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feat(agent): localize generated agent workflow

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This commit is contained in:
Matthias Meister
2026-04-10 13:56:11 +02:00
parent 66646bd62f
commit ddb2412349
10 changed files with 950 additions and 89 deletions
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288
components/canvas/nodes/agent-node.tsx
View File

@@ -5,6 +5,8 @@ import { Bot } from "lucide-react";
import { Handle, Position, type Node, type NodeProps } from "@xyflow/react";
import { useAction } from "convex/react";
import type { FunctionReference } from "convex/server";
import { useTranslations } from "next-intl";
import { useLocale } from "next-intl";
import { api } from "@/convex/_generated/api";
import type { Id } from "@/convex/_generated/dataModel";
@@ -37,6 +39,13 @@ type AgentNodeData = {
templateId?: string;
canvasId?: string;
modelId?: string;
briefConstraints?: {
briefing?: string;
audience?: string;
tone?: string;
targetChannels?: string[];
hardConstraints?: string[];
};
executionSteps?: Array<{ stepIndex?: number; stepTotal?: number }>;
executionStepIndex?: number;
executionStepTotal?: number;
@@ -48,6 +57,14 @@ type AgentNodeData = {
_statusMessage?: string;
};
type AgentBriefConstraints = {
briefing: string;
audience: string;
tone: string;
targetChannels: string[];
hardConstraints: string[];
};
type AgentNodeType = Node<AgentNodeData, "agent">;
const DEFAULT_AGENT_TEMPLATE_ID = "campaign-distributor";
@@ -114,6 +131,46 @@ function areAnswerMapsEqual(
return true;
}
function normalizeDelimitedList(value: string, allowNewLines = false): string[] {
const separator = allowNewLines ? /[\n,]/ : /,/;
return value
.split(separator)
.map((item) => item.trim())
.filter((item) => item.length > 0);
}
function normalizeBriefConstraints(raw: AgentNodeData["briefConstraints"]): AgentBriefConstraints {
return {
briefing: typeof raw?.briefing === "string" ? raw.briefing : "",
audience: typeof raw?.audience === "string" ? raw.audience : "",
tone: typeof raw?.tone === "string" ? raw.tone : "",
targetChannels: Array.isArray(raw?.targetChannels)
? raw.targetChannels.filter((item): item is string => typeof item === "string")
: [],
hardConstraints: Array.isArray(raw?.hardConstraints)
? raw.hardConstraints.filter((item): item is string => typeof item === "string")
: [],
};
}
function areStringArraysEqual(left: string[], right: string[]): boolean {
if (left.length !== right.length) {
return false;
}
return left.every((value, index) => value === right[index]);
}
function areBriefConstraintsEqual(left: AgentBriefConstraints, right: AgentBriefConstraints): boolean {
return (
left.briefing === right.briefing &&
left.audience === right.audience &&
left.tone === right.tone &&
areStringArraysEqual(left.targetChannels, right.targetChannels) &&
areStringArraysEqual(left.hardConstraints, right.hardConstraints)
);
}
function CompactList({ items }: { items: readonly string[] }) {
return (
<ul className="space-y-1">
@@ -127,6 +184,8 @@ function CompactList({ items }: { items: readonly string[] }) {
}
export default function AgentNode({ id, data, selected }: NodeProps<AgentNodeType>) {
const t = useTranslations("agentNode");
const locale = useLocale();
const nodeData = data as AgentNodeData;
const template =
getAgentTemplate(nodeData.templateId ?? DEFAULT_AGENT_TEMPLATE_ID) ??
@@ -140,6 +199,9 @@ export default function AgentNode({ id, data, selected }: NodeProps<AgentNodeTyp
const [clarificationAnswers, setClarificationAnswers] = useState<AgentClarificationAnswerMap>(
normalizeClarificationAnswers(nodeData.clarificationAnswers),
);
const [briefConstraints, setBriefConstraints] = useState<AgentBriefConstraints>(
normalizeBriefConstraints(nodeData.briefConstraints),
);
const agentActionsApi = api as unknown as {
agents: {
@@ -150,6 +212,7 @@ export default function AgentNode({ id, data, selected }: NodeProps<AgentNodeTyp
canvasId: Id<"canvases">;
nodeId: Id<"nodes">;
modelId: string;
locale: "de" | "en";
},
unknown
>;
@@ -160,6 +223,7 @@ export default function AgentNode({ id, data, selected }: NodeProps<AgentNodeTyp
canvasId: Id<"canvases">;
nodeId: Id<"nodes">;
clarificationAnswers: AgentClarificationAnswerMap;
locale: "de" | "en";
},
unknown
>;
@@ -168,6 +232,7 @@ export default function AgentNode({ id, data, selected }: NodeProps<AgentNodeTyp
const runAgent = useSafeAction(agentActionsApi.agents.runAgent);
const resumeAgent = useSafeAction(agentActionsApi.agents.resumeAgent);
const normalizedLocale = locale === "en" ? "en" : "de";
useEffect(() => {
setModelId(nodeData.modelId ?? DEFAULT_AGENT_MODEL_ID);
@@ -183,6 +248,16 @@ export default function AgentNode({ id, data, selected }: NodeProps<AgentNodeTyp
});
}, [nodeData.clarificationAnswers]);
useEffect(() => {
const normalized = normalizeBriefConstraints(nodeData.briefConstraints);
setBriefConstraints((current) => {
if (areBriefConstraintsEqual(current, normalized)) {
return current;
}
return normalized;
});
}, [nodeData.briefConstraints]);
useEffect(() => {
if (availableModels.length === 0) {
return;
@@ -202,6 +277,14 @@ export default function AgentNode({ id, data, selected }: NodeProps<AgentNodeTyp
const resolvedModelId = selectedModel?.id ?? DEFAULT_AGENT_MODEL_ID;
const creditCost = selectedModel?.creditCost ?? 0;
const clarificationQuestions = nodeData.clarificationQuestions ?? [];
const templateName =
template?.id === "campaign-distributor"
? t("templates.campaignDistributor.name")
: (template?.name ?? "");
const templateDescription =
template?.id === "campaign-distributor"
? t("templates.campaignDistributor.description")
: (template?.description ?? "");
const isExecutionActive = nodeData._status === "analyzing" || nodeData._status === "executing";
const executionProgressLine = useMemo(() => {
if (nodeData._status !== "executing") {
@@ -230,14 +313,19 @@ export default function AgentNode({ id, data, selected }: NodeProps<AgentNodeTyp
stepTotalCandidate > 0;
if (hasExecutionNumbers) {
return `Executing step ${Math.max(0, Math.floor(stepIndexCandidate)) + 1}/${Math.floor(stepTotalCandidate)}`;
return t("executingStepFallback", {
current: Math.max(0, Math.floor(stepIndexCandidate)) + 1,
total: Math.floor(stepTotalCandidate),
});
}
if (totalFromSteps > 0) {
return `Executing planned outputs (${totalFromSteps} total)`;
return t("executingPlannedTotalFallback", {
total: totalFromSteps,
});
}
return "Executing planned outputs";
return t("executingPlannedFallback");
}, [
nodeData._executionStepIndex,
nodeData._executionStepTotal,
@@ -246,8 +334,25 @@ export default function AgentNode({ id, data, selected }: NodeProps<AgentNodeTyp
nodeData.executionStepIndex,
nodeData.executionStepTotal,
nodeData.executionSteps,
t,
]);
const resolveClarificationPrompt = useCallback(
(question: AgentClarificationQuestion) => {
if (question.id === "briefing") {
return t("clarificationPrompts.briefing");
}
if (question.id === "target-channels") {
return t("clarificationPrompts.targetChannels");
}
if (question.id === "incoming-context") {
return t("clarificationPrompts.incomingContext");
}
return question.prompt;
},
[t],
);
const persistNodeData = useCallback(
(patch: Partial<AgentNodeData>) => {
const raw = data as Record<string, unknown>;
@@ -288,6 +393,20 @@ export default function AgentNode({ id, data, selected }: NodeProps<AgentNodeTyp
[persistNodeData],
);
const handleBriefConstraintsChange = useCallback(
(patch: Partial<AgentBriefConstraints>) => {
setBriefConstraints((prev) => {
const next = {
...prev,
...patch,
};
void persistNodeData({ briefConstraints: next });
return next;
});
},
[persistNodeData],
);
const handleRunAgent = useCallback(async () => {
if (isExecutionActive) {
return;
@@ -295,8 +414,8 @@ export default function AgentNode({ id, data, selected }: NodeProps<AgentNodeTyp
if (status.isOffline) {
toast.warning(
"Offline aktuell nicht unterstuetzt",
"Agent-Lauf benoetigt eine aktive Verbindung.",
t("offlineTitle"),
t("offlineDescription"),
);
return;
}
@@ -310,14 +429,15 @@ export default function AgentNode({ id, data, selected }: NodeProps<AgentNodeTyp
canvasId,
nodeId: id as Id<"nodes">,
modelId: resolvedModelId,
locale: normalizedLocale,
});
}, [isExecutionActive, nodeData.canvasId, id, resolvedModelId, runAgent, status.isOffline]);
}, [isExecutionActive, nodeData.canvasId, id, normalizedLocale, resolvedModelId, runAgent, status.isOffline, t]);
const handleSubmitClarification = useCallback(async () => {
if (status.isOffline) {
toast.warning(
"Offline aktuell nicht unterstuetzt",
"Agent-Lauf benoetigt eine aktive Verbindung.",
t("offlineTitle"),
t("offlineDescription"),
);
return;
}
@@ -331,8 +451,9 @@ export default function AgentNode({ id, data, selected }: NodeProps<AgentNodeTyp
canvasId,
nodeId: id as Id<"nodes">,
clarificationAnswers,
locale: normalizedLocale,
});
}, [clarificationAnswers, nodeData.canvasId, id, resumeAgent, status.isOffline]);
}, [clarificationAnswers, nodeData.canvasId, id, normalizedLocale, resumeAgent, status.isOffline, t]);
if (!template) {
return null;
@@ -363,14 +484,14 @@ export default function AgentNode({ id, data, selected }: NodeProps<AgentNodeTyp
<div className="flex items-center gap-1.5 text-xs font-medium text-amber-700 dark:text-amber-300">
<Bot className="h-3.5 w-3.5" />
<span>{template.emoji}</span>
<span>{template.name}</span>
<span>{templateName}</span>
</div>
<p className="line-clamp-2 text-xs text-muted-foreground">{template.description}</p>
<p className="line-clamp-2 text-xs text-muted-foreground">{templateDescription}</p>
</header>
<section className="space-y-1.5">
<Label htmlFor={`agent-model-${id}`} className="text-[10px] font-semibold uppercase tracking-wide text-muted-foreground">
Model
{t("modelLabel")}
</Label>
<Select value={resolvedModelId} onValueChange={handleModelChange}>
<SelectTrigger id={`agent-model-${id}`} className="nodrag nowheel w-full" size="sm">
@@ -385,10 +506,98 @@ export default function AgentNode({ id, data, selected }: NodeProps<AgentNodeTyp
</SelectContent>
</Select>
<p className="text-[11px] text-muted-foreground">
{selectedModel?.label ?? resolvedModelId} - {creditCost} Cr
{t("modelCreditMeta", {
model: selectedModel?.label ?? resolvedModelId,
credits: creditCost,
})}
</p>
</section>
<section className="space-y-1.5">
<Label htmlFor={`agent-${id}-briefing`} className="text-[10px] font-semibold uppercase tracking-wide text-muted-foreground">
{t("briefingLabel")}
</Label>
<textarea
id={`agent-${id}-briefing`}
name="agent-briefing"
value={briefConstraints.briefing}
onChange={(event) =>
handleBriefConstraintsChange({ briefing: event.target.value })
}
placeholder={t("briefingPlaceholder")}
className="nodrag nowheel min-h-20 w-full resize-y rounded-md border border-border bg-background px-2 py-1.5 text-sm"
/>
</section>
<section className="space-y-1.5">
<p className="text-[10px] font-semibold uppercase tracking-wide text-muted-foreground">
{t("constraintsLabel")}
</p>
<div className="space-y-1">
<label htmlFor={`agent-${id}-audience`} className="text-[11px] text-muted-foreground">
{t("audienceLabel")}
</label>
<input
id={`agent-${id}-audience`}
name="agent-audience"
type="text"
value={briefConstraints.audience}
onChange={(event) =>
handleBriefConstraintsChange({ audience: event.target.value })
}
className="nodrag nowheel w-full rounded-md border border-border bg-background px-2 py-1.5 text-sm"
/>
</div>
<div className="space-y-1">
<label htmlFor={`agent-${id}-tone`} className="text-[11px] text-muted-foreground">
{t("toneLabel")}
</label>
<input
id={`agent-${id}-tone`}
name="agent-tone"
type="text"
value={briefConstraints.tone}
onChange={(event) => handleBriefConstraintsChange({ tone: event.target.value })}
className="nodrag nowheel w-full rounded-md border border-border bg-background px-2 py-1.5 text-sm"
/>
</div>
<div className="space-y-1">
<label htmlFor={`agent-${id}-target-channels`} className="text-[11px] text-muted-foreground">
{t("targetChannelsLabel")}
</label>
<input
id={`agent-${id}-target-channels`}
name="agent-target-channels"
type="text"
value={briefConstraints.targetChannels.join(", ")}
onChange={(event) =>
handleBriefConstraintsChange({
targetChannels: normalizeDelimitedList(event.target.value),
})
}
placeholder={t("targetChannelsPlaceholder")}
className="nodrag nowheel w-full rounded-md border border-border bg-background px-2 py-1.5 text-sm"
/>
</div>
<div className="space-y-1">
<label htmlFor={`agent-${id}-hard-constraints`} className="text-[11px] text-muted-foreground">
{t("hardConstraintsLabel")}
</label>
<textarea
id={`agent-${id}-hard-constraints`}
name="agent-hard-constraints"
value={briefConstraints.hardConstraints.join("\n")}
onChange={(event) =>
handleBriefConstraintsChange({
hardConstraints: normalizeDelimitedList(event.target.value, true),
})
}
placeholder={t("hardConstraintsPlaceholder")}
className="nodrag nowheel min-h-16 w-full resize-y rounded-md border border-border bg-background px-2 py-1.5 text-sm"
/>
</div>
</section>
<section className="space-y-1.5">
<button
type="button"
@@ -397,7 +606,7 @@ export default function AgentNode({ id, data, selected }: NodeProps<AgentNodeTyp
aria-busy={isExecutionActive}
className="nodrag w-full rounded-md bg-amber-600 px-3 py-2 text-sm font-medium text-white hover:bg-amber-700 disabled:cursor-not-allowed disabled:opacity-60"
>
Run agent
{t("runAgentButton")}
</button>
{executionProgressLine ? (
<p className="text-[11px] text-amber-800/90 dark:text-amber-200/90">{executionProgressLine}</p>
@@ -407,7 +616,7 @@ export default function AgentNode({ id, data, selected }: NodeProps<AgentNodeTyp
{clarificationQuestions.length > 0 ? (
<section className="space-y-2">
<p className="text-[10px] font-semibold uppercase tracking-wide text-muted-foreground">
Clarifications
{t("clarificationsLabel")}
</p>
{clarificationQuestions.map((question) => (
<div key={question.id} className="space-y-1">
@@ -415,7 +624,7 @@ export default function AgentNode({ id, data, selected }: NodeProps<AgentNodeTyp
htmlFor={`agent-${id}-clarification-${question.id}`}
className="text-[11px] text-foreground/90"
>
{question.prompt}
{resolveClarificationPrompt(question)}
{question.required ? " *" : ""}
</label>
<input
@@ -435,31 +644,36 @@ export default function AgentNode({ id, data, selected }: NodeProps<AgentNodeTyp
onClick={() => void handleSubmitClarification()}
className="nodrag w-full rounded-md border border-amber-500/50 bg-amber-500/10 px-3 py-2 text-sm font-medium text-amber-800 hover:bg-amber-500/20 dark:text-amber-200"
>
Submit clarification
{t("submitClarificationButton")}
</button>
</section>
) : null}
<section className="space-y-1">
<p className="text-[10px] font-semibold uppercase tracking-wide text-muted-foreground">
Channels
</p>
<CompactList items={template.channels} />
</section>
<section className="space-y-1">
<p className="text-[10px] font-semibold uppercase tracking-wide text-muted-foreground">
Expected Inputs
</p>
<CompactList items={template.expectedInputs} />
</section>
<section className="space-y-1">
<p className="text-[10px] font-semibold uppercase tracking-wide text-muted-foreground">
Expected Outputs
</p>
<CompactList items={template.expectedOutputs} />
</section>
<details className="rounded-md border border-border/60 bg-muted/20 px-2 py-1.5">
<summary className="cursor-pointer text-[10px] font-semibold uppercase tracking-wide text-muted-foreground">
{t("templateReferenceLabel")}
</summary>
<div className="mt-2 space-y-2">
<section className="space-y-1">
<p className="text-[10px] font-semibold uppercase tracking-wide text-muted-foreground">
{t("templateReferenceChannelsLabel")} ({template.channels.length})
</p>
<CompactList items={template.channels} />
</section>
<section className="space-y-1">
<p className="text-[10px] font-semibold uppercase tracking-wide text-muted-foreground">
{t("templateReferenceInputsLabel")} ({template.expectedInputs.length})
</p>
<CompactList items={template.expectedInputs} />
</section>
<section className="space-y-1">
<p className="text-[10px] font-semibold uppercase tracking-wide text-muted-foreground">
{t("templateReferenceOutputsLabel")} ({template.expectedOutputs.length})
</p>
<CompactList items={template.expectedOutputs} />
</section>
</div>
</details>
</div>
</BaseNodeWrapper>
);

101
components/canvas/nodes/agent-output-node.tsx
View File

@@ -1,6 +1,7 @@
"use client";
import { Handle, Position, type Node, type NodeProps } from "@xyflow/react";
import { useTranslations } from "next-intl";
import BaseNodeWrapper from "./base-node-wrapper";
@@ -19,7 +20,28 @@ type AgentOutputNodeData = {
type AgentOutputNodeType = Node<AgentOutputNodeData, "agent-output">;
function tryFormatJsonBody(body: string): string | null {
const trimmed = body.trim();
if (!trimmed) {
return null;
}
const looksLikeJsonObject = trimmed.startsWith("{") && trimmed.endsWith("}");
const looksLikeJsonArray = trimmed.startsWith("[") && trimmed.endsWith("]");
if (!looksLikeJsonObject && !looksLikeJsonArray) {
return null;
}
try {
const parsed = JSON.parse(trimmed) as unknown;
return JSON.stringify(parsed, null, 2);
} catch {
return null;
}
}
export default function AgentOutputNode({ data, selected }: NodeProps<AgentOutputNodeType>) {
const t = useTranslations("agentOutputNode");
const nodeData = data as AgentOutputNodeData;
const isSkeleton = nodeData.isSkeleton === true;
const hasStepCounter =
@@ -39,7 +61,11 @@ export default function AgentOutputNode({ data, selected }: NodeProps<AgentOutpu
const stepCounter = hasStepCounter
? `${safeStepIndex + 1}/${safeStepTotal}`
: null;
const resolvedTitle = nodeData.title ?? (isSkeleton ? "Planned output" : "Agent output");
const resolvedTitle =
nodeData.title ??
(isSkeleton ? t("plannedOutputDefaultTitle") : t("defaultTitle"));
const body = nodeData.body ?? "";
const formattedJsonBody = isSkeleton ? null : tryFormatJsonBody(body);
return (
<BaseNodeWrapper
@@ -63,52 +89,63 @@ export default function AgentOutputNode({ data, selected }: NodeProps<AgentOutpu
{resolvedTitle}
</p>
{isSkeleton ? (
<span className="shrink-0 rounded-full border border-amber-500/50 bg-amber-500/10 px-2 py-0.5 text-[10px] font-semibold uppercase tracking-wide text-amber-800 dark:text-amber-200">
Skeleton
</span>
<span className="shrink-0 rounded-full border border-amber-500/50 bg-amber-500/10 px-2 py-0.5 text-[10px] font-semibold uppercase tracking-wide text-amber-800 dark:text-amber-200">
{t("skeletonBadge")}
</span>
) : null}
</div>
{isSkeleton ? (
<p className="text-[11px] text-amber-700/90 dark:text-amber-300/90">
{t("plannedOutputLabel")}
{stepCounter ? ` - ${stepCounter}` : ""}
{nodeData.stepId ? ` - ${nodeData.stepId}` : ""}
</p>
) : null}
</div>
{isSkeleton ? (
<p className="text-[11px] text-amber-700/90 dark:text-amber-300/90">
Planned output{stepCounter ? ` - ${stepCounter}` : ""}
{nodeData.stepId ? ` - ${nodeData.stepId}` : ""}
</p>
) : null}
</header>
<section className="space-y-1">
<p className="text-[10px] font-semibold uppercase tracking-wide text-muted-foreground">
Channel
</p>
<p className="truncate text-xs text-foreground/90" title={nodeData.channel}>
{nodeData.channel ?? "-"}
</p>
<section
data-testid="agent-output-meta-strip"
className="grid grid-cols-2 gap-2 rounded-md border border-border/70 bg-muted/30 px-2 py-1.5"
>
<div className="min-w-0">
<p className="text-[10px] font-semibold uppercase tracking-wide text-muted-foreground">{t("channelLabel")}</p>
<p className="truncate text-xs font-medium text-foreground/90" title={nodeData.channel}>
{nodeData.channel ?? "-"}
</p>
</div>
<div className="min-w-0">
<p className="text-[10px] font-semibold uppercase tracking-wide text-muted-foreground">{t("typeLabel")}</p>
<p className="truncate text-xs font-medium text-foreground/90" title={nodeData.outputType}>
{nodeData.outputType ?? "-"}
</p>
</div>
</section>
<section className="space-y-1">
<p className="text-[10px] font-semibold uppercase tracking-wide text-muted-foreground">
Output Type
</p>
<p className="truncate text-xs text-foreground/90" title={nodeData.outputType}>
{nodeData.outputType ?? "-"}
</p>
</section>
<section className="space-y-1">
<p className="text-[10px] font-semibold uppercase tracking-wide text-muted-foreground">
Body
{t("bodyLabel")}
</p>
{isSkeleton ? (
<div
data-testid="agent-output-skeleton-body"
className="animate-pulse rounded-md border border-dashed border-amber-500/40 bg-gradient-to-r from-amber-500/10 via-amber-500/20 to-amber-500/10 p-3"
>
<p className="text-[11px] text-amber-800/90 dark:text-amber-200/90">Planned content</p>
<p className="text-[11px] text-amber-800/90 dark:text-amber-200/90">{t("plannedContent")}</p>
</div>
) : formattedJsonBody ? (
<pre
data-testid="agent-output-json-body"
className="max-h-48 overflow-auto rounded-md border border-border/80 bg-muted/40 p-3 font-mono text-[11px] leading-relaxed text-foreground/95"
>
<code>{formattedJsonBody}</code>
</pre>
) : (
<p className="line-clamp-6 whitespace-pre-wrap text-xs text-foreground/90">
{nodeData.body ?? ""}
</p>
<div
data-testid="agent-output-text-body"
className="max-h-48 overflow-auto rounded-md border border-border/70 bg-background/70 p-3 text-[13px] leading-relaxed text-foreground/90"
>
<p className="whitespace-pre-wrap break-words">{body}</p>
</div>
)}
</section>
</div>

81
convex/agents.ts
View File

@@ -14,8 +14,12 @@ import { getNodeDataRecord } from "./ai_node_data";
import { formatTerminalStatusMessage } from "./ai_errors";
import {
areClarificationAnswersComplete,
buildPreflightClarificationQuestions,
normalizeAgentBriefConstraints,
normalizeAgentExecutionPlan,
normalizeAgentLocale,
normalizeAgentOutputDraft,
type AgentLocale,
type AgentClarificationAnswerMap,
type AgentClarificationQuestion,
type AgentExecutionStep,
@@ -109,6 +113,14 @@ function buildExecuteSchema(stepIds: string[]): Record<string, unknown> {
};
}
function getOutputLanguageInstruction(locale: AgentLocale): string {
if (locale === "de") {
return "Write all generated fields in German (de-DE), including step titles, channel labels, output types, clarification prompts, and body content.";
}
return "Write all generated fields in English (en-US), including step titles, channel labels, output types, clarification prompts, and body content.";
}
type InternalApiShape = {
canvasGraph: {
getInternal: FunctionReference<
@@ -130,6 +142,7 @@ type InternalApiShape = {
canvasId: Id<"canvases">;
nodeId: Id<"nodes">;
modelId: string;
locale: AgentLocale;
userId: string;
reservationId?: Id<"creditTransactions">;
shouldDecrementConcurrency: boolean;
@@ -143,6 +156,7 @@ type InternalApiShape = {
canvasId: Id<"canvases">;
nodeId: Id<"nodes">;
modelId: string;
locale: AgentLocale;
userId: string;
reservationId?: Id<"creditTransactions">;
shouldDecrementConcurrency: boolean;
@@ -401,6 +415,13 @@ function collectIncomingContext(
return lines.length > 0 ? lines.join("\n") : "No incoming nodes connected to this agent.";
}
function countIncomingContext(
graph: { edges: Doc<"edges">[] },
agentNodeId: Id<"nodes">,
): number {
return graph.edges.filter((edge) => edge.targetNodeId === agentNodeId).length;
}
function getAgentNodeFromGraph(
graph: { nodes: Doc<"nodes">[] },
nodeId: Id<"nodes">,
@@ -831,6 +852,7 @@ export const analyzeAgent = internalAction({
canvasId: v.id("canvases"),
nodeId: v.id("nodes"),
modelId: v.string(),
locale: v.union(v.literal("de"), v.literal("en")),
userId: v.string(),
reservationId: v.optional(v.id("creditTransactions")),
shouldDecrementConcurrency: v.boolean(),
@@ -850,7 +872,27 @@ export const analyzeAgent = internalAction({
const agentData = getNodeDataRecord(agentNode.data);
const template = getAgentTemplate(trimText(agentData.templateId) || "campaign-distributor");
const existingAnswers = normalizeAnswerMap(agentData.clarificationAnswers);
const locale = normalizeAgentLocale(args.locale);
const briefConstraints = normalizeAgentBriefConstraints(agentData.briefConstraints);
const incomingContext = collectIncomingContext(graph, args.nodeId);
const incomingContextCount = countIncomingContext(graph, args.nodeId);
const preflightClarificationQuestions = buildPreflightClarificationQuestions({
briefConstraints,
incomingContextCount,
});
const hasPreflightRequiredGaps = !areClarificationAnswersComplete(
preflightClarificationQuestions,
existingAnswers,
);
if (preflightClarificationQuestions.length > 0 && hasPreflightRequiredGaps) {
await ctx.runMutation(internalApi.agents.setAgentClarifying, {
nodeId: args.nodeId,
clarificationQuestions: preflightClarificationQuestions,
});
return;
}
const analysis = await generateStructuredObjectViaOpenRouter<{
analysisSummary: string;
@@ -864,20 +906,25 @@ export const analyzeAgent = internalAction({
{
role: "system",
content:
"You are the LemonSpace Agent Analyzer. Inspect incoming canvas context and decide if clarification is required before execution. Ask only necessary short questions.",
[
"You are the LemonSpace Agent Analyzer. Inspect incoming canvas context and decide if clarification is required before execution. Ask only necessary short questions.",
getOutputLanguageInstruction(locale),
].join(" "),
},
{
role: "user",
content: [
`Template: ${template?.name ?? "Unknown template"}`,
`Template description: ${template?.description ?? ""}`,
"Incoming node context:",
incomingContext,
`Current clarification answers: ${JSON.stringify(existingAnswers)}`,
"Return structured JSON matching the schema.",
].join("\n\n"),
},
],
`Template: ${template?.name ?? "Unknown template"}`,
`Template description: ${template?.description ?? ""}`,
`Brief + constraints: ${JSON.stringify(briefConstraints)}`,
"Incoming node context:",
incomingContext,
`Incoming context node count: ${incomingContextCount}`,
`Current clarification answers: ${JSON.stringify(existingAnswers)}`,
"Return structured JSON matching the schema.",
].join("\n\n"),
},
],
});
const clarificationQuestions = normalizeClarificationQuestions(
@@ -914,6 +961,7 @@ export const analyzeAgent = internalAction({
canvasId: args.canvasId,
nodeId: args.nodeId,
modelId: args.modelId,
locale,
userId: args.userId,
reservationId: args.reservationId,
shouldDecrementConcurrency: args.shouldDecrementConcurrency,
@@ -934,6 +982,7 @@ export const executeAgent = internalAction({
canvasId: v.id("canvases"),
nodeId: v.id("nodes"),
modelId: v.string(),
locale: v.union(v.literal("de"), v.literal("en")),
userId: v.string(),
reservationId: v.optional(v.id("creditTransactions")),
shouldDecrementConcurrency: v.boolean(),
@@ -954,6 +1003,8 @@ export const executeAgent = internalAction({
const agentData = getNodeDataRecord(agentNode.data);
const template = getAgentTemplate(trimText(agentData.templateId) || "campaign-distributor");
const clarificationAnswers = normalizeAnswerMap(agentData.clarificationAnswers);
const locale = normalizeAgentLocale(args.locale);
const briefConstraints = normalizeAgentBriefConstraints(agentData.briefConstraints);
const incomingContext = collectIncomingContext(graph, args.nodeId);
const executionPlanSummary = trimText(agentData.executionPlanSummary);
const executionSteps = normalizeExecutionSteps(agentData.executionSteps);
@@ -975,13 +1026,17 @@ export const executeAgent = internalAction({
{
role: "system",
content:
"You are the LemonSpace Agent Executor. Produce concrete channel outputs from context and clarification answers. Return one output per step, keyed by stepId.",
[
"You are the LemonSpace Agent Executor. Produce concrete channel outputs from context and clarification answers. Return one output per step, keyed by stepId.",
getOutputLanguageInstruction(locale),
].join(" "),
},
{
role: "user",
content: [
`Template: ${template?.name ?? "Unknown template"}`,
`Template description: ${template?.description ?? ""}`,
`Brief + constraints: ${JSON.stringify(briefConstraints)}`,
`Analyze summary: ${executionPlanSummary}`,
`Clarification answers: ${JSON.stringify(clarificationAnswers)}`,
`Execution steps: ${JSON.stringify(
@@ -1066,6 +1121,7 @@ export const runAgent = action({
canvasId: v.id("canvases"),
nodeId: v.id("nodes"),
modelId: v.string(),
locale: v.union(v.literal("de"), v.literal("en")),
},
handler: async (ctx, args): Promise<{ queued: true; nodeId: Id<"nodes"> }> => {
const canvas = await ctx.runQuery(api.canvases.get, {
@@ -1126,6 +1182,7 @@ export const runAgent = action({
canvasId: args.canvasId,
nodeId: args.nodeId,
modelId: selectedModel.id,
locale: normalizeAgentLocale(args.locale),
userId: canvas.ownerId,
reservationId: reservationId ?? undefined,
shouldDecrementConcurrency: usageIncremented,
@@ -1155,6 +1212,7 @@ export const resumeAgent = action({
canvasId: v.id("canvases"),
nodeId: v.id("nodes"),
clarificationAnswers: v.record(v.string(), v.string()),
locale: v.union(v.literal("de"), v.literal("en")),
},
handler: async (ctx, args): Promise<{ queued: true; nodeId: Id<"nodes"> }> => {
const canvas = await ctx.runQuery(api.canvases.get, {
@@ -1211,6 +1269,7 @@ export const resumeAgent = action({
canvasId: args.canvasId,
nodeId: args.nodeId,
modelId,
locale: normalizeAgentLocale(args.locale),
userId: canvas.ownerId,
reservationId,
shouldDecrementConcurrency,

106
lib/agent-run-contract.ts
View File

@@ -25,6 +25,16 @@ export type AgentExecutionPlan = {
steps: AgentExecutionStep[];
};
export type AgentBriefConstraints = {
briefing: string;
audience: string;
tone: string;
targetChannels: string[];
hardConstraints: string[];
};
export type AgentLocale = "de" | "en";
export type AgentAnalyzeResult = {
clarificationQuestions: AgentClarificationQuestion[];
executionPlan: AgentExecutionPlan | null;
@@ -46,6 +56,102 @@ function normalizeStepId(value: unknown): string {
.replace(/\s+/g, "-");
}
function normalizeStringArray(raw: unknown, options?: { lowerCase?: boolean }): string[] {
if (!Array.isArray(raw)) {
return [];
}
const seen = new Set<string>();
const normalized: string[] = [];
for (const item of raw) {
const trimmed = trimString(item);
if (trimmed === "") {
continue;
}
const value = options?.lowerCase ? trimmed.toLowerCase() : trimmed;
if (seen.has(value)) {
continue;
}
seen.add(value);
normalized.push(value);
}
return normalized;
}
export function normalizeAgentBriefConstraints(raw: unknown): AgentBriefConstraints {
const rawRecord =
raw && typeof raw === "object" && !Array.isArray(raw)
? (raw as Record<string, unknown>)
: null;
return {
briefing: trimString(rawRecord?.briefing),
audience: trimString(rawRecord?.audience),
tone: trimString(rawRecord?.tone),
targetChannels: normalizeStringArray(rawRecord?.targetChannels, { lowerCase: true }),
hardConstraints: normalizeStringArray(rawRecord?.hardConstraints),
};
}
export function normalizeAgentLocale(raw: unknown): AgentLocale {
if (raw === "de" || raw === "en") {
return raw;
}
return "de";
}
export type PreflightClarificationInput = {
briefConstraints: AgentBriefConstraints | unknown;
incomingContextCount: number;
};
const BRIEFING_REQUIRED_QUESTION: AgentClarificationQuestion = {
id: "briefing",
prompt: "What should the agent produce? Provide the brief in one or two sentences.",
required: true,
};
const TARGET_CHANNELS_REQUIRED_QUESTION: AgentClarificationQuestion = {
id: "target-channels",
prompt: "Which channels should this run target? List at least one channel.",
required: true,
};
const INCOMING_CONTEXT_REQUIRED_QUESTION: AgentClarificationQuestion = {
id: "incoming-context",
prompt: "No context was provided. What source context should the agent use?",
required: true,
};
export function buildPreflightClarificationQuestions(
input: PreflightClarificationInput,
): AgentClarificationQuestion[] {
const normalizedBriefConstraints = normalizeAgentBriefConstraints(input.briefConstraints);
const incomingContextCount = Number.isFinite(input.incomingContextCount)
? Math.max(0, Math.trunc(input.incomingContextCount))
: 0;
const questions: AgentClarificationQuestion[] = [];
if (normalizedBriefConstraints.briefing === "") {
questions.push(BRIEFING_REQUIRED_QUESTION);
}
if (normalizedBriefConstraints.targetChannels.length === 0) {
questions.push(TARGET_CHANNELS_REQUIRED_QUESTION);
}
if (incomingContextCount === 0) {
questions.push(INCOMING_CONTEXT_REQUIRED_QUESTION);
}
return questions;
}
export function normalizeAgentExecutionPlan(raw: unknown): AgentExecutionPlan {
const rawRecord =
raw && typeof raw === "object" && !Array.isArray(raw)

46
messages/de.json
View File

@@ -176,6 +176,52 @@
"creditMeta": "{credits} Credits",
"errorFallback": "Video-Generierung fehlgeschlagen"
},
"agentNode": {
"templates": {
"campaignDistributor": {
"name": "Campaign Distributor",
"description": "Entwickelt und verteilt LemonSpace-Kampagneninhalte kanal- und plattformgerecht."
}
},
"modelLabel": "Modell",
"modelCreditMeta": "{model} - {credits} Cr",
"briefingLabel": "Briefing",
"briefingPlaceholder": "Beschreibe Aufgabe und gewuenschtes Ergebnis kurz und konkret.",
"constraintsLabel": "Vorgaben",
"audienceLabel": "Zielgruppe",
"toneLabel": "Tonfall",
"targetChannelsLabel": "Zielkanaele",
"targetChannelsPlaceholder": "LinkedIn, Instagram Feed",
"hardConstraintsLabel": "Harte Constraints",
"hardConstraintsPlaceholder": "Keine Emojis\nMaximal 120 Woerter",
"runAgentButton": "Agent starten",
"clarificationsLabel": "Rueckfragen",
"submitClarificationButton": "Rueckfragen bestaetigen",
"templateReferenceLabel": "Template-Referenz",
"templateReferenceChannelsLabel": "Kanaele",
"templateReferenceInputsLabel": "Inputs",
"templateReferenceOutputsLabel": "Outputs",
"executingStepFallback": "Schritt {current}/{total} wird ausgefuehrt",
"executingPlannedTotalFallback": "Geplante Outputs werden erstellt ({total} gesamt)",
"executingPlannedFallback": "Geplante Outputs werden erstellt",
"offlineTitle": "Offline derzeit nicht verfuegbar",
"offlineDescription": "Ein Agent-Lauf benoetigt eine aktive Verbindung.",
"clarificationPrompts": {
"briefing": "Was soll der Agent liefern? Bitte formuliere das Briefing in ein bis zwei Saetzen.",
"targetChannels": "Welche Kanaele soll dieser Lauf bedienen? Bitte nenne mindestens einen Kanal.",
"incomingContext": "Es wurde kein Kontext verbunden. Welche Quelle soll der Agent verwenden?"
}
},
"agentOutputNode": {
"defaultTitle": "Agent-Output",
"plannedOutputDefaultTitle": "Geplanter Output",
"skeletonBadge": "SKELETON",
"plannedOutputLabel": "Geplanter Output",
"channelLabel": "Kanal",
"typeLabel": "Typ",
"bodyLabel": "Inhalt",
"plannedContent": "Geplanter Inhalt"
},
"credits": {
"balance": "Guthaben",
"available": "Verfügbar",

46
messages/en.json
View File

@@ -176,6 +176,52 @@
"creditMeta": "{credits} credits",
"errorFallback": "Video generation failed"
},
"agentNode": {
"templates": {
"campaignDistributor": {
"name": "Campaign Distributor",
"description": "Develops and distributes LemonSpace campaign content across social media and messenger channels."
}
},
"modelLabel": "Model",
"modelCreditMeta": "{model} - {credits} Cr",
"briefingLabel": "Briefing",
"briefingPlaceholder": "Describe the core task and desired output.",
"constraintsLabel": "Constraints",
"audienceLabel": "Audience",
"toneLabel": "Tone",
"targetChannelsLabel": "Target channels",
"targetChannelsPlaceholder": "LinkedIn, Instagram Feed",
"hardConstraintsLabel": "Hard constraints",
"hardConstraintsPlaceholder": "No emojis\nMax 120 words",
"runAgentButton": "Run agent",
"clarificationsLabel": "Clarifications",
"submitClarificationButton": "Submit clarification",
"templateReferenceLabel": "Template reference",
"templateReferenceChannelsLabel": "Channels",
"templateReferenceInputsLabel": "Inputs",
"templateReferenceOutputsLabel": "Outputs",
"executingStepFallback": "Executing step {current}/{total}",
"executingPlannedTotalFallback": "Executing planned outputs ({total} total)",
"executingPlannedFallback": "Executing planned outputs",
"offlineTitle": "Offline currently not supported",
"offlineDescription": "Agent run requires an active connection.",
"clarificationPrompts": {
"briefing": "What should the agent produce? Provide the brief in one or two sentences.",
"targetChannels": "Which channels should this run target? List at least one channel.",
"incomingContext": "No context was provided. What source context should the agent use?"
}
},
"agentOutputNode": {
"defaultTitle": "Agent output",
"plannedOutputDefaultTitle": "Planned output",
"skeletonBadge": "Skeleton",
"plannedOutputLabel": "Planned output",
"channelLabel": "Channel",
"typeLabel": "Type",
"bodyLabel": "Body",
"plannedContent": "Planned content"
},
"credits": {
"balance": "Balance",
"available": "Available",

155
tests/agent-node-runtime.test.ts
View File

@@ -89,6 +89,56 @@ vi.mock("@/components/canvas/nodes/base-node-wrapper", () => ({
default: ({ children }: { children: React.ReactNode }) => React.createElement("div", null, children),
}));
const translations: Record<string, string> = {
"agentNode.templates.campaignDistributor.name": "Campaign Distributor",
"agentNode.templates.campaignDistributor.description":
"Develops and distributes LemonSpace campaign content across social media and messenger channels.",
"agentNode.modelLabel": "Model",
"agentNode.modelCreditMeta": "{model} - {credits} Cr",
"agentNode.briefingLabel": "Briefing",
"agentNode.briefingPlaceholder": "Describe the core task and desired output.",
"agentNode.constraintsLabel": "Constraints",
"agentNode.audienceLabel": "Audience",
"agentNode.toneLabel": "Tone",
"agentNode.targetChannelsLabel": "Target channels",
"agentNode.targetChannelsPlaceholder": "LinkedIn, Instagram Feed",
"agentNode.hardConstraintsLabel": "Hard constraints",
"agentNode.hardConstraintsPlaceholder": "No emojis\nMax 120 words",
"agentNode.runAgentButton": "Run agent",
"agentNode.clarificationsLabel": "Clarifications",
"agentNode.submitClarificationButton": "Submit clarification",
"agentNode.templateReferenceLabel": "Template reference",
"agentNode.templateReferenceChannelsLabel": "Channels",
"agentNode.templateReferenceInputsLabel": "Inputs",
"agentNode.templateReferenceOutputsLabel": "Outputs",
"agentNode.executingStepFallback": "Executing step {current}/{total}",
"agentNode.executingPlannedTotalFallback": "Executing planned outputs ({total} total)",
"agentNode.executingPlannedFallback": "Executing planned outputs",
"agentNode.offlineTitle": "Offline currently not supported",
"agentNode.offlineDescription": "Agent run requires an active connection.",
"agentNode.clarificationPrompts.briefing":
"What should the agent produce? Provide the brief in one or two sentences.",
"agentNode.clarificationPrompts.targetChannels":
"Which channels should this run target? List at least one channel.",
"agentNode.clarificationPrompts.incomingContext":
"No context was provided. What source context should the agent use?",
};
vi.mock("next-intl", () => ({
useLocale: () => "de",
useTranslations: (namespace?: string) =>
(key: string, values?: Record<string, unknown>) => {
const fullKey = namespace ? `${namespace}.${key}` : key;
let text = translations[fullKey] ?? key;
if (values) {
for (const [name, value] of Object.entries(values)) {
text = text.replaceAll(`{${name}}`, String(value));
}
}
return text;
},
}));
vi.mock("@xyflow/react", () => ({
Handle: () => null,
Position: { Left: "left", Right: "right" },
@@ -143,8 +193,15 @@ describe("AgentNode runtime", () => {
canvasId: "canvas-1",
templateId: "campaign-distributor",
modelId: "openai/gpt-5.4-mini",
briefConstraints: {
briefing: "Draft channel-ready campaign copy",
audience: "SaaS founders",
tone: "Confident and practical",
targetChannels: ["LinkedIn", "Instagram Feed"],
hardConstraints: ["No emojis", "Max 120 words"],
},
clarificationQuestions: [
{ id: "audience", prompt: "Target audience?", required: true },
{ id: "briefing", prompt: "RAW_BRIEFING_PROMPT", required: true },
],
clarificationAnswers: {},
} as Record<string, unknown>,
@@ -167,9 +224,27 @@ describe("AgentNode runtime", () => {
expect(container.textContent).toContain("GPT-5.4 Mini");
expect(container.textContent).toContain("15 Cr");
expect(container.textContent).toContain("Channels");
expect(container.textContent).toContain("Expected Inputs");
expect(container.textContent).toContain("Expected Outputs");
expect(container.textContent).toContain("Briefing");
expect(container.textContent).toContain("Constraints");
expect(container.textContent).toContain("Template reference");
const briefingTextarea = container.querySelector('textarea[name="agent-briefing"]');
if (!(briefingTextarea instanceof HTMLTextAreaElement)) {
throw new Error("Briefing textarea not found");
}
expect(briefingTextarea.value).toBe("Draft channel-ready campaign copy");
const targetChannelsInput = container.querySelector('input[name="agent-target-channels"]');
if (!(targetChannelsInput instanceof HTMLInputElement)) {
throw new Error("Target channels input not found");
}
expect(targetChannelsInput.value).toBe("LinkedIn, Instagram Feed");
const hardConstraintsInput = container.querySelector('textarea[name="agent-hard-constraints"]');
if (!(hardConstraintsInput instanceof HTMLTextAreaElement)) {
throw new Error("Hard constraints textarea not found");
}
expect(hardConstraintsInput.value).toBe("No emojis\nMax 120 words");
await act(async () => {
modelSelect.value = "openai/gpt-5.4";
@@ -183,7 +258,71 @@ describe("AgentNode runtime", () => {
}),
);
const clarificationInput = container.querySelector('input[name="clarification-audience"]');
await act(async () => {
const valueSetter = Object.getOwnPropertyDescriptor(
HTMLTextAreaElement.prototype,
"value",
)?.set;
valueSetter?.call(briefingTextarea, "Adapt this launch to each channel");
briefingTextarea.dispatchEvent(new Event("input", { bubbles: true }));
});
expect(mocks.queueNodeDataUpdate).toHaveBeenCalledWith(
expect.objectContaining({
nodeId: "agent-1",
data: expect.objectContaining({
briefConstraints: expect.objectContaining({
briefing: "Adapt this launch to each channel",
}),
}),
}),
);
await act(async () => {
const valueSetter = Object.getOwnPropertyDescriptor(
HTMLInputElement.prototype,
"value",
)?.set;
valueSetter?.call(targetChannelsInput, "LinkedIn, X, TikTok");
targetChannelsInput.dispatchEvent(new Event("input", { bubbles: true }));
});
expect(mocks.queueNodeDataUpdate).toHaveBeenCalledWith(
expect.objectContaining({
nodeId: "agent-1",
data: expect.objectContaining({
briefConstraints: expect.objectContaining({
targetChannels: ["LinkedIn", "X", "TikTok"],
}),
}),
}),
);
await act(async () => {
const valueSetter = Object.getOwnPropertyDescriptor(
HTMLTextAreaElement.prototype,
"value",
)?.set;
valueSetter?.call(hardConstraintsInput, "No emojis\nMax 80 words, include CTA");
hardConstraintsInput.dispatchEvent(new Event("input", { bubbles: true }));
});
expect(mocks.queueNodeDataUpdate).toHaveBeenCalledWith(
expect.objectContaining({
nodeId: "agent-1",
data: expect.objectContaining({
briefConstraints: expect.objectContaining({
hardConstraints: ["No emojis", "Max 80 words", "include CTA"],
}),
}),
}),
);
expect(container.textContent).toContain(
"What should the agent produce? Provide the brief in one or two sentences.",
);
const clarificationInput = container.querySelector('input[name="clarification-briefing"]');
if (!(clarificationInput instanceof HTMLInputElement)) {
throw new Error("Clarification input not found");
}
@@ -201,7 +340,7 @@ describe("AgentNode runtime", () => {
expect.objectContaining({
nodeId: "agent-1",
data: expect.objectContaining({
clarificationAnswers: expect.objectContaining({ audience: "SaaS founders" }),
clarificationAnswers: expect.objectContaining({ briefing: "SaaS founders" }),
}),
}),
);
@@ -221,6 +360,7 @@ describe("AgentNode runtime", () => {
canvasId: "canvas-1",
nodeId: "agent-1",
modelId: "openai/gpt-5.4",
locale: "de",
});
const submitButton = Array.from(container.querySelectorAll("button")).find((element) =>
@@ -237,7 +377,8 @@ describe("AgentNode runtime", () => {
expect(mocks.resumeAgent).toHaveBeenCalledWith({
canvasId: "canvas-1",
nodeId: "agent-1",
clarificationAnswers: { audience: "SaaS founders" },
clarificationAnswers: { briefing: "SaaS founders" },
locale: "de",
});
});

44
tests/agent-node.test.ts
View File

@@ -22,6 +22,45 @@ vi.mock("@xyflow/react", () => ({
Position: { Left: "left", Right: "right" },
}));
const translations: Record<string, string> = {
"agentNode.templates.campaignDistributor.name": "Campaign Distributor",
"agentNode.templates.campaignDistributor.description":
"Develops and distributes LemonSpace campaign content across social media and messenger channels.",
"agentNode.modelLabel": "Model",
"agentNode.modelCreditMeta": "{model} - {credits} Cr",
"agentNode.briefingLabel": "Briefing",
"agentNode.briefingPlaceholder": "Describe the core task and desired output.",
"agentNode.constraintsLabel": "Constraints",
"agentNode.audienceLabel": "Audience",
"agentNode.toneLabel": "Tone",
"agentNode.targetChannelsLabel": "Target channels",
"agentNode.targetChannelsPlaceholder": "LinkedIn, Instagram Feed",
"agentNode.hardConstraintsLabel": "Hard constraints",
"agentNode.hardConstraintsPlaceholder": "No emojis\nMax 120 words",
"agentNode.runAgentButton": "Run agent",
"agentNode.clarificationsLabel": "Clarifications",
"agentNode.submitClarificationButton": "Submit clarification",
"agentNode.templateReferenceLabel": "Template reference",
"agentNode.templateReferenceChannelsLabel": "Channels",
"agentNode.templateReferenceInputsLabel": "Inputs",
"agentNode.templateReferenceOutputsLabel": "Outputs",
};
vi.mock("next-intl", () => ({
useLocale: () => "de",
useTranslations: (namespace?: string) =>
(key: string, values?: Record<string, unknown>) => {
const fullKey = namespace ? `${namespace}.${key}` : key;
let text = translations[fullKey] ?? key;
if (values) {
for (const [name, value] of Object.entries(values)) {
text = text.replaceAll(`{${name}}`, String(value));
}
}
return text;
},
}));
import AgentNode from "@/components/canvas/nodes/agent-node";
(globalThis as typeof globalThis & { IS_REACT_ACT_ENVIRONMENT?: boolean }).IS_REACT_ACT_ENVIRONMENT = true;
@@ -73,8 +112,9 @@ describe("AgentNode", () => {
});
expect(container.textContent).toContain("Campaign Distributor");
expect(container.textContent).toContain("Instagram Feed");
expect(container.textContent).toContain("Caption-Pakete");
expect(container.textContent).toContain("Briefing");
expect(container.textContent).toContain("Constraints");
expect(container.textContent).toContain("Template reference");
expect(handleCalls.filter((call) => call.type === "target")).toHaveLength(1);
expect(handleCalls.filter((call) => call.type === "source")).toHaveLength(1);
});

64
tests/agent-output-node.test.ts
View File

@@ -22,6 +22,31 @@ vi.mock("@xyflow/react", () => ({
Position: { Left: "left", Right: "right" },
}));
const translations: Record<string, string> = {
"agentOutputNode.defaultTitle": "Agent output",
"agentOutputNode.plannedOutputDefaultTitle": "Planned output",
"agentOutputNode.skeletonBadge": "Skeleton",
"agentOutputNode.plannedOutputLabel": "Planned output",
"agentOutputNode.channelLabel": "Channel",
"agentOutputNode.typeLabel": "Type",
"agentOutputNode.bodyLabel": "Body",
"agentOutputNode.plannedContent": "Planned content",
};
vi.mock("next-intl", () => ({
useTranslations: (namespace?: string) =>
(key: string, values?: Record<string, unknown>) => {
const fullKey = namespace ? `${namespace}.${key}` : key;
let text = translations[fullKey] ?? key;
if (values) {
for (const [name, value] of Object.entries(values)) {
text = text.replaceAll(`{${name}}`, String(value));
}
}
return text;
},
}));
import AgentOutputNode from "@/components/canvas/nodes/agent-output-node";
(globalThis as typeof globalThis & { IS_REACT_ACT_ENVIRONMENT?: boolean }).IS_REACT_ACT_ENVIRONMENT = true;
@@ -79,6 +104,45 @@ describe("AgentOutputNode", () => {
expect(container.textContent).toContain("instagram-feed");
expect(container.textContent).toContain("caption");
expect(container.textContent).toContain("A short punchy caption with hashtags");
expect(container.querySelector('[data-testid="agent-output-meta-strip"]')).not.toBeNull();
expect(container.querySelector('[data-testid="agent-output-text-body"]')).not.toBeNull();
});
it("renders parseable json body in a pretty-printed code block", async () => {
container = document.createElement("div");
document.body.appendChild(container);
root = createRoot(container);
await act(async () => {
root?.render(
React.createElement(AgentOutputNode, {
id: "agent-output-4",
selected: false,
dragging: false,
draggable: true,
selectable: true,
deletable: true,
zIndex: 1,
isConnectable: true,
type: "agent-output",
data: {
title: "JSON output",
channel: "api",
outputType: "payload",
body: '{"post":"Hello","tags":["launch","news"]}',
_status: "done",
} as Record<string, unknown>,
positionAbsoluteX: 0,
positionAbsoluteY: 0,
}),
);
});
const jsonBody = container.querySelector('[data-testid="agent-output-json-body"]');
expect(jsonBody).not.toBeNull();
expect(jsonBody?.textContent).toContain('"post": "Hello"');
expect(jsonBody?.textContent).toContain('"tags": [');
expect(container.querySelector('[data-testid="agent-output-text-body"]')).toBeNull();
});
it("renders input-only handle agent-output-in", async () => {

108
tests/lib/agent-run-contract.test.ts
View File

@@ -2,10 +2,14 @@ import { describe, expect, it } from "vitest";
import {
areClarificationAnswersComplete,
buildPreflightClarificationQuestions,
normalizeAgentLocale,
normalizeAgentExecutionPlan,
normalizeAgentBriefConstraints,
normalizeAgentOutputDraft,
type AgentClarificationAnswerMap,
type AgentClarificationQuestion,
type AgentBriefConstraints,
type AgentExecutionPlan,
} from "@/lib/agent-run-contract";
@@ -178,4 +182,108 @@ describe("agent run contract helpers", () => {
expect(normalized.steps.map((step) => step.id)).toEqual(["step", "step-2", "step-3"]);
});
});
describe("normalizeAgentBriefConstraints", () => {
it("trims fields and normalizes target channels", () => {
const normalized = normalizeAgentBriefConstraints({
briefing: " Build a launch sequence ",
audience: " SaaS founders ",
tone: " concise ",
targetChannels: [" Email ", "", "LinkedIn", "email", " "],
hardConstraints: [
" Do not mention pricing ",
"",
"Keep under 120 words",
"Keep under 120 words",
],
});
expect(normalized).toEqual<AgentBriefConstraints>({
briefing: "Build a launch sequence",
audience: "SaaS founders",
tone: "concise",
targetChannels: ["email", "linkedin"],
hardConstraints: ["Do not mention pricing", "Keep under 120 words"],
});
});
it("falls back to safe empty values for invalid payloads", () => {
const normalized = normalizeAgentBriefConstraints({
briefing: null,
audience: undefined,
tone: 3,
targetChannels: [" ", null, 1],
hardConstraints: "must be array",
});
expect(normalized).toEqual<AgentBriefConstraints>({
briefing: "",
audience: "",
tone: "",
targetChannels: [],
hardConstraints: [],
});
});
});
describe("buildPreflightClarificationQuestions", () => {
it("builds deterministic required questions for missing preflight requirements", () => {
const questions = buildPreflightClarificationQuestions({
briefConstraints: {
briefing: "",
audience: "Founders",
tone: "confident",
targetChannels: [],
hardConstraints: [],
},
incomingContextCount: 0,
});
expect(questions).toEqual<AgentClarificationQuestion[]>([
{
id: "briefing",
prompt: "What should the agent produce? Provide the brief in one or two sentences.",
required: true,
},
{
id: "target-channels",
prompt: "Which channels should this run target? List at least one channel.",
required: true,
},
{
id: "incoming-context",
prompt: "No context was provided. What source context should the agent use?",
required: true,
},
]);
});
it("returns an empty list when all preflight requirements are satisfied", () => {
const questions = buildPreflightClarificationQuestions({
briefConstraints: {
briefing: "Create 3 posts",
audience: "Marketers",
tone: "friendly",
targetChannels: ["x"],
hardConstraints: ["No emojis"],
},
incomingContextCount: 2,
});
expect(questions).toEqual([]);
});
});
describe("normalizeAgentLocale", () => {
it("returns supported locale values", () => {
expect(normalizeAgentLocale("de")).toBe("de");
expect(normalizeAgentLocale("en")).toBe("en");
});
it("falls back to de for unsupported values", () => {
expect(normalizeAgentLocale("fr")).toBe("de");
expect(normalizeAgentLocale(undefined)).toBe("de");
expect(normalizeAgentLocale(null)).toBe("de");
});
});
});