ryantzr1/OpenAlita

AI Summary: The task is to improve the MCP tool system in the Open-Alita project by implementing a two-phase approach for code generation and execution. This involves creating a code generator and validator that produces and checks Python/JS scripts, ensuring code quality and safety. A schema-based parameter generation and validation system is also needed to ensure correct parameter types and prevent errors. The goal is to enhance scalability, reliability, security, and developer experience.

AI Summary: The task is to refactor the Open-Alita project to replace its Langchain dependency with native implementations of large language models. This involves rewriting code modules that interact with LLMs, ensuring functionality remains consistent, and potentially simplifying the architecture for improved transparency and maintainability. The goal is to achieve a more streamlined and understandable system, similar to the approach taken in the referenced browser-use project.

AI Summary: The task requires improving the state management and data flow within the LangGraph component of the Open-Alita project. This involves verifying state updates between nodes, optimizing data transfer between the web interface and MCP agents, and implementing features for state persistence, context utilization, validation, and debugging.

AI Summary: Integrate LangGraph into the Open-Alita project to improve task routing. This involves replacing the current orchestrator agent with a state machine, similar to ByteDance's Deerflow, to manage different agents based on task progress and type. This will enhance the agent's ability to handle complex tasks more efficiently.