This is one of the most exciting releases yet. Proud to introduce the latest GPTR x LangGraph integration showcasing the power of flow engineering and multi agent collaboration! Check out the full implementation in the new directory multi_agents.

By using LangGraph, the research process can be significantly improved in depth and quality by leveraging multiple agents with specialized skills. Inspired by the recent STORM paper, this example showcases how a team of AI agents can work together to conduct research on a given topic, from planning to publication. An average run generates a 5-6 page research report in multiple formats such as PDF, Docx and Markdown.

The Multi Agent Team

The research team is made up of 7 AI agents:

• Chief Editor - Oversees the research process and manages the team. This is the "master" agent that coordinates the other agents using Langgraph.
• Researcher (gpt-researcher) - A specialized autonomous agent that conducts in depth research on a given topic.
• Editor - Responsible for planning the research outline and structure.
• Reviewer - Validates the correctness of the research results given a set of criteria.
• Revisor - Revises the research results based on the feedback from the reviewer.
• Writer - Responsible for compiling and writing the final report.
• Publisher - Responsible for publishing the final report in various formats.

Architecture