46 lines
1.4 KiB
Markdown
46 lines
1.4 KiB
Markdown
# LangGraph Research Brief Agent
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## Overview
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This repository implements a **LangGraph** agent that generates a short research brief for any given topic. The agent follows the assignment specification:
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1. Create an outline of 4‑5 bullet points.
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2. For each point perform one web search via Tavily and collect a concise note.
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3. Synthesize all notes into a coherent brief (≈½–1 page).
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The implementation uses:
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- `langgraph` – graph orchestration
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- `langchain-openai` – LLM calls to the BroJS GPT‑OSS model
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- `langchain-tavily` – web search via Tavily API
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- `python-dotenv` – environment variable loading (TAVILY_API_KEY, JOURNAL_MCP_PAT)
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## Installation
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```bash
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pip install -r requirements.txt
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```
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## Usage
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```bash
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# Run the agent for a specific topic
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python main.py "How to integrate LangGraph with Tavily"
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```
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The script prints:
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- The generated outline
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- Notes collected from web searches
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- Final research brief
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You can also import `run_brief` in your own code.
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## Project structure
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```
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├── main.py # Entry point and LangGraph implementation
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├── requirements.txt # Dependencies
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└── README.md # Documentation
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```
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## Example outputs
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1. **Topic:** *How to integrate LangGraph with Tavily*
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2. **Topic:** *Best practices for building research briefs in AI*
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3. **Topic:** *Using LangChain and LangGraph for educational projects*
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Feel free to experiment with different topics.
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"" |