From 148cb44d1c9e1984ea50cd0accbdf3a3fddb0766 Mon Sep 17 00:00:00 2001
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 <kirillkutlahmetov10@gmail.com>
Date: Thu, 4 Jun 2026 16:08:56 +0000
Subject: [PATCH] add README.md

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 README.md | 47 +++++++++++++++++++++++++++++++++++++++++++++--
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-# task-6a219d2dfd30e81cf3146baf
+# LangGraph Research Brief Agent
 
-Solution for BroJS task 6a219d2dfd30e81cf3146baf
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+## 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
+```bash
+pip install -r requirements.txt
+```
+
+## Usage
+```bash
+# 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.
+""
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