Files
arcadia-admin/app/routes/ai.tsx
jules 9cbe921db7 ai: rich-output blocks via lazy-fetched typed-fence protocol
Assistant replies can now emit typed fenced blocks that render as
@crema/*-ui components inline at their position in the reply.

- message-body.tsx: segmented rendering — alternating prose chunks and
  block dispatch (was: all blocks appended at end). Renderers for kpi,
  table, chart-bar/-line/-donut/-spark, code, diff, flowchart, orgchart,
  steps, checklist, welcome, hint, plus the legacy card kinds.
- block-schemas.ts: single source of truth — BLOCK_INDEX (one-line
  purpose per kind, always in prompt) + SCHEMAS (full JSON shape +
  example, fetched on demand).
- admin-tools.ts: new get_block_schema(kind) tool the model calls once
  per kind per thread to fetch the exact schema. Keeps the always-on
  prompt small (~110 tokens vs ~400 inline).
- assistant.tsx: replaces the inline schema dump with the generated
  thin index.
- ai.tsx: empty-state preview button injects a synthetic assistant
  message exercising every block, for renderer/theme smoke-testing.
- console.css + ai.tsx: shrink ATLAS headline so it doesn't slip under
  the composer with the added preview button.
- tsconfig.json + app.css: wire lib-data-ui, lib-code-ui, lib-diagram-ui,
  lib-onboarding-ui as siblings.

Adding a new block kind = add the lib paths, add a renderer case, add
a schema entry. No prompt edits required.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-02 22:47:36 +10:00

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import {
useCallback,
useEffect,
useMemo,
useRef,
useState,
} from "react"
import { createPortal } from "react-dom"
import {
Archive,
ArrowRight,
BookmarkPlus,
ChevronDown,
Command as CommandIcon,
Copy,
Download,
FileText,
Loader2,
Mic,
MicOff,
Plus,
RefreshCw,
RotateCcw,
Sparkles,
Square,
Trash2,
Undo2,
X,
} from "lucide-react"
import {
LLMProvider,
MockLLM,
listModels,
useChat,
useCompletion,
type LLMAdapter,
} from "@crema/llm-ui"
import {
buildAdapter,
getProvider,
useSettings as useProviderSettings,
} from "@crema/llm-providers-ui"
import { TypingIndicator } from "@crema/chat-ui"
import { useToast } from "@crema/notification-ui"
import { AppShell } from "~/components/layout/app-shell"
import { MessageBody } from "~/components/assistant/message-body"
import { Button } from "~/components/ui/button"
import {
DropdownMenu,
DropdownMenuContent,
DropdownMenuItem,
DropdownMenuTrigger,
} from "~/components/ui/dropdown-menu"
import {
Popover,
PopoverContent,
PopoverTrigger,
} from "~/components/ui/popover"
import {
loadActiveAgentId,
saveActiveAgentId,
useAgents,
type Agent,
} from "~/lib/agents"
import { addLibraryItem } from "~/lib/library"
import { Avatar, AvatarFallback } from "~/components/ui/avatar"
import { pageTitle } from "~/lib/page-meta"
import { useArcadiaClient } from "@crema/arcadia-client"
import type { Message as LLMMessage, ToolCall } from "@crema/llm-ui"
import type { DocHit } from "~/lib/docs-search"
import {
AgentAvatar,
ToolCallCard,
type ToolCall as AgentToolCall,
type ToolCallStatus,
} from "@crema/agent-ui"
import {
buildDenialMessages,
classifyCalls,
getOpenAITools,
runLLMToolCalls,
} from "~/lib/admin-tools"
import { ARCADIA_KNOWLEDGE } from "~/lib/arcadia-knowledge"
import {
loadActiveReasoning,
saveActiveReasoning,
subscribeActiveReasoning,
type ReasoningEffort,
} from "~/lib/arcadia/llm-configs"
import { formatAdminContextForPrompt } from "~/lib/admin-context"
import { ConfirmCard } from "~/components/assistant/confirm-card"
import { renderToolResult } from "~/components/assistant/tool-result-renderers"
function ToolResultBlock({ name, result }: { name: string; result: unknown }) {
const rich = renderToolResult(name, result)
if (!rich) return null
return <div className="px-1">{rich}</div>
}
// Synthetic assistant message that exercises every typed rich-output block.
// Wired to the "preview rich-output blocks" button in the empty state — used
// to eyeball renderer + theme without driving a live model. Safe to delete
// once Phase 2 has been validated end-to-end.
const BLOCK_SAMPLES_CONTENT = `Here's one example of every rich-output block, in roughly the order a model would emit them.
A **kpi** strip for headline numbers:
\`\`\`kpi
{ "items": [
{ "label": "Tenants", "value": 42 },
{ "label": "Active users", "value": 318, "unit": "/day" },
{ "label": "Suspended", "value": 4 },
{ "label": "Storage", "value": "1.2", "unit": "TB" }
] }
\`\`\`
A **table** for tabular data:
\`\`\`table
{ "columns": [
{ "id": "slug", "header": "Tenant" },
{ "id": "users", "header": "Users", "align": "right" },
{ "id": "status", "header": "Status" }
],
"rows": [
{ "slug": "acme", "users": 42, "status": "active" },
{ "slug": "globex", "users": 18, "status": "suspended" },
{ "slug": "initech", "users": 73, "status": "active" }
],
"idKey": "slug" }
\`\`\`
A **chart-bar** for category comparison and a **chart-line** for a trend:
\`\`\`chart-bar
{ "title": "Users by tenant",
"data": [
{ "label": "acme", "value": 42 },
{ "label": "globex", "value": 18 },
{ "label": "initech", "value": 73 },
{ "label": "umbrella", "value": 11 }
] }
\`\`\`
\`\`\`chart-line
{ "title": "Signups over time",
"series": [
{ "x": 1, "y": 12 }, { "x": 2, "y": 19 }, { "x": 3, "y": 24 },
{ "x": 4, "y": 31 }, { "x": 5, "y": 28 }, { "x": 6, "y": 42 }
] }
\`\`\`
A **chart-donut** for part-to-whole and a **chart-spark** inline:
\`\`\`chart-donut
{ "title": "Status breakdown",
"data": [
{ "label": "active", "value": 38 },
{ "label": "suspended", "value": 4 },
{ "label": "deactivated", "value": 2 }
] }
\`\`\`
\`\`\`chart-spark
{ "values": [3, 5, 4, 8, 12, 9, 14, 11, 18, 16, 22] }
\`\`\`
A **code** block and a **diff**:
\`\`\`code
{ "code": "SELECT slug, count(*) AS users\\nFROM tenants t\\nJOIN users u ON u.tenant_id = t.id\\nWHERE t.status = 'active'\\nGROUP BY slug\\nORDER BY users DESC;",
"language": "sql",
"title": "Active tenants by user count",
"lineNumbers": true }
\`\`\`
\`\`\`diff
{ "oldCode": "max_users: 100\\nplan: free\\n",
"newCode": "max_users: 250\\nplan: pro\\n",
"language": "yaml",
"title": "Tenant quota change",
"mode": "unified" }
\`\`\`
A **flowchart** for control flow and an **orgchart** for hierarchy:
\`\`\`flowchart
{ "nodes": [
{ "id": "a", "type": "start", "label": "Receive request", "x": 80, "y": 20 },
{ "id": "b", "type": "process", "label": "Validate token", "x": 80, "y": 110 },
{ "id": "c", "type": "decision", "label": "Token valid?", "x": 80, "y": 200 },
{ "id": "d", "type": "process", "label": "Process", "x": 260, "y": 200 },
{ "id": "e", "type": "end", "label": "Reject (401)", "x": 80, "y": 310 }
],
"edges": [
{ "from": "a", "to": "b" },
{ "from": "b", "to": "c" },
{ "from": "c", "to": "d", "label": "yes" },
{ "from": "c", "to": "e", "label": "no" }
] }
\`\`\`
\`\`\`orgchart
{ "data": {
"id": "root", "name": "Platform", "title": "Tenant",
"children": [
{ "id": "a", "name": "Auth", "title": "Service",
"children": [
{ "id": "a1", "name": "Sessions", "title": "Module" },
{ "id": "a2", "name": "MFA", "title": "Module" }
] },
{ "id": "b", "name": "Billing", "title": "Service",
"children": [
{ "id": "b1", "name": "Invoices", "title": "Module" }
] }
] } }
\`\`\`
A **steps** trail for a multi-step plan:
\`\`\`steps
{ "steps": [
{ "id": "1", "title": "List tenants", "status": "done", "detail": "Found 42 tenants" },
{ "id": "2", "title": "Filter suspended", "status": "running" },
{ "id": "3", "title": "Build report", "status": "queued" },
{ "id": "4", "title": "Email summary", "status": "queued" }
] }
\`\`\`
A **welcome** hero, a **checklist**, and a **hint**:
\`\`\`welcome
{ "title": "Welcome to Arcadia Admin",
"description": "Manage tenants, users, and platform settings from one place.",
"badge": "v2",
"primaryAction": { "label": "Create your first tenant", "href": "/tenants" },
"secondaryAction": { "label": "Read the docs", "href": "/library" } }
\`\`\`
\`\`\`checklist
{ "title": "Get started",
"description": "Finish setting up your tenant.",
"tasks": [
{ "id": "1", "title": "Invite your team", "description": "Add at least one admin.", "completed": true, "estimate": "2 min" },
{ "id": "2", "title": "Connect a storage bucket", "completed": false, "href": "/buckets", "estimate": "5 min" },
{ "id": "3", "title": "Set up SSO", "completed": false, "optional": true, "href": "/sso", "estimate": "10 min" }
] }
\`\`\`
\`\`\`hint
{ "title": "Tip", "tone": "info", "body": "Suspending a tenant blocks login but preserves data — use deactivate to permanently disable.", "action": { "label": "See suspension docs", "href": "/library?q=suspend" } }
\`\`\`
And the legacy **card** kinds — pill, stat, callout:
\`\`\`card
{ "kind": "pill", "status": "active", "label": "active" }
\`\`\`
\`\`\`card
{ "kind": "stat", "label": "MRR", "value": "$12.4k" }
\`\`\`
\`\`\`card
{ "kind": "callout", "tone": "warning", "title": "Heads up", "body": "Suspending a tenant blocks all of its users immediately." }
\`\`\`
Clear the conversation to dismiss the preview.`
const SNAPSHOT_KEY = "crema.ai.snapshot"
// Separate key for the live conversation that survives navigation. The
// compact snapshot is reserved for the user-triggered Compact/Restore flow.
const LIVE_KEY = "crema.ai.live"
function loadLive(): LLMMessage[] | null {
if (typeof window === "undefined") return null
try {
const raw = localStorage.getItem(LIVE_KEY)
if (!raw) return null
const parsed = JSON.parse(raw)
if (Array.isArray(parsed)) return parsed as LLMMessage[]
} catch {}
return null
}
function saveLive(msgs: LLMMessage[]) {
if (typeof window === "undefined") return
if (msgs.length === 0) {
localStorage.removeItem(LIVE_KEY)
return
}
try {
localStorage.setItem(LIVE_KEY, JSON.stringify(msgs))
} catch {
// Quota exceeded or similar — silently drop persistence.
}
}
/* Per-message agent attribution + the set of agents that have produced
* turns in the current conversation. Persisted alongside LIVE_KEY so a
* reload mid-thread preserves both who-said-what and the hand-off note
* the next turn carries.
*
* Stored as plain JSON shapes (Maps don't serialize):
* AGENTS_KEY: Array<[agentId, Agent]> ← agentHistory
* MSG_AGENTS_KEY: Array<[index, Agent]> ← messageAgents
*/
const AGENTS_KEY = "crema.ai.agent-history"
const MSG_AGENTS_KEY = "crema.ai.message-agents"
function loadAgentHistory(): Map<string, Agent> {
if (typeof window === "undefined") return new Map()
try {
const raw = localStorage.getItem(AGENTS_KEY)
if (!raw) return new Map()
const parsed = JSON.parse(raw)
if (Array.isArray(parsed)) return new Map(parsed as [string, Agent][])
} catch {}
return new Map()
}
function saveAgentHistory(m: Map<string, Agent>) {
if (typeof window === "undefined") return
if (m.size === 0) {
localStorage.removeItem(AGENTS_KEY)
return
}
try {
localStorage.setItem(AGENTS_KEY, JSON.stringify([...m.entries()]))
} catch {}
}
function loadMessageAgents(): Map<number, Agent> {
if (typeof window === "undefined") return new Map()
try {
const raw = localStorage.getItem(MSG_AGENTS_KEY)
if (!raw) return new Map()
const parsed = JSON.parse(raw)
if (Array.isArray(parsed)) return new Map(parsed as [number, Agent][])
} catch {}
return new Map()
}
function saveMessageAgents(m: Map<number, Agent>) {
if (typeof window === "undefined") return
if (m.size === 0) {
localStorage.removeItem(MSG_AGENTS_KEY)
return
}
try {
localStorage.setItem(MSG_AGENTS_KEY, JSON.stringify([...m.entries()]))
} catch {}
}
function clearAgentMaps() {
if (typeof window === "undefined") return
localStorage.removeItem(AGENTS_KEY)
localStorage.removeItem(MSG_AGENTS_KEY)
}
function clearLive() {
if (typeof window === "undefined") return
localStorage.removeItem(LIVE_KEY)
}
/* Per-conversation reasoning override. Cycle order matters — the composer
* chip walks this array. Storage helpers (load/save/subscribe) live in
* lib/arcadia/llm-configs.ts so the settings panel and the /ai composer
* coordinate via the same crema.ai.reasoning key. */
const REASONING_LEVELS: ReasoningEffort[] = ["off", "low", "medium", "high", "max"]
function withReasoning<T extends Record<string, unknown>>(
extras: T,
effort: ReasoningEffort,
): T & { reasoning_effort?: string } {
if (effort === "off") return extras
return { ...extras, reasoning_effort: effort }
}
type StoredMessage = { role: "user" | "assistant"; content: string }
function loadAISnapshot(): StoredMessage[] | null {
if (typeof window === "undefined") return null
try {
const raw = localStorage.getItem(SNAPSHOT_KEY)
if (!raw) return null
const parsed = JSON.parse(raw)
if (Array.isArray(parsed)) return parsed as StoredMessage[]
} catch {}
return null
}
function saveAISnapshot(msgs: StoredMessage[]) {
if (typeof window === "undefined") return
localStorage.setItem(SNAPSHOT_KEY, JSON.stringify(msgs))
}
function clearAISnapshot() {
if (typeof window === "undefined") return
localStorage.removeItem(SNAPSHOT_KEY)
}
export const meta = () => pageTitle("AI")
const MODEL_KEY = "crema.ai.model"
const PROBE_TIMEOUT_MS = 3000
type Status =
| { kind: "probing" }
| { kind: "live"; models: string[] }
| { kind: "mock"; reason: string }
const mockAdapter = new MockLLM({
label: "Mock",
delayMs: 18,
fallback:
"I'm a stand-in for the local model. Start LM Studio at localhost:1234 and reload to swap me out.",
responses: [],
})
function withTimeout<T>(p: Promise<T>, ms: number, signal: AbortSignal) {
return new Promise<T>((resolve, reject) => {
const t = setTimeout(() => reject(new Error("timeout")), ms)
signal.addEventListener("abort", () => {
clearTimeout(t)
reject(new DOMException("Aborted", "AbortError"))
})
p.then(
(v) => {
clearTimeout(t)
resolve(v)
},
(e) => {
clearTimeout(t)
reject(e)
},
)
})
}
export default function AIRoute() {
const settings = useProviderSettings()
const arcadia = useArcadiaClient()
const provider = getProvider(settings.providerId)
const agents = useAgents()
const [status, setStatus] = useState<Status>({ kind: "probing" })
const [model, setModel] = useState<string>(() => {
if (typeof window === "undefined") return ""
return localStorage.getItem(MODEL_KEY) ?? ""
})
const [adapter, setAdapter] = useState<LLMAdapter>(mockAdapter)
const [activeAgentId, setActiveAgentIdState] = useState<string>(() =>
loadActiveAgentId(),
)
const setActiveAgentId = useCallback((id: string) => {
saveActiveAgentId(id)
setActiveAgentIdState(id)
}, [])
const activeAgent =
agents.find((a) => a.id === activeAgentId) ?? agents[0]
// When the user changes provider/model in Settings, follow along.
useEffect(() => {
if (settings.model) setModel(settings.model)
}, [settings.providerId, settings.model])
// Resolve the API key from the vault (direct mode) or build the proxy
// adapter (proxy mode), then refresh the model list.
const probe = useCallback(() => {
const ac = new AbortController()
setStatus({ kind: "probing" })
const resolveSecret = async (name: string): Promise<string> => {
const res = await arcadia.GET<{ data: { value: string } }>(
`/api/v1/secrets/${encodeURIComponent(name)}`,
)
return res.data.value
}
const arcadiaBaseURL =
(import.meta.env.VITE_ARCADIA_URL as string | undefined) ?? "http://localhost:4000"
const arcadiaTenantId =
(import.meta.env.VITE_ARCADIA_TENANT as string | undefined) ?? "default"
const arcadiaAuthToken =
typeof window !== "undefined"
? sessionStorage.getItem("arcadia_access_token") ?? undefined
: undefined
;(async () => {
// Build the adapter first so chat works even if the model probe fails.
try {
const a = await buildAdapter({
settings,
resolveSecret,
arcadiaBaseURL,
arcadiaAuthToken,
arcadiaTenantId,
})
setAdapter(a)
} catch {
setAdapter(mockAdapter)
}
// Probe for a live model list. Anthropic has no /models endpoint, so
// fall back to the provider catalog's default models.
if (provider.transport === "anthropic") {
const ids = provider.defaultModels.length
? provider.defaultModels
: ["claude-opus-4-7"]
setStatus({ kind: "live", models: ids })
setModel((cur) => (cur && ids.includes(cur) ? cur : settings.model || ids[0]))
return
}
const baseURL = settings.baseURL || provider.baseURL
let apiKey: string | undefined
if (provider.requiresKey && settings.secretName) {
try {
apiKey = await resolveSecret(settings.secretName)
} catch {
// Fall through; listModels may still work for some providers without a key.
}
}
try {
const rows = await withTimeout(
listModels({ baseURL, apiKey, signal: ac.signal }),
PROBE_TIMEOUT_MS,
ac.signal,
)
const ids = rows.map((m) => m.id)
if (ids.length === 0) {
setStatus({ kind: "mock", reason: "endpoint returned no models" })
return
}
setStatus({ kind: "live", models: ids })
setModel((cur) => (cur && ids.includes(cur) ? cur : settings.model || ids[0]))
} catch {
// Probe failed but adapter may still be usable; show the catalog default
// models so the user can pick one and just try sending.
if (provider.defaultModels.length) {
setStatus({ kind: "live", models: provider.defaultModels })
setModel((cur) =>
cur && provider.defaultModels.includes(cur)
? cur
: settings.model || provider.defaultModels[0],
)
} else {
setStatus({ kind: "mock", reason: "endpoint unreachable" })
}
}
})()
return () => ac.abort()
// eslint-disable-next-line react-hooks/exhaustive-deps
}, [
arcadia,
settings.providerId,
settings.baseURL,
settings.secretName,
settings.mode,
settings.model,
provider.transport,
provider.baseURL,
provider.requiresKey,
])
useEffect(() => probe(), [probe])
useEffect(() => {
if (model) localStorage.setItem(MODEL_KEY, model)
}, [model])
const activeModel =
status.kind === "live" ? model || status.models[0] : "mock"
const availableModels = status.kind === "live" ? status.models : ["mock"]
return (
<AppShell title="AI">
<LLMProvider adapter={adapter} model={activeModel}>
{/* Console aesthetic is scoped to this wrapper only, so the appbar
* and sidebar keep using the global skyrise tokens (light/dark
* toggle still works for them). */}
<div
data-theme="console"
className="-m-6 flex h-full min-h-0 flex-col bg-[var(--console-ink)] text-[var(--console-text)]"
>
<ChatSurface
models={availableModels}
model={activeModel}
onModelChange={setModel}
agents={agents}
activeAgent={activeAgent}
onAgentChange={setActiveAgentId}
isMock={status.kind === "mock"}
onRetryProbe={probe}
/>
</div>
</LLMProvider>
</AppShell>
)
}
function ChatSurface({
models,
model,
onModelChange,
agents,
activeAgent,
onAgentChange,
isMock,
onRetryProbe,
}: {
models: string[]
model: string
onModelChange: (m: string) => void
agents: Agent[]
activeAgent: Agent | undefined
onAgentChange: (id: string) => void
isMock: boolean
onRetryProbe: () => void
}) {
const persona = activeAgent
? `Active persona: ${activeAgent.name}${activeAgent.role}\n${activeAgent.prompt}`
: ""
// Track every agent that has produced turns in the current conversation.
// When the operator switches mid-thread, we augment the system prompt so
// the new agent knows it's stepping into a transcript started by another
// persona — without that note it answers as if it produced every prior
// turn itself, which is jarring.
// Both maps are seeded from localStorage so a reload mid-thread keeps
// attribution + hand-off context intact. Persisted on every change via
// the effect lower down, cleared together with the live snapshot.
const [agentHistory, setAgentHistory] = useState<Map<string, Agent>>(
() => loadAgentHistory(),
)
const prevAgentRef = useRef<Agent | undefined>(activeAgent)
// Per-message agent attribution: which agent produced the assistant
// message at each index. Populated when a turn finishes streaming, used
// in MessageRow to show the right name in the signature line.
const [messageAgents, setMessageAgents] = useState<Map<number, Agent>>(
() => loadMessageAgents(),
)
// Persist whenever either map changes.
useEffect(() => {
saveAgentHistory(agentHistory)
}, [agentHistory])
useEffect(() => {
saveMessageAgents(messageAgents)
}, [messageAgents])
// Hand-off prompt — only emitted when this conversation has been touched
// by more than one agent. Lists prior personas the new agent might see in
// the transcript.
const handoffNote = useMemo(() => {
if (agentHistory.size <= 1) return ""
if (!activeAgent || !agentHistory.has(activeAgent.id)) return ""
const others = [...agentHistory.values()].filter((a) => a.id !== activeAgent.id)
if (others.length === 0) return ""
const list = others
.map((a) => `${a.name} (${a.role})`)
.join("\n")
return [
"PRIOR HAND-OFF:",
"Earlier turns in this conversation were produced by other agent personas. Their responses appear in the transcript as assistant turns. Read them as context — they reflect a different voice and may have different style or focus — but answer the next message in your own voice as the current persona. Don't re-introduce yourself unless the user asks who they're talking to.",
`Prior personas in this thread:\n${list}`,
].join("\n\n")
}, [agentHistory, activeAgent])
const systemPrompt = [
"You are the operator's assistant inside Arcadia Admin. Be precise and direct. You have native function tools attached to this conversation — call them whenever the user asks about live platform state (counts, statuses, listings, lookups). Never invent tenant slugs, user counts, or statuses; if you need data, call a tool.",
ARCADIA_KNOWLEDGE,
persona,
handoffNote,
formatAdminContextForPrompt(),
]
.filter(Boolean)
.join("\n\n")
const arcadia = useArcadiaClient()
// Hydrate from the persisted live conversation so navigating away and
// back doesn't reset the chat. Read once on mount.
const initialLive = useRef<LLMMessage[] | null>(null)
if (initialLive.current === null) {
initialLive.current = loadLive() ?? []
}
const { messages, setMessages, send, continueChat, abort, isStreaming } = useChat({
system: systemPrompt,
initialMessages: initialLive.current,
})
// Persist on every change. Streaming partials get saved too, which is what
// we want — refreshing mid-stream restores the partial assistant message.
useEffect(() => {
saveLive(messages)
}, [messages])
// "Clear conversation" must drop three things in lockstep:
// 1. The in-memory messages (setMessages([])).
// 2. The persisted live snapshot (clearLive()).
// 3. The initialLive ref — otherwise on the next render or hook
// reconciliation, useChat's reset() would re-seed from the
// captured-at-mount initialMessages and the old conversation
// pops back. (This was the bug.)
// We deliberately don't call useChat's reset() here because reset
// restores to opts.initialMessages, which we want to be empty.
const resetAndClear = useCallback(() => {
initialLive.current = []
clearLive()
clearAgentMaps()
setMessages([])
setAgentHistory(new Map())
setMessageAgents(new Map())
// Keep reasoningEffort as-is. It's bound to the active config's
// default (set when the operator stars a config in Settings) and
// resetting it would silently undo their intent on every clear.
}, [setMessages])
// Auto tool-loop using native function calls. Reads run automatically;
// writes are held in `pendingConfirm` until the operator clicks Confirm
// or Deny in the inline ConfirmCard.
const toolIterationsRef = useRef(0)
const processedTurnRef = useRef(-1)
const prevStreamingRef = useRef(isStreaming)
// Mirror of reasoningEffort state, kept current via the effect below so
// regenerate/continue callbacks (declared before the state hook) can
// read the latest value without becoming reasoningEffort dependents.
const reasoningEffortRef = useRef<ReasoningEffort>("off")
// Maintain agent-history. Two triggers:
// 1. When a turn finishes streaming and at least one user/assistant
// pair exists, the *current* active agent has demonstrably been
// involved — add it.
// 2. When the operator switches the active agent and there are already
// messages in the thread, the *previous* agent was the one talking
// until that moment — add it (the new one will be added on its
// first turn finish).
// Also reset everything when the conversation is cleared.
useEffect(() => {
if (messages.length === 0) {
// Fresh thread — drop any stale history so empty-state behaves.
if (agentHistory.size > 0) setAgentHistory(new Map())
prevAgentRef.current = activeAgent
return
}
const prev = prevAgentRef.current
if (prev && prev.id !== activeAgent?.id) {
// Operator just switched. Lock in the prior agent so the new one
// sees it in the hand-off note.
setAgentHistory((m) => {
if (m.has(prev.id)) return m
const next = new Map(m)
next.set(prev.id, prev)
return next
})
}
prevAgentRef.current = activeAgent
// Also add the current agent if it has just produced something.
if (activeAgent && !agentHistory.has(activeAgent.id) && !isStreaming) {
const last = messages[messages.length - 1]
if (last?.role === "assistant" && last.content.trim()) {
setAgentHistory((m) => {
if (m.has(activeAgent.id)) return m
const next = new Map(m)
next.set(activeAgent.id, activeAgent)
return next
})
}
}
}, [activeAgent, messages, isStreaming, agentHistory])
const MAX_TOOL_ITERATIONS = 3
const [pendingConfirm, setPendingConfirm] = useState<{
/** Message index that emitted the write calls. */
afterIndex: number
writes: ToolCall[]
readMessages: { role: "tool"; content: string; toolCallId: string; name: string }[]
} | null>(null)
const [confirmBusy, setConfirmBusy] = useState(false)
useEffect(() => {
const justFinished = prevStreamingRef.current && !isStreaming
prevStreamingRef.current = isStreaming
if (!justFinished) return
const lastIdx = messages.length - 1
if (lastIdx < 0) return
const last = messages[lastIdx]
if (last.role !== "assistant") return
// Stamp the agent that produced this turn so the UI signature is
// accurate even after the operator switches personas later. Stamps
// the *current* activeAgent — by definition the producer of the
// turn that just finished.
if (activeAgent) {
setMessageAgents((m) => {
if (m.get(lastIdx)?.id === activeAgent.id) return m
const next = new Map(m)
next.set(lastIdx, activeAgent)
return next
})
}
if (processedTurnRef.current === lastIdx) return
processedTurnRef.current = lastIdx
const calls = last.toolCalls ?? []
if (calls.length === 0) {
toolIterationsRef.current = 0
return
}
if (toolIterationsRef.current >= MAX_TOOL_ITERATIONS) return
toolIterationsRef.current += 1
void (async () => {
const { reads, writes } = classifyCalls(calls)
const { toolMessages: readMsgs } =
reads.length > 0
? await runLLMToolCalls(reads, { arcadia })
: { toolMessages: [] }
if (writes.length > 0) {
setPendingConfirm({ afterIndex: lastIdx, writes, readMessages: readMsgs })
return
}
void continueChat(readMsgs, {
system: systemPrompt,
tools: getOpenAITools(),
})
})()
}, [messages, isStreaming, arcadia, continueChat, systemPrompt])
const onConfirmWrites = useCallback(async () => {
if (!pendingConfirm) return
setConfirmBusy(true)
try {
const { toolMessages: writeMsgs } = await runLLMToolCalls(
pendingConfirm.writes,
{ arcadia },
{ allowWrites: true },
)
void continueChat([...pendingConfirm.readMessages, ...writeMsgs], {
system: systemPrompt,
tools: getOpenAITools(),
})
} finally {
setPendingConfirm(null)
setConfirmBusy(false)
}
}, [pendingConfirm, arcadia, continueChat, systemPrompt])
const onDenyWrites = useCallback(() => {
if (!pendingConfirm) return
const denials = buildDenialMessages(pendingConfirm.writes)
void continueChat([...pendingConfirm.readMessages, ...denials], {
system: systemPrompt,
tools: getOpenAITools(),
})
setPendingConfirm(null)
}, [pendingConfirm, continueChat, systemPrompt])
const { complete: completeOneShot, isLoading: compacting } = useCompletion()
const [input, setInput] = useState("")
const [showPromptOpen, setShowPromptOpen] = useState(false)
const [hasCompactSnapshot, setHasCompactSnapshot] = useState(
() => !!loadAISnapshot(),
)
// Session label — stable for the duration of the page load. Encoded in
// base36 from the mount timestamp; just a unique-feeling moniker for
// the operator's eye, not anything semantic.
const [sessionLabel] = useState(() =>
typeof window === "undefined"
? "0000-0000"
: `${Math.floor(Date.now() / 1000).toString(36).slice(-4).toUpperCase()}-${Math.random()
.toString(36)
.slice(2, 6)
.toUpperCase()}`,
)
// Live clock for the modeline / signatures, ticking every second.
const [now, setNow] = useState(() => new Date())
useEffect(() => {
const id = setInterval(() => setNow(new Date()), 1000)
return () => clearInterval(id)
}, [])
const clockLabel = now
.toISOString()
.slice(11, 19) /* HH:MM:SS in UTC */
+ "Z"
const hasAssistantReply = messages.some((m) => m.role === "assistant")
const buildTranscript = useCallback(() => {
const lines: string[] = [
`# Conversation`,
"",
activeAgent
? `**Persona:** ${activeAgent.name}${activeAgent.role}`
: "",
`**Date:** ${new Date().toISOString()}`,
"",
].filter(Boolean)
for (const m of messages) {
lines.push(`### ${m.role === "user" ? "User" : "Assistant"}`)
lines.push("")
lines.push(m.content.trim())
lines.push("")
}
return lines.join("\n")
}, [messages, activeAgent])
const toast = useToast()
const copyMarkdown = useCallback(async () => {
if (messages.length === 0) return
try {
await navigator.clipboard.writeText(buildTranscript())
toast.success("Copied as Markdown", {
description: `${messages.length} message${messages.length === 1 ? "" : "s"} on the clipboard.`,
})
} catch {
toast.error("Couldn't copy", {
description: "Clipboard access was blocked.",
})
}
}, [buildTranscript, messages.length, toast])
const exportMarkdown = useCallback(() => {
if (messages.length === 0) return
const md = buildTranscript()
const blob = new Blob([md], { type: "text/markdown;charset=utf-8" })
const url = URL.createObjectURL(blob)
const a = document.createElement("a")
a.href = url
const stamp = new Date().toISOString().replace(/[:.]/g, "-").slice(0, 19)
const filename = `ai-${stamp}.md`
a.download = filename
a.click()
URL.revokeObjectURL(url)
toast.success("Exported transcript", { description: filename })
}, [buildTranscript, messages.length, toast])
const saveToLibrary = useCallback(() => {
if (messages.length === 0) return
const md = buildTranscript()
const title =
messages[0]?.content.slice(0, 60).replace(/\s+/g, " ").trim() ||
"AI conversation"
addLibraryItem({
kind: "conversation",
title,
content: md,
tags: activeAgent ? [activeAgent.role.toLowerCase()] : [],
agentName: activeAgent?.name,
agentRole: activeAgent?.role,
messageCount: messages.length,
})
toast.success("Saved to Library", { description: title })
}, [buildTranscript, messages, activeAgent, toast])
const regenerateLast = useCallback(() => {
if (isStreaming) return
let lastUserIdx = -1
for (let i = messages.length - 1; i >= 0; i--) {
if (messages[i].role === "user") {
lastUserIdx = i
break
}
}
if (lastUserIdx === -1) return
const text = messages[lastUserIdx].content
setMessages(messages.slice(0, lastUserIdx))
// Defer so the state flush completes before send() reads `messages`.
setTimeout(
() => void send(text, withReasoning({ tools: getOpenAITools() }, reasoningEffortRef.current)),
0,
)
}, [messages, setMessages, send, isStreaming])
const continueLast = useCallback(() => {
if (isStreaming || messages.length === 0) return
void send(
"Please continue your previous reply.",
withReasoning({ tools: getOpenAITools() }, reasoningEffortRef.current),
)
}, [isStreaming, messages.length, send])
const compactConversation = useCallback(async () => {
if (compacting || isStreaming || messages.length < 2) return
const transcript = messages
.map(
(m) =>
`${m.role === "user" ? "User" : "Assistant"}: ${m.content.trim()}`,
)
.join("\n\n")
const summarySystem =
"You compress conversations. Output a tight 12 paragraph summary that preserves: user goals, key facts, names, decisions, file paths, code snippets, and unfinished tasks. Use third person ('the user wants X'). No commentary, no preamble, no markdown headings."
try {
const summary = await completeOneShot(
[
{ role: "system", content: summarySystem },
{
role: "user",
content: `Summarize this conversation:\n\n${transcript}`,
},
],
{ maxTokens: 800 },
)
// Snapshot first so Restore can undo.
saveAISnapshot(messages as StoredMessage[])
setHasCompactSnapshot(true)
setMessages([
{
role: "assistant",
content: `📋 **Conversation summary** (older turns compacted)\n\n${summary.trim()}`,
},
])
} catch {}
}, [compacting, isStreaming, messages, completeOneShot, setMessages])
const restoreCompact = useCallback(() => {
const snap = loadAISnapshot()
if (!snap) return
setMessages(snap)
clearAISnapshot()
setHasCompactSnapshot(false)
}, [setMessages])
const endRef = useRef<HTMLDivElement | null>(null)
const composerRef = useRef<HTMLDivElement | null>(null)
const lastContent = messages.at(-1)?.content ?? ""
// Track the composer's actual height so the auto-scroll sentinel can
// keep the latest text ~24px above its top edge regardless of how many
// lines the textarea has grown to.
const [composerHeight, setComposerHeight] = useState(160)
useEffect(() => {
const el = composerRef.current
if (!el || typeof ResizeObserver === "undefined") return
const ro = new ResizeObserver(([entry]) => {
if (entry) setComposerHeight(entry.contentRect.height)
})
ro.observe(el)
return () => ro.disconnect()
}, [])
// Auto-stick to the bottom only when the user is already near it. If they
// scroll up to read earlier turns mid-stream, don't yank them back down.
// The ref dodges React render cycles so scroll events feel instant.
const stickRef = useRef(true)
useEffect(() => {
const onScroll = () => {
const distFromBottom =
document.documentElement.scrollHeight -
(window.scrollY + window.innerHeight)
stickRef.current = distFromBottom < 120
}
window.addEventListener("scroll", onScroll, { passive: true })
onScroll()
return () => window.removeEventListener("scroll", onScroll)
}, [])
useEffect(() => {
if (!stickRef.current) return
endRef.current?.scrollIntoView({ block: "end" })
}, [messages.length, lastContent, isStreaming])
// Per-conversation reasoning override. Persists across page reloads via
// localStorage so the operator's chosen level survives a refresh, but
// resets when they clear the conversation. "off" = pass nothing through.
// Initialize from the shared key (settings panel writes this when the
// operator stars a config), persist on change, and live-subscribe so a
// star action in another tab/route updates the chip without a refresh.
const [reasoningEffort, setReasoningEffort] = useState<ReasoningEffort>(
() => loadActiveReasoning(),
)
useEffect(() => {
saveActiveReasoning(reasoningEffort)
reasoningEffortRef.current = reasoningEffort
}, [reasoningEffort])
useEffect(() => {
return subscribeActiveReasoning((next) => {
// Don't loop on our own writes — we already wrote `reasoningEffort`
// when it changed. Only pick up writes that disagree with state.
setReasoningEffort((cur) => (cur === next ? cur : next))
})
}, [])
const cycleReasoning = useCallback(() => {
setReasoningEffort((cur) => {
const idx = REASONING_LEVELS.indexOf(cur)
return REASONING_LEVELS[(idx + 1) % REASONING_LEVELS.length]
})
}, [])
const submit = useCallback(() => {
const text = input.trim()
if (!text || isStreaming) return
setInput("")
stickRef.current = true
void send(text, withReasoning({ tools: getOpenAITools() }, reasoningEffort))
}, [input, isStreaming, send, reasoningEffort])
const isEmpty = messages.length === 0
// Token estimate for the modeline. Cheap heuristic, adequate for
// operator-glance display.
const estTokensTotal = messages.reduce(
(n, m) => n + Math.ceil((m.content?.length ?? 0) / 4),
0,
)
const userTurns = messages.filter((m) => m.role === "user").length
return (
<div className="relative -mb-6 flex h-full min-h-0 flex-col">
{/* Session header — flight-recorder strip. Hidden in the empty state
* because the empty state already shows session metadata. */}
{!isEmpty && (
<div className="console-header sticky top-0 z-10 px-4 py-3 sm:px-6">
<div className="mx-auto flex w-full max-w-3xl items-end justify-between gap-6">
<div className="flex flex-col gap-0.5">
<span className="console-meta-key">session</span>
<span className="console-session-id">
{sessionLabel.split("-")[0]}
<span>·</span>
{sessionLabel.split("-")[1]}
</span>
</div>
<div className="flex flex-wrap items-end justify-end gap-x-6 gap-y-1.5">
<SessionMeta label="agent" value={(activeAgent?.name ?? "Atlas").toLowerCase()} />
<SessionMeta label="model" value={truncateModel(model)} />
<SessionMeta label="turns" value={userTurns.toString().padStart(2, "0")} />
<SessionMeta
label="status"
value={
isStreaming
? "STREAMING"
: pendingConfirm
? "AWAIT-CONFIRM"
: isMock
? "MOCK"
: "READY"
}
tone={
isStreaming
? "amber"
: pendingConfirm
? "rose"
: isMock
? "muted"
: "mint"
}
/>
</div>
</div>
</div>
)}
{/* Empty state — flight-recorder card with staggered reveal */}
<div
aria-hidden={!isEmpty}
className="pointer-events-none absolute inset-x-0 top-[10%] px-8 transition-opacity duration-300"
style={{ opacity: isEmpty ? 1 : 0 }}
>
<div className="mx-auto flex max-w-3xl flex-col gap-4">
<div className="console-empty-line console-mono flex items-center justify-between text-[10.5px] tracking-[0.18em] uppercase text-[var(--console-muted)]">
<span>arcadia // operator console</span>
<span>session {sessionLabel}</span>
</div>
<div className="console-empty-line h-px bg-[var(--console-rule-soft)]" />
<h1 className="console-empty-line console-empty-headline">
ATLAS<span className="text-[var(--console-amber)]">.</span>{" "}
<em>standing&nbsp;by</em>
</h1>
<p className="console-empty-line console-mono max-w-[58ch] text-[13.5px] leading-[1.7] text-[var(--console-text-2)]">
<span className="text-[var(--console-amber)]"></span>{" "}
Issue an instruction. Read tools run automatically. Writes pause for
confirmation. Tab&nbsp; for command palette.
</p>
<div className="console-empty-line pointer-events-auto">
<button
type="button"
onClick={() =>
setMessages([
{ role: "assistant", content: BLOCK_SAMPLES_CONTENT } as LLMMessage,
])
}
className="console-mono inline-flex items-center gap-1.5 rounded-md border border-[var(--console-rule-soft)] bg-transparent px-2.5 py-1 text-[10.5px] uppercase tracking-[0.18em] text-[var(--console-muted)] transition-colors hover:border-[var(--console-amber)] hover:text-[var(--console-amber)]"
>
preview rich-output blocks
</button>
</div>
</div>
</div>
{/* Messages — rendered when there are any. In empty state a flex-grow
* spacer takes its place so the sticky-bottom composer lands at the
* actual bottom of the surface (otherwise it'd sit at the top with
* nothing above it, and the lift transform would push it off-screen). */}
{isEmpty ? (
<div className="flex-1" aria-hidden="true" />
) : (
<div className="flex-1 px-4 py-6 sm:px-6">
<div className="mx-auto flex w-full max-w-3xl flex-col gap-6">
{messages.map((m, i) => {
if (m.role === "system" || m.role === "tool") return null
const calls =
m.role === "assistant" && m.toolCalls
? m.toolCalls.map((tc) =>
buildAgentToolCall(tc, messages, isStreaming, !!pendingConfirm),
)
: []
const isWritePending =
pendingConfirm?.afterIndex === i ? pendingConfirm.writes : null
return (
<div key={i} className="contents">
<MessageRow
role={m.role as "user" | "assistant"}
content={m.content}
toolCalls={m.toolCalls}
turnNum={i + 1}
// Use the agent stamped on this index when known, fall
// back to the active agent (covers the live stream
// before the post-stream effect fires).
agentName={
messageAgents.get(i)?.name ?? activeAgent?.name ?? "Atlas"
}
timestamp={clockLabel}
sources={
m.role === "assistant"
? extractDocSources(messages, i)
: undefined
}
/>
{calls.length > 0 && (
<div className="self-start flex w-full max-w-[80ch] flex-col gap-2">
{calls.map((c) => (
<div key={c.id} className="flex flex-col gap-2">
<ToolCallCard call={c} defaultExpanded={false} />
{c.status === "success" && (
<ToolResultBlock name={c.name} result={c.result} />
)}
</div>
))}
</div>
)}
{isWritePending && (
<ConfirmCard
calls={isWritePending}
onConfirm={onConfirmWrites}
onDeny={onDenyWrites}
busy={confirmBusy}
/>
)}
</div>
)
})}
{(() => {
const activity = deriveAgentActivity({
isStreaming,
lastMessage: messages.at(-1),
pendingConfirm: !!pendingConfirm,
confirmBusy,
})
const isIdle = activity === "idle"
return (
<div
className={`self-start transition-opacity duration-300 ${
isIdle ? "opacity-50" : "opacity-100"
}`}
>
<AgentAvatar
name={activeAgent?.name ?? "Atlas"}
activity={activity}
initials={activeAgent ? agentInitials(activeAgent.name) : "AT"}
size={isIdle ? "sm" : "md"}
showLabel={!isIdle}
/>
</div>
)
})()}
<div
ref={endRef}
aria-hidden="true"
style={{ scrollMarginBottom: `${composerHeight + 24}px` }}
/>
</div>
</div>
)}
{/* Composer — single persistent mount; transform lifts it to viewport
* center when empty, then springs to sticky-bottom on the first message. */}
<div
ref={composerRef}
className="sticky bottom-0 z-20 px-4 pb-3 pt-3 sm:px-6"
style={{
transform: isEmpty
? "translateY(calc(-50dvh + 50% + 4rem))"
: "translateY(0)",
}}
>
<div className="mx-auto w-full max-w-3xl">
<Composer
value={input}
onChange={setInput}
onSubmit={submit}
onAbort={abort}
isStreaming={isStreaming}
models={models}
model={model}
onModelChange={onModelChange}
agents={agents}
activeAgent={activeAgent}
onAgentChange={onAgentChange}
onRegenerate={regenerateLast}
onContinue={continueLast}
onCompact={() => void compactConversation()}
onRestoreCompact={restoreCompact}
onCopyMarkdown={() => void copyMarkdown()}
onExportMarkdown={exportMarkdown}
onSaveToLibrary={saveToLibrary}
onShowPrompt={() => setShowPromptOpen(true)}
onRetryProbe={onRetryProbe}
onClear={resetAndClear}
hasMessages={messages.length > 0}
hasUserMessage={messages.some((m) => m.role === "user")}
hasCompactSnapshot={hasCompactSnapshot}
isMock={isMock}
isCompacting={compacting}
placeholder={isEmpty ? "Ask anything…" : "Reply…"}
reasoning={reasoningEffort}
onCycleReasoning={cycleReasoning}
/>
{showPromptOpen && (
<SystemPromptDialog
prompt={systemPrompt}
onClose={() => setShowPromptOpen(false)}
/>
)}
</div>
</div>
{/* Modeline — vim-style status strip. Pinned above the AppShell's own
* footer/padding so it always reads in the operator's bottom band. */}
<div className="console-modeline px-4 py-1.5 sm:px-6">
<div className="mx-auto flex max-w-3xl flex-wrap items-center justify-between gap-x-6 gap-y-0.5 tabular-nums">
<div className="flex items-center gap-4">
<span>
<span className="console-modeline-key">utc</span>
<span className="console-modeline-val">{clockLabel}</span>
</span>
<span>
<span className="console-modeline-key">turn</span>
<span className="console-modeline-val">
{userTurns.toString().padStart(2, "0")}
</span>
</span>
<span>
<span className="console-modeline-key">tok</span>
<span className="console-modeline-val">~{estTokensTotal.toLocaleString()}</span>
</span>
</div>
<div className="flex items-center gap-4">
{isStreaming ? (
<span className="flex items-center gap-2">
<span className="console-streaming-bar" />
<span className="console-modeline-val text-[var(--console-amber)]">
STREAM
</span>
</span>
) : (
<span>
<span className="console-modeline-key">enter</span>
<span className="console-modeline-val">send</span>
<span className="ml-3 console-modeline-key"></span>
<span className="console-modeline-key ml-1">enter</span>
<span className="console-modeline-val">newline</span>
</span>
)}
</div>
</div>
</div>
</div>
)
}
function deriveAgentActivity({
isStreaming,
lastMessage,
pendingConfirm,
confirmBusy,
}: {
isStreaming: boolean
lastMessage: LLMMessage | undefined
pendingConfirm: boolean
confirmBusy: boolean
}): "idle" | "thinking" | "working" | "waiting" | "speaking" {
if (confirmBusy) return "working"
if (pendingConfirm) return "waiting"
if (!isStreaming) return "idle"
if (!lastMessage || lastMessage.role !== "assistant") return "thinking"
if (lastMessage.content.trim().length > 0) return "speaking"
return "thinking"
}
function buildAgentToolCall(
tc: ToolCall,
allMessages: LLMMessage[],
isStreaming: boolean,
pendingConfirm: boolean,
): AgentToolCall {
const result = allMessages.find(
(m) => m.role === "tool" && m.toolCallId === tc.id,
)
let parsedArgs: Record<string, unknown> | undefined
try {
parsedArgs = tc.arguments ? JSON.parse(tc.arguments) : undefined
} catch {
parsedArgs = undefined
}
if (result) {
let parsedResult: unknown = result.content
let errorMsg: string | undefined
try {
const obj = JSON.parse(result.content) as Record<string, unknown>
if (obj && typeof obj === "object" && typeof obj.error === "string") {
errorMsg = obj.error
} else {
parsedResult = obj
}
} catch {
// leave as raw text
}
return {
id: tc.id,
name: tc.name,
status: errorMsg ? "error" : "success",
args: parsedArgs,
result: errorMsg ? undefined : parsedResult,
error: errorMsg,
}
}
let status: ToolCallStatus = "running"
if (pendingConfirm) status = "pending"
else if (!isStreaming) status = "running"
return {
id: tc.id,
name: tc.name,
status,
args: parsedArgs,
}
}
function SessionMeta({
label,
value,
tone = "default",
}: {
label: string
value: string
tone?: "default" | "amber" | "rose" | "mint" | "muted"
}) {
const toneColor = {
default: "var(--console-text)",
amber: "var(--console-amber)",
rose: "var(--console-rose)",
mint: "var(--console-mint)",
muted: "var(--console-muted)",
}[tone]
return (
<div className="flex flex-col gap-0.5 text-right">
<span className="console-meta-key">{label}</span>
<span className="console-meta-val tabular-nums" style={{ color: toneColor }}>
{value}
</span>
</div>
)
}
function truncateModel(m: string): string {
if (!m) return "—"
if (m.length <= 22) return m
return m.slice(0, 10) + "…" + m.slice(-9)
}
/** Walk forward from an assistant message and collect doc-search hits from
* any matching `tool` result messages. Deduped by sourcePath so a chunk and
* its sibling chunk in the same file collapse to one citation. */
function extractDocSources(
messages: LLMMessage[],
assistantIdx: number,
): DocHit[] {
const msg = messages[assistantIdx]
if (msg?.role !== "assistant" || !msg.toolCalls?.length) return []
const docCallIds = new Set(
msg.toolCalls.filter((tc) => tc.name === "search_docs").map((tc) => tc.id),
)
if (docCallIds.size === 0) return []
const seen = new Set<string>()
const out: DocHit[] = []
for (let i = assistantIdx + 1; i < messages.length; i++) {
const m = messages[i]
if (m.role === "assistant") break // hit the next turn
if (m.role !== "tool" || !m.toolCallId || !docCallIds.has(m.toolCallId)) {
continue
}
try {
const parsed = JSON.parse(m.content) as { hits?: DocHit[] }
for (const h of parsed.hits ?? []) {
if (seen.has(h.sourcePath + "#" + h.id)) continue
seen.add(h.sourcePath + "#" + h.id)
out.push(h)
}
} catch {
// Tool errors come back as { error } — no hits to surface.
}
}
return out
}
function SourcesFooter({ sources }: { sources: DocHit[] }) {
if (sources.length === 0) return null
return (
<div className="console-mono mt-3 flex flex-wrap items-center gap-1.5 text-[10.5px] tracking-[0.08em] text-[var(--console-muted)]">
<span className="uppercase text-[var(--console-muted-2)]">sources</span>
<span className="text-[var(--console-muted-2)]"></span>
{sources.map((s) => (
<span
key={s.id}
title={`${s.sourcePath}\n\n${s.excerpt}`}
className="inline-flex max-w-[28ch] items-center gap-1 truncate rounded border border-[var(--console-rule-soft)] bg-[var(--console-deck)] px-1.5 py-0.5 text-[var(--console-text-2)]"
>
<span className="truncate">{s.title}</span>
</span>
))}
</div>
)
}
function MessageRow({
role,
content,
toolCalls,
turnNum,
agentName,
timestamp,
sources,
}: {
role: "user" | "assistant"
content: string
toolCalls?: ToolCall[]
turnNum?: number
agentName?: string
timestamp?: string
sources?: DocHit[]
}) {
// Operator turn — monospace, sodium-amber prompt, no bubble. The whole
// row hangs from a left gutter showing the turn number.
if (role === "user") {
return (
<div className="grid grid-cols-[3.5rem_1fr] gap-x-3 self-stretch">
<div className="flex flex-col items-end pt-[3px]">
<span className="console-turn-num">
T{(turnNum ?? 0).toString().padStart(2, "0")}
</span>
{timestamp ? (
<span className="console-mono mt-0.5 text-[9.5px] tracking-[0.1em] text-[var(--console-muted-2)]">
{timestamp}
</span>
) : null}
</div>
<div className="border-l border-[var(--console-rule-soft)] pl-4">
<div className="console-op-line whitespace-pre-wrap">
<span className="console-op-prompt">&nbsp;</span>
{content}
</div>
</div>
</div>
)
}
// Assistant turn — set in serif, with a tiny mono signature beneath. If
// there's no prose (just tool calls), suppress the row entirely.
if (!content.trim()) return null
return (
<div className="grid grid-cols-[3.5rem_1fr] gap-x-3 self-stretch">
<div className="flex flex-col items-end pt-[2px]">
<span className="console-turn-num text-[var(--console-cyan)]">
T{(turnNum ?? 0).toString().padStart(2, "0")}
</span>
<span className="console-mono mt-0.5 text-[9.5px] tracking-[0.1em] text-[var(--console-muted-2)]">
{agentName?.slice(0, 6).toLowerCase() ?? "atlas"}
</span>
</div>
<div className="border-l border-[var(--console-cyan-deep)]/40 pl-4">
<div className="console-agent-prose">
<MessageBody content={content} toolCalls={toolCalls} />
</div>
{sources && sources.length > 0 && <SourcesFooter sources={sources} />}
<div className="console-sig mt-2 flex items-center gap-2">
<span className="console-sig-name">
{agentName?.toLowerCase() ?? "atlas"}»
</span>
{timestamp ? <span>{timestamp}</span> : null}
<span className="text-[var(--console-muted-2)]">·</span>
<span>recv</span>
</div>
</div>
</div>
)
}
function Composer({
value,
onChange,
onSubmit,
onAbort,
isStreaming,
models,
model,
onModelChange,
agents,
activeAgent,
onAgentChange,
onRegenerate,
onContinue,
onCompact,
onRestoreCompact,
onCopyMarkdown,
onExportMarkdown,
onSaveToLibrary,
onShowPrompt,
onRetryProbe,
onClear,
hasMessages,
hasUserMessage,
hasCompactSnapshot,
isMock,
isCompacting,
placeholder,
reasoning,
onCycleReasoning,
}: {
value: string
onChange: (v: string) => void
onSubmit: () => void
onAbort: () => void
isStreaming: boolean
models: string[]
model: string
onModelChange: (m: string) => void
agents: Agent[]
activeAgent: Agent | undefined
onAgentChange: (id: string) => void
onRegenerate: () => void
onContinue: () => void
onCompact: () => void
onRestoreCompact: () => void
onCopyMarkdown: () => void
onExportMarkdown: () => void
onSaveToLibrary: () => void
onShowPrompt: () => void
onRetryProbe: () => void
onClear: () => void
hasMessages: boolean
hasUserMessage: boolean
hasCompactSnapshot: boolean
isMock: boolean
isCompacting: boolean
placeholder: string
reasoning: ReasoningEffort
onCycleReasoning: () => void
}) {
const taRef = useRef<HTMLTextAreaElement | null>(null)
// Auto-grow the textarea.
useEffect(() => {
const el = taRef.current
if (!el) return
el.style.height = "auto"
el.style.height = Math.min(el.scrollHeight, 240) + "px"
}, [value])
const onKey = (e: React.KeyboardEvent<HTMLTextAreaElement>) => {
if (e.key === "Enter" && !e.shiftKey) {
e.preventDefault()
onSubmit()
}
}
return (
<div className="console-composer">
<div className="flex flex-col gap-3 px-4 pt-3 pb-3">
<div className="flex items-start gap-2">
<span
aria-hidden
className="console-mono select-none pt-[2px] text-[14px] font-semibold leading-[1.55] text-[var(--console-amber)]"
>
_
</span>
<textarea
ref={taRef}
value={value}
onChange={(e) => onChange(e.target.value)}
onKeyDown={onKey}
placeholder={placeholder}
rows={2}
data-action="ai-composer-input"
className="min-h-[3.5rem] w-full resize-none bg-transparent outline-none"
/>
</div>
<div className="flex items-center justify-between gap-2">
<div className="flex items-center gap-1">
<button
type="button"
data-action="ai-attach"
aria-label="Attach"
className="inline-flex size-9 items-center justify-center rounded-full text-muted-foreground transition-colors hover:bg-accent hover:text-foreground"
>
<Plus className="size-5" />
</button>
<CommandsMenu
onRegenerate={onRegenerate}
onContinue={onContinue}
onCompact={onCompact}
onRestoreCompact={onRestoreCompact}
onCopyMarkdown={onCopyMarkdown}
onExportMarkdown={onExportMarkdown}
onSaveToLibrary={onSaveToLibrary}
onShowPrompt={onShowPrompt}
onRetryProbe={onRetryProbe}
onClear={onClear}
isStreaming={isStreaming}
isCompacting={isCompacting}
hasMessages={hasMessages}
hasUserMessage={hasUserMessage}
hasCompactSnapshot={hasCompactSnapshot}
isMock={isMock}
/>
</div>
<div className="flex items-center gap-1">
<AgentChip
agents={agents}
activeAgent={activeAgent}
onAgentChange={onAgentChange}
/>
<ModelSelector
models={models}
model={model}
onModelChange={onModelChange}
/>
<ReasoningChip value={reasoning} onCycle={onCycleReasoning} />
<VoiceInputButton
onTranscript={(t) => onChange((value ? value + " " : "") + t)}
/>
{isStreaming ? (
<Button
type="button"
size="sm"
variant="ghost"
onClick={onAbort}
aria-label="Stop"
data-action="ai-stop"
className="rounded-full"
>
<Square className="size-4" />
</Button>
) : null}
</div>
</div>
</div>
</div>
)
}
function ModelSelector({
models,
model,
onModelChange,
}: {
models: string[]
model: string
onModelChange: (m: string) => void
}) {
const label = prettyModelName(model)
return (
<DropdownMenu>
{/* base-ui's Menu.Trigger renders its own <button>, so we don't wrap
* a nested <button> here (which Radix's asChild pattern would require).
* Styles + data-action go straight on the Trigger. */}
<DropdownMenuTrigger
data-action="ai-model"
className="inline-flex items-center gap-1 rounded-full px-3 py-1.5 text-sm text-muted-foreground transition-colors hover:bg-accent hover:text-foreground"
>
<span>{label}</span>
<ChevronDown className="size-4 opacity-70" />
</DropdownMenuTrigger>
<DropdownMenuContent align="end">
{models.map((m) => (
<DropdownMenuItem
key={m}
onClick={() => onModelChange(m)}
className={m === model ? "font-medium" : ""}
>
{prettyModelName(m)}
</DropdownMenuItem>
))}
</DropdownMenuContent>
</DropdownMenu>
)
}
/**
* Reasoning-effort chip for the composer. Click cycles off → low → medium →
* high → max → off. When non-off, the next send includes
* `reasoning_effort: <level>` which the proxy passes to OpenAI/DeepSeek
* natively and translates to Anthropic's thinking block server-side.
*
* Visually: hidden when off (no chrome clutter for the common case),
* surfaces as a sodium-amber pill when set.
*/
function ReasoningChip({
value,
onCycle,
}: {
value: ReasoningEffort
onCycle: () => void
}) {
const active = value !== "off"
return (
<button
type="button"
onClick={onCycle}
data-action="ai-reasoning"
title={
active
? `Reasoning: ${value}. Click to cycle.`
: "Reasoning: off. Click to enable thinking mode."
}
className={[
"inline-flex items-center gap-1.5 rounded-full px-2.5 py-1 text-[11px] font-mono uppercase tracking-[0.12em] transition-colors",
active
? "bg-amber-500/15 text-amber-500 hover:bg-amber-500/25 dark:text-amber-300"
: "text-muted-foreground hover:bg-accent hover:text-foreground",
].join(" ")}
>
<Sparkles className="size-3" />
<span className="select-none">
think
{active ? <span className="ml-1 font-semibold">{value}</span> : null}
</span>
</button>
)
}
function AgentChip({
agents,
activeAgent,
onAgentChange,
}: {
agents: Agent[]
activeAgent: Agent | undefined
onAgentChange: (id: string) => void
}) {
return (
<DropdownMenu>
<DropdownMenuTrigger
data-action="ai-agent"
className="inline-flex items-center gap-1.5 rounded-full py-1 pl-1 pr-2.5 text-sm text-muted-foreground transition-colors hover:bg-accent hover:text-foreground focus:outline-none focus-visible:ring-2 focus-visible:ring-ring"
title={
activeAgent
? `${activeAgent.name}${activeAgent.role}`
: "Pick a persona"
}
>
<Avatar className="size-5">
<AvatarFallback
style={{
background: agentTint(activeAgent?.id ?? ""),
color: "var(--primary-foreground)",
}}
className="text-[10px] font-semibold"
>
{agentInitials(activeAgent?.name)}
</AvatarFallback>
</Avatar>
<span className="font-medium">
{activeAgent?.name ?? "Agent"}
</span>
<ChevronDown className="size-4 opacity-70" />
</DropdownMenuTrigger>
<DropdownMenuContent
align="start"
sideOffset={6}
className="max-h-80 w-72 overflow-y-auto"
>
<div className="px-2 py-1 text-[10px] font-medium uppercase tracking-wide text-muted-foreground">
Switch persona
</div>
{agents.map((a) => (
<DropdownMenuItem
key={a.id}
onClick={() => onAgentChange(a.id)}
data-state={activeAgent?.id === a.id ? "checked" : undefined}
data-action={`ai-agent-${a.id}`}
className="flex items-center gap-2.5"
>
<Avatar className="size-7">
<AvatarFallback
style={{
background: agentTint(a.id),
color: "var(--primary-foreground)",
}}
className="text-[11px] font-semibold"
>
{agentInitials(a.name)}
</AvatarFallback>
</Avatar>
<span className="flex min-w-0 flex-col">
<span className="truncate font-medium">{a.name}</span>
<span className="truncate text-xs text-muted-foreground">
{a.role}
</span>
</span>
</DropdownMenuItem>
))}
</DropdownMenuContent>
</DropdownMenu>
)
}
function agentInitials(name: string | undefined): string {
if (!name) return "?"
const words = name.trim().split(/\s+/).filter(Boolean)
if (words.length === 0) return "?"
if (words.length === 1) return words[0].slice(0, 2).toUpperCase()
return (words[0][0] + words[words.length - 1][0]).toUpperCase()
}
function agentTint(id: string): string {
let hash = 0
for (let i = 0; i < id.length; i++) {
hash = (hash * 31 + id.charCodeAt(i)) | 0
}
const hue = ((hash % 360) + 360) % 360
return `oklch(0.55 0.18 ${hue})`
}
function CommandsMenu({
onRegenerate,
onContinue,
onCompact,
onRestoreCompact,
onCopyMarkdown,
onExportMarkdown,
onSaveToLibrary,
onShowPrompt,
onRetryProbe,
onClear,
isStreaming,
isCompacting,
hasMessages,
hasUserMessage,
hasCompactSnapshot,
isMock,
}: {
onRegenerate: () => void
onContinue: () => void
onCompact: () => void
onRestoreCompact: () => void
onCopyMarkdown: () => void
onExportMarkdown: () => void
onSaveToLibrary: () => void
onShowPrompt: () => void
onRetryProbe: () => void
onClear: () => void
isStreaming: boolean
isCompacting: boolean
hasMessages: boolean
hasUserMessage: boolean
hasCompactSnapshot: boolean
isMock: boolean
}) {
const [open, setOpen] = useState(false)
// Close the popover after a tile is clicked, so the menu acknowledges the
// action visually even when the action itself produces no obvious change
// (Copy MD, Export MD, etc — those also fire a toast at the call site).
const close = useCallback(
(fn: () => void) => () => {
fn()
setOpen(false)
},
[],
)
return (
<Popover open={open} onOpenChange={setOpen}>
<PopoverTrigger
render={
<button
type="button"
data-action="ai-commands"
aria-label="Commands"
title="Commands"
className="inline-flex size-9 items-center justify-center rounded-full text-muted-foreground transition-colors hover:bg-accent hover:text-foreground"
>
<CommandIcon className="size-5" />
</button>
}
/>
<PopoverContent align="start" side="top" className="w-80 p-2">
<SectionLabel>Conversation</SectionLabel>
<div className="grid grid-cols-2 gap-1">
<ToolTile
data-action="ai-cmd-regenerate"
onClick={close(onRegenerate)}
disabled={isStreaming || !hasUserMessage}
icon={<RotateCcw className="size-4" />}
label="Regenerate"
title="Re-run the most recent prompt"
/>
<ToolTile
data-action="ai-cmd-continue"
onClick={close(onContinue)}
disabled={isStreaming || !hasMessages}
icon={<ArrowRight className="size-4" />}
label="Continue"
title="Ask the model to keep going"
/>
<ToolTile
data-action="ai-cmd-compact"
onClick={close(onCompact)}
disabled={isCompacting || isStreaming || !hasMessages}
icon={
isCompacting ? (
<Loader2 className="size-4 animate-spin" />
) : (
<Archive className="size-4" />
)
}
label="Compact"
title="Summarize older turns to free context"
/>
<ToolTile
data-action="ai-cmd-restore-compact"
onClick={close(onRestoreCompact)}
disabled={!hasCompactSnapshot}
icon={<Undo2 className="size-4" />}
label="Restore"
title={
hasCompactSnapshot
? "Undo the most recent compact"
: "No snapshot available"
}
/>
</div>
<SectionLabel>Share</SectionLabel>
<div className="grid grid-cols-2 gap-1">
<ToolTile
data-action="ai-cmd-copy-md"
onClick={close(onCopyMarkdown)}
disabled={!hasMessages}
icon={<Copy className="size-4" />}
label="Copy MD"
title="Copy conversation as Markdown"
/>
<ToolTile
data-action="ai-cmd-export-md"
onClick={close(onExportMarkdown)}
disabled={!hasMessages}
icon={<Download className="size-4" />}
label="Export MD"
title="Download a .md file"
/>
<ToolTile
data-action="ai-cmd-save-library"
onClick={close(onSaveToLibrary)}
disabled={!hasMessages}
icon={<BookmarkPlus className="size-4" />}
label="Save to Library"
title="Snapshot this conversation"
/>
<ToolTile
data-action="ai-cmd-show-prompt"
onClick={close(onShowPrompt)}
icon={<FileText className="size-4" />}
label="Show prompt"
title="Preview the system prompt"
/>
</div>
{isMock && (
<>
<SectionLabel>Connection</SectionLabel>
<div className="grid grid-cols-2 gap-1">
<ToolTile
data-action="ai-cmd-retry-probe"
onClick={close(onRetryProbe)}
icon={<RefreshCw className="size-4" />}
label="Reconnect"
title="Probe the LLM endpoint again"
/>
</div>
</>
)}
<div className="my-2 h-px bg-border" />
<ToolTile
data-action="ai-cmd-clear"
onClick={close(onClear)}
disabled={!hasMessages}
icon={<Trash2 className="size-4" />}
label="Clear conversation"
title="Wipe history and start fresh"
destructive
fullWidth
/>
</PopoverContent>
</Popover>
)
}
function SystemPromptDialog({
prompt,
onClose,
}: {
prompt: string
onClose: () => void
}) {
const copy = async () => {
try {
await navigator.clipboard.writeText(prompt)
} catch {}
}
if (typeof document === "undefined") return null
return createPortal(
<div
role="dialog"
aria-modal="true"
onClick={onClose}
className="fixed inset-0 z-50 flex items-center justify-center bg-background/70 p-4 backdrop-blur-sm"
>
<div
onClick={(e) => e.stopPropagation()}
className="flex max-h-[80vh] w-full max-w-2xl flex-col rounded-lg border bg-card shadow-lg"
>
<div className="flex items-center gap-2 border-b px-4 py-3">
<FileText className="size-4 text-muted-foreground" />
<div className="flex flex-1 flex-col">
<span className="text-sm font-semibold">System prompt</span>
<span className="text-xs text-muted-foreground">
Base prompt + active persona
</span>
</div>
<Button variant="ghost" size="sm" onClick={copy}>
<Copy className="size-3.5" /> Copy
</Button>
<Button
variant="ghost"
size="icon-sm"
onClick={onClose}
aria-label="Close"
>
<X className="size-4" />
</Button>
</div>
<pre className="flex-1 overflow-auto whitespace-pre-wrap p-4 font-mono text-xs leading-relaxed">
{prompt}
</pre>
</div>
</div>,
document.body,
)
}
function SectionLabel({ children }: { children: React.ReactNode }) {
return (
<div className="mt-2 mb-1 px-1 text-[10px] font-medium uppercase tracking-wide text-muted-foreground">
{children}
</div>
)
}
function ToolTile({
icon,
label,
title,
onClick,
disabled,
destructive,
fullWidth,
...rest
}: {
icon: React.ReactNode
label: string
title: string
onClick: () => void
disabled?: boolean
destructive?: boolean
fullWidth?: boolean
} & Omit<React.ButtonHTMLAttributes<HTMLButtonElement>, "onClick" | "title">) {
return (
<button
type="button"
onClick={onClick}
disabled={disabled}
title={title}
className={
"flex items-center gap-2 rounded-md border border-transparent px-2 py-1.5 text-left text-xs transition-colors disabled:cursor-not-allowed disabled:opacity-50 " +
(fullWidth ? "w-full " : "") +
(destructive
? "text-destructive hover:bg-destructive/10"
: "hover:bg-accent hover:text-accent-foreground")
}
{...rest}
>
<span className="shrink-0">{icon}</span>
<span className="truncate font-medium">{label}</span>
</button>
)
}
function prettyModelName(id: string): string {
if (!id) return "model"
// Trim known prefixes / paths so the chip stays compact.
const last = id.split(/[\\/]/).pop() ?? id
return last.length > 28 ? last.slice(0, 26) + "…" : last
}
type SpeechRecognitionLike = {
lang: string
interimResults: boolean
continuous: boolean
onresult: (e: { results: { [k: number]: { [k: number]: { transcript: string } } } }) => void
onerror: () => void
onend: () => void
start: () => void
stop: () => void
}
function getSpeechRecognition(): (new () => SpeechRecognitionLike) | null {
if (typeof window === "undefined") return null
const w = window as unknown as {
SpeechRecognition?: new () => SpeechRecognitionLike
webkitSpeechRecognition?: new () => SpeechRecognitionLike
}
return w.SpeechRecognition ?? w.webkitSpeechRecognition ?? null
}
function VoiceInputButton({
onTranscript,
}: {
onTranscript: (text: string) => void
}) {
const Ctor = getSpeechRecognition()
const [listening, setListening] = useState(false)
const recRef = useRef<SpeechRecognitionLike | null>(null)
if (!Ctor) return null
const start = () => {
try {
const rec = new Ctor()
rec.lang = navigator.language || "en-US"
rec.interimResults = false
rec.continuous = false
rec.onresult = (e) => {
const text = e.results[0]?.[0]?.transcript ?? ""
if (text.trim()) onTranscript(text.trim())
}
rec.onerror = () => setListening(false)
rec.onend = () => setListening(false)
recRef.current = rec
rec.start()
setListening(true)
} catch {
setListening(false)
}
}
const stop = () => {
recRef.current?.stop()
setListening(false)
}
return (
<button
type="button"
data-action="ai-voice"
onClick={() => (listening ? stop() : start())}
aria-label={listening ? "Stop listening" : "Voice input"}
className={
"inline-flex size-9 items-center justify-center rounded-full transition-colors " +
(listening
? "bg-destructive/10 text-destructive animate-pulse"
: "text-muted-foreground hover:bg-accent hover:text-foreground")
}
>
{listening ? <MicOff className="size-5" /> : <Mic className="size-5" />}
</button>
)
}