Welcome to the Multiagent Workflows repository! This repository showcases projects that demonstrate the power of multi-agent systems using advanced AI frameworks like LlamaIndex and LangChain's LangGraph. Multi-agent systems are composed of multiple specialized AI agents working collaboratively to solve complex tasks efficiently.

Multi-agent systems function like teams of specialized workers, each with unique expertise. These agents collaborate to accomplish intricate workflows that would be challenging for a single entity to handle alone. By leveraging frameworks like LangGraph, we can structure these agents into dynamic workflows where each agent contributes to the overall task.

• Agents: Independent actors powered by Large Language Models (LLMs), each with its own configuration.
• Collaboration: Agents share information using a common "scratchpad," enabling transparent communication.
• LangGraph Framework: A tool that structures agents as nodes in a graph, with edges representing communication and control conditions guiding data flow.

This repository contains several projects that exemplify multi-agent workflows:

• Description: A system that generates high-quality Anki flashcards from any text input using a multi-agent approach.
• Features:
  • Text analysis to extract key points.
  • Collaborative agent workflow to ensure card quality.
  • Easy-to-integrate output for Anki flashcards.
• Technologies:
  • LlamaIndex for text parsing and analysis.
  • Multi-agent collaboration for quality assurance.

• Description: A more complex system featuring multiple agents, each with a specific role, working together on a shared task.
• Features:
  • Dynamic agent connections modeled as a graph.
  • State management for tracking agent progress.
  • Conditional logic to guide task flow.
• Technologies:
  • LangChain's LangGraph for graph-based agent design.
  • Flexible prompts and tools tailored to each agent.

• Python 3.10+
• Install dependencies:

  pip install -r requirements.txt

1. Clone the repository:

   git clone https://github.com/your-username/multiagent-workflows.git
   cd multiagent-workflows

2. Set up your environment:

   python -m venv env
   source env/bin/activate  # On Windows, use `env\Scripts\activate`

3. Install required packages:

   pip install -r requirements.txt

• Each project is in its own directory under the projects/ folder.
• Follow the README.md in each project's folder for specific instructions on running the examples.

Contributions are welcome! Please follow these steps:

1. Fork the repository.
2. Create a new branch (feature/your-feature-name).
3. Commit your changes.
4. Push to the branch and submit a Pull Request.

This repository is licensed under the MIT License. See the LICENSE file for details.

• LangChain for the LangGraph framework.
• LlamaIndex for enabling advanced text analysis.

• Building a Multi-Agent System using CrewAI
• Build Multi-Agent System
• Multi-Agent Workflows using LangGraph and Langchain
• Build Multi-Agent with LlamaIndex

Happy building with multi-agent workflows! 🚀