LobeHub Store Data Structures

How to structure data in Zustand stores for fast list rendering, multi-detail caching, and ergonomic optimistic updates.

Core Principles

✅ DO

1. Separate List and Detail — different structures for list pages and detail pages
2. Use Map for Details — cache multiple detail pages with Record<string, Detail>
3. Use Array for Lists — simple arrays for list display
4. Types from @lobechat/types — never use @lobechat/database types in stores
5. Distinguish List and Detail types — List types may have computed UI fields

❌ DON'T

1. Don't use a single detail object — can't cache multiple pages
2. Don't mix List and Detail types — they have different purposes
3. Don't use database types — use types from @lobechat/types
4. Don't use Map for lists — simple arrays are sufficient

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Type Definitions

Each entity gets its own file under @lobechat/types/. Each file exports two types:

• Detail type — full entity, including heavy fields (rubrics, content, editor state, …)
• List item type — a subset that excludes heavy fields, may add computed UI fields (counts, timestamps formatted for display)

Important: the List type is a subset, not an extends of Detail. Extending pulls the heavy fields right back in.

See references/types.md for full worked examples (Benchmark, Document) and the heavy-field exclusion checklist.

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When to Use Map vs Array

Use Map + Reducer — for Detail Data

✅ Detail page data caching — multiple detail pages cached simultaneously ✅ Optimistic updates — update UI before API responds ✅ Per-item loading states — track which items are being updated ✅ Multi-page navigation — user can switch between details without refetching

benchmarkDetailMap: Record<string, AgentEvalBenchmark>;

Examples: benchmark detail pages, dataset detail pages, user profiles.

Use Simple Array — for List Data

✅ List display — lists, tables, cards ✅ Refresh as a whole — entire list refreshes together ✅ No per-item updates — no need to mutate individual rows in place ✅ Simple data flow — fewer moving parts

benchmarkList: AgentEvalBenchmarkListItem[];

Examples: benchmark list, dataset list, user list.

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State Structure Pattern

// src/store/eval/slices/benchmark/initialState.ts
import type { AgentEvalBenchmark, AgentEvalBenchmarkListItem } from '@lobechat/types';

export interface BenchmarkSliceState {
  // List — simple array
  benchmarkList: AgentEvalBenchmarkListItem[];
  benchmarkListInit: boolean;

  // Detail — map for multi-entity caching
  benchmarkDetailMap: Record<string, AgentEvalBenchmark>;
  loadingBenchmarkDetailIds: string[]; // per-item loading

  // Mutation states (drive form-level UI)
  isCreatingBenchmark: boolean;
  isUpdatingBenchmark: boolean;
  isDeletingBenchmark: boolean;
}

export const benchmarkInitialState: BenchmarkSliceState = {
  benchmarkList: [],
  benchmarkListInit: false,
  benchmarkDetailMap: {},
  loadingBenchmarkDetailIds: [],
  isCreatingBenchmark: false,
  isUpdatingBenchmark: false,
  isDeletingBenchmark: false,
};

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Reducer Pattern (for Detail Map)

When the Detail Map needs optimistic updates (i.e. the user edits a row and the UI should reflect it before the server confirms), wire a typed reducer instead of inlining set calls. This keeps mutations testable and the dispatch surface small.

See references/reducer.md for the full discriminated-union action types, the produce-based reducer, and the internal_dispatch* slice methods that connect them to Zustand.

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Data Structure Comparison

❌ WRONG — Single Detail Object

interface BenchmarkSliceState {
  benchmarkDetail: AgentEvalBenchmark | null;
  isLoadingBenchmarkDetail: boolean;
}

Problems:

• Can only cache one detail page at a time
• Switching between details forces refetch
• No optimistic updates
• No per-item loading states

✅ CORRECT — Separate List and Detail

interface BenchmarkSliceState {
  benchmarkList: AgentEvalBenchmarkListItem[];
  benchmarkListInit: boolean;

  benchmarkDetailMap: Record<string, AgentEvalBenchmark>;
  loadingBenchmarkDetailIds: string[];

  isCreatingBenchmark: boolean;
  isUpdatingBenchmark: boolean;
  isDeletingBenchmark: boolean;
}

Benefits:

• Cache multiple detail pages
• Fast navigation between cached details
• Optimistic updates via reducer
• Per-item loading states
• Clear separation of concerns

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Component Usage

Accessing List Data

const BenchmarkList = () => {
  const benchmarks = useEvalStore((s) => s.benchmarkList);
  const isInit = useEvalStore((s) => s.benchmarkListInit);

  if (!isInit) return <Loading />;
  return (
    <div>
      {benchmarks.map((b) => (
        <BenchmarkCard key={b.id} name={b.name} testCaseCount={b.testCaseCount} />
      ))}
    </div>
  );
};

Accessing Detail Data

const BenchmarkDetail = () => {
  const { benchmarkId } = useParams<{ benchmarkId: string }>();

  const benchmark = useEvalStore((s) =>
    benchmarkId ? s.benchmarkDetailMap[benchmarkId] : undefined,
  );
  const isLoading = useEvalStore((s) =>
    benchmarkId ? s.loadingBenchmarkDetailIds.includes(benchmarkId) : false,
  );

  if (!benchmark) return <Loading />;
  return (
    <div>
      <h1>{benchmark.name}</h1>
      {isLoading && <Spinner />}
    </div>
  );
};

Using Selectors (Recommended)

// src/store/eval/slices/benchmark/selectors.ts
export const benchmarkSelectors = {
  getBenchmarkDetail: (id: string) => (s: EvalStore) => s.benchmarkDetailMap[id],
  isLoadingBenchmarkDetail: (id: string) => (s: EvalStore) =>
    s.loadingBenchmarkDetailIds.includes(id),
};

// In component
const benchmark = useEvalStore(benchmarkSelectors.getBenchmarkDetail(benchmarkId!));
const isLoading = useEvalStore(benchmarkSelectors.isLoadingBenchmarkDetail(benchmarkId!));

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Decision Tree

Need to store data?
│
├─ Is it a LIST for display?
│  └─ ✅ Use simple array: `xxxList: XxxListItem[]`
│     - May include computed fields
│     - Refreshed as a whole
│     - No optimistic updates needed
│
└─ Is it DETAIL page data?
   └─ ✅ Use Map: `xxxDetailMap: Record<string, Xxx>`
      - Cache multiple details
      - Support optimistic updates
      - Per-item loading states
      - Requires reducer for mutations

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Checklist

When designing store state structure:

• Organize types by entity in separate files (e.g. benchmark.ts, agentEvalDataset.ts)
• Create Detail type (full entity with all fields including heavy ones)
• Create ListItem type:
  • Subset of Detail (exclude heavy fields)
  • May include computed statistics for UI
  • NOT extends Detail
• Use array for list data: xxxList: XxxListItem[]
• Use Map for detail data: xxxDetailMap: Record<string, Xxx>
• Per-item loading: loadingXxxDetailIds: string[]
• Reducer for detail map if optimistic updates needed (see references/reducer.md)
• Internal dispatch and loading methods
• Selectors for clean access (optional but recommended)
• Document in comments which fields are excluded from List and why

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Best Practices

1. File organization — one entity per file, not mixed
2. List is a subset — ListItem excludes heavy fields, does not extends Detail
3. Clear naming — xxxList for arrays, xxxDetailMap for maps
4. Consistent patterns — all detail maps follow the same shape
5. Type safety — never use any, always use proper types
6. Document exclusions — comment which fields are excluded and why
7. Selectors — encapsulate access patterns
8. Loading states — per-item for details, global for mutations
9. Immutability — use Immer in reducers

Common Mistakes to Avoid

❌ DON'T extend Detail in List:

// Wrong — pulls heavy fields back in
export interface BenchmarkListItem extends Benchmark {
  testCaseCount?: number;
}

✅ DO create separate subset:

export interface BenchmarkListItem {
  id: string;
  name: string;
  // ... only necessary fields
  testCaseCount?: number; // Computed
}

❌ DON'T mix entities in one file:

// Wrong — all entities in agentEvalEntities.ts

✅ DO separate by entity:

// Correct — separate files
// benchmark.ts
// agentEvalDataset.ts
// agentEvalRun.ts

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Related Skills

• data-fetching-architecture — how to fetch and update this data
• zustand — general Zustand patterns