feat(docs): update README.md to show how new data fetching works (#10268)

This PR demonstrates how the new data fetching strategy works, so other
developers don’t get confused.

### Changes
- Updated `README.md` to explain the new data fetching strategy.

### Checklist 📋

- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
  - [x] Nothing is breaking, everything works great
This commit is contained in:
Abhimanyu Yadav
2025-06-30 18:20:10 +05:30
committed by GitHub
parent 6ef8119708
commit fae927e2a7

View File

@@ -63,9 +63,147 @@ Every time a new Front-end dependency is added by you or others, you will need t
- `pnpm type-check` - Run TypeScript type checking
- `pnpm test` - Run Playwright tests
- `pnpm test-ui` - Run Playwright tests with UI
- `pnpm fetch:openapi` - Fetch OpenAPI spec from backend
- `pnpm generate:api-client` - Generate API client from OpenAPI spec
- `pnpm generate:api-all` - Fetch OpenAPI spec and generate API client
This project uses [`next/font`](https://nextjs.org/docs/basic-features/font-optimization) to automatically optimize and load Inter, a custom Google Font.
## 🔄 Data Fetching Strategy
This project uses an auto-generated API client powered by [**Orval**](https://orval.dev/), which creates type-safe API clients from OpenAPI specifications.
### How It Works
1. **Backend Requirements**: Each API endpoint needs a summary and tag in the OpenAPI spec
2. **Operation ID Generation**: FastAPI generates operation IDs using the pattern `{method}{tag}{summary}`
3. **Spec Fetching**: The OpenAPI spec is fetched from `http://localhost:8006/openapi.json` and saved to the frontend
4. **Spec Transformation**: The OpenAPI spec is cleaned up using a custom transformer (see `autogpt_platform/frontend/src/app/api/transformers`)
5. **Client Generation**: Auto-generated client includes TypeScript types, API endpoints, and Zod schemas, organized by tags
### API Client Commands
```bash
# Fetch OpenAPI spec from backend and generate client
pnpm generate:api-all
# Only fetch the OpenAPI spec
pnpm fetch:openapi
# Only generate the client (after spec is fetched)
pnpm generate:api-client
```
### Using the Generated Client
The generated client provides React Query hooks for both queries and mutations:
#### Queries (GET requests)
```typescript
import { useGetV1GetNotificationPreferences } from "@/app/api/__generated__/endpoints/auth/auth";
const { data, isLoading, isError } = useGetV1GetNotificationPreferences({
query: {
select: (res) => res.data,
// Other React Query options
},
});
```
#### Mutations (POST, PUT, DELETE requests)
```typescript
import { useDeleteV2DeleteStoreSubmission } from "@/app/api/__generated__/endpoints/store/store";
import { getGetV2ListMySubmissionsQueryKey } from "@/app/api/__generated__/endpoints/store/store";
import { useQueryClient } from "@tanstack/react-query";
const queryClient = useQueryClient();
const { mutateAsync: deleteSubmission } = useDeleteV2DeleteStoreSubmission({
mutation: {
onSuccess: () => {
// Invalidate related queries to refresh data
queryClient.invalidateQueries({
queryKey: getGetV2ListMySubmissionsQueryKey(),
});
},
},
});
// Usage
await deleteSubmission({
submissionId: submission_id,
});
```
#### Server Actions
For server-side operations, you can also use the generated client functions directly:
```typescript
import { postV1UpdateNotificationPreferences } from "@/app/api/__generated__/endpoints/auth/auth";
// In a server action
const preferences = {
email: "user@example.com",
preferences: {
AGENT_RUN: true,
ZERO_BALANCE: false,
// ... other preferences
},
daily_limit: 0,
};
await postV1UpdateNotificationPreferences(preferences);
```
#### Server-Side Prefetching
For server-side components, you can prefetch data on the server and hydrate it in the client cache. This allows immediate access to cached data when queries are called:
```typescript
import { getQueryClient } from "@/lib/tanstack-query/getQueryClient";
import {
prefetchGetV2ListStoreAgentsQuery,
prefetchGetV2ListStoreCreatorsQuery
} from "@/app/api/__generated__/endpoints/store/store";
import { HydrationBoundary, dehydrate } from "@tanstack/react-query";
// In your server component
const queryClient = getQueryClient();
await Promise.all([
prefetchGetV2ListStoreAgentsQuery(queryClient, {
featured: true,
}),
prefetchGetV2ListStoreAgentsQuery(queryClient, {
sorted_by: "runs",
}),
prefetchGetV2ListStoreCreatorsQuery(queryClient, {
featured: true,
sorted_by: "num_agents",
}),
]);
return (
<HydrationBoundary state={dehydrate(queryClient)}>
<MainMarkeplacePage />
</HydrationBoundary>
);
```
This pattern improves performance by serving pre-fetched data from the server while maintaining the benefits of client-side React Query features.
### Configuration
The Orval configuration is located in `autogpt_platform/frontend/orval.config.ts`. It generates two separate clients:
1. **autogpt_api_client**: React Query hooks for client-side data fetching
2. **autogpt_zod_schema**: Zod schemas for validation
For more details, see the [Orval documentation](https://orval.dev/) or check the configuration file.
## 🚚 Deploy
TODO