+2 -1
View File
@@ -56,7 +56,8 @@ export type ActionPreviewKind =
| "appointment"
| "task"
| "prescription"
| "invoice";
| "invoice"
| "inventory";
export type ActionPreviewData = {
token: string;
kind: ActionPreviewKind;
@@ -795,7 +795,8 @@
},
"queue": {
"label": "Queued · {{count}}",
"remove": "Remove from queue"
"remove": "Remove from queue",
"attachmentsOnly": "{{count}} attachment(s)"
},
"veil": {
"title": "Veil",
@@ -810,14 +811,17 @@
"appointment": "Proposed appointment",
"task": "Proposed task",
"prescription": "Proposed prescription",
"invoice": "Proposed invoice"
"invoice": "Proposed invoice",
"inventory": "Proposed inventory"
},
"kind": {
"appointment": "Appointment added.",
"task": "Task added.",
"prescription": "Prescription added.",
"invoice": "Invoice added."
"invoice": "Invoice added.",
"inventory": "Inventory updated."
},
"inventoryItems": "{{count}} item(s)",
"approve": "Add",
"adding": "Adding…",
"discard": "Discard",