Add safe chat reasoning disclosure
This commit is contained in:
@@ -4,7 +4,7 @@ title: Modernize savings chat agent UI with AI Elements phases
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status: In Progress
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assignee: []
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created_date: '2026-06-16 08:38'
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updated_date: '2026-06-16 08:41'
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updated_date: '2026-06-16 08:46'
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labels: []
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dependencies: []
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priority: high
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@@ -20,7 +20,7 @@ Implement the planned AI Elements-inspired savings chat agent UI in three sequen
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## Acceptance Criteria
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<!-- AC:BEGIN -->
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- [x] #1 Phase 1 replaces the basic chat surface with reusable conversation, message, prompt input, and tool trace UI primitives
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- [ ] #2 Phase 2 adds a safe reasoning/work-progress disclosure derived from existing tool traces, without exposing hidden chain-of-thought
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- [x] #2 Phase 2 adds a safe reasoning/work-progress disclosure derived from existing tool traces, without exposing hidden chain-of-thought
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- [ ] #3 Phase 3 adds structured source/citation support through stored assistant metadata and visible UI affordances
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- [ ] #4 Each phase is covered by failing-first tests, verified after implementation, and committed separately
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<!-- AC:END -->
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@@ -41,4 +41,6 @@ Implement the planned AI Elements-inspired savings chat agent UI in three sequen
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<!-- SECTION:NOTES:BEGIN -->
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Phase 1 complete: added AgentChat primitives for conversation, message rendering, prompt input, and tool trace disclosure; integrated SavingsChatPage. Verification: npx vitest src/components/chat/AgentChat.test.tsx --run, npx eslint targeted chat/page files, npm run build (Vite chunk-size warning only).
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Phase 2 complete locally: added safe work-progress/reasoning disclosure derived from toolTrace result summaries, removed raw inputSummary display from the disclosure, and added active progress state while a response is pending. Verification: npx vitest src/components/chat/AgentChat.test.tsx --run (9 tests), targeted eslint, npm run build (Vite chunk-size warning only). Spec subagent review approved.
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<!-- SECTION:NOTES:END -->
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@@ -6,7 +6,7 @@ import {
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AgentPromptInput,
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type AgentChatMessage,
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} from "./AgentChat";
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import { getToolTraceSummary } from "./agentChatModel";
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import { buildReasoningSteps, getToolTraceSummary } from "./agentChatModel";
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const assistantMessage: AgentChatMessage = {
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id: "assistant-1",
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@@ -111,3 +111,40 @@ describe("AgentChat phase 1 components", () => {
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expect(markup).not.toContain("Werkzeuge verwendet");
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});
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});
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describe("AgentChat phase 2 reasoning disclosure", () => {
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test("builds safe reasoning steps from tool traces without exposing raw inputs", () => {
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const steps = buildReasoningSteps(assistantMessage.toolTrace);
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expect(steps).toEqual([
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{
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label: "summarize_transactions",
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description: "12 Umsaetze zusammengefasst",
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status: "complete",
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},
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{
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label: "list_transactions",
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description: "1 Treffer",
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status: "complete",
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},
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]);
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expect(JSON.stringify(steps)).not.toContain("Mai 2026");
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});
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test("renders an assistant work-progress disclosure from tool traces", () => {
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const markup = renderToStaticMarkup(<AgentMessage message={assistantMessage} />);
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expect(markup).toContain("So wurde gearbeitet");
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expect(markup).toContain("summarize_transactions");
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expect(markup).toContain("12 Umsaetze zusammengefasst");
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});
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test("marks the current agent step as active while submitting", () => {
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const markup = renderToStaticMarkup(
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<AgentConversation messages={[assistantMessage]} isSubmitting />,
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);
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expect(markup).toContain("Antwort wird vorbereitet");
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expect(markup).toContain("data-status=\"active\"");
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});
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});
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@@ -2,15 +2,16 @@ import {
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type ChangeEvent,
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type FormEvent,
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type HTMLAttributes,
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type ReactNode,
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type Ref,
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} from "react";
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import { Loader2, Send, Wrench } from "lucide-react";
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import { Button } from "@/components/ui/button";
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import { cn } from "@/lib/utils";
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import {
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buildReasoningSteps,
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getToolTraceSummary,
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type AgentChatMessage,
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type AgentReasoningStep,
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type AgentToolTrace,
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} from "./agentChatModel";
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export type { AgentChatMessage, AgentToolTrace } from "./agentChatModel";
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@@ -89,39 +90,43 @@ export function AgentMessage({ message, className, ...props }: AgentMessageProps
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}
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function AgentToolTracePanel({ toolTrace }: { toolTrace: AgentToolTrace[] }) {
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const steps = buildReasoningSteps(toolTrace);
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return (
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<details className="mt-3 rounded-md border bg-muted/30 px-2 py-1.5">
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<summary className="flex cursor-pointer list-none items-center gap-2 text-xs font-medium text-muted-foreground">
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<Wrench className="h-3.5 w-3.5" />
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{getToolTraceSummary(toolTrace)}
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So wurde gearbeitet ({getToolTraceSummary(toolTrace)})
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</summary>
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<div className="mt-2 space-y-2">
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{toolTrace.map((tool, toolIndex) => (
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<div key={`${tool.name}-${toolIndex}`} className="rounded-md bg-background/80 p-2 text-xs">
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<p className="font-medium text-foreground">{tool.name}</p>
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<ToolTraceLine label="Eingabe" value={tool.inputSummary} />
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<ToolTraceLine label="Ergebnis" value={tool.resultSummary} />
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</div>
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{steps.map((step, stepIndex) => (
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<ReasoningStep key={`${step.label}-${stepIndex}`} step={step} />
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))}
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</div>
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</details>
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);
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}
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function ToolTraceLine({ label, value }: { label: ReactNode; value: ReactNode }) {
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function ReasoningStep({ step }: { step: AgentReasoningStep }) {
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return (
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<p className="mt-1 text-muted-foreground">
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<span className="font-medium text-foreground">{label}: </span>
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{value}
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</p>
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<div className="rounded-md bg-background/80 p-2 text-xs" data-status={step.status}>
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<p className="font-medium text-foreground">{step.label}</p>
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<p className="mt-1 text-muted-foreground">{step.description}</p>
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</div>
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);
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}
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function AgentThinkingIndicator() {
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return (
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<div className="flex items-center gap-2 px-1 text-sm text-muted-foreground">
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<Loader2 className="h-4 w-4 animate-spin" />
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Denk mit der KI nach...
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<div className="space-y-2 px-1 text-sm text-muted-foreground">
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<div className="flex items-center gap-2">
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<Loader2 className="h-4 w-4 animate-spin" />
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Denk mit der KI nach...
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</div>
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<div className="rounded-md border bg-muted/30 p-2 text-xs" data-status="active">
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<p className="font-medium text-foreground">Antwort wird vorbereitet</p>
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<p className="mt-1">Der Agent prueft den aktuellen Finanzkontext.</p>
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</div>
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</div>
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);
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}
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@@ -11,7 +11,23 @@ export type AgentChatMessage = {
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toolTrace?: AgentToolTrace[];
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};
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export type AgentReasoningStep = {
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label: string;
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description: string;
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status: "complete" | "active" | "pending";
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};
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export function getToolTraceSummary(toolTrace: AgentToolTrace[] | undefined) {
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if (!toolTrace || toolTrace.length === 0) return "Keine Werkzeuge";
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return `${toolTrace.length} ${toolTrace.length === 1 ? "Werkzeug" : "Werkzeuge"} verwendet`;
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}
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export function buildReasoningSteps(toolTrace: AgentToolTrace[] | undefined): AgentReasoningStep[] {
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if (!toolTrace || toolTrace.length === 0) return [];
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return toolTrace.map((tool) => ({
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label: tool.name,
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description: tool.resultSummary,
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status: "complete",
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}));
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}
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