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Author SHA1 Message Date
Zamil Majdy 89eb5d1189
feat(feature-flag): add LaunchDarkly user context and metadata support (#10595) 
## Summary

Enable LaunchDarkly feature flags to use rich user context and metadata
for advanced targeting, including user segments, account age, email
domains, and custom attributes. This unlocks LaunchDarkly's powerful
targeting capabilities beyond simple user ID checks.

## Problem

LaunchDarkly feature flags were only receiving basic user IDs,
preventing the use of:
- **Segment-based targeting** (e.g., "employees", "beta users", "new
accounts")
- **Contextual rules** (e.g., account age, email domain, custom
metadata)
- **Advanced LaunchDarkly features** like percentage rollouts by user
attributes

This limited feature flag flexibility and required manual user ID
management for targeting.

## Solution

### 🎯 **LaunchDarkly Context Enhancement**
- **Rich user context**: Send user metadata, segments, account age,
email domain to LaunchDarkly
- **Automatic segmentation**: Users automatically categorized as
"employee", "new_user", "established_user" etc.
- **Custom metadata support**: Any user metadata becomes available for
LaunchDarkly targeting
- **24-hour caching**: Efficient user context retrieval with TTL cache
to reduce database calls

### 📊 **User Context Data**
```python
# Before: Only user ID
context = Context.builder("user-123").build()

# After: Full context with targeting data
context = {
    "email": "user@agpt.co",
    "created_at": "2023-01-15T10:00:00Z",
    "segments": ["employee", "established_user"],
    "email_domain": "agpt.co", 
    "account_age_days": 365,
    "custom_role": "admin"
}
```

### 🏗️ **Required Infrastructure Changes**

To support proper LaunchDarkly serialization, we needed to implement
clean application models:

#### **Application-Layer User Model**
- Created snake_case User model (`created_at`, `email_verified`) for
proper JSON serialization
- LaunchDarkly expects consistent field naming - camelCase Prisma
objects caused validation errors
- Added `User.from_db()` converter to safely transform database objects

#### **HTTP Client Reliability**  
- Fixed HTTP 4xx retry issue that was causing unnecessary load
- Added layer validation to prevent database objects leaking to external
services

#### **Type Safety**
- Eliminated `Any` types and defensive coding patterns
- Proper typing enables better IDE support and catches errors early

## Technical Implementation

### **Core LaunchDarkly Enhancement**
```python
# autogpt_libs/feature_flag/client.py
@async_ttl_cache(maxsize=1000, ttl_seconds=86400)  # 24h cache
async def _fetch_user_context_data(user_id: str) -> dict[str, Any]:
    user = await get_user_by_id(user_id)
    return _build_launchdarkly_context(user)

def _build_launchdarkly_context(user: User) -> dict[str, Any]:
    return {
        "email": user.email,
        "created_at": user.created_at.isoformat(),  # snake_case for serialization
        "segments": determine_user_segments(user),
        "account_age_days": calculate_account_age(user),
        # ... more context data
    }
```

### **User Segmentation Logic**
- **Role-based**: `admin`, `user`, `system` segments
- **Domain-based**: `employee` for @agpt.co emails  
- **Account age**: `new_user` (<7 days), `recent_user` (7-30 days),
`established_user` (>30 days)
- **Custom metadata**: Any user metadata becomes available for targeting

### **Infrastructure Updates**
- `backend/data/model.py`: Application User model with proper
serialization
- `backend/util/service.py`: HTTP client improvements and layer
validation
- Multiple files: Migration to use application models for consistency

## LaunchDarkly Usage Examples

With this enhancement, you can now create LaunchDarkly rules like:

```yaml
# Target employees only
- variation: true
  targets:
    - values: ["employee"]
      contextKind: "user"
      attribute: "segments"

# Target new users for gradual rollout  
- variation: true
  rollout:
    variations:
      - variation: true
        weight: 25000  # 25% of new users
    contextKind: "user" 
    bucketBy: "segments"
    filters:
      - attribute: "segments"
        op: "contains"
        values: ["new_user"]
```

## Performance & Caching

- **24-hour TTL cache**: Dramatically reduces database calls for user
context
- **Graceful fallbacks**: Simple user ID context if database unavailable
- **Efficient caching**: 1000 entry LRU cache with automatic TTL
expiration

## Testing

- [x] LaunchDarkly context includes all expected user attributes
- [x] Segmentation logic correctly categorizes users
- [x] 24-hour cache reduces database load
- [x] Fallback to simple context works when database unavailable
- [x] All existing feature flag functionality preserved
- [x] HTTP retry improvements work correctly

## Breaking Changes

✅ **No external API changes** - all existing feature flag usage
continues to work

⚠️ **Internal changes only**:
- `get_user_by_id()` returns application User model instead of Prisma
model
- Test utilities need to import User from `backend.data.model`

## Impact

🎯 **Product Impact**:
- **Advanced targeting**: Product teams can now use sophisticated
LaunchDarkly rules
- **Better user experience**: Gradual rollouts, A/B testing, and
segment-based features
- **Operational efficiency**: Reduced need for manual user ID management

🚀 **Performance Impact**:
- **Reduced database load**: 24-hour caching minimizes repeated user
context queries
- **Improved reliability**: Fixed HTTP retry inefficiencies
- **Better monitoring**: Cleaner logs without 4xx retry noise

---

**Primary goal**: Enable rich LaunchDarkly targeting with user context
and segments
**Infrastructure changes**: Required for proper serialization and
reliability

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

---------

Co-authored-by: Claude <noreply@anthropic.com>
 2025-08-12 05:25:56 +00:00
Abhimanyu Yadav 4f208d262e
test(frontend): add e2e tests for agent dashboard page (#10572) 
I have added e2e tests for agent dashboard page

It includes, tests like 
- dashboard page loads successfully
- submit agent button works correctly
- agent table displays data correctly
- agent table actions work correctly

I’ve also updated the e2e test script to include some static agent
submissions, so I can test if it loads on the frontend.

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
  - [x] All tests are working perfectly locally
  
  
<img width="469" height="177" alt="Screenshot 2025-08-08 at 12 13 42 PM"
src="https://github.com/user-attachments/assets/5e37afc3-c151-476a-84de-0a06f44a0722"
/>
 2025-08-08 07:29:11 +00:00
Abhimanyu Yadav 9848266474
test(frontend): e2e tests for library page (#10355) 
In this PR, I’ve added library page tests.

### Changes

I’ve added 9 tests: 8 for normal flows and 1 for checking edge cases.

Test names are something like:
- Library navigation is accessible from the navbar.
- The library page loads successfully.
- Agents are visible, and cards work correctly.
- Pagination works correctly.
- Sorting works correctly.
- Searching works correctly.
- Pagination while searching works correctly.
- Uploading an agent works correctly.
- Edge case: Search edge cases and error handling behave correctly.

Other than that, I’ve added a new utility that uses the build page to
help us create users at the start, which we could use to test the
library page.

- All tests are passing locally

<img width="514" height="465" alt="Screenshot 2025-07-12 at 11 13 41 AM"
src="https://github.com/user-attachments/assets/7a46c437-7db5-458b-b99a-4fa0d479866f"
/>

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
  - [x] All library tests are working locally and on CI perfectly.
 2025-08-06 08:00:04 +00:00
Abhimanyu Yadav 878f61aaf4
fix(test): Enhance E2E test data script to include featured creators and agents (#10517) 
This PR updates the existing E2E test data script to support the
creation of featured creators and featured agents. Previously, these
entities were not included, which limited our ability to fully test
certain flows during Playwright E2E testing.

### Changes
- Added logic to create featured creators
- Added logic to create featured agents

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
  - [x] All tests are passing locally after updating the data script.
 2025-08-01 11:09:39 +00:00
Zamil Majdy 0c9b7334c1
feat(backend): Register agent subgraphs as library entries during agent import (#10409) 
Currently, we only create a library entry of the top-most graph when
importing the graph from an exported file.
This can cause some complications, as there is no way to remove the
library entry of it.

### Changes 🏗️

Create the library entry for all the subgraphs during the import
process.

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
  <!-- Put your test plan here: -->
  - [x] Export an agent with subgraphs and import it back.
 2025-07-21 11:54:42 +00:00
Abhimanyu Yadav e720f92123
feat(tests): Add E2E test data creator script for comprehensive testing (#10368) 
### Changes
- Introduced a new script to generate test data for end-to-end (E2E)
tests using API functions, ensuring compatibility with future model
changes.
- The script creates test users, agent blocks, graphs, profiles, library
agents, presets, API keys, and store submissions.
- Utilizes external services for image and video URLs, and includes
error handling for data creation processes.
- Provides a summary of created data upon completion, enhancing the
testing framework for the AutoGPT platform.

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] Test scripts are working perfectly and not breaking anything. Data
is also correctly visible in the database.
 2025-07-17 15:47:21 +00:00