https://github.com/nickhawn/news-agent
a news agent build using langgraph, interrupts, memory, and tavily
https://github.com/nickhawn/news-agent
Last synced: about 1 month ago
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a news agent build using langgraph, interrupts, memory, and tavily
- Host: GitHub
- URL: https://github.com/nickhawn/news-agent
- Owner: nickhawn
- Created: 2025-07-20T22:11:26.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2025-07-21T16:02:10.000Z (3 months ago)
- Last Synced: 2025-09-01T18:48:35.748Z (about 2 months ago)
- Language: Python
- Homepage:
- Size: 823 KB
- Stars: 45
- Watchers: 0
- Forks: 6
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome-LangGraph - nickhawn/news-agent - agent?style=social) | (🌐 Web Automation & Scraping / 🟩 Development Tools 🛠️)
README
# News Agent
A simple AI-powered news aggregation agent built with LangGraph that crawls your preferred news sources and provides personalized news summaries based on your interests.
## Overview
This news agent can:
- Provide daily news debriefs from your preferred sources
- Share interesting news facts
- Summarize news from specific sources
- Learn and adapt to your content preferences over time
The agent uses [Tavily](https://www.tavily.com/) for web crawling and OpenAI GPT-4.1 for intelligent content curation.
## Installation
1. Clone this repository
2. Create a virtual environment
3. Install dependencies using uv:
```bash
uv sync
```
## Environment Setup
Copy the `.env.example` file and rename it to `.env`, then fill in the API keys for LangSmith, OpenAI, and Tavily.
## Running
Start the LangGraph server:
```bash
langgraph dev
```
The dev command will launch the LangGraph Studio interface that you can interact with the graph through.
You can ask the agent things like:
- "Give me today's daily digest"
- "What's an interesting tech fact from today?"
- "Summarize the latest from TechCrunch"
The agent should learn your preferences over time and you provide feedback and provide increasingly personalized results.
## Demo
### Agent Graph Structure
The news agent uses a LangGraph workflow that includes web crawling tools, content curation, and a feedback loop for learning user preferences.
### Memory and Personalization
The agent maintains separate memory profiles for news source preferences and content preferences, allowing it to provide increasingly personalized results over time.