Version 6.4.1 is no longer distributed on PyPI (6.4.2 is the
closest available in the 6.4.x line). Four requirements.txt
files still pin the unavailable version, causing a hard
`pip install` failure on a clean checkout.
Widen to `>=6.4.2,<9` so the resolver picks the latest
compatible release (currently 8.1.1); the lower bound preserves
the original intent of pinning within the 6.4.x family, and the
upper bound matches the loosest existing pin elsewhere in the
repo (ai_competitor_intelligence_agent_team uses 7.2.1, the
ADK crash course uses `>=6.0.0`).
Affected projects:
- starter_ai_agents/ai_medical_imaging_agent
- rag_tutorials/rag_database_routing
- rag_tutorials/rag_agent_cohere
- advanced_ai_agents/multi_agent_apps/agent_teams/ai_teaching_agent_team
Fixes#63
Made-with: Cursor
- Changed response type to `RunOutput` in multimodal design and coding agent teams for improved type safety.
- Updated the `agno` package version in requirements.txt to ensure compatibility across all agents.
- Changed response type to `RunOutput` in the AI real estate and recruitment agent teams for improved type safety.
- Updated the `agno` package version in requirements.txt to ensure compatibility across all agents.
- Adjusted requirements for other dependencies to maintain consistency.
- Refactored legal agent team to utilize the new `Knowledge` class instead of `PDFKnowledgeBase`.
- Updated response type to `RunOutput` for better type safety across multiple functions.
- Changed agent model version from GPT-4.1 to GPT-5 for enhanced performance.
- Specified minimum version for the 'agno' package in requirements.txt for compatibility.
- Integrated ExaTools for competitor URL retrieval in the AI competitor intelligence agent.
- Updated response handling to utilize `RunOutput` for improved type safety.
- Specified minimum version for the 'agno' package in requirements.txt for compatibility across agents.
- Introduced a new multi-agent system for analyzing landing page designs and providing expert UI/UX feedback.
- Implemented a Coordinator/Dispatcher pattern with specialized agents for visual analysis, design strategy, and visual implementation.
- Added tools for editing and generating improved landing pages, along with comprehensive reporting features.
- 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.
