- Introduced a new multi-agent system for web research, including a main coordinator agent and specialized research and summary agents.
- Added detailed README for setup, usage, and agent configuration.
- Changed section headers to use more descriptive icons for better visual guidance.
- Improved tutorial structure and overview sections for enhanced readability.
- Updated callback examples to include clearer print statements for better understanding of agent interactions.
- Introduced multiple tutorials covering memory agents, including in-memory and persistent conversation agents, with detailed README documentation.
- Implemented agent lifecycle callbacks and LLM interaction callbacks to enhance monitoring and control over agent execution.
- Added examples for tool execution callbacks, demonstrating how to track tool usage and performance.
- Updated requirements for new tutorials and removed outdated dependencies from previous versions.
- Introduced a new AI Real Estate Agent Team with multi-agent capabilities for property search, market analysis, and valuation.
- Added comprehensive README documentation detailing features, setup instructions, and API requirements.
- Implemented the Enterprise MCP AI Agent Team for orchestrating knowledge management across local files and SaaS platforms, including specialized agents for Notion, GitHub, and Figma.
- Enhanced the overall architecture with intelligent routing and task delegation using the Model Context Protocol (MCP).
- Included necessary requirements for both teams to ensure proper functionality.
