Memory layer integration patterns for FastAPI with Mem0 including client setup, memory service patterns, user tracking, conversation persistence, and background task integration. Use when implementing AI memory, adding Mem0 to FastAPI, building chat with memory, or when user mentions Mem0, conversation history, user context, or memory layer.
View on GitHubvanman2024/ai-dev-marketplace
fastapi-backend
February 1, 2026
Select agents to install to:
npx add-skill https://github.com/vanman2024/ai-dev-marketplace/blob/main/plugins/fastapi-backend/skills/mem0-fastapi-integration/SKILL.md -a claude-code --skill mem0-fastapi-integrationInstallation paths:
.claude/skills/mem0-fastapi-integration/# Mem0 FastAPI Integration Patterns
**Purpose:** Provide complete Mem0 integration templates, memory service patterns, user tracking implementations, and conversation persistence strategies for building FastAPI applications with intelligent AI memory.
**Activation Triggers:**
- Integrating Mem0 memory layer into FastAPI
- Building chat applications with conversation history
- Implementing user context and personalization
- Adding memory to AI agents
- Creating stateful AI interactions
- User preference management
**Key Resources:**
- `templates/memory_service.py` - Complete Mem0 service implementation
- `templates/memory_middleware.py` - Request-scoped memory middleware
- `templates/memory_client.py` - Mem0 client configuration
- `templates/memory_routes.py` - API routes for memory operations
- `scripts/setup-mem0.sh` - Mem0 installation and configuration
- `scripts/test-memory.sh` - Memory service testing utility
- `examples/chat_with_memory.py` - Complete chat implementation
- `examples/user_preferences.py` - User preference management
## Core Mem0 Integration
### 1. Client Configuration
**Template:** `templates/memory_client.py`
**Workflow:**
```python
from mem0 import Memory, AsyncMemory, MemoryClient
from mem0.configs.base import MemoryConfig
# Hosted Mem0 Platform
client = MemoryClient(api_key=settings.MEM0_API_KEY)
# Self-Hosted Configuration
config = MemoryConfig(
vector_store={
"provider": "qdrant",
"config": {
"host": settings.QDRANT_HOST,
"port": settings.QDRANT_PORT,
"api_key": settings.QDRANT_API_KEY
}
},
llm={
"provider": "openai",
"config": {
"model": "gpt-4",
"api_key": settings.OPENAI_API_KEY
}
},
embedder={
"provider": "openai",
"config": {
"model": "text-embedding-3-small",
"api_key": settings.OPENAI_API_KEY
}
}
)
memory = AsyncMemory(config)
```
### 2. Memory