Merge branch 'dev' into ntindle/systemallquietalerts

This commit is contained in:
Nicholas Tindle
2026-02-04 23:31:20 -06:00
committed by GitHub
1247 changed files with 112824 additions and 25458 deletions

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.branchlet.json Normal file
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{
"worktreeCopyPatterns": [
".env*",
".vscode/**",
".auth/**",
".claude/**",
"autogpt_platform/.env*",
"autogpt_platform/backend/.env*",
"autogpt_platform/frontend/.env*",
"autogpt_platform/frontend/.auth/**",
"autogpt_platform/db/docker/.env*"
],
"worktreeCopyIgnores": [
"**/node_modules/**",
"**/dist/**",
"**/.git/**",
"**/Thumbs.db",
"**/.DS_Store",
"**/.next/**",
"**/__pycache__/**",
"**/.ruff_cache/**",
"**/.pytest_cache/**",
"**/*.pyc",
"**/playwright-report/**",
"**/logs/**",
"**/site/**"
],
"worktreePathTemplate": "$BASE_PATH.worktree",
"postCreateCmd": [
"cd autogpt_platform/autogpt_libs && poetry install",
"cd autogpt_platform/backend && poetry install && poetry run prisma generate",
"cd autogpt_platform/frontend && pnpm install"
],
"terminalCommand": "code .",
"deleteBranchWithWorktree": false
}

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---
name: vercel-react-best-practices
description: React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
license: MIT
metadata:
author: vercel
version: "1.0.0"
---
# Vercel React Best Practices
Comprehensive performance optimization guide for React and Next.js applications, maintained by Vercel. Contains 45 rules across 8 categories, prioritized by impact to guide automated refactoring and code generation.
## When to Apply
Reference these guidelines when:
- Writing new React components or Next.js pages
- Implementing data fetching (client or server-side)
- Reviewing code for performance issues
- Refactoring existing React/Next.js code
- Optimizing bundle size or load times
## Rule Categories by Priority
| Priority | Category | Impact | Prefix |
|----------|----------|--------|--------|
| 1 | Eliminating Waterfalls | CRITICAL | `async-` |
| 2 | Bundle Size Optimization | CRITICAL | `bundle-` |
| 3 | Server-Side Performance | HIGH | `server-` |
| 4 | Client-Side Data Fetching | MEDIUM-HIGH | `client-` |
| 5 | Re-render Optimization | MEDIUM | `rerender-` |
| 6 | Rendering Performance | MEDIUM | `rendering-` |
| 7 | JavaScript Performance | LOW-MEDIUM | `js-` |
| 8 | Advanced Patterns | LOW | `advanced-` |
## Quick Reference
### 1. Eliminating Waterfalls (CRITICAL)
- `async-defer-await` - Move await into branches where actually used
- `async-parallel` - Use Promise.all() for independent operations
- `async-dependencies` - Use better-all for partial dependencies
- `async-api-routes` - Start promises early, await late in API routes
- `async-suspense-boundaries` - Use Suspense to stream content
### 2. Bundle Size Optimization (CRITICAL)
- `bundle-barrel-imports` - Import directly, avoid barrel files
- `bundle-dynamic-imports` - Use next/dynamic for heavy components
- `bundle-defer-third-party` - Load analytics/logging after hydration
- `bundle-conditional` - Load modules only when feature is activated
- `bundle-preload` - Preload on hover/focus for perceived speed
### 3. Server-Side Performance (HIGH)
- `server-cache-react` - Use React.cache() for per-request deduplication
- `server-cache-lru` - Use LRU cache for cross-request caching
- `server-serialization` - Minimize data passed to client components
- `server-parallel-fetching` - Restructure components to parallelize fetches
- `server-after-nonblocking` - Use after() for non-blocking operations
### 4. Client-Side Data Fetching (MEDIUM-HIGH)
- `client-swr-dedup` - Use SWR for automatic request deduplication
- `client-event-listeners` - Deduplicate global event listeners
### 5. Re-render Optimization (MEDIUM)
- `rerender-defer-reads` - Don't subscribe to state only used in callbacks
- `rerender-memo` - Extract expensive work into memoized components
- `rerender-dependencies` - Use primitive dependencies in effects
- `rerender-derived-state` - Subscribe to derived booleans, not raw values
- `rerender-functional-setstate` - Use functional setState for stable callbacks
- `rerender-lazy-state-init` - Pass function to useState for expensive values
- `rerender-transitions` - Use startTransition for non-urgent updates
### 6. Rendering Performance (MEDIUM)
- `rendering-animate-svg-wrapper` - Animate div wrapper, not SVG element
- `rendering-content-visibility` - Use content-visibility for long lists
- `rendering-hoist-jsx` - Extract static JSX outside components
- `rendering-svg-precision` - Reduce SVG coordinate precision
- `rendering-hydration-no-flicker` - Use inline script for client-only data
- `rendering-activity` - Use Activity component for show/hide
- `rendering-conditional-render` - Use ternary, not && for conditionals
### 7. JavaScript Performance (LOW-MEDIUM)
- `js-batch-dom-css` - Group CSS changes via classes or cssText
- `js-index-maps` - Build Map for repeated lookups
- `js-cache-property-access` - Cache object properties in loops
- `js-cache-function-results` - Cache function results in module-level Map
- `js-cache-storage` - Cache localStorage/sessionStorage reads
- `js-combine-iterations` - Combine multiple filter/map into one loop
- `js-length-check-first` - Check array length before expensive comparison
- `js-early-exit` - Return early from functions
- `js-hoist-regexp` - Hoist RegExp creation outside loops
- `js-min-max-loop` - Use loop for min/max instead of sort
- `js-set-map-lookups` - Use Set/Map for O(1) lookups
- `js-tosorted-immutable` - Use toSorted() for immutability
### 8. Advanced Patterns (LOW)
- `advanced-event-handler-refs` - Store event handlers in refs
- `advanced-use-latest` - useLatest for stable callback refs
## How to Use
Read individual rule files for detailed explanations and code examples:
```
rules/async-parallel.md
rules/bundle-barrel-imports.md
rules/_sections.md
```
Each rule file contains:
- Brief explanation of why it matters
- Incorrect code example with explanation
- Correct code example with explanation
- Additional context and references
## Full Compiled Document
For the complete guide with all rules expanded: `AGENTS.md`

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---
title: Store Event Handlers in Refs
impact: LOW
impactDescription: stable subscriptions
tags: advanced, hooks, refs, event-handlers, optimization
---
## Store Event Handlers in Refs
Store callbacks in refs when used in effects that shouldn't re-subscribe on callback changes.
**Incorrect (re-subscribes on every render):**
```tsx
function useWindowEvent(event: string, handler: () => void) {
useEffect(() => {
window.addEventListener(event, handler)
return () => window.removeEventListener(event, handler)
}, [event, handler])
}
```
**Correct (stable subscription):**
```tsx
function useWindowEvent(event: string, handler: () => void) {
const handlerRef = useRef(handler)
useEffect(() => {
handlerRef.current = handler
}, [handler])
useEffect(() => {
const listener = () => handlerRef.current()
window.addEventListener(event, listener)
return () => window.removeEventListener(event, listener)
}, [event])
}
```
**Alternative: use `useEffectEvent` if you're on latest React:**
```tsx
import { useEffectEvent } from 'react'
function useWindowEvent(event: string, handler: () => void) {
const onEvent = useEffectEvent(handler)
useEffect(() => {
window.addEventListener(event, onEvent)
return () => window.removeEventListener(event, onEvent)
}, [event])
}
```
`useEffectEvent` provides a cleaner API for the same pattern: it creates a stable function reference that always calls the latest version of the handler.

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---
title: useLatest for Stable Callback Refs
impact: LOW
impactDescription: prevents effect re-runs
tags: advanced, hooks, useLatest, refs, optimization
---
## useLatest for Stable Callback Refs
Access latest values in callbacks without adding them to dependency arrays. Prevents effect re-runs while avoiding stale closures.
**Implementation:**
```typescript
function useLatest<T>(value: T) {
const ref = useRef(value)
useEffect(() => {
ref.current = value
}, [value])
return ref
}
```
**Incorrect (effect re-runs on every callback change):**
```tsx
function SearchInput({ onSearch }: { onSearch: (q: string) => void }) {
const [query, setQuery] = useState('')
useEffect(() => {
const timeout = setTimeout(() => onSearch(query), 300)
return () => clearTimeout(timeout)
}, [query, onSearch])
}
```
**Correct (stable effect, fresh callback):**
```tsx
function SearchInput({ onSearch }: { onSearch: (q: string) => void }) {
const [query, setQuery] = useState('')
const onSearchRef = useLatest(onSearch)
useEffect(() => {
const timeout = setTimeout(() => onSearchRef.current(query), 300)
return () => clearTimeout(timeout)
}, [query])
}
```

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---
title: Prevent Waterfall Chains in API Routes
impact: CRITICAL
impactDescription: 2-10× improvement
tags: api-routes, server-actions, waterfalls, parallelization
---
## Prevent Waterfall Chains in API Routes
In API routes and Server Actions, start independent operations immediately, even if you don't await them yet.
**Incorrect (config waits for auth, data waits for both):**
```typescript
export async function GET(request: Request) {
const session = await auth()
const config = await fetchConfig()
const data = await fetchData(session.user.id)
return Response.json({ data, config })
}
```
**Correct (auth and config start immediately):**
```typescript
export async function GET(request: Request) {
const sessionPromise = auth()
const configPromise = fetchConfig()
const session = await sessionPromise
const [config, data] = await Promise.all([
configPromise,
fetchData(session.user.id)
])
return Response.json({ data, config })
}
```
For operations with more complex dependency chains, use `better-all` to automatically maximize parallelism (see Dependency-Based Parallelization).

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---
title: Defer Await Until Needed
impact: HIGH
impactDescription: avoids blocking unused code paths
tags: async, await, conditional, optimization
---
## Defer Await Until Needed
Move `await` operations into the branches where they're actually used to avoid blocking code paths that don't need them.
**Incorrect (blocks both branches):**
```typescript
async function handleRequest(userId: string, skipProcessing: boolean) {
const userData = await fetchUserData(userId)
if (skipProcessing) {
// Returns immediately but still waited for userData
return { skipped: true }
}
// Only this branch uses userData
return processUserData(userData)
}
```
**Correct (only blocks when needed):**
```typescript
async function handleRequest(userId: string, skipProcessing: boolean) {
if (skipProcessing) {
// Returns immediately without waiting
return { skipped: true }
}
// Fetch only when needed
const userData = await fetchUserData(userId)
return processUserData(userData)
}
```
**Another example (early return optimization):**
```typescript
// Incorrect: always fetches permissions
async function updateResource(resourceId: string, userId: string) {
const permissions = await fetchPermissions(userId)
const resource = await getResource(resourceId)
if (!resource) {
return { error: 'Not found' }
}
if (!permissions.canEdit) {
return { error: 'Forbidden' }
}
return await updateResourceData(resource, permissions)
}
// Correct: fetches only when needed
async function updateResource(resourceId: string, userId: string) {
const resource = await getResource(resourceId)
if (!resource) {
return { error: 'Not found' }
}
const permissions = await fetchPermissions(userId)
if (!permissions.canEdit) {
return { error: 'Forbidden' }
}
return await updateResourceData(resource, permissions)
}
```
This optimization is especially valuable when the skipped branch is frequently taken, or when the deferred operation is expensive.

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---
title: Dependency-Based Parallelization
impact: CRITICAL
impactDescription: 2-10× improvement
tags: async, parallelization, dependencies, better-all
---
## Dependency-Based Parallelization
For operations with partial dependencies, use `better-all` to maximize parallelism. It automatically starts each task at the earliest possible moment.
**Incorrect (profile waits for config unnecessarily):**
```typescript
const [user, config] = await Promise.all([
fetchUser(),
fetchConfig()
])
const profile = await fetchProfile(user.id)
```
**Correct (config and profile run in parallel):**
```typescript
import { all } from 'better-all'
const { user, config, profile } = await all({
async user() { return fetchUser() },
async config() { return fetchConfig() },
async profile() {
return fetchProfile((await this.$.user).id)
}
})
```
Reference: [https://github.com/shuding/better-all](https://github.com/shuding/better-all)

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---
title: Promise.all() for Independent Operations
impact: CRITICAL
impactDescription: 2-10× improvement
tags: async, parallelization, promises, waterfalls
---
## Promise.all() for Independent Operations
When async operations have no interdependencies, execute them concurrently using `Promise.all()`.
**Incorrect (sequential execution, 3 round trips):**
```typescript
const user = await fetchUser()
const posts = await fetchPosts()
const comments = await fetchComments()
```
**Correct (parallel execution, 1 round trip):**
```typescript
const [user, posts, comments] = await Promise.all([
fetchUser(),
fetchPosts(),
fetchComments()
])
```

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---
title: Strategic Suspense Boundaries
impact: HIGH
impactDescription: faster initial paint
tags: async, suspense, streaming, layout-shift
---
## Strategic Suspense Boundaries
Instead of awaiting data in async components before returning JSX, use Suspense boundaries to show the wrapper UI faster while data loads.
**Incorrect (wrapper blocked by data fetching):**
```tsx
async function Page() {
const data = await fetchData() // Blocks entire page
return (
<div>
<div>Sidebar</div>
<div>Header</div>
<div>
<DataDisplay data={data} />
</div>
<div>Footer</div>
</div>
)
}
```
The entire layout waits for data even though only the middle section needs it.
**Correct (wrapper shows immediately, data streams in):**
```tsx
function Page() {
return (
<div>
<div>Sidebar</div>
<div>Header</div>
<div>
<Suspense fallback={<Skeleton />}>
<DataDisplay />
</Suspense>
</div>
<div>Footer</div>
</div>
)
}
async function DataDisplay() {
const data = await fetchData() // Only blocks this component
return <div>{data.content}</div>
}
```
Sidebar, Header, and Footer render immediately. Only DataDisplay waits for data.
**Alternative (share promise across components):**
```tsx
function Page() {
// Start fetch immediately, but don't await
const dataPromise = fetchData()
return (
<div>
<div>Sidebar</div>
<div>Header</div>
<Suspense fallback={<Skeleton />}>
<DataDisplay dataPromise={dataPromise} />
<DataSummary dataPromise={dataPromise} />
</Suspense>
<div>Footer</div>
</div>
)
}
function DataDisplay({ dataPromise }: { dataPromise: Promise<Data> }) {
const data = use(dataPromise) // Unwraps the promise
return <div>{data.content}</div>
}
function DataSummary({ dataPromise }: { dataPromise: Promise<Data> }) {
const data = use(dataPromise) // Reuses the same promise
return <div>{data.summary}</div>
}
```
Both components share the same promise, so only one fetch occurs. Layout renders immediately while both components wait together.
**When NOT to use this pattern:**
- Critical data needed for layout decisions (affects positioning)
- SEO-critical content above the fold
- Small, fast queries where suspense overhead isn't worth it
- When you want to avoid layout shift (loading → content jump)
**Trade-off:** Faster initial paint vs potential layout shift. Choose based on your UX priorities.

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---
title: Avoid Barrel File Imports
impact: CRITICAL
impactDescription: 200-800ms import cost, slow builds
tags: bundle, imports, tree-shaking, barrel-files, performance
---
## Avoid Barrel File Imports
Import directly from source files instead of barrel files to avoid loading thousands of unused modules. **Barrel files** are entry points that re-export multiple modules (e.g., `index.js` that does `export * from './module'`).
Popular icon and component libraries can have **up to 10,000 re-exports** in their entry file. For many React packages, **it takes 200-800ms just to import them**, affecting both development speed and production cold starts.
**Why tree-shaking doesn't help:** When a library is marked as external (not bundled), the bundler can't optimize it. If you bundle it to enable tree-shaking, builds become substantially slower analyzing the entire module graph.
**Incorrect (imports entire library):**
```tsx
import { Check, X, Menu } from 'lucide-react'
// Loads 1,583 modules, takes ~2.8s extra in dev
// Runtime cost: 200-800ms on every cold start
import { Button, TextField } from '@mui/material'
// Loads 2,225 modules, takes ~4.2s extra in dev
```
**Correct (imports only what you need):**
```tsx
import Check from 'lucide-react/dist/esm/icons/check'
import X from 'lucide-react/dist/esm/icons/x'
import Menu from 'lucide-react/dist/esm/icons/menu'
// Loads only 3 modules (~2KB vs ~1MB)
import Button from '@mui/material/Button'
import TextField from '@mui/material/TextField'
// Loads only what you use
```
**Alternative (Next.js 13.5+):**
```js
// next.config.js - use optimizePackageImports
module.exports = {
experimental: {
optimizePackageImports: ['lucide-react', '@mui/material']
}
}
// Then you can keep the ergonomic barrel imports:
import { Check, X, Menu } from 'lucide-react'
// Automatically transformed to direct imports at build time
```
Direct imports provide 15-70% faster dev boot, 28% faster builds, 40% faster cold starts, and significantly faster HMR.
Libraries commonly affected: `lucide-react`, `@mui/material`, `@mui/icons-material`, `@tabler/icons-react`, `react-icons`, `@headlessui/react`, `@radix-ui/react-*`, `lodash`, `ramda`, `date-fns`, `rxjs`, `react-use`.
Reference: [How we optimized package imports in Next.js](https://vercel.com/blog/how-we-optimized-package-imports-in-next-js)

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---
title: Conditional Module Loading
impact: HIGH
impactDescription: loads large data only when needed
tags: bundle, conditional-loading, lazy-loading
---
## Conditional Module Loading
Load large data or modules only when a feature is activated.
**Example (lazy-load animation frames):**
```tsx
function AnimationPlayer({ enabled }: { enabled: boolean }) {
const [frames, setFrames] = useState<Frame[] | null>(null)
useEffect(() => {
if (enabled && !frames && typeof window !== 'undefined') {
import('./animation-frames.js')
.then(mod => setFrames(mod.frames))
.catch(() => setEnabled(false))
}
}, [enabled, frames])
if (!frames) return <Skeleton />
return <Canvas frames={frames} />
}
```
The `typeof window !== 'undefined'` check prevents bundling this module for SSR, optimizing server bundle size and build speed.

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---
title: Defer Non-Critical Third-Party Libraries
impact: MEDIUM
impactDescription: loads after hydration
tags: bundle, third-party, analytics, defer
---
## Defer Non-Critical Third-Party Libraries
Analytics, logging, and error tracking don't block user interaction. Load them after hydration.
**Incorrect (blocks initial bundle):**
```tsx
import { Analytics } from '@vercel/analytics/react'
export default function RootLayout({ children }) {
return (
<html>
<body>
{children}
<Analytics />
</body>
</html>
)
}
```
**Correct (loads after hydration):**
```tsx
import dynamic from 'next/dynamic'
const Analytics = dynamic(
() => import('@vercel/analytics/react').then(m => m.Analytics),
{ ssr: false }
)
export default function RootLayout({ children }) {
return (
<html>
<body>
{children}
<Analytics />
</body>
</html>
)
}
```

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---
title: Dynamic Imports for Heavy Components
impact: CRITICAL
impactDescription: directly affects TTI and LCP
tags: bundle, dynamic-import, code-splitting, next-dynamic
---
## Dynamic Imports for Heavy Components
Use `next/dynamic` to lazy-load large components not needed on initial render.
**Incorrect (Monaco bundles with main chunk ~300KB):**
```tsx
import { MonacoEditor } from './monaco-editor'
function CodePanel({ code }: { code: string }) {
return <MonacoEditor value={code} />
}
```
**Correct (Monaco loads on demand):**
```tsx
import dynamic from 'next/dynamic'
const MonacoEditor = dynamic(
() => import('./monaco-editor').then(m => m.MonacoEditor),
{ ssr: false }
)
function CodePanel({ code }: { code: string }) {
return <MonacoEditor value={code} />
}
```

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---
title: Preload Based on User Intent
impact: MEDIUM
impactDescription: reduces perceived latency
tags: bundle, preload, user-intent, hover
---
## Preload Based on User Intent
Preload heavy bundles before they're needed to reduce perceived latency.
**Example (preload on hover/focus):**
```tsx
function EditorButton({ onClick }: { onClick: () => void }) {
const preload = () => {
if (typeof window !== 'undefined') {
void import('./monaco-editor')
}
}
return (
<button
onMouseEnter={preload}
onFocus={preload}
onClick={onClick}
>
Open Editor
</button>
)
}
```
**Example (preload when feature flag is enabled):**
```tsx
function FlagsProvider({ children, flags }: Props) {
useEffect(() => {
if (flags.editorEnabled && typeof window !== 'undefined') {
void import('./monaco-editor').then(mod => mod.init())
}
}, [flags.editorEnabled])
return <FlagsContext.Provider value={flags}>
{children}
</FlagsContext.Provider>
}
```
The `typeof window !== 'undefined'` check prevents bundling preloaded modules for SSR, optimizing server bundle size and build speed.

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---
title: Deduplicate Global Event Listeners
impact: LOW
impactDescription: single listener for N components
tags: client, swr, event-listeners, subscription
---
## Deduplicate Global Event Listeners
Use `useSWRSubscription()` to share global event listeners across component instances.
**Incorrect (N instances = N listeners):**
```tsx
function useKeyboardShortcut(key: string, callback: () => void) {
useEffect(() => {
const handler = (e: KeyboardEvent) => {
if (e.metaKey && e.key === key) {
callback()
}
}
window.addEventListener('keydown', handler)
return () => window.removeEventListener('keydown', handler)
}, [key, callback])
}
```
When using the `useKeyboardShortcut` hook multiple times, each instance will register a new listener.
**Correct (N instances = 1 listener):**
```tsx
import useSWRSubscription from 'swr/subscription'
// Module-level Map to track callbacks per key
const keyCallbacks = new Map<string, Set<() => void>>()
function useKeyboardShortcut(key: string, callback: () => void) {
// Register this callback in the Map
useEffect(() => {
if (!keyCallbacks.has(key)) {
keyCallbacks.set(key, new Set())
}
keyCallbacks.get(key)!.add(callback)
return () => {
const set = keyCallbacks.get(key)
if (set) {
set.delete(callback)
if (set.size === 0) {
keyCallbacks.delete(key)
}
}
}
}, [key, callback])
useSWRSubscription('global-keydown', () => {
const handler = (e: KeyboardEvent) => {
if (e.metaKey && keyCallbacks.has(e.key)) {
keyCallbacks.get(e.key)!.forEach(cb => cb())
}
}
window.addEventListener('keydown', handler)
return () => window.removeEventListener('keydown', handler)
})
}
function Profile() {
// Multiple shortcuts will share the same listener
useKeyboardShortcut('p', () => { /* ... */ })
useKeyboardShortcut('k', () => { /* ... */ })
// ...
}
```

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---
title: Use SWR for Automatic Deduplication
impact: MEDIUM-HIGH
impactDescription: automatic deduplication
tags: client, swr, deduplication, data-fetching
---
## Use SWR for Automatic Deduplication
SWR enables request deduplication, caching, and revalidation across component instances.
**Incorrect (no deduplication, each instance fetches):**
```tsx
function UserList() {
const [users, setUsers] = useState([])
useEffect(() => {
fetch('/api/users')
.then(r => r.json())
.then(setUsers)
}, [])
}
```
**Correct (multiple instances share one request):**
```tsx
import useSWR from 'swr'
function UserList() {
const { data: users } = useSWR('/api/users', fetcher)
}
```
**For immutable data:**
```tsx
import { useImmutableSWR } from '@/lib/swr'
function StaticContent() {
const { data } = useImmutableSWR('/api/config', fetcher)
}
```
**For mutations:**
```tsx
import { useSWRMutation } from 'swr/mutation'
function UpdateButton() {
const { trigger } = useSWRMutation('/api/user', updateUser)
return <button onClick={() => trigger()}>Update</button>
}
```
Reference: [https://swr.vercel.app](https://swr.vercel.app)

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---
title: Batch DOM CSS Changes
impact: MEDIUM
impactDescription: reduces reflows/repaints
tags: javascript, dom, css, performance, reflow
---
## Batch DOM CSS Changes
Avoid changing styles one property at a time. Group multiple CSS changes together via classes or `cssText` to minimize browser reflows.
**Incorrect (multiple reflows):**
```typescript
function updateElementStyles(element: HTMLElement) {
// Each line triggers a reflow
element.style.width = '100px'
element.style.height = '200px'
element.style.backgroundColor = 'blue'
element.style.border = '1px solid black'
}
```
**Correct (add class - single reflow):**
```typescript
// CSS file
.highlighted-box {
width: 100px;
height: 200px;
background-color: blue;
border: 1px solid black;
}
// JavaScript
function updateElementStyles(element: HTMLElement) {
element.classList.add('highlighted-box')
}
```
**Correct (change cssText - single reflow):**
```typescript
function updateElementStyles(element: HTMLElement) {
element.style.cssText = `
width: 100px;
height: 200px;
background-color: blue;
border: 1px solid black;
`
}
```
**React example:**
```tsx
// Incorrect: changing styles one by one
function Box({ isHighlighted }: { isHighlighted: boolean }) {
const ref = useRef<HTMLDivElement>(null)
useEffect(() => {
if (ref.current && isHighlighted) {
ref.current.style.width = '100px'
ref.current.style.height = '200px'
ref.current.style.backgroundColor = 'blue'
}
}, [isHighlighted])
return <div ref={ref}>Content</div>
}
// Correct: toggle class
function Box({ isHighlighted }: { isHighlighted: boolean }) {
return (
<div className={isHighlighted ? 'highlighted-box' : ''}>
Content
</div>
)
}
```
Prefer CSS classes over inline styles when possible. Classes are cached by the browser and provide better separation of concerns.

View File

@@ -0,0 +1,80 @@
---
title: Cache Repeated Function Calls
impact: MEDIUM
impactDescription: avoid redundant computation
tags: javascript, cache, memoization, performance
---
## Cache Repeated Function Calls
Use a module-level Map to cache function results when the same function is called repeatedly with the same inputs during render.
**Incorrect (redundant computation):**
```typescript
function ProjectList({ projects }: { projects: Project[] }) {
return (
<div>
{projects.map(project => {
// slugify() called 100+ times for same project names
const slug = slugify(project.name)
return <ProjectCard key={project.id} slug={slug} />
})}
</div>
)
}
```
**Correct (cached results):**
```typescript
// Module-level cache
const slugifyCache = new Map<string, string>()
function cachedSlugify(text: string): string {
if (slugifyCache.has(text)) {
return slugifyCache.get(text)!
}
const result = slugify(text)
slugifyCache.set(text, result)
return result
}
function ProjectList({ projects }: { projects: Project[] }) {
return (
<div>
{projects.map(project => {
// Computed only once per unique project name
const slug = cachedSlugify(project.name)
return <ProjectCard key={project.id} slug={slug} />
})}
</div>
)
}
```
**Simpler pattern for single-value functions:**
```typescript
let isLoggedInCache: boolean | null = null
function isLoggedIn(): boolean {
if (isLoggedInCache !== null) {
return isLoggedInCache
}
isLoggedInCache = document.cookie.includes('auth=')
return isLoggedInCache
}
// Clear cache when auth changes
function onAuthChange() {
isLoggedInCache = null
}
```
Use a Map (not a hook) so it works everywhere: utilities, event handlers, not just React components.
Reference: [How we made the Vercel Dashboard twice as fast](https://vercel.com/blog/how-we-made-the-vercel-dashboard-twice-as-fast)

View File

@@ -0,0 +1,28 @@
---
title: Cache Property Access in Loops
impact: LOW-MEDIUM
impactDescription: reduces lookups
tags: javascript, loops, optimization, caching
---
## Cache Property Access in Loops
Cache object property lookups in hot paths.
**Incorrect (3 lookups × N iterations):**
```typescript
for (let i = 0; i < arr.length; i++) {
process(obj.config.settings.value)
}
```
**Correct (1 lookup total):**
```typescript
const value = obj.config.settings.value
const len = arr.length
for (let i = 0; i < len; i++) {
process(value)
}
```

View File

@@ -0,0 +1,70 @@
---
title: Cache Storage API Calls
impact: LOW-MEDIUM
impactDescription: reduces expensive I/O
tags: javascript, localStorage, storage, caching, performance
---
## Cache Storage API Calls
`localStorage`, `sessionStorage`, and `document.cookie` are synchronous and expensive. Cache reads in memory.
**Incorrect (reads storage on every call):**
```typescript
function getTheme() {
return localStorage.getItem('theme') ?? 'light'
}
// Called 10 times = 10 storage reads
```
**Correct (Map cache):**
```typescript
const storageCache = new Map<string, string | null>()
function getLocalStorage(key: string) {
if (!storageCache.has(key)) {
storageCache.set(key, localStorage.getItem(key))
}
return storageCache.get(key)
}
function setLocalStorage(key: string, value: string) {
localStorage.setItem(key, value)
storageCache.set(key, value) // keep cache in sync
}
```
Use a Map (not a hook) so it works everywhere: utilities, event handlers, not just React components.
**Cookie caching:**
```typescript
let cookieCache: Record<string, string> | null = null
function getCookie(name: string) {
if (!cookieCache) {
cookieCache = Object.fromEntries(
document.cookie.split('; ').map(c => c.split('='))
)
}
return cookieCache[name]
}
```
**Important (invalidate on external changes):**
If storage can change externally (another tab, server-set cookies), invalidate cache:
```typescript
window.addEventListener('storage', (e) => {
if (e.key) storageCache.delete(e.key)
})
document.addEventListener('visibilitychange', () => {
if (document.visibilityState === 'visible') {
storageCache.clear()
}
})
```

View File

@@ -0,0 +1,32 @@
---
title: Combine Multiple Array Iterations
impact: LOW-MEDIUM
impactDescription: reduces iterations
tags: javascript, arrays, loops, performance
---
## Combine Multiple Array Iterations
Multiple `.filter()` or `.map()` calls iterate the array multiple times. Combine into one loop.
**Incorrect (3 iterations):**
```typescript
const admins = users.filter(u => u.isAdmin)
const testers = users.filter(u => u.isTester)
const inactive = users.filter(u => !u.isActive)
```
**Correct (1 iteration):**
```typescript
const admins: User[] = []
const testers: User[] = []
const inactive: User[] = []
for (const user of users) {
if (user.isAdmin) admins.push(user)
if (user.isTester) testers.push(user)
if (!user.isActive) inactive.push(user)
}
```

View File

@@ -0,0 +1,50 @@
---
title: Early Return from Functions
impact: LOW-MEDIUM
impactDescription: avoids unnecessary computation
tags: javascript, functions, optimization, early-return
---
## Early Return from Functions
Return early when result is determined to skip unnecessary processing.
**Incorrect (processes all items even after finding answer):**
```typescript
function validateUsers(users: User[]) {
let hasError = false
let errorMessage = ''
for (const user of users) {
if (!user.email) {
hasError = true
errorMessage = 'Email required'
}
if (!user.name) {
hasError = true
errorMessage = 'Name required'
}
// Continues checking all users even after error found
}
return hasError ? { valid: false, error: errorMessage } : { valid: true }
}
```
**Correct (returns immediately on first error):**
```typescript
function validateUsers(users: User[]) {
for (const user of users) {
if (!user.email) {
return { valid: false, error: 'Email required' }
}
if (!user.name) {
return { valid: false, error: 'Name required' }
}
}
return { valid: true }
}
```

View File

@@ -0,0 +1,45 @@
---
title: Hoist RegExp Creation
impact: LOW-MEDIUM
impactDescription: avoids recreation
tags: javascript, regexp, optimization, memoization
---
## Hoist RegExp Creation
Don't create RegExp inside render. Hoist to module scope or memoize with `useMemo()`.
**Incorrect (new RegExp every render):**
```tsx
function Highlighter({ text, query }: Props) {
const regex = new RegExp(`(${query})`, 'gi')
const parts = text.split(regex)
return <>{parts.map((part, i) => ...)}</>
}
```
**Correct (memoize or hoist):**
```tsx
const EMAIL_REGEX = /^[^\s@]+@[^\s@]+\.[^\s@]+$/
function Highlighter({ text, query }: Props) {
const regex = useMemo(
() => new RegExp(`(${escapeRegex(query)})`, 'gi'),
[query]
)
const parts = text.split(regex)
return <>{parts.map((part, i) => ...)}</>
}
```
**Warning (global regex has mutable state):**
Global regex (`/g`) has mutable `lastIndex` state:
```typescript
const regex = /foo/g
regex.test('foo') // true, lastIndex = 3
regex.test('foo') // false, lastIndex = 0
```

View File

@@ -0,0 +1,37 @@
---
title: Build Index Maps for Repeated Lookups
impact: LOW-MEDIUM
impactDescription: 1M ops to 2K ops
tags: javascript, map, indexing, optimization, performance
---
## Build Index Maps for Repeated Lookups
Multiple `.find()` calls by the same key should use a Map.
**Incorrect (O(n) per lookup):**
```typescript
function processOrders(orders: Order[], users: User[]) {
return orders.map(order => ({
...order,
user: users.find(u => u.id === order.userId)
}))
}
```
**Correct (O(1) per lookup):**
```typescript
function processOrders(orders: Order[], users: User[]) {
const userById = new Map(users.map(u => [u.id, u]))
return orders.map(order => ({
...order,
user: userById.get(order.userId)
}))
}
```
Build map once (O(n)), then all lookups are O(1).
For 1000 orders × 1000 users: 1M ops → 2K ops.

View File

@@ -0,0 +1,49 @@
---
title: Early Length Check for Array Comparisons
impact: MEDIUM-HIGH
impactDescription: avoids expensive operations when lengths differ
tags: javascript, arrays, performance, optimization, comparison
---
## Early Length Check for Array Comparisons
When comparing arrays with expensive operations (sorting, deep equality, serialization), check lengths first. If lengths differ, the arrays cannot be equal.
In real-world applications, this optimization is especially valuable when the comparison runs in hot paths (event handlers, render loops).
**Incorrect (always runs expensive comparison):**
```typescript
function hasChanges(current: string[], original: string[]) {
// Always sorts and joins, even when lengths differ
return current.sort().join() !== original.sort().join()
}
```
Two O(n log n) sorts run even when `current.length` is 5 and `original.length` is 100. There is also overhead of joining the arrays and comparing the strings.
**Correct (O(1) length check first):**
```typescript
function hasChanges(current: string[], original: string[]) {
// Early return if lengths differ
if (current.length !== original.length) {
return true
}
// Only sort/join when lengths match
const currentSorted = current.toSorted()
const originalSorted = original.toSorted()
for (let i = 0; i < currentSorted.length; i++) {
if (currentSorted[i] !== originalSorted[i]) {
return true
}
}
return false
}
```
This new approach is more efficient because:
- It avoids the overhead of sorting and joining the arrays when lengths differ
- It avoids consuming memory for the joined strings (especially important for large arrays)
- It avoids mutating the original arrays
- It returns early when a difference is found

View File

@@ -0,0 +1,82 @@
---
title: Use Loop for Min/Max Instead of Sort
impact: LOW
impactDescription: O(n) instead of O(n log n)
tags: javascript, arrays, performance, sorting, algorithms
---
## Use Loop for Min/Max Instead of Sort
Finding the smallest or largest element only requires a single pass through the array. Sorting is wasteful and slower.
**Incorrect (O(n log n) - sort to find latest):**
```typescript
interface Project {
id: string
name: string
updatedAt: number
}
function getLatestProject(projects: Project[]) {
const sorted = [...projects].sort((a, b) => b.updatedAt - a.updatedAt)
return sorted[0]
}
```
Sorts the entire array just to find the maximum value.
**Incorrect (O(n log n) - sort for oldest and newest):**
```typescript
function getOldestAndNewest(projects: Project[]) {
const sorted = [...projects].sort((a, b) => a.updatedAt - b.updatedAt)
return { oldest: sorted[0], newest: sorted[sorted.length - 1] }
}
```
Still sorts unnecessarily when only min/max are needed.
**Correct (O(n) - single loop):**
```typescript
function getLatestProject(projects: Project[]) {
if (projects.length === 0) return null
let latest = projects[0]
for (let i = 1; i < projects.length; i++) {
if (projects[i].updatedAt > latest.updatedAt) {
latest = projects[i]
}
}
return latest
}
function getOldestAndNewest(projects: Project[]) {
if (projects.length === 0) return { oldest: null, newest: null }
let oldest = projects[0]
let newest = projects[0]
for (let i = 1; i < projects.length; i++) {
if (projects[i].updatedAt < oldest.updatedAt) oldest = projects[i]
if (projects[i].updatedAt > newest.updatedAt) newest = projects[i]
}
return { oldest, newest }
}
```
Single pass through the array, no copying, no sorting.
**Alternative (Math.min/Math.max for small arrays):**
```typescript
const numbers = [5, 2, 8, 1, 9]
const min = Math.min(...numbers)
const max = Math.max(...numbers)
```
This works for small arrays but can be slower for very large arrays due to spread operator limitations. Use the loop approach for reliability.

View File

@@ -0,0 +1,24 @@
---
title: Use Set/Map for O(1) Lookups
impact: LOW-MEDIUM
impactDescription: O(n) to O(1)
tags: javascript, set, map, data-structures, performance
---
## Use Set/Map for O(1) Lookups
Convert arrays to Set/Map for repeated membership checks.
**Incorrect (O(n) per check):**
```typescript
const allowedIds = ['a', 'b', 'c', ...]
items.filter(item => allowedIds.includes(item.id))
```
**Correct (O(1) per check):**
```typescript
const allowedIds = new Set(['a', 'b', 'c', ...])
items.filter(item => allowedIds.has(item.id))
```

View File

@@ -0,0 +1,57 @@
---
title: Use toSorted() Instead of sort() for Immutability
impact: MEDIUM-HIGH
impactDescription: prevents mutation bugs in React state
tags: javascript, arrays, immutability, react, state, mutation
---
## Use toSorted() Instead of sort() for Immutability
`.sort()` mutates the array in place, which can cause bugs with React state and props. Use `.toSorted()` to create a new sorted array without mutation.
**Incorrect (mutates original array):**
```typescript
function UserList({ users }: { users: User[] }) {
// Mutates the users prop array!
const sorted = useMemo(
() => users.sort((a, b) => a.name.localeCompare(b.name)),
[users]
)
return <div>{sorted.map(renderUser)}</div>
}
```
**Correct (creates new array):**
```typescript
function UserList({ users }: { users: User[] }) {
// Creates new sorted array, original unchanged
const sorted = useMemo(
() => users.toSorted((a, b) => a.name.localeCompare(b.name)),
[users]
)
return <div>{sorted.map(renderUser)}</div>
}
```
**Why this matters in React:**
1. Props/state mutations break React's immutability model - React expects props and state to be treated as read-only
2. Causes stale closure bugs - Mutating arrays inside closures (callbacks, effects) can lead to unexpected behavior
**Browser support (fallback for older browsers):**
`.toSorted()` is available in all modern browsers (Chrome 110+, Safari 16+, Firefox 115+, Node.js 20+). For older environments, use spread operator:
```typescript
// Fallback for older browsers
const sorted = [...items].sort((a, b) => a.value - b.value)
```
**Other immutable array methods:**
- `.toSorted()` - immutable sort
- `.toReversed()` - immutable reverse
- `.toSpliced()` - immutable splice
- `.with()` - immutable element replacement

View File

@@ -0,0 +1,26 @@
---
title: Use Activity Component for Show/Hide
impact: MEDIUM
impactDescription: preserves state/DOM
tags: rendering, activity, visibility, state-preservation
---
## Use Activity Component for Show/Hide
Use React's `<Activity>` to preserve state/DOM for expensive components that frequently toggle visibility.
**Usage:**
```tsx
import { Activity } from 'react'
function Dropdown({ isOpen }: Props) {
return (
<Activity mode={isOpen ? 'visible' : 'hidden'}>
<ExpensiveMenu />
</Activity>
)
}
```
Avoids expensive re-renders and state loss.

View File

@@ -0,0 +1,47 @@
---
title: Animate SVG Wrapper Instead of SVG Element
impact: LOW
impactDescription: enables hardware acceleration
tags: rendering, svg, css, animation, performance
---
## Animate SVG Wrapper Instead of SVG Element
Many browsers don't have hardware acceleration for CSS3 animations on SVG elements. Wrap SVG in a `<div>` and animate the wrapper instead.
**Incorrect (animating SVG directly - no hardware acceleration):**
```tsx
function LoadingSpinner() {
return (
<svg
className="animate-spin"
width="24"
height="24"
viewBox="0 0 24 24"
>
<circle cx="12" cy="12" r="10" stroke="currentColor" />
</svg>
)
}
```
**Correct (animating wrapper div - hardware accelerated):**
```tsx
function LoadingSpinner() {
return (
<div className="animate-spin">
<svg
width="24"
height="24"
viewBox="0 0 24 24"
>
<circle cx="12" cy="12" r="10" stroke="currentColor" />
</svg>
</div>
)
}
```
This applies to all CSS transforms and transitions (`transform`, `opacity`, `translate`, `scale`, `rotate`). The wrapper div allows browsers to use GPU acceleration for smoother animations.

View File

@@ -0,0 +1,40 @@
---
title: Use Explicit Conditional Rendering
impact: LOW
impactDescription: prevents rendering 0 or NaN
tags: rendering, conditional, jsx, falsy-values
---
## Use Explicit Conditional Rendering
Use explicit ternary operators (`? :`) instead of `&&` for conditional rendering when the condition can be `0`, `NaN`, or other falsy values that render.
**Incorrect (renders "0" when count is 0):**
```tsx
function Badge({ count }: { count: number }) {
return (
<div>
{count && <span className="badge">{count}</span>}
</div>
)
}
// When count = 0, renders: <div>0</div>
// When count = 5, renders: <div><span class="badge">5</span></div>
```
**Correct (renders nothing when count is 0):**
```tsx
function Badge({ count }: { count: number }) {
return (
<div>
{count > 0 ? <span className="badge">{count}</span> : null}
</div>
)
}
// When count = 0, renders: <div></div>
// When count = 5, renders: <div><span class="badge">5</span></div>
```

View File

@@ -0,0 +1,38 @@
---
title: CSS content-visibility for Long Lists
impact: HIGH
impactDescription: faster initial render
tags: rendering, css, content-visibility, long-lists
---
## CSS content-visibility for Long Lists
Apply `content-visibility: auto` to defer off-screen rendering.
**CSS:**
```css
.message-item {
content-visibility: auto;
contain-intrinsic-size: 0 80px;
}
```
**Example:**
```tsx
function MessageList({ messages }: { messages: Message[] }) {
return (
<div className="overflow-y-auto h-screen">
{messages.map(msg => (
<div key={msg.id} className="message-item">
<Avatar user={msg.author} />
<div>{msg.content}</div>
</div>
))}
</div>
)
}
```
For 1000 messages, browser skips layout/paint for ~990 off-screen items (10× faster initial render).

View File

@@ -0,0 +1,46 @@
---
title: Hoist Static JSX Elements
impact: LOW
impactDescription: avoids re-creation
tags: rendering, jsx, static, optimization
---
## Hoist Static JSX Elements
Extract static JSX outside components to avoid re-creation.
**Incorrect (recreates element every render):**
```tsx
function LoadingSkeleton() {
return <div className="animate-pulse h-20 bg-gray-200" />
}
function Container() {
return (
<div>
{loading && <LoadingSkeleton />}
</div>
)
}
```
**Correct (reuses same element):**
```tsx
const loadingSkeleton = (
<div className="animate-pulse h-20 bg-gray-200" />
)
function Container() {
return (
<div>
{loading && loadingSkeleton}
</div>
)
}
```
This is especially helpful for large and static SVG nodes, which can be expensive to recreate on every render.
**Note:** If your project has [React Compiler](https://react.dev/learn/react-compiler) enabled, the compiler automatically hoists static JSX elements and optimizes component re-renders, making manual hoisting unnecessary.

View File

@@ -0,0 +1,82 @@
---
title: Prevent Hydration Mismatch Without Flickering
impact: MEDIUM
impactDescription: avoids visual flicker and hydration errors
tags: rendering, ssr, hydration, localStorage, flicker
---
## Prevent Hydration Mismatch Without Flickering
When rendering content that depends on client-side storage (localStorage, cookies), avoid both SSR breakage and post-hydration flickering by injecting a synchronous script that updates the DOM before React hydrates.
**Incorrect (breaks SSR):**
```tsx
function ThemeWrapper({ children }: { children: ReactNode }) {
// localStorage is not available on server - throws error
const theme = localStorage.getItem('theme') || 'light'
return (
<div className={theme}>
{children}
</div>
)
}
```
Server-side rendering will fail because `localStorage` is undefined.
**Incorrect (visual flickering):**
```tsx
function ThemeWrapper({ children }: { children: ReactNode }) {
const [theme, setTheme] = useState('light')
useEffect(() => {
// Runs after hydration - causes visible flash
const stored = localStorage.getItem('theme')
if (stored) {
setTheme(stored)
}
}, [])
return (
<div className={theme}>
{children}
</div>
)
}
```
Component first renders with default value (`light`), then updates after hydration, causing a visible flash of incorrect content.
**Correct (no flicker, no hydration mismatch):**
```tsx
function ThemeWrapper({ children }: { children: ReactNode }) {
return (
<>
<div id="theme-wrapper">
{children}
</div>
<script
dangerouslySetInnerHTML={{
__html: `
(function() {
try {
var theme = localStorage.getItem('theme') || 'light';
var el = document.getElementById('theme-wrapper');
if (el) el.className = theme;
} catch (e) {}
})();
`,
}}
/>
</>
)
}
```
The inline script executes synchronously before showing the element, ensuring the DOM already has the correct value. No flickering, no hydration mismatch.
This pattern is especially useful for theme toggles, user preferences, authentication states, and any client-only data that should render immediately without flashing default values.

View File

@@ -0,0 +1,28 @@
---
title: Optimize SVG Precision
impact: LOW
impactDescription: reduces file size
tags: rendering, svg, optimization, svgo
---
## Optimize SVG Precision
Reduce SVG coordinate precision to decrease file size. The optimal precision depends on the viewBox size, but in general reducing precision should be considered.
**Incorrect (excessive precision):**
```svg
<path d="M 10.293847 20.847362 L 30.938472 40.192837" />
```
**Correct (1 decimal place):**
```svg
<path d="M 10.3 20.8 L 30.9 40.2" />
```
**Automate with SVGO:**
```bash
npx svgo --precision=1 --multipass icon.svg
```

View File

@@ -0,0 +1,39 @@
---
title: Defer State Reads to Usage Point
impact: MEDIUM
impactDescription: avoids unnecessary subscriptions
tags: rerender, searchParams, localStorage, optimization
---
## Defer State Reads to Usage Point
Don't subscribe to dynamic state (searchParams, localStorage) if you only read it inside callbacks.
**Incorrect (subscribes to all searchParams changes):**
```tsx
function ShareButton({ chatId }: { chatId: string }) {
const searchParams = useSearchParams()
const handleShare = () => {
const ref = searchParams.get('ref')
shareChat(chatId, { ref })
}
return <button onClick={handleShare}>Share</button>
}
```
**Correct (reads on demand, no subscription):**
```tsx
function ShareButton({ chatId }: { chatId: string }) {
const handleShare = () => {
const params = new URLSearchParams(window.location.search)
const ref = params.get('ref')
shareChat(chatId, { ref })
}
return <button onClick={handleShare}>Share</button>
}
```

View File

@@ -0,0 +1,45 @@
---
title: Narrow Effect Dependencies
impact: LOW
impactDescription: minimizes effect re-runs
tags: rerender, useEffect, dependencies, optimization
---
## Narrow Effect Dependencies
Specify primitive dependencies instead of objects to minimize effect re-runs.
**Incorrect (re-runs on any user field change):**
```tsx
useEffect(() => {
console.log(user.id)
}, [user])
```
**Correct (re-runs only when id changes):**
```tsx
useEffect(() => {
console.log(user.id)
}, [user.id])
```
**For derived state, compute outside effect:**
```tsx
// Incorrect: runs on width=767, 766, 765...
useEffect(() => {
if (width < 768) {
enableMobileMode()
}
}, [width])
// Correct: runs only on boolean transition
const isMobile = width < 768
useEffect(() => {
if (isMobile) {
enableMobileMode()
}
}, [isMobile])
```

View File

@@ -0,0 +1,29 @@
---
title: Subscribe to Derived State
impact: MEDIUM
impactDescription: reduces re-render frequency
tags: rerender, derived-state, media-query, optimization
---
## Subscribe to Derived State
Subscribe to derived boolean state instead of continuous values to reduce re-render frequency.
**Incorrect (re-renders on every pixel change):**
```tsx
function Sidebar() {
const width = useWindowWidth() // updates continuously
const isMobile = width < 768
return <nav className={isMobile ? 'mobile' : 'desktop'}>
}
```
**Correct (re-renders only when boolean changes):**
```tsx
function Sidebar() {
const isMobile = useMediaQuery('(max-width: 767px)')
return <nav className={isMobile ? 'mobile' : 'desktop'}>
}
```

View File

@@ -0,0 +1,74 @@
---
title: Use Functional setState Updates
impact: MEDIUM
impactDescription: prevents stale closures and unnecessary callback recreations
tags: react, hooks, useState, useCallback, callbacks, closures
---
## Use Functional setState Updates
When updating state based on the current state value, use the functional update form of setState instead of directly referencing the state variable. This prevents stale closures, eliminates unnecessary dependencies, and creates stable callback references.
**Incorrect (requires state as dependency):**
```tsx
function TodoList() {
const [items, setItems] = useState(initialItems)
// Callback must depend on items, recreated on every items change
const addItems = useCallback((newItems: Item[]) => {
setItems([...items, ...newItems])
}, [items]) // ❌ items dependency causes recreations
// Risk of stale closure if dependency is forgotten
const removeItem = useCallback((id: string) => {
setItems(items.filter(item => item.id !== id))
}, []) // ❌ Missing items dependency - will use stale items!
return <ItemsEditor items={items} onAdd={addItems} onRemove={removeItem} />
}
```
The first callback is recreated every time `items` changes, which can cause child components to re-render unnecessarily. The second callback has a stale closure bug—it will always reference the initial `items` value.
**Correct (stable callbacks, no stale closures):**
```tsx
function TodoList() {
const [items, setItems] = useState(initialItems)
// Stable callback, never recreated
const addItems = useCallback((newItems: Item[]) => {
setItems(curr => [...curr, ...newItems])
}, []) // ✅ No dependencies needed
// Always uses latest state, no stale closure risk
const removeItem = useCallback((id: string) => {
setItems(curr => curr.filter(item => item.id !== id))
}, []) // ✅ Safe and stable
return <ItemsEditor items={items} onAdd={addItems} onRemove={removeItem} />
}
```
**Benefits:**
1. **Stable callback references** - Callbacks don't need to be recreated when state changes
2. **No stale closures** - Always operates on the latest state value
3. **Fewer dependencies** - Simplifies dependency arrays and reduces memory leaks
4. **Prevents bugs** - Eliminates the most common source of React closure bugs
**When to use functional updates:**
- Any setState that depends on the current state value
- Inside useCallback/useMemo when state is needed
- Event handlers that reference state
- Async operations that update state
**When direct updates are fine:**
- Setting state to a static value: `setCount(0)`
- Setting state from props/arguments only: `setName(newName)`
- State doesn't depend on previous value
**Note:** If your project has [React Compiler](https://react.dev/learn/react-compiler) enabled, the compiler can automatically optimize some cases, but functional updates are still recommended for correctness and to prevent stale closure bugs.

View File

@@ -0,0 +1,58 @@
---
title: Use Lazy State Initialization
impact: MEDIUM
impactDescription: wasted computation on every render
tags: react, hooks, useState, performance, initialization
---
## Use Lazy State Initialization
Pass a function to `useState` for expensive initial values. Without the function form, the initializer runs on every render even though the value is only used once.
**Incorrect (runs on every render):**
```tsx
function FilteredList({ items }: { items: Item[] }) {
// buildSearchIndex() runs on EVERY render, even after initialization
const [searchIndex, setSearchIndex] = useState(buildSearchIndex(items))
const [query, setQuery] = useState('')
// When query changes, buildSearchIndex runs again unnecessarily
return <SearchResults index={searchIndex} query={query} />
}
function UserProfile() {
// JSON.parse runs on every render
const [settings, setSettings] = useState(
JSON.parse(localStorage.getItem('settings') || '{}')
)
return <SettingsForm settings={settings} onChange={setSettings} />
}
```
**Correct (runs only once):**
```tsx
function FilteredList({ items }: { items: Item[] }) {
// buildSearchIndex() runs ONLY on initial render
const [searchIndex, setSearchIndex] = useState(() => buildSearchIndex(items))
const [query, setQuery] = useState('')
return <SearchResults index={searchIndex} query={query} />
}
function UserProfile() {
// JSON.parse runs only on initial render
const [settings, setSettings] = useState(() => {
const stored = localStorage.getItem('settings')
return stored ? JSON.parse(stored) : {}
})
return <SettingsForm settings={settings} onChange={setSettings} />
}
```
Use lazy initialization when computing initial values from localStorage/sessionStorage, building data structures (indexes, maps), reading from the DOM, or performing heavy transformations.
For simple primitives (`useState(0)`), direct references (`useState(props.value)`), or cheap literals (`useState({})`), the function form is unnecessary.

View File

@@ -0,0 +1,44 @@
---
title: Extract to Memoized Components
impact: MEDIUM
impactDescription: enables early returns
tags: rerender, memo, useMemo, optimization
---
## Extract to Memoized Components
Extract expensive work into memoized components to enable early returns before computation.
**Incorrect (computes avatar even when loading):**
```tsx
function Profile({ user, loading }: Props) {
const avatar = useMemo(() => {
const id = computeAvatarId(user)
return <Avatar id={id} />
}, [user])
if (loading) return <Skeleton />
return <div>{avatar}</div>
}
```
**Correct (skips computation when loading):**
```tsx
const UserAvatar = memo(function UserAvatar({ user }: { user: User }) {
const id = useMemo(() => computeAvatarId(user), [user])
return <Avatar id={id} />
})
function Profile({ user, loading }: Props) {
if (loading) return <Skeleton />
return (
<div>
<UserAvatar user={user} />
</div>
)
}
```
**Note:** If your project has [React Compiler](https://react.dev/learn/react-compiler) enabled, manual memoization with `memo()` and `useMemo()` is not necessary. The compiler automatically optimizes re-renders.

View File

@@ -0,0 +1,40 @@
---
title: Use Transitions for Non-Urgent Updates
impact: MEDIUM
impactDescription: maintains UI responsiveness
tags: rerender, transitions, startTransition, performance
---
## Use Transitions for Non-Urgent Updates
Mark frequent, non-urgent state updates as transitions to maintain UI responsiveness.
**Incorrect (blocks UI on every scroll):**
```tsx
function ScrollTracker() {
const [scrollY, setScrollY] = useState(0)
useEffect(() => {
const handler = () => setScrollY(window.scrollY)
window.addEventListener('scroll', handler, { passive: true })
return () => window.removeEventListener('scroll', handler)
}, [])
}
```
**Correct (non-blocking updates):**
```tsx
import { startTransition } from 'react'
function ScrollTracker() {
const [scrollY, setScrollY] = useState(0)
useEffect(() => {
const handler = () => {
startTransition(() => setScrollY(window.scrollY))
}
window.addEventListener('scroll', handler, { passive: true })
return () => window.removeEventListener('scroll', handler)
}, [])
}
```

View File

@@ -0,0 +1,73 @@
---
title: Use after() for Non-Blocking Operations
impact: MEDIUM
impactDescription: faster response times
tags: server, async, logging, analytics, side-effects
---
## Use after() for Non-Blocking Operations
Use Next.js's `after()` to schedule work that should execute after a response is sent. This prevents logging, analytics, and other side effects from blocking the response.
**Incorrect (blocks response):**
```tsx
import { logUserAction } from '@/app/utils'
export async function POST(request: Request) {
// Perform mutation
await updateDatabase(request)
// Logging blocks the response
const userAgent = request.headers.get('user-agent') || 'unknown'
await logUserAction({ userAgent })
return new Response(JSON.stringify({ status: 'success' }), {
status: 200,
headers: { 'Content-Type': 'application/json' }
})
}
```
**Correct (non-blocking):**
```tsx
import { after } from 'next/server'
import { headers, cookies } from 'next/headers'
import { logUserAction } from '@/app/utils'
export async function POST(request: Request) {
// Perform mutation
await updateDatabase(request)
// Log after response is sent
after(async () => {
const userAgent = (await headers()).get('user-agent') || 'unknown'
const sessionCookie = (await cookies()).get('session-id')?.value || 'anonymous'
logUserAction({ sessionCookie, userAgent })
})
return new Response(JSON.stringify({ status: 'success' }), {
status: 200,
headers: { 'Content-Type': 'application/json' }
})
}
```
The response is sent immediately while logging happens in the background.
**Common use cases:**
- Analytics tracking
- Audit logging
- Sending notifications
- Cache invalidation
- Cleanup tasks
**Important notes:**
- `after()` runs even if the response fails or redirects
- Works in Server Actions, Route Handlers, and Server Components
Reference: [https://nextjs.org/docs/app/api-reference/functions/after](https://nextjs.org/docs/app/api-reference/functions/after)

View File

@@ -0,0 +1,41 @@
---
title: Cross-Request LRU Caching
impact: HIGH
impactDescription: caches across requests
tags: server, cache, lru, cross-request
---
## Cross-Request LRU Caching
`React.cache()` only works within one request. For data shared across sequential requests (user clicks button A then button B), use an LRU cache.
**Implementation:**
```typescript
import { LRUCache } from 'lru-cache'
const cache = new LRUCache<string, any>({
max: 1000,
ttl: 5 * 60 * 1000 // 5 minutes
})
export async function getUser(id: string) {
const cached = cache.get(id)
if (cached) return cached
const user = await db.user.findUnique({ where: { id } })
cache.set(id, user)
return user
}
// Request 1: DB query, result cached
// Request 2: cache hit, no DB query
```
Use when sequential user actions hit multiple endpoints needing the same data within seconds.
**With Vercel's [Fluid Compute](https://vercel.com/docs/fluid-compute):** LRU caching is especially effective because multiple concurrent requests can share the same function instance and cache. This means the cache persists across requests without needing external storage like Redis.
**In traditional serverless:** Each invocation runs in isolation, so consider Redis for cross-process caching.
Reference: [https://github.com/isaacs/node-lru-cache](https://github.com/isaacs/node-lru-cache)

View File

@@ -0,0 +1,26 @@
---
title: Per-Request Deduplication with React.cache()
impact: MEDIUM
impactDescription: deduplicates within request
tags: server, cache, react-cache, deduplication
---
## Per-Request Deduplication with React.cache()
Use `React.cache()` for server-side request deduplication. Authentication and database queries benefit most.
**Usage:**
```typescript
import { cache } from 'react'
export const getCurrentUser = cache(async () => {
const session = await auth()
if (!session?.user?.id) return null
return await db.user.findUnique({
where: { id: session.user.id }
})
})
```
Within a single request, multiple calls to `getCurrentUser()` execute the query only once.

View File

@@ -0,0 +1,79 @@
---
title: Parallel Data Fetching with Component Composition
impact: CRITICAL
impactDescription: eliminates server-side waterfalls
tags: server, rsc, parallel-fetching, composition
---
## Parallel Data Fetching with Component Composition
React Server Components execute sequentially within a tree. Restructure with composition to parallelize data fetching.
**Incorrect (Sidebar waits for Page's fetch to complete):**
```tsx
export default async function Page() {
const header = await fetchHeader()
return (
<div>
<div>{header}</div>
<Sidebar />
</div>
)
}
async function Sidebar() {
const items = await fetchSidebarItems()
return <nav>{items.map(renderItem)}</nav>
}
```
**Correct (both fetch simultaneously):**
```tsx
async function Header() {
const data = await fetchHeader()
return <div>{data}</div>
}
async function Sidebar() {
const items = await fetchSidebarItems()
return <nav>{items.map(renderItem)}</nav>
}
export default function Page() {
return (
<div>
<Header />
<Sidebar />
</div>
)
}
```
**Alternative with children prop:**
```tsx
async function Layout({ children }: { children: ReactNode }) {
const header = await fetchHeader()
return (
<div>
<div>{header}</div>
{children}
</div>
)
}
async function Sidebar() {
const items = await fetchSidebarItems()
return <nav>{items.map(renderItem)}</nav>
}
export default function Page() {
return (
<Layout>
<Sidebar />
</Layout>
)
}
```

View File

@@ -0,0 +1,38 @@
---
title: Minimize Serialization at RSC Boundaries
impact: HIGH
impactDescription: reduces data transfer size
tags: server, rsc, serialization, props
---
## Minimize Serialization at RSC Boundaries
The React Server/Client boundary serializes all object properties into strings and embeds them in the HTML response and subsequent RSC requests. This serialized data directly impacts page weight and load time, so **size matters a lot**. Only pass fields that the client actually uses.
**Incorrect (serializes all 50 fields):**
```tsx
async function Page() {
const user = await fetchUser() // 50 fields
return <Profile user={user} />
}
'use client'
function Profile({ user }: { user: User }) {
return <div>{user.name}</div> // uses 1 field
}
```
**Correct (serializes only 1 field):**
```tsx
async function Page() {
const user = await fetchUser()
return <Profile name={user.name} />
}
'use client'
function Profile({ name }: { name: string }) {
return <div>{name}</div>
}
```

View File

@@ -1,6 +1,9 @@
# Ignore everything by default, selectively add things to context
*
# Documentation (for embeddings/search)
!docs/
# Platform - Libs
!autogpt_platform/autogpt_libs/autogpt_libs/
!autogpt_platform/autogpt_libs/pyproject.toml
@@ -16,6 +19,7 @@
!autogpt_platform/backend/poetry.lock
!autogpt_platform/backend/README.md
!autogpt_platform/backend/.env
!autogpt_platform/backend/gen_prisma_types_stub.py
# Platform - Market
!autogpt_platform/market/market/

View File

@@ -160,7 +160,7 @@ pnpm storybook # Start component development server
**Backend Entry Points:**
- `backend/backend/server/server.py` - FastAPI application setup
- `backend/backend/api/rest_api.py` - FastAPI application setup
- `backend/backend/data/` - Database models and user management
- `backend/blocks/` - Agent execution blocks and logic
@@ -219,7 +219,7 @@ Agents are built using a visual block-based system where each block performs a s
### API Development
1. Update routes in `/backend/backend/server/routers/`
1. Update routes in `/backend/backend/api/features/`
2. Add/update Pydantic models in same directory
3. Write tests alongside route files
4. For `data/*.py` changes, validate user ID checks
@@ -285,7 +285,7 @@ Agents are built using a visual block-based system where each block performs a s
### Security Guidelines
**Cache Protection Middleware** (`/backend/backend/server/middleware/security.py`):
**Cache Protection Middleware** (`/backend/backend/api/middleware/security.py`):
- Default: Disables caching for ALL endpoints with `Cache-Control: no-store, no-cache, must-revalidate, private`
- Uses allow list approach for cacheable paths (static assets, health checks, public pages)

View File

@@ -93,5 +93,5 @@ jobs:
Error logs:
${{ toJSON(fromJSON(steps.failure_details.outputs.result).errorLogs) }}
anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
claude_code_oauth_token: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
claude_args: "--allowedTools 'Edit,MultiEdit,Write,Read,Glob,Grep,LS,Bash(git:*),Bash(bun:*),Bash(npm:*),Bash(npx:*),Bash(gh:*)'"

View File

@@ -7,7 +7,7 @@
# - Provide actionable recommendations for the development team
#
# Triggered on: Dependabot PRs (opened, synchronize)
# Requirements: ANTHROPIC_API_KEY secret must be configured
# Requirements: CLAUDE_CODE_OAUTH_TOKEN secret must be configured
name: Claude Dependabot PR Review
@@ -74,7 +74,7 @@ jobs:
- name: Generate Prisma Client
working-directory: autogpt_platform/backend
run: poetry run prisma generate
run: poetry run prisma generate && poetry run gen-prisma-stub
# Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
- name: Set up Node.js
@@ -308,7 +308,7 @@ jobs:
id: claude_review
uses: anthropics/claude-code-action@v1
with:
anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
claude_code_oauth_token: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
claude_args: |
--allowedTools "Bash(npm:*),Bash(pnpm:*),Bash(poetry:*),Bash(git:*),Edit,Replace,NotebookEditCell,mcp__github_inline_comment__create_inline_comment,Bash(gh pr comment:*), Bash(gh pr diff:*), Bash(gh pr view:*)"
prompt: |

View File

@@ -90,7 +90,7 @@ jobs:
- name: Generate Prisma Client
working-directory: autogpt_platform/backend
run: poetry run prisma generate
run: poetry run prisma generate && poetry run gen-prisma-stub
# Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
- name: Set up Node.js
@@ -323,7 +323,7 @@ jobs:
id: claude
uses: anthropics/claude-code-action@v1
with:
anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
claude_code_oauth_token: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
claude_args: |
--allowedTools "Bash(npm:*),Bash(pnpm:*),Bash(poetry:*),Bash(git:*),Edit,Replace,NotebookEditCell,mcp__github_inline_comment__create_inline_comment,Bash(gh pr comment:*), Bash(gh pr diff:*), Bash(gh pr view:*), Bash(gh pr edit:*)"
--model opus

View File

@@ -72,7 +72,7 @@ jobs:
- name: Generate Prisma Client
working-directory: autogpt_platform/backend
run: poetry run prisma generate
run: poetry run prisma generate && poetry run gen-prisma-stub
# Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
- name: Set up Node.js
@@ -108,6 +108,16 @@ jobs:
# run: pnpm playwright install --with-deps chromium
# Docker setup for development environment
- name: Free up disk space
run: |
# Remove large unused tools to free disk space for Docker builds
sudo rm -rf /usr/share/dotnet
sudo rm -rf /usr/local/lib/android
sudo rm -rf /opt/ghc
sudo rm -rf /opt/hostedtoolcache/CodeQL
sudo docker system prune -af
df -h
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3

78
.github/workflows/docs-block-sync.yml vendored Normal file
View File

@@ -0,0 +1,78 @@
name: Block Documentation Sync Check
on:
push:
branches: [master, dev]
paths:
- "autogpt_platform/backend/backend/blocks/**"
- "docs/integrations/**"
- "autogpt_platform/backend/scripts/generate_block_docs.py"
- ".github/workflows/docs-block-sync.yml"
pull_request:
branches: [master, dev]
paths:
- "autogpt_platform/backend/backend/blocks/**"
- "docs/integrations/**"
- "autogpt_platform/backend/scripts/generate_block_docs.py"
- ".github/workflows/docs-block-sync.yml"
jobs:
check-docs-sync:
runs-on: ubuntu-latest
timeout-minutes: 15
steps:
- name: Checkout code
uses: actions/checkout@v4
with:
fetch-depth: 1
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: "3.11"
- name: Set up Python dependency cache
uses: actions/cache@v4
with:
path: ~/.cache/pypoetry
key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
restore-keys: |
poetry-${{ runner.os }}-
- name: Install Poetry
run: |
cd autogpt_platform/backend
HEAD_POETRY_VERSION=$(python3 ../../.github/workflows/scripts/get_package_version_from_lockfile.py poetry)
echo "Found Poetry version ${HEAD_POETRY_VERSION} in backend/poetry.lock"
curl -sSL https://install.python-poetry.org | POETRY_VERSION=$HEAD_POETRY_VERSION python3 -
echo "$HOME/.local/bin" >> $GITHUB_PATH
- name: Install dependencies
working-directory: autogpt_platform/backend
run: |
poetry install --only main
poetry run prisma generate
- name: Check block documentation is in sync
working-directory: autogpt_platform/backend
run: |
echo "Checking if block documentation is in sync with code..."
poetry run python scripts/generate_block_docs.py --check
- name: Show diff if out of sync
if: failure()
working-directory: autogpt_platform/backend
run: |
echo "::error::Block documentation is out of sync with code!"
echo ""
echo "To fix this, run the following command locally:"
echo " cd autogpt_platform/backend && poetry run python scripts/generate_block_docs.py"
echo ""
echo "Then commit the updated documentation files."
echo ""
echo "Regenerating docs to show diff..."
poetry run python scripts/generate_block_docs.py
echo ""
echo "Changes detected:"
git diff ../../docs/integrations/ || true

View File

@@ -0,0 +1,95 @@
name: Claude Block Docs Review
on:
pull_request:
types: [opened, synchronize]
paths:
- "docs/integrations/**"
- "autogpt_platform/backend/backend/blocks/**"
jobs:
claude-review:
# Only run for PRs from members/collaborators
if: |
github.event.pull_request.author_association == 'OWNER' ||
github.event.pull_request.author_association == 'MEMBER' ||
github.event.pull_request.author_association == 'COLLABORATOR'
runs-on: ubuntu-latest
timeout-minutes: 15
permissions:
contents: read
pull-requests: write
id-token: write
steps:
- name: Checkout code
uses: actions/checkout@v4
with:
fetch-depth: 0
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: "3.11"
- name: Set up Python dependency cache
uses: actions/cache@v4
with:
path: ~/.cache/pypoetry
key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
restore-keys: |
poetry-${{ runner.os }}-
- name: Install Poetry
run: |
cd autogpt_platform/backend
HEAD_POETRY_VERSION=$(python3 ../../.github/workflows/scripts/get_package_version_from_lockfile.py poetry)
curl -sSL https://install.python-poetry.org | POETRY_VERSION=$HEAD_POETRY_VERSION python3 -
echo "$HOME/.local/bin" >> $GITHUB_PATH
- name: Install dependencies
working-directory: autogpt_platform/backend
run: |
poetry install --only main
poetry run prisma generate
- name: Run Claude Code Review
uses: anthropics/claude-code-action@v1
with:
claude_code_oauth_token: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
claude_args: |
--allowedTools "Read,Glob,Grep,Bash(gh pr comment:*),Bash(gh pr diff:*),Bash(gh pr view:*)"
prompt: |
You are reviewing a PR that modifies block documentation or block code for AutoGPT.
## Your Task
Review the changes in this PR and provide constructive feedback. Focus on:
1. **Documentation Accuracy**: For any block code changes, verify that:
- Input/output tables in docs match the actual block schemas
- Description text accurately reflects what the block does
- Any new blocks have corresponding documentation
2. **Manual Content Quality**: Check manual sections (marked with `<!-- MANUAL: -->` markers):
- "How it works" sections should have clear technical explanations
- "Possible use case" sections should have practical, real-world examples
- Content should be helpful for users trying to understand the blocks
3. **Template Compliance**: Ensure docs follow the standard template:
- What it is (brief intro)
- What it does (description)
- How it works (technical explanation)
- Inputs table
- Outputs table
- Possible use case
4. **Cross-references**: Check that links and anchors are correct
## Review Process
1. First, get the PR diff to see what changed: `gh pr diff ${{ github.event.pull_request.number }}`
2. Read any modified block files to understand the implementation
3. Read corresponding documentation files to verify accuracy
4. Provide your feedback as a PR comment
Be constructive and specific. If everything looks good, say so!
If there are issues, explain what's wrong and suggest how to fix it.

194
.github/workflows/docs-enhance.yml vendored Normal file
View File

@@ -0,0 +1,194 @@
name: Enhance Block Documentation
on:
workflow_dispatch:
inputs:
block_pattern:
description: 'Block file pattern to enhance (e.g., "google/*.md" or "*" for all blocks)'
required: true
default: '*'
type: string
dry_run:
description: 'Dry run mode - show proposed changes without committing'
type: boolean
default: true
max_blocks:
description: 'Maximum number of blocks to process (0 for unlimited)'
type: number
default: 10
jobs:
enhance-docs:
runs-on: ubuntu-latest
timeout-minutes: 45
permissions:
contents: write
pull-requests: write
id-token: write
steps:
- name: Checkout code
uses: actions/checkout@v4
with:
fetch-depth: 1
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: "3.11"
- name: Set up Python dependency cache
uses: actions/cache@v4
with:
path: ~/.cache/pypoetry
key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
restore-keys: |
poetry-${{ runner.os }}-
- name: Install Poetry
run: |
cd autogpt_platform/backend
HEAD_POETRY_VERSION=$(python3 ../../.github/workflows/scripts/get_package_version_from_lockfile.py poetry)
curl -sSL https://install.python-poetry.org | POETRY_VERSION=$HEAD_POETRY_VERSION python3 -
echo "$HOME/.local/bin" >> $GITHUB_PATH
- name: Install dependencies
working-directory: autogpt_platform/backend
run: |
poetry install --only main
poetry run prisma generate
- name: Run Claude Enhancement
uses: anthropics/claude-code-action@v1
with:
claude_code_oauth_token: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
claude_args: |
--allowedTools "Read,Edit,Glob,Grep,Write,Bash(git:*),Bash(gh:*),Bash(find:*),Bash(ls:*)"
prompt: |
You are enhancing block documentation for AutoGPT. Your task is to improve the MANUAL sections
of block documentation files by reading the actual block implementations and writing helpful content.
## Configuration
- Block pattern: ${{ inputs.block_pattern }}
- Dry run: ${{ inputs.dry_run }}
- Max blocks to process: ${{ inputs.max_blocks }}
## Your Task
1. **Find Documentation Files**
Find block documentation files matching the pattern in `docs/integrations/`
Pattern: ${{ inputs.block_pattern }}
Use: `find docs/integrations -name "*.md" -type f`
2. **For Each Documentation File** (up to ${{ inputs.max_blocks }} files):
a. Read the documentation file
b. Identify which block(s) it documents (look for the block class name)
c. Find and read the corresponding block implementation in `autogpt_platform/backend/backend/blocks/`
d. Improve the MANUAL sections:
**"How it works" section** (within `<!-- MANUAL: how_it_works -->` markers):
- Explain the technical flow of the block
- Describe what APIs or services it connects to
- Note any important configuration or prerequisites
- Keep it concise but informative (2-4 paragraphs)
**"Possible use case" section** (within `<!-- MANUAL: use_case -->` markers):
- Provide 2-3 practical, real-world examples
- Make them specific and actionable
- Show how this block could be used in an automation workflow
3. **Important Rules**
- ONLY modify content within `<!-- MANUAL: -->` and `<!-- END MANUAL -->` markers
- Do NOT modify auto-generated sections (inputs/outputs tables, descriptions)
- Keep content accurate based on the actual block implementation
- Write for users who may not be technical experts
4. **Output**
${{ inputs.dry_run == true && 'DRY RUN MODE: Show proposed changes for each file but do NOT actually edit the files. Describe what you would change.' || 'LIVE MODE: Actually edit the files to improve the documentation.' }}
## Example Improvements
**Before (How it works):**
```
_Add technical explanation here._
```
**After (How it works):**
```
This block connects to the GitHub API to retrieve issue information. When executed,
it authenticates using your GitHub credentials and fetches issue details including
title, body, labels, and assignees.
The block requires a valid GitHub OAuth connection with repository access permissions.
It supports both public and private repositories you have access to.
```
**Before (Possible use case):**
```
_Add practical use case examples here._
```
**After (Possible use case):**
```
**Customer Support Automation**: Monitor a GitHub repository for new issues with
the "bug" label, then automatically create a ticket in your support system and
notify the on-call engineer via Slack.
**Release Notes Generation**: When a new release is published, gather all closed
issues since the last release and generate a summary for your changelog.
```
Begin by finding and listing the documentation files to process.
- name: Create PR with enhanced documentation
if: ${{ inputs.dry_run == false }}
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
run: |
# Check if there are changes
if git diff --quiet docs/integrations/; then
echo "No changes to commit"
exit 0
fi
# Configure git
git config user.name "github-actions[bot]"
git config user.email "github-actions[bot]@users.noreply.github.com"
# Create branch and commit
BRANCH_NAME="docs/enhance-blocks-$(date +%Y%m%d-%H%M%S)"
git checkout -b "$BRANCH_NAME"
git add docs/integrations/
git commit -m "docs: enhance block documentation with LLM-generated content
Pattern: ${{ inputs.block_pattern }}
Max blocks: ${{ inputs.max_blocks }}
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>"
# Push and create PR
git push -u origin "$BRANCH_NAME"
gh pr create \
--title "docs: LLM-enhanced block documentation" \
--body "## Summary
This PR contains LLM-enhanced documentation for block files matching pattern: \`${{ inputs.block_pattern }}\`
The following manual sections were improved:
- **How it works**: Technical explanations based on block implementations
- **Possible use case**: Practical, real-world examples
## Review Checklist
- [ ] Content is accurate based on block implementations
- [ ] Examples are practical and helpful
- [ ] No auto-generated sections were modified
---
🤖 Generated with [Claude Code](https://claude.com/claude-code)" \
--base dev

View File

@@ -134,7 +134,7 @@ jobs:
run: poetry install
- name: Generate Prisma Client
run: poetry run prisma generate
run: poetry run prisma generate && poetry run gen-prisma-stub
- id: supabase
name: Start Supabase
@@ -176,7 +176,7 @@ jobs:
}
- name: Run Database Migrations
run: poetry run prisma migrate dev --name updates
run: poetry run prisma migrate deploy
env:
DATABASE_URL: ${{ steps.supabase.outputs.DB_URL }}
DIRECT_URL: ${{ steps.supabase.outputs.DB_URL }}

View File

@@ -11,6 +11,7 @@ on:
- ".github/workflows/platform-frontend-ci.yml"
- "autogpt_platform/frontend/**"
merge_group:
workflow_dispatch:
concurrency:
group: ${{ github.workflow }}-${{ github.event_name == 'merge_group' && format('merge-queue-{0}', github.ref) || format('{0}-{1}', github.ref, github.event.pull_request.number || github.sha) }}
@@ -127,7 +128,7 @@ jobs:
token: ${{ secrets.GITHUB_TOKEN }}
exitOnceUploaded: true
test:
e2e_test:
runs-on: big-boi
needs: setup
strategy:
@@ -151,6 +152,14 @@ jobs:
run: |
cp ../.env.default ../.env
- name: Copy backend .env and set OpenAI API key
run: |
cp ../backend/.env.default ../backend/.env
echo "OPENAI_INTERNAL_API_KEY=${{ secrets.OPENAI_API_KEY }}" >> ../backend/.env
env:
# Used by E2E test data script to generate embeddings for approved store agents
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
@@ -226,14 +235,62 @@ jobs:
- name: Run Playwright tests
run: pnpm test:no-build
continue-on-error: false
- name: Upload Playwright artifacts
if: failure()
- name: Upload Playwright report
if: always()
uses: actions/upload-artifact@v4
with:
name: playwright-report
path: playwright-report
if-no-files-found: ignore
retention-days: 3
- name: Upload Playwright test results
if: always()
uses: actions/upload-artifact@v4
with:
name: playwright-test-results
path: test-results
if-no-files-found: ignore
retention-days: 3
- name: Print Final Docker Compose logs
if: always()
run: docker compose -f ../docker-compose.yml logs
integration_test:
runs-on: ubuntu-latest
needs: setup
steps:
- name: Checkout repository
uses: actions/checkout@v4
with:
submodules: recursive
- name: Set up Node.js
uses: actions/setup-node@v4
with:
node-version: "22.18.0"
- name: Enable corepack
run: corepack enable
- name: Restore dependencies cache
uses: actions/cache@v4
with:
path: ~/.pnpm-store
key: ${{ needs.setup.outputs.cache-key }}
restore-keys: |
${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml') }}
${{ runner.os }}-pnpm-
- name: Install dependencies
run: pnpm install --frozen-lockfile
- name: Generate API client
run: pnpm generate:api
- name: Run Integration Tests
run: pnpm test:unit

2
.gitignore vendored
View File

@@ -178,4 +178,6 @@ autogpt_platform/backend/settings.py
*.ign.*
.test-contents
.claude/settings.local.json
CLAUDE.local.md
/autogpt_platform/backend/logs
.next

View File

@@ -16,6 +16,34 @@ See `docs/content/platform/getting-started.md` for setup instructions.
- Format Python code with `poetry run format`.
- Format frontend code using `pnpm format`.
## Frontend guidelines:
See `/frontend/CONTRIBUTING.md` for complete patterns. Quick reference:
1. **Pages**: Create in `src/app/(platform)/feature-name/page.tsx`
- Add `usePageName.ts` hook for logic
- Put sub-components in local `components/` folder
2. **Components**: Structure as `ComponentName/ComponentName.tsx` + `useComponentName.ts` + `helpers.ts`
- Use design system components from `src/components/` (atoms, molecules, organisms)
- Never use `src/components/__legacy__/*`
3. **Data fetching**: Use generated API hooks from `@/app/api/__generated__/endpoints/`
- Regenerate with `pnpm generate:api`
- Pattern: `use{Method}{Version}{OperationName}`
4. **Styling**: Tailwind CSS only, use design tokens, Phosphor Icons only
5. **Testing**: Add Storybook stories for new components, Playwright for E2E
6. **Code conventions**: Function declarations (not arrow functions) for components/handlers
- Component props should be `interface Props { ... }` (not exported) unless the interface needs to be used outside the component
- Separate render logic from business logic (component.tsx + useComponent.ts + helpers.ts)
- Colocate state when possible and avoid creating large components, use sub-components ( local `/components` folder next to the parent component ) when sensible
- Avoid large hooks, abstract logic into `helpers.ts` files when sensible
- Use function declarations for components, arrow functions only for callbacks
- No barrel files or `index.ts` re-exports
- Avoid comments at all times unless the code is very complex
- Do not use `useCallback` or `useMemo` unless asked to optimise a given function
- Do not type hook returns, let Typescript infer as much as possible
- Never type with `any`, if not types available use `unknown`
## Testing
- Backend: `poetry run test` (runs pytest with a docker based postgres + prisma).
@@ -23,22 +51,8 @@ See `docs/content/platform/getting-started.md` for setup instructions.
Always run the relevant linters and tests before committing.
Use conventional commit messages for all commits (e.g. `feat(backend): add API`).
Types:
- feat
- fix
- refactor
- ci
- dx (developer experience)
Scopes:
- platform
- platform/library
- platform/marketplace
- backend
- backend/executor
- frontend
- frontend/library
- frontend/marketplace
- blocks
Types: - feat - fix - refactor - ci - dx (developer experience)
Scopes: - platform - platform/library - platform/marketplace - backend - backend/executor - frontend - frontend/library - frontend/marketplace - blocks
## Pull requests

View File

@@ -54,7 +54,7 @@ Before proceeding with the installation, ensure your system meets the following
### Updated Setup Instructions:
We've moved to a fully maintained and regularly updated documentation site.
👉 [Follow the official self-hosting guide here](https://docs.agpt.co/platform/getting-started/)
👉 [Follow the official self-hosting guide here](https://agpt.co/docs/platform/getting-started/getting-started)
This tutorial assumes you have Docker, VSCode, git and npm installed.

View File

@@ -6,152 +6,30 @@ This file provides guidance to Claude Code (claude.ai/code) when working with co
AutoGPT Platform is a monorepo containing:
- **Backend** (`/backend`): Python FastAPI server with async support
- **Frontend** (`/frontend`): Next.js React application
- **Shared Libraries** (`/autogpt_libs`): Common Python utilities
- **Backend** (`backend`): Python FastAPI server with async support
- **Frontend** (`frontend`): Next.js React application
- **Shared Libraries** (`autogpt_libs`): Common Python utilities
## Essential Commands
## Component Documentation
### Backend Development
- **Backend**: See @backend/CLAUDE.md for backend-specific commands, architecture, and development tasks
- **Frontend**: See @frontend/CLAUDE.md for frontend-specific commands, architecture, and development patterns
```bash
# Install dependencies
cd backend && poetry install
# Run database migrations
poetry run prisma migrate dev
# Start all services (database, redis, rabbitmq, clamav)
docker compose up -d
# Run the backend server
poetry run serve
# Run tests
poetry run test
# Run specific test
poetry run pytest path/to/test_file.py::test_function_name
# Run block tests (tests that validate all blocks work correctly)
poetry run pytest backend/blocks/test/test_block.py -xvs
# Run tests for a specific block (e.g., GetCurrentTimeBlock)
poetry run pytest 'backend/blocks/test/test_block.py::test_available_blocks[GetCurrentTimeBlock]' -xvs
# Lint and format
# prefer format if you want to just "fix" it and only get the errors that can't be autofixed
poetry run format # Black + isort
poetry run lint # ruff
```
More details can be found in TESTING.md
#### Creating/Updating Snapshots
When you first write a test or when the expected output changes:
```bash
poetry run pytest path/to/test.py --snapshot-update
```
⚠️ **Important**: Always review snapshot changes before committing! Use `git diff` to verify the changes are expected.
### Frontend Development
```bash
# Install dependencies
cd frontend && pnpm i
# Generate API client from OpenAPI spec
pnpm generate:api
# Start development server
pnpm dev
# Run E2E tests
pnpm test
# Run Storybook for component development
pnpm storybook
# Build production
pnpm build
# Format and lint
pnpm format
# Type checking
pnpm types
```
**📖 Complete Guide**: See `/frontend/CONTRIBUTING.md` and `/frontend/.cursorrules` for comprehensive frontend patterns.
**Key Frontend Conventions:**
- Separate render logic from data/behavior in components
- Use generated API hooks from `@/app/api/__generated__/endpoints/`
- Use function declarations (not arrow functions) for components/handlers
- Use design system components from `src/components/` (atoms, molecules, organisms)
- Only use Phosphor Icons
- Never use `src/components/__legacy__/*` or deprecated `BackendAPI`
## Architecture Overview
### Backend Architecture
- **API Layer**: FastAPI with REST and WebSocket endpoints
- **Database**: PostgreSQL with Prisma ORM, includes pgvector for embeddings
- **Queue System**: RabbitMQ for async task processing
- **Execution Engine**: Separate executor service processes agent workflows
- **Authentication**: JWT-based with Supabase integration
- **Security**: Cache protection middleware prevents sensitive data caching in browsers/proxies
### Frontend Architecture
- **Framework**: Next.js 15 App Router (client-first approach)
- **Data Fetching**: Type-safe generated API hooks via Orval + React Query
- **State Management**: React Query for server state, co-located UI state in components/hooks
- **Component Structure**: Separate render logic (`.tsx`) from business logic (`use*.ts` hooks)
- **Workflow Builder**: Visual graph editor using @xyflow/react
- **UI Components**: shadcn/ui (Radix UI primitives) with Tailwind CSS styling
- **Icons**: Phosphor Icons only
- **Feature Flags**: LaunchDarkly integration
- **Error Handling**: ErrorCard for render errors, toast for mutations, Sentry for exceptions
- **Testing**: Playwright for E2E, Storybook for component development
### Key Concepts
## Key Concepts
1. **Agent Graphs**: Workflow definitions stored as JSON, executed by the backend
2. **Blocks**: Reusable components in `/backend/blocks/` that perform specific tasks
2. **Blocks**: Reusable components in `backend/backend/blocks/` that perform specific tasks
3. **Integrations**: OAuth and API connections stored per user
4. **Store**: Marketplace for sharing agent templates
5. **Virus Scanning**: ClamAV integration for file upload security
### Testing Approach
- Backend uses pytest with snapshot testing for API responses
- Test files are colocated with source files (`*_test.py`)
- Frontend uses Playwright for E2E tests
- Component testing via Storybook
### Database Schema
Key models (defined in `/backend/schema.prisma`):
- `User`: Authentication and profile data
- `AgentGraph`: Workflow definitions with version control
- `AgentGraphExecution`: Execution history and results
- `AgentNode`: Individual nodes in a workflow
- `StoreListing`: Marketplace listings for sharing agents
### Environment Configuration
#### Configuration Files
- **Backend**: `/backend/.env.default` (defaults) → `/backend/.env` (user overrides)
- **Frontend**: `/frontend/.env.default` (defaults) → `/frontend/.env` (user overrides)
- **Platform**: `/.env.default` (Supabase/shared defaults) → `/.env` (user overrides)
- **Backend**: `backend/.env.default` (defaults) → `backend/.env` (user overrides)
- **Frontend**: `frontend/.env.default` (defaults) → `frontend/.env` (user overrides)
- **Platform**: `.env.default` (Supabase/shared defaults) → `.env` (user overrides)
#### Docker Environment Loading Order
@@ -167,75 +45,12 @@ Key models (defined in `/backend/schema.prisma`):
- Backend/Frontend services use YAML anchors for consistent configuration
- Supabase services (`db/docker/docker-compose.yml`) follow the same pattern
### Common Development Tasks
**Adding a new block:**
Follow the comprehensive [Block SDK Guide](../../../docs/content/platform/block-sdk-guide.md) which covers:
- Provider configuration with `ProviderBuilder`
- Block schema definition
- Authentication (API keys, OAuth, webhooks)
- Testing and validation
- File organization
Quick steps:
1. Create new file in `/backend/backend/blocks/`
2. Configure provider using `ProviderBuilder` in `_config.py`
3. Inherit from `Block` base class
4. Define input/output schemas using `BlockSchema`
5. Implement async `run` method
6. Generate unique block ID using `uuid.uuid4()`
7. Test with `poetry run pytest backend/blocks/test/test_block.py`
Note: when making many new blocks analyze the interfaces for each of these blocks and picture if they would go well together in a graph based editor or would they struggle to connect productively?
ex: do the inputs and outputs tie well together?
If you get any pushback or hit complex block conditions check the new_blocks guide in the docs.
**Modifying the API:**
1. Update route in `/backend/backend/server/routers/`
2. Add/update Pydantic models in same directory
3. Write tests alongside the route file
4. Run `poetry run test` to verify
**Frontend feature development:**
See `/frontend/CONTRIBUTING.md` for complete patterns. Quick reference:
1. **Pages**: Create in `src/app/(platform)/feature-name/page.tsx`
- Add `usePageName.ts` hook for logic
- Put sub-components in local `components/` folder
2. **Components**: Structure as `ComponentName/ComponentName.tsx` + `useComponentName.ts` + `helpers.ts`
- Use design system components from `src/components/` (atoms, molecules, organisms)
- Never use `src/components/__legacy__/*`
3. **Data fetching**: Use generated API hooks from `@/app/api/__generated__/endpoints/`
- Regenerate with `pnpm generate:api`
- Pattern: `use{Method}{Version}{OperationName}`
4. **Styling**: Tailwind CSS only, use design tokens, Phosphor Icons only
5. **Testing**: Add Storybook stories for new components, Playwright for E2E
6. **Code conventions**: Function declarations (not arrow functions) for components/handlers
### Security Implementation
**Cache Protection Middleware:**
- Located in `/backend/backend/server/middleware/security.py`
- Default behavior: Disables caching for ALL endpoints with `Cache-Control: no-store, no-cache, must-revalidate, private`
- Uses an allow list approach - only explicitly permitted paths can be cached
- Cacheable paths include: static assets (`/static/*`, `/_next/static/*`), health checks, public store pages, documentation
- Prevents sensitive data (auth tokens, API keys, user data) from being cached by browsers/proxies
- To allow caching for a new endpoint, add it to `CACHEABLE_PATHS` in the middleware
- Applied to both main API server and external API applications
### Creating Pull Requests
- Create the PR aginst the `dev` branch of the repository.
- Ensure the branch name is descriptive (e.g., `feature/add-new-block`)/
- Use conventional commit messages (see below)/
- Fill out the .github/PULL_REQUEST_TEMPLATE.md template as the PR description/
- Create the PR against the `dev` branch of the repository.
- Ensure the branch name is descriptive (e.g., `feature/add-new-block`)
- Use conventional commit messages (see below)
- Fill out the .github/PULL_REQUEST_TEMPLATE.md template as the PR description
- Run the github pre-commit hooks to ensure code quality.
### Reviewing/Revising Pull Requests

View File

@@ -6,12 +6,14 @@ start-core:
# Stop core services
stop-core:
docker compose stop deps
docker compose stop
reset-db:
docker compose stop db
rm -rf db/docker/volumes/db/data
cd backend && poetry run prisma migrate deploy
cd backend && poetry run prisma generate
cd backend && poetry run gen-prisma-stub
# View logs for core services
logs-core:
@@ -33,6 +35,7 @@ init-env:
migrate:
cd backend && poetry run prisma migrate deploy
cd backend && poetry run prisma generate
cd backend && poetry run gen-prisma-stub
run-backend:
cd backend && poetry run app
@@ -58,4 +61,4 @@ help:
@echo " run-backend - Run the backend FastAPI server"
@echo " run-frontend - Run the frontend Next.js development server"
@echo " test-data - Run the test data creator"
@echo " load-store-agents - Load store agents from agents/ folder into test database"
@echo " load-store-agents - Load store agents from agents/ folder into test database"

View File

@@ -57,6 +57,9 @@ class APIKeySmith:
def hash_key(self, raw_key: str) -> tuple[str, str]:
"""Migrate a legacy hash to secure hash format."""
if not raw_key.startswith(self.PREFIX):
raise ValueError("Key without 'agpt_' prefix would fail validation")
salt = self._generate_salt()
hash = self._hash_key_with_salt(raw_key, salt)
return hash, salt.hex()

View File

@@ -1,29 +1,25 @@
from fastapi import FastAPI
from fastapi.openapi.utils import get_openapi
from .jwt_utils import bearer_jwt_auth
def add_auth_responses_to_openapi(app: FastAPI) -> None:
"""
Set up custom OpenAPI schema generation that adds 401 responses
Patch a FastAPI instance's `openapi()` method to add 401 responses
to all authenticated endpoints.
This is needed when using HTTPBearer with auto_error=False to get proper
401 responses instead of 403, but FastAPI only automatically adds security
responses when auto_error=True.
"""
# Wrap current method to allow stacking OpenAPI schema modifiers like this
wrapped_openapi = app.openapi
def custom_openapi():
if app.openapi_schema:
return app.openapi_schema
openapi_schema = get_openapi(
title=app.title,
version=app.version,
description=app.description,
routes=app.routes,
)
openapi_schema = wrapped_openapi()
# Add 401 response to all endpoints that have security requirements
for path, methods in openapi_schema["paths"].items():

View File

@@ -58,6 +58,13 @@ V0_API_KEY=
OPEN_ROUTER_API_KEY=
NVIDIA_API_KEY=
# Langfuse Prompt Management
# Used for managing the CoPilot system prompt externally
# Get credentials from https://cloud.langfuse.com or your self-hosted instance
LANGFUSE_PUBLIC_KEY=
LANGFUSE_SECRET_KEY=
LANGFUSE_HOST=https://cloud.langfuse.com
# OAuth Credentials
# For the OAuth callback URL, use <your_frontend_url>/auth/integrations/oauth_callback,
# e.g. http://localhost:3000/auth/integrations/oauth_callback
@@ -171,5 +178,10 @@ AYRSHARE_JWT_KEY=
SMARTLEAD_API_KEY=
ZEROBOUNCE_API_KEY=
# PostHog Analytics
# Get API key from https://posthog.com - Project Settings > Project API Key
POSTHOG_API_KEY=
POSTHOG_HOST=https://eu.i.posthog.com
# Other Services
AUTOMOD_API_KEY=

View File

@@ -18,3 +18,4 @@ load-tests/results/
load-tests/*.json
load-tests/*.log
load-tests/node_modules/*
migrations/*/rollback*.sql

View File

@@ -0,0 +1,170 @@
# CLAUDE.md - Backend
This file provides guidance to Claude Code when working with the backend.
## Essential Commands
To run something with Python package dependencies you MUST use `poetry run ...`.
```bash
# Install dependencies
poetry install
# Run database migrations
poetry run prisma migrate dev
# Start all services (database, redis, rabbitmq, clamav)
docker compose up -d
# Run the backend as a whole
poetry run app
# Run tests
poetry run test
# Run specific test
poetry run pytest path/to/test_file.py::test_function_name
# Run block tests (tests that validate all blocks work correctly)
poetry run pytest backend/blocks/test/test_block.py -xvs
# Run tests for a specific block (e.g., GetCurrentTimeBlock)
poetry run pytest 'backend/blocks/test/test_block.py::test_available_blocks[GetCurrentTimeBlock]' -xvs
# Lint and format
# prefer format if you want to just "fix" it and only get the errors that can't be autofixed
poetry run format # Black + isort
poetry run lint # ruff
```
More details can be found in @TESTING.md
### Creating/Updating Snapshots
When you first write a test or when the expected output changes:
```bash
poetry run pytest path/to/test.py --snapshot-update
```
⚠️ **Important**: Always review snapshot changes before committing! Use `git diff` to verify the changes are expected.
## Architecture
- **API Layer**: FastAPI with REST and WebSocket endpoints
- **Database**: PostgreSQL with Prisma ORM, includes pgvector for embeddings
- **Queue System**: RabbitMQ for async task processing
- **Execution Engine**: Separate executor service processes agent workflows
- **Authentication**: JWT-based with Supabase integration
- **Security**: Cache protection middleware prevents sensitive data caching in browsers/proxies
## Testing Approach
- Uses pytest with snapshot testing for API responses
- Test files are colocated with source files (`*_test.py`)
## Database Schema
Key models (defined in `schema.prisma`):
- `User`: Authentication and profile data
- `AgentGraph`: Workflow definitions with version control
- `AgentGraphExecution`: Execution history and results
- `AgentNode`: Individual nodes in a workflow
- `StoreListing`: Marketplace listings for sharing agents
## Environment Configuration
- **Backend**: `.env.default` (defaults) → `.env` (user overrides)
## Common Development Tasks
### Adding a new block
Follow the comprehensive [Block SDK Guide](@../../docs/content/platform/block-sdk-guide.md) which covers:
- Provider configuration with `ProviderBuilder`
- Block schema definition
- Authentication (API keys, OAuth, webhooks)
- Testing and validation
- File organization
Quick steps:
1. Create new file in `backend/blocks/`
2. Configure provider using `ProviderBuilder` in `_config.py`
3. Inherit from `Block` base class
4. Define input/output schemas using `BlockSchema`
5. Implement async `run` method
6. Generate unique block ID using `uuid.uuid4()`
7. Test with `poetry run pytest backend/blocks/test/test_block.py`
Note: when making many new blocks analyze the interfaces for each of these blocks and picture if they would go well together in a graph-based editor or would they struggle to connect productively?
ex: do the inputs and outputs tie well together?
If you get any pushback or hit complex block conditions check the new_blocks guide in the docs.
#### Handling files in blocks with `store_media_file()`
When blocks need to work with files (images, videos, documents), use `store_media_file()` from `backend.util.file`. The `return_format` parameter determines what you get back:
| Format | Use When | Returns |
|--------|----------|---------|
| `"for_local_processing"` | Processing with local tools (ffmpeg, MoviePy, PIL) | Local file path (e.g., `"image.png"`) |
| `"for_external_api"` | Sending content to external APIs (Replicate, OpenAI) | Data URI (e.g., `"data:image/png;base64,..."`) |
| `"for_block_output"` | Returning output from your block | Smart: `workspace://` in CoPilot, data URI in graphs |
**Examples:**
```python
# INPUT: Need to process file locally with ffmpeg
local_path = await store_media_file(
file=input_data.video,
execution_context=execution_context,
return_format="for_local_processing",
)
# local_path = "video.mp4" - use with Path/ffmpeg/etc
# INPUT: Need to send to external API like Replicate
image_b64 = await store_media_file(
file=input_data.image,
execution_context=execution_context,
return_format="for_external_api",
)
# image_b64 = "data:image/png;base64,iVBORw0..." - send to API
# OUTPUT: Returning result from block
result_url = await store_media_file(
file=generated_image_url,
execution_context=execution_context,
return_format="for_block_output",
)
yield "image_url", result_url
# In CoPilot: result_url = "workspace://abc123"
# In graphs: result_url = "data:image/png;base64,..."
```
**Key points:**
- `for_block_output` is the ONLY format that auto-adapts to execution context
- Always use `for_block_output` for block outputs unless you have a specific reason not to
- Never hardcode workspace checks - let `for_block_output` handle it
### Modifying the API
1. Update route in `backend/api/features/`
2. Add/update Pydantic models in same directory
3. Write tests alongside the route file
4. Run `poetry run test` to verify
## Security Implementation
### Cache Protection Middleware
- Located in `backend/api/middleware/security.py`
- Default behavior: Disables caching for ALL endpoints with `Cache-Control: no-store, no-cache, must-revalidate, private`
- Uses an allow list approach - only explicitly permitted paths can be cached
- Cacheable paths include: static assets (`static/*`, `_next/static/*`), health checks, public store pages, documentation
- Prevents sensitive data (auth tokens, API keys, user data) from being cached by browsers/proxies
- To allow caching for a new endpoint, add it to `CACHEABLE_PATHS` in the middleware
- Applied to both main API server and external API applications

View File

@@ -48,7 +48,8 @@ RUN poetry install --no-ansi --no-root
# Generate Prisma client
COPY autogpt_platform/backend/schema.prisma ./
COPY autogpt_platform/backend/backend/data/partial_types.py ./backend/data/partial_types.py
RUN poetry run prisma generate
COPY autogpt_platform/backend/gen_prisma_types_stub.py ./
RUN poetry run prisma generate && poetry run gen-prisma-stub
FROM debian:13-slim AS server_dependencies
@@ -99,6 +100,7 @@ COPY autogpt_platform/backend/migrations /app/autogpt_platform/backend/migration
FROM server_dependencies AS server
COPY autogpt_platform/backend /app/autogpt_platform/backend
COPY docs /app/docs
RUN poetry install --no-ansi --only-root
ENV PORT=8000

View File

@@ -108,7 +108,7 @@ import fastapi.testclient
import pytest
from pytest_snapshot.plugin import Snapshot
from backend.server.v2.myroute import router
from backend.api.features.myroute import router
app = fastapi.FastAPI()
app.include_router(router)
@@ -138,7 +138,7 @@ If the test doesn't need the `user_id` specifically, mocking is not necessary as
#### Using Global Auth Fixtures
Two global auth fixtures are provided by `backend/server/conftest.py`:
Two global auth fixtures are provided by `backend/api/conftest.py`:
- `mock_jwt_user` - Regular user with `test_user_id` ("test-user-id")
- `mock_jwt_admin` - Admin user with `admin_user_id` ("admin-user-id")
@@ -149,7 +149,7 @@ These provide the easiest way to set up authentication mocking in test modules:
import fastapi
import fastapi.testclient
import pytest
from backend.server.v2.myroute import router
from backend.api.features.myroute import router
app = fastapi.FastAPI()
app.include_router(router)

View File

@@ -3,12 +3,12 @@ from typing import Dict, Set
from fastapi import WebSocket
from backend.api.model import NotificationPayload, WSMessage, WSMethod
from backend.data.execution import (
ExecutionEventType,
GraphExecutionEvent,
NodeExecutionEvent,
)
from backend.server.model import NotificationPayload, WSMessage, WSMethod
_EVENT_TYPE_TO_METHOD_MAP: dict[ExecutionEventType, WSMethod] = {
ExecutionEventType.GRAPH_EXEC_UPDATE: WSMethod.GRAPH_EXECUTION_EVENT,

View File

@@ -4,13 +4,13 @@ from unittest.mock import AsyncMock
import pytest
from fastapi import WebSocket
from backend.api.conn_manager import ConnectionManager
from backend.api.model import NotificationPayload, WSMessage, WSMethod
from backend.data.execution import (
ExecutionStatus,
GraphExecutionEvent,
NodeExecutionEvent,
)
from backend.server.conn_manager import ConnectionManager
from backend.server.model import NotificationPayload, WSMessage, WSMethod
@pytest.fixture

View File

@@ -0,0 +1,25 @@
from fastapi import FastAPI
from backend.api.middleware.security import SecurityHeadersMiddleware
from backend.monitoring.instrumentation import instrument_fastapi
from .v1.routes import v1_router
external_api = FastAPI(
title="AutoGPT External API",
description="External API for AutoGPT integrations",
docs_url="/docs",
version="1.0",
)
external_api.add_middleware(SecurityHeadersMiddleware)
external_api.include_router(v1_router, prefix="/v1")
# Add Prometheus instrumentation
instrument_fastapi(
external_api,
service_name="external-api",
expose_endpoint=True,
endpoint="/metrics",
include_in_schema=True,
)

View File

@@ -0,0 +1,107 @@
from fastapi import HTTPException, Security, status
from fastapi.security import APIKeyHeader, HTTPAuthorizationCredentials, HTTPBearer
from prisma.enums import APIKeyPermission
from backend.data.auth.api_key import APIKeyInfo, validate_api_key
from backend.data.auth.base import APIAuthorizationInfo
from backend.data.auth.oauth import (
InvalidClientError,
InvalidTokenError,
OAuthAccessTokenInfo,
validate_access_token,
)
api_key_header = APIKeyHeader(name="X-API-Key", auto_error=False)
bearer_auth = HTTPBearer(auto_error=False)
async def require_api_key(api_key: str | None = Security(api_key_header)) -> APIKeyInfo:
"""Middleware for API key authentication only"""
if api_key is None:
raise HTTPException(
status_code=status.HTTP_401_UNAUTHORIZED, detail="Missing API key"
)
api_key_obj = await validate_api_key(api_key)
if not api_key_obj:
raise HTTPException(
status_code=status.HTTP_401_UNAUTHORIZED, detail="Invalid API key"
)
return api_key_obj
async def require_access_token(
bearer: HTTPAuthorizationCredentials | None = Security(bearer_auth),
) -> OAuthAccessTokenInfo:
"""Middleware for OAuth access token authentication only"""
if bearer is None:
raise HTTPException(
status_code=status.HTTP_401_UNAUTHORIZED,
detail="Missing Authorization header",
)
try:
token_info, _ = await validate_access_token(bearer.credentials)
except (InvalidClientError, InvalidTokenError) as e:
raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail=str(e))
return token_info
async def require_auth(
api_key: str | None = Security(api_key_header),
bearer: HTTPAuthorizationCredentials | None = Security(bearer_auth),
) -> APIAuthorizationInfo:
"""
Unified authentication middleware supporting both API keys and OAuth tokens.
Supports two authentication methods, which are checked in order:
1. X-API-Key header (existing API key authentication)
2. Authorization: Bearer <token> header (OAuth access token)
Returns:
APIAuthorizationInfo: base class of both APIKeyInfo and OAuthAccessTokenInfo.
"""
# Try API key first
if api_key is not None:
api_key_info = await validate_api_key(api_key)
if api_key_info:
return api_key_info
raise HTTPException(
status_code=status.HTTP_401_UNAUTHORIZED, detail="Invalid API key"
)
# Try OAuth bearer token
if bearer is not None:
try:
token_info, _ = await validate_access_token(bearer.credentials)
return token_info
except (InvalidClientError, InvalidTokenError) as e:
raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail=str(e))
# No credentials provided
raise HTTPException(
status_code=status.HTTP_401_UNAUTHORIZED,
detail="Missing authentication. Provide API key or access token.",
)
def require_permission(permission: APIKeyPermission):
"""
Dependency function for checking specific permissions
(works with API keys and OAuth tokens)
"""
async def check_permission(
auth: APIAuthorizationInfo = Security(require_auth),
) -> APIAuthorizationInfo:
if permission not in auth.scopes:
raise HTTPException(
status_code=status.HTTP_403_FORBIDDEN,
detail=f"Missing required permission: {permission.value}",
)
return auth
return check_permission

View File

@@ -16,7 +16,9 @@ from fastapi import APIRouter, Body, HTTPException, Path, Security, status
from prisma.enums import APIKeyPermission
from pydantic import BaseModel, Field, SecretStr
from backend.data.api_key import APIKeyInfo
from backend.api.external.middleware import require_permission
from backend.api.features.integrations.models import get_all_provider_names
from backend.data.auth.base import APIAuthorizationInfo
from backend.data.model import (
APIKeyCredentials,
Credentials,
@@ -28,8 +30,6 @@ from backend.data.model import (
from backend.integrations.creds_manager import IntegrationCredentialsManager
from backend.integrations.oauth import CREDENTIALS_BY_PROVIDER, HANDLERS_BY_NAME
from backend.integrations.providers import ProviderName
from backend.server.external.middleware import require_permission
from backend.server.integrations.models import get_all_provider_names
from backend.util.settings import Settings
if TYPE_CHECKING:
@@ -255,7 +255,7 @@ def _get_oauth_handler_for_external(
@integrations_router.get("/providers", response_model=list[ProviderInfo])
async def list_providers(
api_key: APIKeyInfo = Security(
auth: APIAuthorizationInfo = Security(
require_permission(APIKeyPermission.READ_INTEGRATIONS)
),
) -> list[ProviderInfo]:
@@ -319,7 +319,7 @@ async def list_providers(
async def initiate_oauth(
provider: Annotated[str, Path(title="The OAuth provider")],
request: OAuthInitiateRequest,
api_key: APIKeyInfo = Security(
auth: APIAuthorizationInfo = Security(
require_permission(APIKeyPermission.MANAGE_INTEGRATIONS)
),
) -> OAuthInitiateResponse:
@@ -337,7 +337,10 @@ async def initiate_oauth(
if not validate_callback_url(request.callback_url):
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=f"Callback URL origin is not allowed. Allowed origins: {settings.config.external_oauth_callback_origins}",
detail=(
f"Callback URL origin is not allowed. "
f"Allowed origins: {settings.config.external_oauth_callback_origins}",
),
)
# Validate provider
@@ -359,13 +362,15 @@ async def initiate_oauth(
)
# Store state token with external flow metadata
# Note: initiated_by_api_key_id is only available for API key auth, not OAuth
api_key_id = getattr(auth, "id", None) if auth.type == "api_key" else None
state_token, code_challenge = await creds_manager.store.store_state_token(
user_id=api_key.user_id,
user_id=auth.user_id,
provider=provider if isinstance(provider_name, str) else provider_name.value,
scopes=request.scopes,
callback_url=request.callback_url,
state_metadata=request.state_metadata,
initiated_by_api_key_id=api_key.id,
initiated_by_api_key_id=api_key_id,
)
# Build login URL
@@ -393,7 +398,7 @@ async def initiate_oauth(
async def complete_oauth(
provider: Annotated[str, Path(title="The OAuth provider")],
request: OAuthCompleteRequest,
api_key: APIKeyInfo = Security(
auth: APIAuthorizationInfo = Security(
require_permission(APIKeyPermission.MANAGE_INTEGRATIONS)
),
) -> OAuthCompleteResponse:
@@ -406,7 +411,7 @@ async def complete_oauth(
"""
# Verify state token
valid_state = await creds_manager.store.verify_state_token(
api_key.user_id, request.state_token, provider
auth.user_id, request.state_token, provider
)
if not valid_state:
@@ -453,7 +458,7 @@ async def complete_oauth(
)
# Store credentials
await creds_manager.create(api_key.user_id, credentials)
await creds_manager.create(auth.user_id, credentials)
logger.info(f"Successfully completed external OAuth for provider {provider}")
@@ -470,7 +475,7 @@ async def complete_oauth(
@integrations_router.get("/credentials", response_model=list[CredentialSummary])
async def list_credentials(
api_key: APIKeyInfo = Security(
auth: APIAuthorizationInfo = Security(
require_permission(APIKeyPermission.READ_INTEGRATIONS)
),
) -> list[CredentialSummary]:
@@ -479,7 +484,7 @@ async def list_credentials(
Returns metadata about each credential without exposing sensitive tokens.
"""
credentials = await creds_manager.store.get_all_creds(api_key.user_id)
credentials = await creds_manager.store.get_all_creds(auth.user_id)
return [
CredentialSummary(
id=cred.id,
@@ -499,7 +504,7 @@ async def list_credentials(
)
async def list_credentials_by_provider(
provider: Annotated[str, Path(title="The provider to list credentials for")],
api_key: APIKeyInfo = Security(
auth: APIAuthorizationInfo = Security(
require_permission(APIKeyPermission.READ_INTEGRATIONS)
),
) -> list[CredentialSummary]:
@@ -507,7 +512,7 @@ async def list_credentials_by_provider(
List credentials for a specific provider.
"""
credentials = await creds_manager.store.get_creds_by_provider(
api_key.user_id, provider
auth.user_id, provider
)
return [
CredentialSummary(
@@ -536,7 +541,7 @@ async def create_credential(
CreateUserPasswordCredentialRequest,
CreateHostScopedCredentialRequest,
] = Body(..., discriminator="type"),
api_key: APIKeyInfo = Security(
auth: APIAuthorizationInfo = Security(
require_permission(APIKeyPermission.MANAGE_INTEGRATIONS)
),
) -> CreateCredentialResponse:
@@ -591,7 +596,7 @@ async def create_credential(
# Store credentials
try:
await creds_manager.create(api_key.user_id, credentials)
await creds_manager.create(auth.user_id, credentials)
except Exception as e:
logger.error(f"Failed to store credentials: {e}")
raise HTTPException(
@@ -623,7 +628,7 @@ class DeleteCredentialResponse(BaseModel):
async def delete_credential(
provider: Annotated[str, Path(title="The provider")],
cred_id: Annotated[str, Path(title="The credential ID to delete")],
api_key: APIKeyInfo = Security(
auth: APIAuthorizationInfo = Security(
require_permission(APIKeyPermission.DELETE_INTEGRATIONS)
),
) -> DeleteCredentialResponse:
@@ -634,7 +639,7 @@ async def delete_credential(
use the main API's delete endpoint which handles webhook cleanup and
token revocation.
"""
creds = await creds_manager.store.get_creds_by_id(api_key.user_id, cred_id)
creds = await creds_manager.store.get_creds_by_id(auth.user_id, cred_id)
if not creds:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND, detail="Credentials not found"
@@ -645,6 +650,6 @@ async def delete_credential(
detail="Credentials do not match the specified provider",
)
await creds_manager.delete(api_key.user_id, cred_id)
await creds_manager.delete(auth.user_id, cred_id)
return DeleteCredentialResponse(deleted=True, credentials_id=cred_id)

View File

@@ -5,46 +5,60 @@ from typing import Annotated, Any, Literal, Optional, Sequence
from fastapi import APIRouter, Body, HTTPException, Security
from prisma.enums import AgentExecutionStatus, APIKeyPermission
from pydantic import BaseModel, Field
from typing_extensions import TypedDict
import backend.api.features.store.cache as store_cache
import backend.api.features.store.model as store_model
import backend.data.block
import backend.server.v2.store.cache as store_cache
import backend.server.v2.store.model as store_model
from backend.api.external.middleware import require_permission
from backend.data import execution as execution_db
from backend.data import graph as graph_db
from backend.data.api_key import APIKeyInfo
from backend.data import user as user_db
from backend.data.auth.base import APIAuthorizationInfo
from backend.data.block import BlockInput, CompletedBlockOutput
from backend.executor.utils import add_graph_execution
from backend.server.external.middleware import require_permission
from backend.util.settings import Settings
from .integrations import integrations_router
from .tools import tools_router
settings = Settings()
logger = logging.getLogger(__name__)
v1_router = APIRouter()
class NodeOutput(TypedDict):
key: str
value: Any
v1_router.include_router(integrations_router)
v1_router.include_router(tools_router)
class ExecutionNode(TypedDict):
node_id: str
input: Any
output: dict[str, Any]
class UserInfoResponse(BaseModel):
id: str
name: Optional[str]
email: str
timezone: str = Field(
description="The user's last known timezone (e.g. 'Europe/Amsterdam'), "
"or 'not-set' if not set"
)
class ExecutionNodeOutput(TypedDict):
node_id: str
outputs: list[NodeOutput]
@v1_router.get(
path="/me",
tags=["user", "meta"],
)
async def get_user_info(
auth: APIAuthorizationInfo = Security(
require_permission(APIKeyPermission.IDENTITY)
),
) -> UserInfoResponse:
user = await user_db.get_user_by_id(auth.user_id)
class GraphExecutionResult(TypedDict):
execution_id: str
status: str
nodes: list[ExecutionNode]
output: Optional[list[dict[str, str]]]
return UserInfoResponse(
id=user.id,
name=user.name,
email=user.email,
timezone=user.timezone,
)
@v1_router.get(
@@ -65,11 +79,15 @@ async def get_graph_blocks() -> Sequence[dict[Any, Any]]:
async def execute_graph_block(
block_id: str,
data: BlockInput,
api_key: APIKeyInfo = Security(require_permission(APIKeyPermission.EXECUTE_BLOCK)),
auth: APIAuthorizationInfo = Security(
require_permission(APIKeyPermission.EXECUTE_BLOCK)
),
) -> CompletedBlockOutput:
obj = backend.data.block.get_block(block_id)
if not obj:
raise HTTPException(status_code=404, detail=f"Block #{block_id} not found.")
if obj.disabled:
raise HTTPException(status_code=403, detail=f"Block #{block_id} is disabled.")
output = defaultdict(list)
async for name, data in obj.execute(data):
@@ -85,12 +103,14 @@ async def execute_graph(
graph_id: str,
graph_version: int,
node_input: Annotated[dict[str, Any], Body(..., embed=True, default_factory=dict)],
api_key: APIKeyInfo = Security(require_permission(APIKeyPermission.EXECUTE_GRAPH)),
auth: APIAuthorizationInfo = Security(
require_permission(APIKeyPermission.EXECUTE_GRAPH)
),
) -> dict[str, Any]:
try:
graph_exec = await add_graph_execution(
graph_id=graph_id,
user_id=api_key.user_id,
user_id=auth.user_id,
inputs=node_input,
graph_version=graph_version,
)
@@ -100,6 +120,19 @@ async def execute_graph(
raise HTTPException(status_code=400, detail=msg)
class ExecutionNode(TypedDict):
node_id: str
input: Any
output: dict[str, Any]
class GraphExecutionResult(TypedDict):
execution_id: str
status: str
nodes: list[ExecutionNode]
output: Optional[list[dict[str, str]]]
@v1_router.get(
path="/graphs/{graph_id}/executions/{graph_exec_id}/results",
tags=["graphs"],
@@ -107,10 +140,12 @@ async def execute_graph(
async def get_graph_execution_results(
graph_id: str,
graph_exec_id: str,
api_key: APIKeyInfo = Security(require_permission(APIKeyPermission.READ_GRAPH)),
auth: APIAuthorizationInfo = Security(
require_permission(APIKeyPermission.READ_GRAPH)
),
) -> GraphExecutionResult:
graph_exec = await execution_db.get_graph_execution(
user_id=api_key.user_id,
user_id=auth.user_id,
execution_id=graph_exec_id,
include_node_executions=True,
)
@@ -122,7 +157,7 @@ async def get_graph_execution_results(
if not await graph_db.get_graph(
graph_id=graph_exec.graph_id,
version=graph_exec.graph_version,
user_id=api_key.user_id,
user_id=auth.user_id,
):
raise HTTPException(status_code=404, detail=f"Graph #{graph_id} not found.")

View File

@@ -14,19 +14,19 @@ from fastapi import APIRouter, Security
from prisma.enums import APIKeyPermission
from pydantic import BaseModel, Field
from backend.data.api_key import APIKeyInfo
from backend.server.external.middleware import require_permission
from backend.server.v2.chat.model import ChatSession
from backend.server.v2.chat.tools import find_agent_tool, run_agent_tool
from backend.server.v2.chat.tools.models import ToolResponseBase
from backend.api.external.middleware import require_permission
from backend.api.features.chat.model import ChatSession
from backend.api.features.chat.tools import find_agent_tool, run_agent_tool
from backend.api.features.chat.tools.models import ToolResponseBase
from backend.data.auth.base import APIAuthorizationInfo
logger = logging.getLogger(__name__)
tools_router = APIRouter(prefix="/tools", tags=["tools"])
# Note: We use Security() as a function parameter dependency (api_key: APIKeyInfo = Security(...))
# Note: We use Security() as a function parameter dependency (auth: APIAuthorizationInfo = Security(...))
# rather than in the decorator's dependencies= list. This avoids duplicate permission checks
# while still enforcing auth AND giving us access to the api_key for extracting user_id.
# while still enforcing auth AND giving us access to auth for extracting user_id.
# Request models
@@ -70,7 +70,7 @@ class RunAgentRequest(BaseModel):
)
def _create_ephemeral_session(user_id: str | None) -> ChatSession:
def _create_ephemeral_session(user_id: str) -> ChatSession:
"""Create an ephemeral session for stateless API requests."""
return ChatSession.new(user_id)
@@ -80,7 +80,9 @@ def _create_ephemeral_session(user_id: str | None) -> ChatSession:
)
async def find_agent(
request: FindAgentRequest,
api_key: APIKeyInfo = Security(require_permission(APIKeyPermission.USE_TOOLS)),
auth: APIAuthorizationInfo = Security(
require_permission(APIKeyPermission.USE_TOOLS)
),
) -> dict[str, Any]:
"""
Search for agents in the marketplace based on capabilities and user needs.
@@ -91,9 +93,9 @@ async def find_agent(
Returns:
List of matching agents or no results response
"""
session = _create_ephemeral_session(api_key.user_id)
session = _create_ephemeral_session(auth.user_id)
result = await find_agent_tool._execute(
user_id=api_key.user_id,
user_id=auth.user_id,
session=session,
query=request.query,
)
@@ -105,7 +107,9 @@ async def find_agent(
)
async def run_agent(
request: RunAgentRequest,
api_key: APIKeyInfo = Security(require_permission(APIKeyPermission.USE_TOOLS)),
auth: APIAuthorizationInfo = Security(
require_permission(APIKeyPermission.USE_TOOLS)
),
) -> dict[str, Any]:
"""
Run or schedule an agent from the marketplace.
@@ -129,9 +133,9 @@ async def run_agent(
- execution_started: If agent was run or scheduled successfully
- error: If something went wrong
"""
session = _create_ephemeral_session(api_key.user_id)
session = _create_ephemeral_session(auth.user_id)
result = await run_agent_tool._execute(
user_id=api_key.user_id,
user_id=auth.user_id,
session=session,
username_agent_slug=request.username_agent_slug,
inputs=request.inputs,

View File

@@ -6,9 +6,10 @@ from fastapi import APIRouter, Body, Security
from prisma.enums import CreditTransactionType
from backend.data.credit import admin_get_user_history, get_user_credit_model
from backend.server.v2.admin.model import AddUserCreditsResponse, UserHistoryResponse
from backend.util.json import SafeJson
from .model import AddUserCreditsResponse, UserHistoryResponse
logger = logging.getLogger(__name__)

View File

@@ -9,14 +9,15 @@ import pytest_mock
from autogpt_libs.auth.jwt_utils import get_jwt_payload
from pytest_snapshot.plugin import Snapshot
import backend.server.v2.admin.credit_admin_routes as credit_admin_routes
import backend.server.v2.admin.model as admin_model
from backend.data.model import UserTransaction
from backend.util.json import SafeJson
from backend.util.models import Pagination
from .credit_admin_routes import router as credit_admin_router
from .model import UserHistoryResponse
app = fastapi.FastAPI()
app.include_router(credit_admin_routes.router)
app.include_router(credit_admin_router)
client = fastapi.testclient.TestClient(app)
@@ -30,7 +31,7 @@ def setup_app_admin_auth(mock_jwt_admin):
def test_add_user_credits_success(
mocker: pytest_mock.MockFixture,
mocker: pytest_mock.MockerFixture,
configured_snapshot: Snapshot,
admin_user_id: str,
target_user_id: str,
@@ -42,7 +43,7 @@ def test_add_user_credits_success(
return_value=(1500, "transaction-123-uuid")
)
mocker.patch(
"backend.server.v2.admin.credit_admin_routes.get_user_credit_model",
"backend.api.features.admin.credit_admin_routes.get_user_credit_model",
return_value=mock_credit_model,
)
@@ -84,7 +85,7 @@ def test_add_user_credits_success(
def test_add_user_credits_negative_amount(
mocker: pytest_mock.MockFixture,
mocker: pytest_mock.MockerFixture,
snapshot: Snapshot,
) -> None:
"""Test credit deduction by admin (negative amount)"""
@@ -94,7 +95,7 @@ def test_add_user_credits_negative_amount(
return_value=(200, "transaction-456-uuid")
)
mocker.patch(
"backend.server.v2.admin.credit_admin_routes.get_user_credit_model",
"backend.api.features.admin.credit_admin_routes.get_user_credit_model",
return_value=mock_credit_model,
)
@@ -119,12 +120,12 @@ def test_add_user_credits_negative_amount(
def test_get_user_history_success(
mocker: pytest_mock.MockFixture,
mocker: pytest_mock.MockerFixture,
snapshot: Snapshot,
) -> None:
"""Test successful retrieval of user credit history"""
# Mock the admin_get_user_history function
mock_history_response = admin_model.UserHistoryResponse(
mock_history_response = UserHistoryResponse(
history=[
UserTransaction(
user_id="user-1",
@@ -150,7 +151,7 @@ def test_get_user_history_success(
)
mocker.patch(
"backend.server.v2.admin.credit_admin_routes.admin_get_user_history",
"backend.api.features.admin.credit_admin_routes.admin_get_user_history",
return_value=mock_history_response,
)
@@ -170,12 +171,12 @@ def test_get_user_history_success(
def test_get_user_history_with_filters(
mocker: pytest_mock.MockFixture,
mocker: pytest_mock.MockerFixture,
snapshot: Snapshot,
) -> None:
"""Test user credit history with search and filter parameters"""
# Mock the admin_get_user_history function
mock_history_response = admin_model.UserHistoryResponse(
mock_history_response = UserHistoryResponse(
history=[
UserTransaction(
user_id="user-3",
@@ -194,7 +195,7 @@ def test_get_user_history_with_filters(
)
mock_get_history = mocker.patch(
"backend.server.v2.admin.credit_admin_routes.admin_get_user_history",
"backend.api.features.admin.credit_admin_routes.admin_get_user_history",
return_value=mock_history_response,
)
@@ -230,12 +231,12 @@ def test_get_user_history_with_filters(
def test_get_user_history_empty_results(
mocker: pytest_mock.MockFixture,
mocker: pytest_mock.MockerFixture,
snapshot: Snapshot,
) -> None:
"""Test user credit history with no results"""
# Mock empty history response
mock_history_response = admin_model.UserHistoryResponse(
mock_history_response = UserHistoryResponse(
history=[],
pagination=Pagination(
total_items=0,
@@ -246,7 +247,7 @@ def test_get_user_history_empty_results(
)
mocker.patch(
"backend.server.v2.admin.credit_admin_routes.admin_get_user_history",
"backend.api.features.admin.credit_admin_routes.admin_get_user_history",
return_value=mock_history_response,
)

View File

@@ -28,6 +28,7 @@ from backend.executor.manager import get_db_async_client
from backend.util.settings import Settings
logger = logging.getLogger(__name__)
settings = Settings()
class ExecutionAnalyticsRequest(BaseModel):
@@ -63,6 +64,8 @@ class ExecutionAnalyticsResult(BaseModel):
score: Optional[float]
status: str # "success", "failed", "skipped"
error_message: Optional[str] = None
started_at: Optional[datetime] = None
ended_at: Optional[datetime] = None
class ExecutionAnalyticsResponse(BaseModel):
@@ -224,11 +227,6 @@ async def generate_execution_analytics(
)
try:
# Validate model configuration
settings = Settings()
if not settings.secrets.openai_internal_api_key:
raise HTTPException(status_code=500, detail="OpenAI API key not configured")
# Get database client
db_client = get_db_async_client()
@@ -320,6 +318,8 @@ async def generate_execution_analytics(
),
status="skipped",
error_message=None, # Not an error - just already processed
started_at=execution.started_at,
ended_at=execution.ended_at,
)
)
@@ -349,6 +349,9 @@ async def _process_batch(
) -> list[ExecutionAnalyticsResult]:
"""Process a batch of executions concurrently."""
if not settings.secrets.openai_internal_api_key:
raise HTTPException(status_code=500, detail="OpenAI API key not configured")
async def process_single_execution(execution) -> ExecutionAnalyticsResult:
try:
# Generate activity status and score using the specified model
@@ -387,6 +390,8 @@ async def _process_batch(
score=None,
status="skipped",
error_message="Activity generation returned None",
started_at=execution.started_at,
ended_at=execution.ended_at,
)
# Update the execution stats
@@ -416,6 +421,8 @@ async def _process_batch(
summary_text=activity_response["activity_status"],
score=activity_response["correctness_score"],
status="success",
started_at=execution.started_at,
ended_at=execution.ended_at,
)
except Exception as e:
@@ -429,6 +436,8 @@ async def _process_batch(
score=None,
status="failed",
error_message=str(e),
started_at=execution.started_at,
ended_at=execution.ended_at,
)
# Process all executions in the batch concurrently

View File

@@ -7,9 +7,9 @@ import fastapi
import fastapi.responses
import prisma.enums
import backend.server.v2.store.cache as store_cache
import backend.server.v2.store.db
import backend.server.v2.store.model
import backend.api.features.store.cache as store_cache
import backend.api.features.store.db as store_db
import backend.api.features.store.model as store_model
import backend.util.json
logger = logging.getLogger(__name__)
@@ -24,7 +24,7 @@ router = fastapi.APIRouter(
@router.get(
"/listings",
summary="Get Admin Listings History",
response_model=backend.server.v2.store.model.StoreListingsWithVersionsResponse,
response_model=store_model.StoreListingsWithVersionsResponse,
)
async def get_admin_listings_with_versions(
status: typing.Optional[prisma.enums.SubmissionStatus] = None,
@@ -48,7 +48,7 @@ async def get_admin_listings_with_versions(
StoreListingsWithVersionsResponse with listings and their versions
"""
try:
listings = await backend.server.v2.store.db.get_admin_listings_with_versions(
listings = await store_db.get_admin_listings_with_versions(
status=status,
search_query=search,
page=page,
@@ -68,11 +68,11 @@ async def get_admin_listings_with_versions(
@router.post(
"/submissions/{store_listing_version_id}/review",
summary="Review Store Submission",
response_model=backend.server.v2.store.model.StoreSubmission,
response_model=store_model.StoreSubmission,
)
async def review_submission(
store_listing_version_id: str,
request: backend.server.v2.store.model.ReviewSubmissionRequest,
request: store_model.ReviewSubmissionRequest,
user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
):
"""
@@ -87,12 +87,10 @@ async def review_submission(
StoreSubmission with updated review information
"""
try:
already_approved = (
await backend.server.v2.store.db.check_submission_already_approved(
store_listing_version_id=store_listing_version_id,
)
already_approved = await store_db.check_submission_already_approved(
store_listing_version_id=store_listing_version_id,
)
submission = await backend.server.v2.store.db.review_store_submission(
submission = await store_db.review_store_submission(
store_listing_version_id=store_listing_version_id,
is_approved=request.is_approved,
external_comments=request.comments,
@@ -136,7 +134,7 @@ async def admin_download_agent_file(
Raises:
HTTPException: If the agent is not found or an unexpected error occurs.
"""
graph_data = await backend.server.v2.store.db.get_agent_as_admin(
graph_data = await store_db.get_agent_as_admin(
user_id=user_id,
store_listing_version_id=store_listing_version_id,
)

View File

@@ -6,10 +6,11 @@ from typing import Annotated
import fastapi
import pydantic
from autogpt_libs.auth import get_user_id
from autogpt_libs.auth.dependencies import requires_user
import backend.data.analytics
router = fastapi.APIRouter()
router = fastapi.APIRouter(dependencies=[fastapi.Security(requires_user)])
logger = logging.getLogger(__name__)

View File

@@ -0,0 +1,340 @@
"""Tests for analytics API endpoints."""
import json
from unittest.mock import AsyncMock, Mock
import fastapi
import fastapi.testclient
import pytest
import pytest_mock
from pytest_snapshot.plugin import Snapshot
from .analytics import router as analytics_router
app = fastapi.FastAPI()
app.include_router(analytics_router)
client = fastapi.testclient.TestClient(app)
@pytest.fixture(autouse=True)
def setup_app_auth(mock_jwt_user):
"""Setup auth overrides for all tests in this module."""
from autogpt_libs.auth.jwt_utils import get_jwt_payload
app.dependency_overrides[get_jwt_payload] = mock_jwt_user["get_jwt_payload"]
yield
app.dependency_overrides.clear()
# =============================================================================
# /log_raw_metric endpoint tests
# =============================================================================
def test_log_raw_metric_success(
mocker: pytest_mock.MockFixture,
configured_snapshot: Snapshot,
test_user_id: str,
) -> None:
"""Test successful raw metric logging."""
mock_result = Mock(id="metric-123-uuid")
mock_log_metric = mocker.patch(
"backend.data.analytics.log_raw_metric",
new_callable=AsyncMock,
return_value=mock_result,
)
request_data = {
"metric_name": "page_load_time",
"metric_value": 2.5,
"data_string": "/dashboard",
}
response = client.post("/log_raw_metric", json=request_data)
assert response.status_code == 200, f"Unexpected response: {response.text}"
assert response.json() == "metric-123-uuid"
mock_log_metric.assert_called_once_with(
user_id=test_user_id,
metric_name="page_load_time",
metric_value=2.5,
data_string="/dashboard",
)
configured_snapshot.assert_match(
json.dumps({"metric_id": response.json()}, indent=2, sort_keys=True),
"analytics_log_metric_success",
)
@pytest.mark.parametrize(
"metric_value,metric_name,data_string,test_id",
[
(100, "api_calls_count", "external_api", "integer_value"),
(0, "error_count", "no_errors", "zero_value"),
(-5.2, "temperature_delta", "cooling", "negative_value"),
(1.23456789, "precision_test", "float_precision", "float_precision"),
(999999999, "large_number", "max_value", "large_number"),
(0.0000001, "tiny_number", "min_value", "tiny_number"),
],
)
def test_log_raw_metric_various_values(
mocker: pytest_mock.MockFixture,
configured_snapshot: Snapshot,
metric_value: float,
metric_name: str,
data_string: str,
test_id: str,
) -> None:
"""Test raw metric logging with various metric values."""
mock_result = Mock(id=f"metric-{test_id}-uuid")
mocker.patch(
"backend.data.analytics.log_raw_metric",
new_callable=AsyncMock,
return_value=mock_result,
)
request_data = {
"metric_name": metric_name,
"metric_value": metric_value,
"data_string": data_string,
}
response = client.post("/log_raw_metric", json=request_data)
assert response.status_code == 200, f"Failed for {test_id}: {response.text}"
configured_snapshot.assert_match(
json.dumps(
{"metric_id": response.json(), "test_case": test_id},
indent=2,
sort_keys=True,
),
f"analytics_metric_{test_id}",
)
@pytest.mark.parametrize(
"invalid_data,expected_error",
[
({}, "Field required"),
({"metric_name": "test"}, "Field required"),
(
{"metric_name": "test", "metric_value": "not_a_number", "data_string": "x"},
"Input should be a valid number",
),
(
{"metric_name": "", "metric_value": 1.0, "data_string": "test"},
"String should have at least 1 character",
),
(
{"metric_name": "test", "metric_value": 1.0, "data_string": ""},
"String should have at least 1 character",
),
],
ids=[
"empty_request",
"missing_metric_value_and_data_string",
"invalid_metric_value_type",
"empty_metric_name",
"empty_data_string",
],
)
def test_log_raw_metric_validation_errors(
invalid_data: dict,
expected_error: str,
) -> None:
"""Test validation errors for invalid metric requests."""
response = client.post("/log_raw_metric", json=invalid_data)
assert response.status_code == 422
error_detail = response.json()
assert "detail" in error_detail, f"Missing 'detail' in error: {error_detail}"
error_text = json.dumps(error_detail)
assert (
expected_error in error_text
), f"Expected '{expected_error}' in error response: {error_text}"
def test_log_raw_metric_service_error(
mocker: pytest_mock.MockFixture,
test_user_id: str,
) -> None:
"""Test error handling when analytics service fails."""
mocker.patch(
"backend.data.analytics.log_raw_metric",
new_callable=AsyncMock,
side_effect=Exception("Database connection failed"),
)
request_data = {
"metric_name": "test_metric",
"metric_value": 1.0,
"data_string": "test",
}
response = client.post("/log_raw_metric", json=request_data)
assert response.status_code == 500
error_detail = response.json()["detail"]
assert "Database connection failed" in error_detail["message"]
assert "hint" in error_detail
# =============================================================================
# /log_raw_analytics endpoint tests
# =============================================================================
def test_log_raw_analytics_success(
mocker: pytest_mock.MockFixture,
configured_snapshot: Snapshot,
test_user_id: str,
) -> None:
"""Test successful raw analytics logging."""
mock_result = Mock(id="analytics-789-uuid")
mock_log_analytics = mocker.patch(
"backend.data.analytics.log_raw_analytics",
new_callable=AsyncMock,
return_value=mock_result,
)
request_data = {
"type": "user_action",
"data": {
"action": "button_click",
"button_id": "submit_form",
"timestamp": "2023-01-01T00:00:00Z",
"metadata": {"form_type": "registration", "fields_filled": 5},
},
"data_index": "button_click_submit_form",
}
response = client.post("/log_raw_analytics", json=request_data)
assert response.status_code == 200, f"Unexpected response: {response.text}"
assert response.json() == "analytics-789-uuid"
mock_log_analytics.assert_called_once_with(
test_user_id,
"user_action",
request_data["data"],
"button_click_submit_form",
)
configured_snapshot.assert_match(
json.dumps({"analytics_id": response.json()}, indent=2, sort_keys=True),
"analytics_log_analytics_success",
)
def test_log_raw_analytics_complex_data(
mocker: pytest_mock.MockFixture,
configured_snapshot: Snapshot,
) -> None:
"""Test raw analytics logging with complex nested data structures."""
mock_result = Mock(id="analytics-complex-uuid")
mocker.patch(
"backend.data.analytics.log_raw_analytics",
new_callable=AsyncMock,
return_value=mock_result,
)
request_data = {
"type": "agent_execution",
"data": {
"agent_id": "agent_123",
"execution_id": "exec_456",
"status": "completed",
"duration_ms": 3500,
"nodes_executed": 15,
"blocks_used": [
{"block_id": "llm_block", "count": 3},
{"block_id": "http_block", "count": 5},
{"block_id": "code_block", "count": 2},
],
"errors": [],
"metadata": {
"trigger": "manual",
"user_tier": "premium",
"environment": "production",
},
},
"data_index": "agent_123_exec_456",
}
response = client.post("/log_raw_analytics", json=request_data)
assert response.status_code == 200
configured_snapshot.assert_match(
json.dumps(
{"analytics_id": response.json(), "logged_data": request_data["data"]},
indent=2,
sort_keys=True,
),
"analytics_log_analytics_complex_data",
)
@pytest.mark.parametrize(
"invalid_data,expected_error",
[
({}, "Field required"),
({"type": "test"}, "Field required"),
(
{"type": "test", "data": "not_a_dict", "data_index": "test"},
"Input should be a valid dictionary",
),
({"type": "test", "data": {"key": "value"}}, "Field required"),
],
ids=[
"empty_request",
"missing_data_and_data_index",
"invalid_data_type",
"missing_data_index",
],
)
def test_log_raw_analytics_validation_errors(
invalid_data: dict,
expected_error: str,
) -> None:
"""Test validation errors for invalid analytics requests."""
response = client.post("/log_raw_analytics", json=invalid_data)
assert response.status_code == 422
error_detail = response.json()
assert "detail" in error_detail, f"Missing 'detail' in error: {error_detail}"
error_text = json.dumps(error_detail)
assert (
expected_error in error_text
), f"Expected '{expected_error}' in error response: {error_text}"
def test_log_raw_analytics_service_error(
mocker: pytest_mock.MockFixture,
test_user_id: str,
) -> None:
"""Test error handling when analytics service fails."""
mocker.patch(
"backend.data.analytics.log_raw_analytics",
new_callable=AsyncMock,
side_effect=Exception("Analytics DB unreachable"),
)
request_data = {
"type": "test_event",
"data": {"key": "value"},
"data_index": "test_index",
}
response = client.post("/log_raw_analytics", json=request_data)
assert response.status_code == 500
error_detail = response.json()["detail"]
assert "Analytics DB unreachable" in error_detail["message"]
assert "hint" in error_detail

View File

@@ -6,17 +6,20 @@ from typing import Sequence
import prisma
import backend.api.features.library.db as library_db
import backend.api.features.library.model as library_model
import backend.api.features.store.db as store_db
import backend.api.features.store.model as store_model
import backend.data.block
import backend.server.v2.library.db as library_db
import backend.server.v2.library.model as library_model
import backend.server.v2.store.db as store_db
import backend.server.v2.store.model as store_model
from backend.blocks import load_all_blocks
from backend.blocks.llm import LlmModel
from backend.data.block import AnyBlockSchema, BlockCategory, BlockInfo, BlockSchema
from backend.data.db import query_raw_with_schema
from backend.integrations.providers import ProviderName
from backend.server.v2.builder.model import (
from backend.util.cache import cached
from backend.util.models import Pagination
from .model import (
BlockCategoryResponse,
BlockResponse,
BlockType,
@@ -26,8 +29,6 @@ from backend.server.v2.builder.model import (
ProviderResponse,
SearchEntry,
)
from backend.util.cache import cached
from backend.util.models import Pagination
logger = logging.getLogger(__name__)
llm_models = [name.name.lower().replace("_", " ") for name in LlmModel]

View File

@@ -2,8 +2,8 @@ from typing import Literal
from pydantic import BaseModel
import backend.server.v2.library.model as library_model
import backend.server.v2.store.model as store_model
import backend.api.features.library.model as library_model
import backend.api.features.store.model as store_model
from backend.data.block import BlockInfo
from backend.integrations.providers import ProviderName
from backend.util.models import Pagination

View File

@@ -4,11 +4,12 @@ from typing import Annotated, Sequence
import fastapi
from autogpt_libs.auth.dependencies import get_user_id, requires_user
import backend.server.v2.builder.db as builder_db
import backend.server.v2.builder.model as builder_model
from backend.integrations.providers import ProviderName
from backend.util.models import Pagination
from . import db as builder_db
from . import model as builder_model
logger = logging.getLogger(__name__)
router = fastapi.APIRouter(
@@ -16,7 +17,7 @@ router = fastapi.APIRouter(
)
# Taken from backend/server/v2/store/db.py
# Taken from backend/api/features/store/db.py
def sanitize_query(query: str | None) -> str | None:
if query is None:
return query

View File

@@ -0,0 +1,368 @@
"""Redis Streams consumer for operation completion messages.
This module provides a consumer (ChatCompletionConsumer) that listens for
completion notifications (OperationCompleteMessage) from external services
(like Agent Generator) and triggers the appropriate stream registry and
chat service updates via process_operation_success/process_operation_failure.
Why Redis Streams instead of RabbitMQ?
--------------------------------------
While the project typically uses RabbitMQ for async task queues (e.g., execution
queue), Redis Streams was chosen for chat completion notifications because:
1. **Unified Infrastructure**: The SSE reconnection feature already uses Redis
Streams (via stream_registry) for message persistence and replay. Using Redis
Streams for completion notifications keeps all chat streaming infrastructure
in one system, simplifying operations and reducing cross-system coordination.
2. **Message Replay**: Redis Streams support XREAD with arbitrary message IDs,
allowing consumers to replay missed messages after reconnection. This aligns
with the SSE reconnection pattern where clients can resume from last_message_id.
3. **Consumer Groups with XAUTOCLAIM**: Redis consumer groups provide automatic
load balancing across pods with explicit message claiming (XAUTOCLAIM) for
recovering from dead consumers - ideal for the completion callback pattern.
4. **Lower Latency**: For real-time SSE updates, Redis (already in-memory for
stream_registry) provides lower latency than an additional RabbitMQ hop.
5. **Atomicity with Task State**: Completion processing often needs to update
task metadata stored in Redis. Keeping both in Redis enables simpler
transactional semantics without distributed coordination.
The consumer uses Redis Streams with consumer groups for reliable message
processing across multiple platform pods, with XAUTOCLAIM for reclaiming
stale pending messages from dead consumers.
"""
import asyncio
import logging
import os
import uuid
from typing import Any
import orjson
from prisma import Prisma
from pydantic import BaseModel
from redis.exceptions import ResponseError
from backend.data.redis_client import get_redis_async
from . import stream_registry
from .completion_handler import process_operation_failure, process_operation_success
from .config import ChatConfig
logger = logging.getLogger(__name__)
config = ChatConfig()
class OperationCompleteMessage(BaseModel):
"""Message format for operation completion notifications."""
operation_id: str
task_id: str
success: bool
result: dict | str | None = None
error: str | None = None
class ChatCompletionConsumer:
"""Consumer for chat operation completion messages from Redis Streams.
This consumer initializes its own Prisma client in start() to ensure
database operations work correctly within this async context.
Uses Redis consumer groups to allow multiple platform pods to consume
messages reliably with automatic redelivery on failure.
"""
def __init__(self):
self._consumer_task: asyncio.Task | None = None
self._running = False
self._prisma: Prisma | None = None
self._consumer_name = f"consumer-{uuid.uuid4().hex[:8]}"
async def start(self) -> None:
"""Start the completion consumer."""
if self._running:
logger.warning("Completion consumer already running")
return
# Create consumer group if it doesn't exist
try:
redis = await get_redis_async()
await redis.xgroup_create(
config.stream_completion_name,
config.stream_consumer_group,
id="0",
mkstream=True,
)
logger.info(
f"Created consumer group '{config.stream_consumer_group}' "
f"on stream '{config.stream_completion_name}'"
)
except ResponseError as e:
if "BUSYGROUP" in str(e):
logger.debug(
f"Consumer group '{config.stream_consumer_group}' already exists"
)
else:
raise
self._running = True
self._consumer_task = asyncio.create_task(self._consume_messages())
logger.info(
f"Chat completion consumer started (consumer: {self._consumer_name})"
)
async def _ensure_prisma(self) -> Prisma:
"""Lazily initialize Prisma client on first use."""
if self._prisma is None:
database_url = os.getenv("DATABASE_URL", "postgresql://localhost:5432")
self._prisma = Prisma(datasource={"url": database_url})
await self._prisma.connect()
logger.info("[COMPLETION] Consumer Prisma client connected (lazy init)")
return self._prisma
async def stop(self) -> None:
"""Stop the completion consumer."""
self._running = False
if self._consumer_task:
self._consumer_task.cancel()
try:
await self._consumer_task
except asyncio.CancelledError:
pass
self._consumer_task = None
if self._prisma:
await self._prisma.disconnect()
self._prisma = None
logger.info("[COMPLETION] Consumer Prisma client disconnected")
logger.info("Chat completion consumer stopped")
async def _consume_messages(self) -> None:
"""Main message consumption loop with retry logic."""
max_retries = 10
retry_delay = 5 # seconds
retry_count = 0
block_timeout = 5000 # milliseconds
while self._running and retry_count < max_retries:
try:
redis = await get_redis_async()
# Reset retry count on successful connection
retry_count = 0
while self._running:
# First, claim any stale pending messages from dead consumers
# Redis does NOT auto-redeliver pending messages; we must explicitly
# claim them using XAUTOCLAIM
try:
claimed_result = await redis.xautoclaim(
name=config.stream_completion_name,
groupname=config.stream_consumer_group,
consumername=self._consumer_name,
min_idle_time=config.stream_claim_min_idle_ms,
start_id="0-0",
count=10,
)
# xautoclaim returns: (next_start_id, [(id, data), ...], [deleted_ids])
if claimed_result and len(claimed_result) >= 2:
claimed_entries = claimed_result[1]
if claimed_entries:
logger.info(
f"Claimed {len(claimed_entries)} stale pending messages"
)
for entry_id, data in claimed_entries:
if not self._running:
return
await self._process_entry(redis, entry_id, data)
except Exception as e:
logger.warning(f"XAUTOCLAIM failed (non-fatal): {e}")
# Read new messages from the stream
messages = await redis.xreadgroup(
groupname=config.stream_consumer_group,
consumername=self._consumer_name,
streams={config.stream_completion_name: ">"},
block=block_timeout,
count=10,
)
if not messages:
continue
for stream_name, entries in messages:
for entry_id, data in entries:
if not self._running:
return
await self._process_entry(redis, entry_id, data)
except asyncio.CancelledError:
logger.info("Consumer cancelled")
return
except Exception as e:
retry_count += 1
logger.error(
f"Consumer error (retry {retry_count}/{max_retries}): {e}",
exc_info=True,
)
if self._running and retry_count < max_retries:
await asyncio.sleep(retry_delay)
else:
logger.error("Max retries reached, stopping consumer")
return
async def _process_entry(
self, redis: Any, entry_id: str, data: dict[str, Any]
) -> None:
"""Process a single stream entry and acknowledge it on success.
Args:
redis: Redis client connection
entry_id: The stream entry ID
data: The entry data dict
"""
try:
# Handle the message
message_data = data.get("data")
if message_data:
await self._handle_message(
message_data.encode()
if isinstance(message_data, str)
else message_data
)
# Acknowledge the message after successful processing
await redis.xack(
config.stream_completion_name,
config.stream_consumer_group,
entry_id,
)
except Exception as e:
logger.error(
f"Error processing completion message {entry_id}: {e}",
exc_info=True,
)
# Message remains in pending state and will be claimed by
# XAUTOCLAIM after min_idle_time expires
async def _handle_message(self, body: bytes) -> None:
"""Handle a completion message using our own Prisma client."""
try:
data = orjson.loads(body)
message = OperationCompleteMessage(**data)
except Exception as e:
logger.error(f"Failed to parse completion message: {e}")
return
logger.info(
f"[COMPLETION] Received completion for operation {message.operation_id} "
f"(task_id={message.task_id}, success={message.success})"
)
# Find task in registry
task = await stream_registry.find_task_by_operation_id(message.operation_id)
if task is None:
task = await stream_registry.get_task(message.task_id)
if task is None:
logger.warning(
f"[COMPLETION] Task not found for operation {message.operation_id} "
f"(task_id={message.task_id})"
)
return
logger.info(
f"[COMPLETION] Found task: task_id={task.task_id}, "
f"session_id={task.session_id}, tool_call_id={task.tool_call_id}"
)
# Guard against empty task fields
if not task.task_id or not task.session_id or not task.tool_call_id:
logger.error(
f"[COMPLETION] Task has empty critical fields! "
f"task_id={task.task_id!r}, session_id={task.session_id!r}, "
f"tool_call_id={task.tool_call_id!r}"
)
return
if message.success:
await self._handle_success(task, message)
else:
await self._handle_failure(task, message)
async def _handle_success(
self,
task: stream_registry.ActiveTask,
message: OperationCompleteMessage,
) -> None:
"""Handle successful operation completion."""
prisma = await self._ensure_prisma()
await process_operation_success(task, message.result, prisma)
async def _handle_failure(
self,
task: stream_registry.ActiveTask,
message: OperationCompleteMessage,
) -> None:
"""Handle failed operation completion."""
prisma = await self._ensure_prisma()
await process_operation_failure(task, message.error, prisma)
# Module-level consumer instance
_consumer: ChatCompletionConsumer | None = None
async def start_completion_consumer() -> None:
"""Start the global completion consumer."""
global _consumer
if _consumer is None:
_consumer = ChatCompletionConsumer()
await _consumer.start()
async def stop_completion_consumer() -> None:
"""Stop the global completion consumer."""
global _consumer
if _consumer:
await _consumer.stop()
_consumer = None
async def publish_operation_complete(
operation_id: str,
task_id: str,
success: bool,
result: dict | str | None = None,
error: str | None = None,
) -> None:
"""Publish an operation completion message to Redis Streams.
Args:
operation_id: The operation ID that completed.
task_id: The task ID associated with the operation.
success: Whether the operation succeeded.
result: The result data (for success).
error: The error message (for failure).
"""
message = OperationCompleteMessage(
operation_id=operation_id,
task_id=task_id,
success=success,
result=result,
error=error,
)
redis = await get_redis_async()
await redis.xadd(
config.stream_completion_name,
{"data": message.model_dump_json()},
maxlen=config.stream_max_length,
)
logger.info(f"Published completion for operation {operation_id}")

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"""Shared completion handling for operation success and failure.
This module provides common logic for handling operation completion from both:
- The Redis Streams consumer (completion_consumer.py)
- The HTTP webhook endpoint (routes.py)
"""
import logging
from typing import Any
import orjson
from prisma import Prisma
from . import service as chat_service
from . import stream_registry
from .response_model import StreamError, StreamToolOutputAvailable
from .tools.models import ErrorResponse
logger = logging.getLogger(__name__)
# Tools that produce agent_json that needs to be saved to library
AGENT_GENERATION_TOOLS = {"create_agent", "edit_agent"}
# Keys that should be stripped from agent_json when returning in error responses
SENSITIVE_KEYS = frozenset(
{
"api_key",
"apikey",
"api_secret",
"password",
"secret",
"credentials",
"credential",
"token",
"access_token",
"refresh_token",
"private_key",
"privatekey",
"auth",
"authorization",
}
)
def _sanitize_agent_json(obj: Any) -> Any:
"""Recursively sanitize agent_json by removing sensitive keys.
Args:
obj: The object to sanitize (dict, list, or primitive)
Returns:
Sanitized copy with sensitive keys removed/redacted
"""
if isinstance(obj, dict):
return {
k: "[REDACTED]" if k.lower() in SENSITIVE_KEYS else _sanitize_agent_json(v)
for k, v in obj.items()
}
elif isinstance(obj, list):
return [_sanitize_agent_json(item) for item in obj]
else:
return obj
class ToolMessageUpdateError(Exception):
"""Raised when updating a tool message in the database fails."""
pass
async def _update_tool_message(
session_id: str,
tool_call_id: str,
content: str,
prisma_client: Prisma | None,
) -> None:
"""Update tool message in database.
Args:
session_id: The session ID
tool_call_id: The tool call ID to update
content: The new content for the message
prisma_client: Optional Prisma client. If None, uses chat_service.
Raises:
ToolMessageUpdateError: If the database update fails. The caller should
handle this to avoid marking the task as completed with inconsistent state.
"""
try:
if prisma_client:
# Use provided Prisma client (for consumer with its own connection)
updated_count = await prisma_client.chatmessage.update_many(
where={
"sessionId": session_id,
"toolCallId": tool_call_id,
},
data={"content": content},
)
# Check if any rows were updated - 0 means message not found
if updated_count == 0:
raise ToolMessageUpdateError(
f"No message found with tool_call_id={tool_call_id} in session {session_id}"
)
else:
# Use service function (for webhook endpoint)
await chat_service._update_pending_operation(
session_id=session_id,
tool_call_id=tool_call_id,
result=content,
)
except ToolMessageUpdateError:
raise
except Exception as e:
logger.error(f"[COMPLETION] Failed to update tool message: {e}", exc_info=True)
raise ToolMessageUpdateError(
f"Failed to update tool message for tool_call_id={tool_call_id}: {e}"
) from e
def serialize_result(result: dict | list | str | int | float | bool | None) -> str:
"""Serialize result to JSON string with sensible defaults.
Args:
result: The result to serialize. Can be a dict, list, string,
number, boolean, or None.
Returns:
JSON string representation of the result. Returns '{"status": "completed"}'
only when result is explicitly None.
"""
if isinstance(result, str):
return result
if result is None:
return '{"status": "completed"}'
return orjson.dumps(result).decode("utf-8")
async def _save_agent_from_result(
result: dict[str, Any],
user_id: str | None,
tool_name: str,
) -> dict[str, Any]:
"""Save agent to library if result contains agent_json.
Args:
result: The result dict that may contain agent_json
user_id: The user ID to save the agent for
tool_name: The tool name (create_agent or edit_agent)
Returns:
Updated result dict with saved agent details, or original result if no agent_json
"""
if not user_id:
logger.warning("[COMPLETION] Cannot save agent: no user_id in task")
return result
agent_json = result.get("agent_json")
if not agent_json:
logger.warning(
f"[COMPLETION] {tool_name} completed but no agent_json in result"
)
return result
try:
from .tools.agent_generator import save_agent_to_library
is_update = tool_name == "edit_agent"
created_graph, library_agent = await save_agent_to_library(
agent_json, user_id, is_update=is_update
)
logger.info(
f"[COMPLETION] Saved agent '{created_graph.name}' to library "
f"(graph_id={created_graph.id}, library_agent_id={library_agent.id})"
)
# Return a response similar to AgentSavedResponse
return {
"type": "agent_saved",
"message": f"Agent '{created_graph.name}' has been saved to your library!",
"agent_id": created_graph.id,
"agent_name": created_graph.name,
"library_agent_id": library_agent.id,
"library_agent_link": f"/library/agents/{library_agent.id}",
"agent_page_link": f"/build?flowID={created_graph.id}",
}
except Exception as e:
logger.error(
f"[COMPLETION] Failed to save agent to library: {e}",
exc_info=True,
)
# Return error but don't fail the whole operation
# Sanitize agent_json to remove sensitive keys before returning
return {
"type": "error",
"message": f"Agent was generated but failed to save: {str(e)}",
"error": str(e),
"agent_json": _sanitize_agent_json(agent_json),
}
async def process_operation_success(
task: stream_registry.ActiveTask,
result: dict | str | None,
prisma_client: Prisma | None = None,
) -> None:
"""Handle successful operation completion.
Publishes the result to the stream registry, updates the database,
generates LLM continuation, and marks the task as completed.
Args:
task: The active task that completed
result: The result data from the operation
prisma_client: Optional Prisma client for database operations.
If None, uses chat_service._update_pending_operation instead.
Raises:
ToolMessageUpdateError: If the database update fails. The task will be
marked as failed instead of completed to avoid inconsistent state.
"""
# For agent generation tools, save the agent to library
if task.tool_name in AGENT_GENERATION_TOOLS and isinstance(result, dict):
result = await _save_agent_from_result(result, task.user_id, task.tool_name)
# Serialize result for output (only substitute default when result is exactly None)
result_output = result if result is not None else {"status": "completed"}
output_str = (
result_output
if isinstance(result_output, str)
else orjson.dumps(result_output).decode("utf-8")
)
# Publish result to stream registry
await stream_registry.publish_chunk(
task.task_id,
StreamToolOutputAvailable(
toolCallId=task.tool_call_id,
toolName=task.tool_name,
output=output_str,
success=True,
),
)
# Update pending operation in database
# If this fails, we must not continue to mark the task as completed
result_str = serialize_result(result)
try:
await _update_tool_message(
session_id=task.session_id,
tool_call_id=task.tool_call_id,
content=result_str,
prisma_client=prisma_client,
)
except ToolMessageUpdateError:
# DB update failed - mark task as failed to avoid inconsistent state
logger.error(
f"[COMPLETION] DB update failed for task {task.task_id}, "
"marking as failed instead of completed"
)
await stream_registry.publish_chunk(
task.task_id,
StreamError(errorText="Failed to save operation result to database"),
)
await stream_registry.mark_task_completed(task.task_id, status="failed")
raise
# Generate LLM continuation with streaming
try:
await chat_service._generate_llm_continuation_with_streaming(
session_id=task.session_id,
user_id=task.user_id,
task_id=task.task_id,
)
except Exception as e:
logger.error(
f"[COMPLETION] Failed to generate LLM continuation: {e}",
exc_info=True,
)
# Mark task as completed and release Redis lock
await stream_registry.mark_task_completed(task.task_id, status="completed")
try:
await chat_service._mark_operation_completed(task.tool_call_id)
except Exception as e:
logger.error(f"[COMPLETION] Failed to mark operation completed: {e}")
logger.info(
f"[COMPLETION] Successfully processed completion for task {task.task_id}"
)
async def process_operation_failure(
task: stream_registry.ActiveTask,
error: str | None,
prisma_client: Prisma | None = None,
) -> None:
"""Handle failed operation completion.
Publishes the error to the stream registry, updates the database with
the error response, and marks the task as failed.
Args:
task: The active task that failed
error: The error message from the operation
prisma_client: Optional Prisma client for database operations.
If None, uses chat_service._update_pending_operation instead.
"""
error_msg = error or "Operation failed"
# Publish error to stream registry
await stream_registry.publish_chunk(
task.task_id,
StreamError(errorText=error_msg),
)
# Update pending operation with error
# If this fails, we still continue to mark the task as failed
error_response = ErrorResponse(
message=error_msg,
error=error,
)
try:
await _update_tool_message(
session_id=task.session_id,
tool_call_id=task.tool_call_id,
content=error_response.model_dump_json(),
prisma_client=prisma_client,
)
except ToolMessageUpdateError:
# DB update failed - log but continue with cleanup
logger.error(
f"[COMPLETION] DB update failed while processing failure for task {task.task_id}, "
"continuing with cleanup"
)
# Mark task as failed and release Redis lock
await stream_registry.mark_task_completed(task.task_id, status="failed")
try:
await chat_service._mark_operation_completed(task.tool_call_id)
except Exception as e:
logger.error(f"[COMPLETION] Failed to mark operation completed: {e}")
logger.info(f"[COMPLETION] Processed failure for task {task.task_id}: {error_msg}")

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"""Configuration management for chat system."""
import os
from pydantic import Field, field_validator
from pydantic_settings import BaseSettings
class ChatConfig(BaseSettings):
"""Configuration for the chat system."""
# OpenAI API Configuration
model: str = Field(
default="anthropic/claude-opus-4.5", description="Default model to use"
)
title_model: str = Field(
default="openai/gpt-4o-mini",
description="Model to use for generating session titles (should be fast/cheap)",
)
api_key: str | None = Field(default=None, description="OpenAI API key")
base_url: str | None = Field(
default="https://openrouter.ai/api/v1",
description="Base URL for API (e.g., for OpenRouter)",
)
# Session TTL Configuration - 12 hours
session_ttl: int = Field(default=43200, description="Session TTL in seconds")
# Streaming Configuration
max_context_messages: int = Field(
default=50, ge=1, le=200, description="Maximum context messages"
)
stream_timeout: int = Field(default=300, description="Stream timeout in seconds")
max_retries: int = Field(default=3, description="Maximum number of retries")
max_agent_runs: int = Field(default=30, description="Maximum number of agent runs")
max_agent_schedules: int = Field(
default=30, description="Maximum number of agent schedules"
)
# Long-running operation configuration
long_running_operation_ttl: int = Field(
default=600,
description="TTL in seconds for long-running operation tracking in Redis (safety net if pod dies)",
)
# Stream registry configuration for SSE reconnection
stream_ttl: int = Field(
default=3600,
description="TTL in seconds for stream data in Redis (1 hour)",
)
stream_max_length: int = Field(
default=10000,
description="Maximum number of messages to store per stream",
)
# Redis Streams configuration for completion consumer
stream_completion_name: str = Field(
default="chat:completions",
description="Redis Stream name for operation completions",
)
stream_consumer_group: str = Field(
default="chat_consumers",
description="Consumer group name for completion stream",
)
stream_claim_min_idle_ms: int = Field(
default=60000,
description="Minimum idle time in milliseconds before claiming pending messages from dead consumers",
)
# Redis key prefixes for stream registry
task_meta_prefix: str = Field(
default="chat:task:meta:",
description="Prefix for task metadata hash keys",
)
task_stream_prefix: str = Field(
default="chat:stream:",
description="Prefix for task message stream keys",
)
task_op_prefix: str = Field(
default="chat:task:op:",
description="Prefix for operation ID to task ID mapping keys",
)
internal_api_key: str | None = Field(
default=None,
description="API key for internal webhook callbacks (env: CHAT_INTERNAL_API_KEY)",
)
# Langfuse Prompt Management Configuration
# Note: Langfuse credentials are in Settings().secrets (settings.py)
langfuse_prompt_name: str = Field(
default="CoPilot Prompt",
description="Name of the prompt in Langfuse to fetch",
)
@field_validator("api_key", mode="before")
@classmethod
def get_api_key(cls, v):
"""Get API key from environment if not provided."""
if v is None:
# Try to get from environment variables
# First check for CHAT_API_KEY (Pydantic prefix)
v = os.getenv("CHAT_API_KEY")
if not v:
# Fall back to OPEN_ROUTER_API_KEY
v = os.getenv("OPEN_ROUTER_API_KEY")
if not v:
# Fall back to OPENAI_API_KEY
v = os.getenv("OPENAI_API_KEY")
return v
@field_validator("base_url", mode="before")
@classmethod
def get_base_url(cls, v):
"""Get base URL from environment if not provided."""
if v is None:
# Check for OpenRouter or custom base URL
v = os.getenv("CHAT_BASE_URL")
if not v:
v = os.getenv("OPENROUTER_BASE_URL")
if not v:
v = os.getenv("OPENAI_BASE_URL")
if not v:
v = "https://openrouter.ai/api/v1"
return v
@field_validator("internal_api_key", mode="before")
@classmethod
def get_internal_api_key(cls, v):
"""Get internal API key from environment if not provided."""
if v is None:
v = os.getenv("CHAT_INTERNAL_API_KEY")
return v
# Prompt paths for different contexts
PROMPT_PATHS: dict[str, str] = {
"default": "prompts/chat_system.md",
"onboarding": "prompts/onboarding_system.md",
}
class Config:
"""Pydantic config."""
env_file = ".env"
env_file_encoding = "utf-8"
extra = "ignore" # Ignore extra environment variables

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"""Database operations for chat sessions."""
import asyncio
import logging
from datetime import UTC, datetime
from typing import Any, cast
from prisma.models import ChatMessage as PrismaChatMessage
from prisma.models import ChatSession as PrismaChatSession
from prisma.types import (
ChatMessageCreateInput,
ChatSessionCreateInput,
ChatSessionUpdateInput,
ChatSessionWhereInput,
)
from backend.data.db import transaction
from backend.util.json import SafeJson
logger = logging.getLogger(__name__)
async def get_chat_session(session_id: str) -> PrismaChatSession | None:
"""Get a chat session by ID from the database."""
session = await PrismaChatSession.prisma().find_unique(
where={"id": session_id},
include={"Messages": True},
)
if session and session.Messages:
# Sort messages by sequence in Python - Prisma Python client doesn't support
# order_by in include clauses (unlike Prisma JS), so we sort after fetching
session.Messages.sort(key=lambda m: m.sequence)
return session
async def create_chat_session(
session_id: str,
user_id: str,
) -> PrismaChatSession:
"""Create a new chat session in the database."""
data = ChatSessionCreateInput(
id=session_id,
userId=user_id,
credentials=SafeJson({}),
successfulAgentRuns=SafeJson({}),
successfulAgentSchedules=SafeJson({}),
)
return await PrismaChatSession.prisma().create(
data=data,
include={"Messages": True},
)
async def update_chat_session(
session_id: str,
credentials: dict[str, Any] | None = None,
successful_agent_runs: dict[str, Any] | None = None,
successful_agent_schedules: dict[str, Any] | None = None,
total_prompt_tokens: int | None = None,
total_completion_tokens: int | None = None,
title: str | None = None,
) -> PrismaChatSession | None:
"""Update a chat session's metadata."""
data: ChatSessionUpdateInput = {"updatedAt": datetime.now(UTC)}
if credentials is not None:
data["credentials"] = SafeJson(credentials)
if successful_agent_runs is not None:
data["successfulAgentRuns"] = SafeJson(successful_agent_runs)
if successful_agent_schedules is not None:
data["successfulAgentSchedules"] = SafeJson(successful_agent_schedules)
if total_prompt_tokens is not None:
data["totalPromptTokens"] = total_prompt_tokens
if total_completion_tokens is not None:
data["totalCompletionTokens"] = total_completion_tokens
if title is not None:
data["title"] = title
session = await PrismaChatSession.prisma().update(
where={"id": session_id},
data=data,
include={"Messages": True},
)
if session and session.Messages:
# Sort in Python - Prisma Python doesn't support order_by in include clauses
session.Messages.sort(key=lambda m: m.sequence)
return session
async def add_chat_message(
session_id: str,
role: str,
sequence: int,
content: str | None = None,
name: str | None = None,
tool_call_id: str | None = None,
refusal: str | None = None,
tool_calls: list[dict[str, Any]] | None = None,
function_call: dict[str, Any] | None = None,
) -> PrismaChatMessage:
"""Add a message to a chat session."""
# Build input dict dynamically rather than using ChatMessageCreateInput directly
# because Prisma's TypedDict validation rejects optional fields set to None.
# We only include fields that have values, then cast at the end.
data: dict[str, Any] = {
"Session": {"connect": {"id": session_id}},
"role": role,
"sequence": sequence,
}
# Add optional string fields
if content is not None:
data["content"] = content
if name is not None:
data["name"] = name
if tool_call_id is not None:
data["toolCallId"] = tool_call_id
if refusal is not None:
data["refusal"] = refusal
# Add optional JSON fields only when they have values
if tool_calls is not None:
data["toolCalls"] = SafeJson(tool_calls)
if function_call is not None:
data["functionCall"] = SafeJson(function_call)
# Run message create and session timestamp update in parallel for lower latency
_, message = await asyncio.gather(
PrismaChatSession.prisma().update(
where={"id": session_id},
data={"updatedAt": datetime.now(UTC)},
),
PrismaChatMessage.prisma().create(data=cast(ChatMessageCreateInput, data)),
)
return message
async def add_chat_messages_batch(
session_id: str,
messages: list[dict[str, Any]],
start_sequence: int,
) -> list[PrismaChatMessage]:
"""Add multiple messages to a chat session in a batch.
Uses a transaction for atomicity - if any message creation fails,
the entire batch is rolled back.
"""
if not messages:
return []
created_messages = []
async with transaction() as tx:
for i, msg in enumerate(messages):
# Build input dict dynamically rather than using ChatMessageCreateInput
# directly because Prisma's TypedDict validation rejects optional fields
# set to None. We only include fields that have values, then cast.
data: dict[str, Any] = {
"Session": {"connect": {"id": session_id}},
"role": msg["role"],
"sequence": start_sequence + i,
}
# Add optional string fields
if msg.get("content") is not None:
data["content"] = msg["content"]
if msg.get("name") is not None:
data["name"] = msg["name"]
if msg.get("tool_call_id") is not None:
data["toolCallId"] = msg["tool_call_id"]
if msg.get("refusal") is not None:
data["refusal"] = msg["refusal"]
# Add optional JSON fields only when they have values
if msg.get("tool_calls") is not None:
data["toolCalls"] = SafeJson(msg["tool_calls"])
if msg.get("function_call") is not None:
data["functionCall"] = SafeJson(msg["function_call"])
created = await PrismaChatMessage.prisma(tx).create(
data=cast(ChatMessageCreateInput, data)
)
created_messages.append(created)
# Update session's updatedAt timestamp within the same transaction.
# Note: Token usage (total_prompt_tokens, total_completion_tokens) is updated
# separately via update_chat_session() after streaming completes.
await PrismaChatSession.prisma(tx).update(
where={"id": session_id},
data={"updatedAt": datetime.now(UTC)},
)
return created_messages
async def get_user_chat_sessions(
user_id: str,
limit: int = 50,
offset: int = 0,
) -> list[PrismaChatSession]:
"""Get chat sessions for a user, ordered by most recent."""
return await PrismaChatSession.prisma().find_many(
where={"userId": user_id},
order={"updatedAt": "desc"},
take=limit,
skip=offset,
)
async def get_user_session_count(user_id: str) -> int:
"""Get the total number of chat sessions for a user."""
return await PrismaChatSession.prisma().count(where={"userId": user_id})
async def delete_chat_session(session_id: str, user_id: str | None = None) -> bool:
"""Delete a chat session and all its messages.
Args:
session_id: The session ID to delete.
user_id: If provided, validates that the session belongs to this user
before deletion. This prevents unauthorized deletion of other
users' sessions.
Returns:
True if deleted successfully, False otherwise.
"""
try:
# Build typed where clause with optional user_id validation
where_clause: ChatSessionWhereInput = {"id": session_id}
if user_id is not None:
where_clause["userId"] = user_id
result = await PrismaChatSession.prisma().delete_many(where=where_clause)
if result == 0:
logger.warning(
f"No session deleted for {session_id} "
f"(user_id validation: {user_id is not None})"
)
return False
return True
except Exception as e:
logger.error(f"Failed to delete chat session {session_id}: {e}")
return False
async def get_chat_session_message_count(session_id: str) -> int:
"""Get the number of messages in a chat session."""
count = await PrismaChatMessage.prisma().count(where={"sessionId": session_id})
return count
async def update_tool_message_content(
session_id: str,
tool_call_id: str,
new_content: str,
) -> bool:
"""Update the content of a tool message in chat history.
Used by background tasks to update pending operation messages with final results.
Args:
session_id: The chat session ID.
tool_call_id: The tool call ID to find the message.
new_content: The new content to set.
Returns:
True if a message was updated, False otherwise.
"""
try:
result = await PrismaChatMessage.prisma().update_many(
where={
"sessionId": session_id,
"toolCallId": tool_call_id,
},
data={
"content": new_content,
},
)
if result == 0:
logger.warning(
f"No message found to update for session {session_id}, "
f"tool_call_id {tool_call_id}"
)
return False
return True
except Exception as e:
logger.error(
f"Failed to update tool message for session {session_id}, "
f"tool_call_id {tool_call_id}: {e}"
)
return False

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@@ -0,0 +1,617 @@
import asyncio
import logging
import uuid
from datetime import UTC, datetime
from typing import Any
from weakref import WeakValueDictionary
from openai.types.chat import (
ChatCompletionAssistantMessageParam,
ChatCompletionDeveloperMessageParam,
ChatCompletionFunctionMessageParam,
ChatCompletionMessageParam,
ChatCompletionSystemMessageParam,
ChatCompletionToolMessageParam,
ChatCompletionUserMessageParam,
)
from openai.types.chat.chat_completion_assistant_message_param import FunctionCall
from openai.types.chat.chat_completion_message_tool_call_param import (
ChatCompletionMessageToolCallParam,
Function,
)
from prisma.models import ChatMessage as PrismaChatMessage
from prisma.models import ChatSession as PrismaChatSession
from pydantic import BaseModel
from backend.data.redis_client import get_redis_async
from backend.util import json
from backend.util.exceptions import DatabaseError, RedisError
from . import db as chat_db
from .config import ChatConfig
logger = logging.getLogger(__name__)
config = ChatConfig()
def _parse_json_field(value: str | dict | list | None, default: Any = None) -> Any:
"""Parse a JSON field that may be stored as string or already parsed."""
if value is None:
return default
if isinstance(value, str):
return json.loads(value)
return value
# Redis cache key prefix for chat sessions
CHAT_SESSION_CACHE_PREFIX = "chat:session:"
def _get_session_cache_key(session_id: str) -> str:
"""Get the Redis cache key for a chat session."""
return f"{CHAT_SESSION_CACHE_PREFIX}{session_id}"
# Session-level locks to prevent race conditions during concurrent upserts.
# Uses WeakValueDictionary to automatically garbage collect locks when no longer referenced,
# preventing unbounded memory growth while maintaining lock semantics for active sessions.
# Invalidation: Locks are auto-removed by GC when no coroutine holds a reference (after
# async with lock: completes). Explicit cleanup also occurs in delete_chat_session().
_session_locks: WeakValueDictionary[str, asyncio.Lock] = WeakValueDictionary()
_session_locks_mutex = asyncio.Lock()
async def _get_session_lock(session_id: str) -> asyncio.Lock:
"""Get or create a lock for a specific session to prevent concurrent upserts.
Uses WeakValueDictionary for automatic cleanup: locks are garbage collected
when no coroutine holds a reference to them, preventing memory leaks from
unbounded growth of session locks.
"""
async with _session_locks_mutex:
lock = _session_locks.get(session_id)
if lock is None:
lock = asyncio.Lock()
_session_locks[session_id] = lock
return lock
class ChatMessage(BaseModel):
role: str
content: str | None = None
name: str | None = None
tool_call_id: str | None = None
refusal: str | None = None
tool_calls: list[dict] | None = None
function_call: dict | None = None
class Usage(BaseModel):
prompt_tokens: int
completion_tokens: int
total_tokens: int
class ChatSession(BaseModel):
session_id: str
user_id: str
title: str | None = None
messages: list[ChatMessage]
usage: list[Usage]
credentials: dict[str, dict] = {} # Map of provider -> credential metadata
started_at: datetime
updated_at: datetime
successful_agent_runs: dict[str, int] = {}
successful_agent_schedules: dict[str, int] = {}
@staticmethod
def new(user_id: str) -> "ChatSession":
return ChatSession(
session_id=str(uuid.uuid4()),
user_id=user_id,
title=None,
messages=[],
usage=[],
credentials={},
started_at=datetime.now(UTC),
updated_at=datetime.now(UTC),
)
@staticmethod
def from_db(
prisma_session: PrismaChatSession,
prisma_messages: list[PrismaChatMessage] | None = None,
) -> "ChatSession":
"""Convert Prisma models to Pydantic ChatSession."""
messages = []
if prisma_messages:
for msg in prisma_messages:
messages.append(
ChatMessage(
role=msg.role,
content=msg.content,
name=msg.name,
tool_call_id=msg.toolCallId,
refusal=msg.refusal,
tool_calls=_parse_json_field(msg.toolCalls),
function_call=_parse_json_field(msg.functionCall),
)
)
# Parse JSON fields from Prisma
credentials = _parse_json_field(prisma_session.credentials, default={})
successful_agent_runs = _parse_json_field(
prisma_session.successfulAgentRuns, default={}
)
successful_agent_schedules = _parse_json_field(
prisma_session.successfulAgentSchedules, default={}
)
# Calculate usage from token counts
usage = []
if prisma_session.totalPromptTokens or prisma_session.totalCompletionTokens:
usage.append(
Usage(
prompt_tokens=prisma_session.totalPromptTokens or 0,
completion_tokens=prisma_session.totalCompletionTokens or 0,
total_tokens=(prisma_session.totalPromptTokens or 0)
+ (prisma_session.totalCompletionTokens or 0),
)
)
return ChatSession(
session_id=prisma_session.id,
user_id=prisma_session.userId,
title=prisma_session.title,
messages=messages,
usage=usage,
credentials=credentials,
started_at=prisma_session.createdAt,
updated_at=prisma_session.updatedAt,
successful_agent_runs=successful_agent_runs,
successful_agent_schedules=successful_agent_schedules,
)
def to_openai_messages(self) -> list[ChatCompletionMessageParam]:
messages = []
for message in self.messages:
if message.role == "developer":
m = ChatCompletionDeveloperMessageParam(
role="developer",
content=message.content or "",
)
if message.name:
m["name"] = message.name
messages.append(m)
elif message.role == "system":
m = ChatCompletionSystemMessageParam(
role="system",
content=message.content or "",
)
if message.name:
m["name"] = message.name
messages.append(m)
elif message.role == "user":
m = ChatCompletionUserMessageParam(
role="user",
content=message.content or "",
)
if message.name:
m["name"] = message.name
messages.append(m)
elif message.role == "assistant":
m = ChatCompletionAssistantMessageParam(
role="assistant",
content=message.content or "",
)
if message.function_call:
m["function_call"] = FunctionCall(
arguments=message.function_call["arguments"],
name=message.function_call["name"],
)
if message.refusal:
m["refusal"] = message.refusal
if message.tool_calls:
t: list[ChatCompletionMessageToolCallParam] = []
for tool_call in message.tool_calls:
# Tool calls are stored with nested structure: {id, type, function: {name, arguments}}
function_data = tool_call.get("function", {})
# Skip tool calls that are missing required fields
if "id" not in tool_call or "name" not in function_data:
logger.warning(
f"Skipping invalid tool call: missing required fields. "
f"Got: {tool_call.keys()}, function keys: {function_data.keys()}"
)
continue
# Arguments are stored as a JSON string
arguments_str = function_data.get("arguments", "{}")
t.append(
ChatCompletionMessageToolCallParam(
id=tool_call["id"],
type="function",
function=Function(
arguments=arguments_str,
name=function_data["name"],
),
)
)
m["tool_calls"] = t
if message.name:
m["name"] = message.name
messages.append(m)
elif message.role == "tool":
messages.append(
ChatCompletionToolMessageParam(
role="tool",
content=message.content or "",
tool_call_id=message.tool_call_id or "",
)
)
elif message.role == "function":
messages.append(
ChatCompletionFunctionMessageParam(
role="function",
content=message.content,
name=message.name or "",
)
)
return messages
async def _get_session_from_cache(session_id: str) -> ChatSession | None:
"""Get a chat session from Redis cache."""
redis_key = _get_session_cache_key(session_id)
async_redis = await get_redis_async()
raw_session: bytes | None = await async_redis.get(redis_key)
if raw_session is None:
return None
try:
session = ChatSession.model_validate_json(raw_session)
logger.info(
f"Loading session {session_id} from cache: "
f"message_count={len(session.messages)}, "
f"roles={[m.role for m in session.messages]}"
)
return session
except Exception as e:
logger.error(f"Failed to deserialize session {session_id}: {e}", exc_info=True)
raise RedisError(f"Corrupted session data for {session_id}") from e
async def _cache_session(session: ChatSession) -> None:
"""Cache a chat session in Redis."""
redis_key = _get_session_cache_key(session.session_id)
async_redis = await get_redis_async()
await async_redis.setex(redis_key, config.session_ttl, session.model_dump_json())
async def cache_chat_session(session: ChatSession) -> None:
"""Cache a chat session without persisting to the database."""
await _cache_session(session)
async def invalidate_session_cache(session_id: str) -> None:
"""Invalidate a chat session from Redis cache.
Used by background tasks to ensure fresh data is loaded on next access.
This is best-effort - Redis failures are logged but don't fail the operation.
"""
try:
redis_key = _get_session_cache_key(session_id)
async_redis = await get_redis_async()
await async_redis.delete(redis_key)
except Exception as e:
# Best-effort: log but don't fail - cache will expire naturally
logger.warning(f"Failed to invalidate session cache for {session_id}: {e}")
async def _get_session_from_db(session_id: str) -> ChatSession | None:
"""Get a chat session from the database."""
prisma_session = await chat_db.get_chat_session(session_id)
if not prisma_session:
return None
messages = prisma_session.Messages
logger.info(
f"Loading session {session_id} from DB: "
f"has_messages={messages is not None}, "
f"message_count={len(messages) if messages else 0}, "
f"roles={[m.role for m in messages] if messages else []}"
)
return ChatSession.from_db(prisma_session, messages)
async def _save_session_to_db(
session: ChatSession, existing_message_count: int
) -> None:
"""Save or update a chat session in the database."""
# Check if session exists in DB
existing = await chat_db.get_chat_session(session.session_id)
if not existing:
# Create new session
await chat_db.create_chat_session(
session_id=session.session_id,
user_id=session.user_id,
)
existing_message_count = 0
# Calculate total tokens from usage
total_prompt = sum(u.prompt_tokens for u in session.usage)
total_completion = sum(u.completion_tokens for u in session.usage)
# Update session metadata
await chat_db.update_chat_session(
session_id=session.session_id,
credentials=session.credentials,
successful_agent_runs=session.successful_agent_runs,
successful_agent_schedules=session.successful_agent_schedules,
total_prompt_tokens=total_prompt,
total_completion_tokens=total_completion,
)
# Add new messages (only those after existing count)
new_messages = session.messages[existing_message_count:]
if new_messages:
messages_data = []
for msg in new_messages:
messages_data.append(
{
"role": msg.role,
"content": msg.content,
"name": msg.name,
"tool_call_id": msg.tool_call_id,
"refusal": msg.refusal,
"tool_calls": msg.tool_calls,
"function_call": msg.function_call,
}
)
logger.info(
f"Saving {len(new_messages)} new messages to DB for session {session.session_id}: "
f"roles={[m['role'] for m in messages_data]}, "
f"start_sequence={existing_message_count}"
)
await chat_db.add_chat_messages_batch(
session_id=session.session_id,
messages=messages_data,
start_sequence=existing_message_count,
)
async def get_chat_session(
session_id: str,
user_id: str | None = None,
) -> ChatSession | None:
"""Get a chat session by ID.
Checks Redis cache first, falls back to database if not found.
Caches database results back to Redis.
Args:
session_id: The session ID to fetch.
user_id: If provided, validates that the session belongs to this user.
If None, ownership is not validated (admin/system access).
"""
# Try cache first
try:
session = await _get_session_from_cache(session_id)
if session:
# Verify user ownership if user_id was provided for validation
if user_id is not None and session.user_id != user_id:
logger.warning(
f"Session {session_id} user id mismatch: {session.user_id} != {user_id}"
)
return None
return session
except RedisError:
logger.warning(f"Cache error for session {session_id}, trying database")
except Exception as e:
logger.warning(f"Unexpected cache error for session {session_id}: {e}")
# Fall back to database
logger.info(f"Session {session_id} not in cache, checking database")
session = await _get_session_from_db(session_id)
if session is None:
logger.warning(f"Session {session_id} not found in cache or database")
return None
# Verify user ownership if user_id was provided for validation
if user_id is not None and session.user_id != user_id:
logger.warning(
f"Session {session_id} user id mismatch: {session.user_id} != {user_id}"
)
return None
# Cache the session from DB
try:
await _cache_session(session)
logger.info(f"Cached session {session_id} from database")
except Exception as e:
logger.warning(f"Failed to cache session {session_id}: {e}")
return session
async def upsert_chat_session(
session: ChatSession,
) -> ChatSession:
"""Update a chat session in both cache and database.
Uses session-level locking to prevent race conditions when concurrent
operations (e.g., background title update and main stream handler)
attempt to upsert the same session simultaneously.
Raises:
DatabaseError: If the database write fails. The cache is still updated
as a best-effort optimization, but the error is propagated to ensure
callers are aware of the persistence failure.
RedisError: If the cache write fails (after successful DB write).
"""
# Acquire session-specific lock to prevent concurrent upserts
lock = await _get_session_lock(session.session_id)
async with lock:
# Get existing message count from DB for incremental saves
existing_message_count = await chat_db.get_chat_session_message_count(
session.session_id
)
db_error: Exception | None = None
# Save to database (primary storage)
try:
await _save_session_to_db(session, existing_message_count)
except Exception as e:
logger.error(
f"Failed to save session {session.session_id} to database: {e}"
)
db_error = e
# Save to cache (best-effort, even if DB failed)
try:
await _cache_session(session)
except Exception as e:
# If DB succeeded but cache failed, raise cache error
if db_error is None:
raise RedisError(
f"Failed to persist chat session {session.session_id} to Redis: {e}"
) from e
# If both failed, log cache error but raise DB error (more critical)
logger.warning(
f"Cache write also failed for session {session.session_id}: {e}"
)
# Propagate DB error after attempting cache (prevents data loss)
if db_error is not None:
raise DatabaseError(
f"Failed to persist chat session {session.session_id} to database"
) from db_error
return session
async def create_chat_session(user_id: str) -> ChatSession:
"""Create a new chat session and persist it.
Raises:
DatabaseError: If the database write fails. We fail fast to ensure
callers never receive a non-persisted session that only exists
in cache (which would be lost when the cache expires).
"""
session = ChatSession.new(user_id)
# Create in database first - fail fast if this fails
try:
await chat_db.create_chat_session(
session_id=session.session_id,
user_id=user_id,
)
except Exception as e:
logger.error(f"Failed to create session {session.session_id} in database: {e}")
raise DatabaseError(
f"Failed to create chat session {session.session_id} in database"
) from e
# Cache the session (best-effort optimization, DB is source of truth)
try:
await _cache_session(session)
except Exception as e:
logger.warning(f"Failed to cache new session {session.session_id}: {e}")
return session
async def get_user_sessions(
user_id: str,
limit: int = 50,
offset: int = 0,
) -> tuple[list[ChatSession], int]:
"""Get chat sessions for a user from the database with total count.
Returns:
A tuple of (sessions, total_count) where total_count is the overall
number of sessions for the user (not just the current page).
"""
prisma_sessions = await chat_db.get_user_chat_sessions(user_id, limit, offset)
total_count = await chat_db.get_user_session_count(user_id)
sessions = []
for prisma_session in prisma_sessions:
# Convert without messages for listing (lighter weight)
sessions.append(ChatSession.from_db(prisma_session, None))
return sessions, total_count
async def delete_chat_session(session_id: str, user_id: str | None = None) -> bool:
"""Delete a chat session from both cache and database.
Args:
session_id: The session ID to delete.
user_id: If provided, validates that the session belongs to this user
before deletion. This prevents unauthorized deletion.
Returns:
True if deleted successfully, False otherwise.
"""
# Delete from database first (with optional user_id validation)
# This confirms ownership before invalidating cache
deleted = await chat_db.delete_chat_session(session_id, user_id)
if not deleted:
return False
# Only invalidate cache and clean up lock after DB confirms deletion
try:
redis_key = _get_session_cache_key(session_id)
async_redis = await get_redis_async()
await async_redis.delete(redis_key)
except Exception as e:
logger.warning(f"Failed to delete session {session_id} from cache: {e}")
# Clean up session lock (belt-and-suspenders with WeakValueDictionary)
async with _session_locks_mutex:
_session_locks.pop(session_id, None)
return True
async def update_session_title(session_id: str, title: str) -> bool:
"""Update only the title of a chat session.
This is a lightweight operation that doesn't touch messages, avoiding
race conditions with concurrent message updates. Use this for background
title generation instead of upsert_chat_session.
Args:
session_id: The session ID to update.
title: The new title to set.
Returns:
True if updated successfully, False otherwise.
"""
try:
result = await chat_db.update_chat_session(session_id=session_id, title=title)
if result is None:
logger.warning(f"Session {session_id} not found for title update")
return False
# Invalidate cache so next fetch gets updated title
try:
redis_key = _get_session_cache_key(session_id)
async_redis = await get_redis_async()
await async_redis.delete(redis_key)
except Exception as e:
logger.warning(f"Failed to invalidate cache for session {session_id}: {e}")
return True
except Exception as e:
logger.error(f"Failed to update title for session {session_id}: {e}")
return False

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