Technical implementation and scalability of multi-framework adaptations
Agent-Wiz uses Abstract Syntax Tree (AST) analysis technology to write a dedicated parser for each supported framework. Currently, it stably supports seven frameworks, including LangGraph's directed graph workflow, CrewAI's team collaboration model, and AutoGen's AgentChat module, covering mainstream intelligent body development scenarios above 90%.
The technical implementation is such that each parser recognizes framework-specific syntactic patterns: e.g., parsing query routing logic in LlamaIndex and extracting automation node chains in n8n. The parsing process retains full type annotations and code context, ensuring that the generated JSON contains metadata such as agent/tool type definitions, input/output patterns, and so on.
With the provided SDK, developers can extend support for the new framework. Typical examples of extensions include adding the ability to parse Haystack pipelines, a process that requires about 200 lines of Python code to implement the AST accessor logic.
This answer comes from the articleAgent-Wiz: Analyzing AI Intelligentsia Workflows and Security RisksThe
