LangGraph Research Brief Agent

Overview

This repository implements a LangGraph agent that generates a short research brief for any given topic. The agent follows the assignment specification:

1. Create an outline of 4‑5 bullet points.
2. For each point perform one web search via Tavily and collect a concise note.
3. Synthesize all notes into a coherent brief (≈½–1 page).

The implementation uses:

• langgraph – graph orchestration
• langchain-openai – LLM calls to the BroJS GPT‑OSS model
• langchain-tavily – web search via Tavily API
• python-dotenv – environment variable loading (TAVILY_API_KEY, JOURNAL_MCP_PAT)

Installation

pip install -r requirements.txt

Usage

# Run the agent for a specific topic
python main.py "How to integrate LangGraph with Tavily"

The script prints:

• The generated outline
• Notes collected from web searches
• Final research brief

You can also import run_brief in your own code.

Project structure

├── main.py          # Entry point and LangGraph implementation
├── requirements.txt # Dependencies
└── README.md        # Documentation

Example outputs

1. Topic: How to integrate LangGraph with Tavily
2. Topic: Best practices for building research briefs in AI
3. Topic: Using LangChain and LangGraph for educational projects

Feel free to experiment with different topics. ""