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automation

WFGY: Cut AI Workflow Complexity with Advanced Reasoning

Open-source toolkit for AI agents and RAG workflows that simplifies complex reasoning and debugging for technical founders building intelligent systems. 1.8k+ GitHub stars.
1,752 stars162 forksJupyter NotebookUpdated 6/2/2026100% free · open source
What it does

Provides an open-source toolkit for building advanced AI agents with enhanced reasoning and debugging capabilities for complex workflow automation.

When to use it
  • •When creating intelligent systems that require multi-step problem solving
  • •For startups needing advanced RAG (Retrieval-Augmented Generation) workflows
  • •When you need sophisticated debugging and tracing for AI agent development
Quick start
  1. 1Clone the GitHub repository: git clone https://github.com/onestardao/WFGY
  2. 2Install dependencies using pip or conda
  3. 3Review the Problem Map documentation for initial workflow design
  4. 4Experiment with the Global Debug Card to trace AI reasoning paths
Ready-to-paste prompt
python wfgy_agent.py --mode='reasoning' --workflow='startup_problem_solver'

Topics

ai-agents
alignment
debugging
evaluation
graphrag
hallucination
information-retrieval
knowledge-graph
llm
rag
reasoning
retrieval-augmented-generation
Quick Actions
Details
Creator
onestardao
Language
Jupyter Notebook
Category
automation
Published
6/4/2025

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