Server state management with TanStack Query v5 for Google Antigravity projects including queries, mutations, and optimistic updates.
# TanStack Query v5 Patterns for Google Antigravity
Master server state management with TanStack Query v5 in your Google Antigravity IDE projects. This comprehensive guide covers queries, mutations, optimistic updates, and caching strategies optimized for Gemini 3 agentic development.
## Query Client Configuration
Set up TanStack Query with proper defaults:
```typescript
// lib/query-client.ts
import { QueryClient } from '@tanstack/react-query';
export function makeQueryClient() {
return new QueryClient({
defaultOptions: {
queries: {
staleTime: 60 * 1000, // 1 minute
gcTime: 5 * 60 * 1000, // 5 minutes (formerly cacheTime)
retry: (failureCount, error) => {
// Don't retry on 4xx errors
if (error instanceof Response && error.status >= 400 && error.status < 500) {
return false;
}
return failureCount < 3;
},
refetchOnWindowFocus: false,
},
mutations: {
retry: false,
},
},
});
}
// Singleton for client-side
let browserQueryClient: QueryClient | undefined = undefined;
export function getQueryClient() {
if (typeof window === 'undefined') {
// Server: always make a new query client
return makeQueryClient();
}
// Browser: make a new client if we don't have one
if (!browserQueryClient) {
browserQueryClient = makeQueryClient();
}
return browserQueryClient;
}
```
## Provider Setup
Configure the query provider for Next.js:
```typescript
// components/providers/QueryProvider.tsx
'use client';
import { QueryClientProvider } from '@tanstack/react-query';
import { ReactQueryDevtools } from '@tanstack/react-query-devtools';
import { getQueryClient } from '@/lib/query-client';
export function QueryProvider({ children }: { children: React.ReactNode }) {
const queryClient = getQueryClient();
return (
<QueryClientProvider client={queryClient}>
{children}
<ReactQueryDevtools initialIsOpen={false} />
</QueryClientProvider>
);
}
```
## Query Patterns
Create type-safe query hooks:
```typescript
// hooks/queries/usePrompts.ts
import { useQuery, useInfiniteQuery, useSuspenseQuery } from '@tanstack/react-query';
// Query key factory for type safety
export const promptKeys = {
all: ['prompts'] as const,
lists: () => [...promptKeys.all, 'list'] as const,
list: (filters: PromptFilters) => [...promptKeys.lists(), filters] as const,
details: () => [...promptKeys.all, 'detail'] as const,
detail: (slug: string) => [...promptKeys.details(), slug] as const,
starred: (userId: string) => [...promptKeys.all, 'starred', userId] as const,
};
interface PromptFilters {
search?: string;
category?: string;
page?: number;
}
// Fetch function
async function fetchPrompts(filters: PromptFilters) {
const params = new URLSearchParams();
if (filters.search) params.set('search', filters.search);
if (filters.category) params.set('category', filters.category);
if (filters.page) params.set('page', String(filters.page));
const response = await fetch(`/api/prompts?${params}`);
if (!response.ok) throw new Error('Failed to fetch prompts');
return response.json() as Promise<PromptsResponse>;
}
// Basic query hook
export function usePrompts(filters: PromptFilters = {}) {
return useQuery({
queryKey: promptKeys.list(filters),
queryFn: () => fetchPrompts(filters),
placeholderData: (previousData) => previousData,
});
}
// Suspense query hook (for React Suspense)
export function usePromptsSuspense(filters: PromptFilters = {}) {
return useSuspenseQuery({
queryKey: promptKeys.list(filters),
queryFn: () => fetchPrompts(filters),
});
}
// Infinite query for pagination
export function useInfinitePrompts(filters: Omit<PromptFilters, 'page'> = {}) {
return useInfiniteQuery({
queryKey: promptKeys.list(filters),
queryFn: ({ pageParam }) => fetchPrompts({ ...filters, page: pageParam }),
initialPageParam: 1,
getNextPageParam: (lastPage) =>
lastPage.hasMore ? lastPage.page + 1 : undefined,
getPreviousPageParam: (firstPage) =>
firstPage.page > 1 ? firstPage.page - 1 : undefined,
});
}
// Single prompt query
export function usePrompt(slug: string) {
return useQuery({
queryKey: promptKeys.detail(slug),
queryFn: async () => {
const response = await fetch(`/api/prompts/${slug}`);
if (!response.ok) {
if (response.status === 404) {
throw new NotFoundError('Prompt not found');
}
throw new Error('Failed to fetch prompt');
}
return response.json() as Promise<Prompt>;
},
enabled: Boolean(slug),
});
}
```
## Mutation Patterns
Implement mutations with optimistic updates:
```typescript
// hooks/mutations/useStarPrompt.ts
import { useMutation, useQueryClient } from '@tanstack/react-query';
import { promptKeys } from '../queries/usePrompts';
interface StarMutationContext {
previousPrompt?: Prompt;
previousList?: PromptsResponse;
}
export function useStarPrompt() {
const queryClient = useQueryClient();
return useMutation({
mutationFn: async ({ promptId }: { promptId: string }) => {
const response = await fetch(`/api/prompts/${promptId}/star`, {
method: 'POST',
});
if (!response.ok) throw new Error('Failed to star prompt');
return response.json() as Promise<{ starred: boolean }>;
},
onMutate: async ({ promptId }): Promise<StarMutationContext> => {
// Cancel outgoing queries
await queryClient.cancelQueries({ queryKey: promptKeys.all });
// Snapshot current state
const previousPrompt = queryClient.getQueryData<Prompt>(
promptKeys.detail(promptId)
);
// Optimistically update the detail
if (previousPrompt) {
queryClient.setQueryData<Prompt>(promptKeys.detail(promptId), {
...previousPrompt,
isStarred: !previousPrompt.isStarred,
starCount: previousPrompt.isStarred
? previousPrompt.starCount - 1
: previousPrompt.starCount + 1,
});
}
return { previousPrompt };
},
onError: (error, variables, context) => {
// Rollback on error
if (context?.previousPrompt) {
queryClient.setQueryData(
promptKeys.detail(variables.promptId),
context.previousPrompt
);
}
},
onSettled: (data, error, variables) => {
// Invalidate to refetch fresh data
queryClient.invalidateQueries({
queryKey: promptKeys.detail(variables.promptId),
});
queryClient.invalidateQueries({
queryKey: promptKeys.lists(),
});
},
});
}
// Create prompt mutation
export function useCreatePrompt() {
const queryClient = useQueryClient();
return useMutation({
mutationFn: async (data: CreatePromptInput) => {
const response = await fetch('/api/prompts', {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify(data),
});
if (!response.ok) {
const error = await response.json();
throw new Error(error.message || 'Failed to create prompt');
}
return response.json() as Promise<Prompt>;
},
onSuccess: (newPrompt) => {
// Add to cache
queryClient.setQueryData(
promptKeys.detail(newPrompt.slug),
newPrompt
);
// Invalidate lists to include new prompt
queryClient.invalidateQueries({
queryKey: promptKeys.lists(),
});
},
});
}
```
## Prefetching Strategies
Implement smart prefetching:
```typescript
// lib/prefetch.ts
import { QueryClient } from '@tanstack/react-query';
import { promptKeys } from '@/hooks/queries/usePrompts';
export async function prefetchPrompt(queryClient: QueryClient, slug: string) {
await queryClient.prefetchQuery({
queryKey: promptKeys.detail(slug),
queryFn: () => fetch(`/api/prompts/${slug}`).then((r) => r.json()),
staleTime: 60 * 1000,
});
}
// Component with prefetch on hover
export function PromptCard({ prompt }: { prompt: PromptSummary }) {
const queryClient = useQueryClient();
const handleMouseEnter = () => {
// Prefetch prompt details on hover
queryClient.prefetchQuery({
queryKey: promptKeys.detail(prompt.slug),
queryFn: () => fetch(`/api/prompts/${prompt.slug}`).then((r) => r.json()),
staleTime: 60 * 1000,
});
};
return (
<Link
href={`/prompts/${prompt.slug}`}
onMouseEnter={handleMouseEnter}
className="prompt-card"
>
<h3>{prompt.title}</h3>
<p>{prompt.description}</p>
</Link>
);
}
// Server-side prefetching with Next.js
// app/prompts/[slug]/page.tsx
import { dehydrate, HydrationBoundary } from '@tanstack/react-query';
import { getQueryClient } from '@/lib/query-client';
import { promptKeys } from '@/hooks/queries/usePrompts';
export default async function PromptPage({ params }: { params: { slug: string } }) {
const queryClient = getQueryClient();
await queryClient.prefetchQuery({
queryKey: promptKeys.detail(params.slug),
queryFn: () => fetchPrompt(params.slug),
});
return (
<HydrationBoundary state={dehydrate(queryClient)}>
<PromptDetail slug={params.slug} />
</HydrationBoundary>
);
}
```
## Query Composition
Combine queries for complex data needs:
```typescript
// hooks/queries/usePromptWithRelated.ts
import { useQueries, useQuery } from '@tanstack/react-query';
export function usePromptWithRelated(slug: string) {
const promptQuery = useQuery({
queryKey: promptKeys.detail(slug),
queryFn: () => fetchPrompt(slug),
enabled: Boolean(slug),
});
const relatedQueries = useQueries({
queries: (promptQuery.data?.tags || []).slice(0, 3).map((tag) => ({
queryKey: [...promptKeys.lists(), { tag, limit: 4 }],
queryFn: () => fetchPrompts({ tag, limit: 4 }),
enabled: Boolean(promptQuery.data),
})),
});
const isLoading = promptQuery.isLoading || relatedQueries.some((q) => q.isLoading);
const isError = promptQuery.isError || relatedQueries.some((q) => q.isError);
const relatedPrompts = relatedQueries
.flatMap((q) => q.data?.prompts || [])
.filter((p) => p.slug !== slug)
.slice(0, 6);
return {
prompt: promptQuery.data,
relatedPrompts,
isLoading,
isError,
};
}
```
## Best Practices
1. **Use query key factories** for consistent key management
2. **Implement optimistic updates** for better UX
3. **Configure appropriate stale times** based on data volatility
4. **Use suspense queries** with React Suspense boundaries
5. **Prefetch data** on hover for faster navigation
6. **Leverage infinite queries** for pagination
7. **Handle errors gracefully** with error boundariesThis tanstack-query prompt is ideal for developers working on:
By using this prompt, you can save hours of manual coding and ensure best practices are followed from the start. It's particularly valuable for teams looking to maintain consistency across their tanstack-query implementations.
Yes! All prompts on Antigravity AI Directory are free to use for both personal and commercial projects. No attribution required, though it's always appreciated.
This prompt works excellently with Claude, ChatGPT, Cursor, GitHub Copilot, and other modern AI coding assistants. For best results, use models with large context windows.
You can modify the prompt by adding specific requirements, constraints, or preferences. For tanstack-query projects, consider mentioning your framework version, coding style, and any specific libraries you're using.