- Fix ID generation consistency between MongoDB and SQLite storage
- Fix inconsistent error handling in memory operations
- Fix security issue with hardcoded API key placeholders in examples
- Fix unused imports in mongodb_tools.py
- Fix pymongo version to >= 4.6.3 to address security vulnerabilities
- Improve datetime import organization
- Ensure consistent storage order for better reliability
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-authored-by: Mervin Praison <[email protected]>
Add comprehensive MongoDB integration for PraisonAI agents including:
**Memory Provider**:
- MongoDB as persistent memory storage option
- Vector search capabilities with Atlas Vector Search
- Support for both key-value and vector operations
- Quality scoring and filtering
- User-specific memory isolation
- Graceful fallback to existing SQLite/ChromaDB
**Knowledge Store**:
- MongoDB as vector store for knowledge base
- Document processing with embeddings
- Vector similarity search for knowledge retrieval
- Chunking and metadata management
- Compatible with existing Mem0/ChromaDB workflow
**Tools Integration**:
- Complete MongoDB tools suite (CRUD operations)
- Vector search and text search capabilities
- Collection management and indexing
- Production-ready connection handling
- Error handling and logging
**Examples**:
- Memory provider example with persistent storage
- Knowledge store example with vector search
- Tools integration example with database operations
- Comprehensive business scenario simulation
- Complete documentation and best practices
**Technical Details**:
- Optional dependency: pip install ''praisonaiagents[mongodb]''
- Backward compatibility maintained
- Supports both local MongoDB and Atlas
- Configurable connection pooling and timeouts
- Comprehensive error handling
Resolves#992🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Mervin Praison <[email protected]>
