feat: AI assistant (HartBOT), demand filling, budget-per-role, project favorites, and UX improvements
AI Assistant (HartBOT): - Chat panel with inline layout, session persistence, message history (up-arrow recall) - OpenAI function calling with 20+ tools (search, navigate, create/cancel allocations, update status) - RBAC-aware tool filtering, fuzzy search with word-level matching - Navigation actions (router.push) and data invalidation after mutations - Country/metro city/org unit/role filtering on resource search Demand Filling Enhancements: - Two-phase fill modal: plan multiple resources, then confirm & assign all at once - Availability preview per resource (available/partial/conflict days, existing bookings) - Coverage bar showing demand hours distribution across assigned resources - Fill demand from project detail page (new Assign button per demand) - Fixed: filled demands no longer shown on timeline, demand bars no longer overlap Budget per Role: - DemandRequirement.budgetCents field (schema + API + UI) - Project wizard step 3: budget input per role with allocation summary bar - Project detail: allocated vs booked budget per demand - Fill demand modal: role budget display with cost estimates - AllocationModal: budget field for demand editing Project Favorites: - User.favoriteProjectIds (JSONB) with toggle API - Star button on projects list and detail page (optimistic updates) - "My Projects" dashboard widget (favorites + responsible person projects) Project Management: - Edit project from detail page (ProjectModal integration) - Edit demands from detail page (AllocationModal integration) - Admin-only project deletion (cascades assignments + demands) - Create user accounts from admin panel Timeline Fixes: - Country multi-select filter with backend support - URL param sync for same-page navigation (AI assistant integration) - Demand lane stacking (no more overlapping bars) - Single-day booking resize handles (always visible, min 6px) - Single-day resize allowed (start === end) - "All Clients" toggle (select all / deselect all) Other Fixes: - crypto.randomUUID fallback for non-secure contexts - Chat message limit raised (200 max, client sends last 40) - Status dropdown portal (no longer clipped by table overflow) - Cents display restored in budget views (2 decimal places) - Allocations grouped view with project sub-groups (collapsed by default) - Server-side resource search for project wizard (no 500 limit) Co-Authored-By: claude-flow <ruv@ruv.net>
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/**
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* AI Assistant router — provides a chat endpoint that uses OpenAI Function Calling
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* to answer questions about Planarchy data and modify resources/projects.
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*/
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import { z } from "zod";
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import { TRPCError } from "@trpc/server";
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import { resolvePermissions, type PermissionOverrides, type SystemRole } from "@planarchy/shared";
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import { createTRPCRouter, protectedProcedure } from "../trpc.js";
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import { createAiClient, isAiConfigured, parseAiError } from "../ai-client.js";
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import { TOOL_DEFINITIONS, executeTool, type ToolContext, type ToolAction } from "./assistant-tools.js";
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const MAX_TOOL_ITERATIONS = 8;
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const SYSTEM_PROMPT = `Du bist der Planarchy-Assistent — ein hilfreicher AI-Assistent für Ressourcenplanung und Projektmanagement in einer 3D-Produktionsumgebung.
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Deine Fähigkeiten:
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- Fragen über Ressourcen, Projekte, Allokationen, Budget, Urlaub, Estimates, Org-Struktur beantworten
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- Chargeability-Analysen, Urlaubsübersichten, Budget-Analysen
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- Ressourcen/Projekte aktualisieren, Allokationen erstellen/stornieren (nur mit Berechtigung + expliziter Bestätigung)
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- Den User zu relevanten Seiten navigieren (Timeline, Dashboard, etc. mit Filtern)
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Wichtige Regeln:
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- Antworte in der Sprache des Users (Deutsch oder Englisch)
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- Geldbeträge: intern in Cent, konvertiere zu EUR für den User
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- Vor Datenänderungen: kurze Zusammenfassung + Bestätigung einholen
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- Sei KURZ und DIREKT. Keine langen Erklärungen wenn nicht nötig. Antworte knapp und präzise.
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- Rufe Tools PARALLEL auf wenn möglich (z.B. search_resources + list_allocations gleichzeitig)
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- Fasse Ergebnisse kompakt zusammen — keine unnötigen Wiederholungen der Tool-Ergebnisse
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- Wenn eine Suche keine Treffer ergibt, versuche einzelne Wörter aus der Anfrage als Suchbegriffe. Die Tools unterstützen automatisch wort-basierte Fuzzy-Suche — zeige dem User die Vorschläge wenn welche gefunden werden
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Datenmodell:
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- Ressourcen: EID, FTE (0-1), LCR (EUR/h), Chargeability-Target, Skills, Chapter, OrgUnit
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- Projekte: ShortCode, Budget (Cent), Win-Probability, Status (DRAFT/ACTIVE/ON_HOLD/COMPLETED/CANCELLED)
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- Allokationen (Assignments): resourceId + projectId, hoursPerDay, dailyCostCents, Zeitraum, Status (PROPOSED/CONFIRMED/ACTIVE/COMPLETED/CANCELLED)
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- Chargeability = gebuchte/verfügbare Stunden × 100%
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- Urlaub: Typen VACATION/SICK/PARENTAL/SPECIAL/PUBLIC_HOLIDAY, Status PENDING/APPROVED/REJECTED/CANCELLED
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`;
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/** Map tool names to the permission required to use them */
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const TOOL_PERMISSION_MAP: Record<string, string> = {
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update_resource: "manageResources",
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update_project: "manageProjects",
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create_allocation: "manageAllocations",
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cancel_allocation: "manageAllocations",
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update_allocation_status: "manageAllocations",
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};
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/** Tools that require cost visibility */
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const COST_TOOLS = new Set(["get_budget_status", "get_chargeability"]);
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export const assistantRouter = createTRPCRouter({
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chat: protectedProcedure
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.input(z.object({
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messages: z.array(z.object({
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role: z.enum(["user", "assistant"]),
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content: z.string(),
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})).min(1).max(200),
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pageContext: z.string().optional(),
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}))
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.mutation(async ({ ctx, input }) => {
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// 1. Load AI settings
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const settings = await ctx.db.systemSettings.findUnique({
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where: { id: "singleton" },
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});
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if (!isAiConfigured(settings)) {
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throw new TRPCError({
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code: "PRECONDITION_FAILED",
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message: "AI is not configured. Please set up OpenAI credentials in Admin → Settings.",
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});
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}
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const client = createAiClient(settings!);
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const userRole = ctx.dbUser?.systemRole ?? "USER";
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// Use configured token limit, but ensure a reasonable minimum for multi-tool responses
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const maxTokens = Math.max(settings?.aiMaxCompletionTokens ?? 2500, 1500);
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const temperature = settings?.aiTemperature ?? 0.7;
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const model = settings?.azureOpenAiDeployment ?? "gpt-4o-mini";
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// 2. Resolve granular permissions
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const permissions = resolvePermissions(
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userRole as SystemRole,
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(ctx.dbUser?.permissionOverrides as PermissionOverrides | null) ?? null,
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);
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const permissionList = [...permissions];
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// 3. Build system prompt with user context
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let contextBlock = `\n\nAktueller User: ${ctx.session?.user?.name ?? "Unknown"} (Rolle: ${userRole})`;
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contextBlock += `\nBerechtigungen: ${permissionList.length > 0 ? permissionList.join(", ") : "Nur Lese-Zugriff auf eigene Daten"}`;
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if (input.pageContext) {
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contextBlock += `\nAktuelle Seite: ${input.pageContext}`;
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contextBlock += `\nHinweis: Beziehe dich bevorzugt auf den Kontext der aktuellen Seite wenn die Frage des Users dazu passt.`;
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}
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// eslint-disable-next-line @typescript-eslint/no-explicit-any
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const openaiMessages: any[] = [
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{ role: "system", content: SYSTEM_PROMPT + contextBlock },
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...input.messages.slice(-20).map((m) => ({
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role: m.role,
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content: m.content,
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})),
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];
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// 4. Filter tools based on granular permissions
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const availableTools = TOOL_DEFINITIONS.filter((t) => {
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const toolName = t.function.name;
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// Check write permission
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const requiredPerm = TOOL_PERMISSION_MAP[toolName];
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if (requiredPerm && !permissions.has(requiredPerm as import("@planarchy/shared").PermissionKey)) {
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return false;
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}
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// Hide cost/budget tools if user lacks viewCosts
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if (COST_TOOLS.has(toolName) && !permissions.has("viewCosts" as import("@planarchy/shared").PermissionKey)) {
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return false;
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}
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return true;
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});
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// 5. Function calling loop
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const toolCtx: ToolContext = { db: ctx.db, userRole, permissions };
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const collectedActions: ToolAction[] = [];
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for (let i = 0; i < MAX_TOOL_ITERATIONS; i++) {
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// eslint-disable-next-line @typescript-eslint/no-explicit-any
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let response: any;
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try {
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response = await client.chat.completions.create({
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model,
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messages: openaiMessages,
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// eslint-disable-next-line @typescript-eslint/no-explicit-any
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tools: availableTools as any,
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max_completion_tokens: maxTokens,
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temperature,
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});
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} catch (err) {
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throw new TRPCError({
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code: "INTERNAL_SERVER_ERROR",
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message: `AI error: ${parseAiError(err)}`,
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});
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}
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const choice = response.choices?.[0];
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if (!choice) {
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throw new TRPCError({ code: "INTERNAL_SERVER_ERROR", message: "No response from AI" });
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}
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// eslint-disable-next-line @typescript-eslint/no-explicit-any
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const msg = choice.message as any;
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// If the AI wants to call tools
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if (msg.tool_calls && msg.tool_calls.length > 0) {
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openaiMessages.push(msg);
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// eslint-disable-next-line @typescript-eslint/no-explicit-any
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for (const toolCall of msg.tool_calls as Array<{ id: string; function: { name: string; arguments: string } }>) {
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const result = await executeTool(
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toolCall.function.name,
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toolCall.function.arguments,
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toolCtx,
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);
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// Collect any actions (e.g. navigation)
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if (result.action) {
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collectedActions.push(result.action);
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}
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openaiMessages.push({
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role: "tool",
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tool_call_id: toolCall.id,
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content: result.content,
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});
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}
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continue;
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}
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// AI returned a text response — we're done
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return {
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content: (msg.content as string) ?? "I couldn't generate a response.",
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role: "assistant" as const,
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...(collectedActions.length > 0 ? { actions: collectedActions } : {}),
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};
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}
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// Exceeded max iterations
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return {
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content: "I had to stop after too many tool calls. Please try a simpler question.",
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role: "assistant" as const,
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...(collectedActions.length > 0 ? { actions: collectedActions } : {}),
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};
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}),
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});
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