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Knowledge graph + AI Agent analysis of news using multi modal GraphRAG approach with Dgraph and Modus

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# HyperNews

Knowledge graph + AI Agent analysis of news using multi modal GraphRAG approach with Dgraph and Modus.

![hyper-news graph data model](https://raw.githubusercontent.com/johnymontana/hyper-news/main/img/graph-model.png)

## Frontend Interface

The HyperNews frontend provides two main interfaces for exploring and analyzing news content:

<table>
  
  <tr>
    
    <td width="50%">
      
      <img src="img/hypernews-home.png" alt="HyperNews Home Interface" width="100%">
      
      <p align="center"><em>Article browsing interface with latest news</em></p>
    </td>
    
    <td width="50%">
      
      <img src="img/hypernews-chat-1.png" alt="HyperNews Chat Interface" width="100%">
      
      <p align="center"><em>AI chat interface for interactive news analysis</em></p>
    </td>
  </tr>
</table>

### Home Page (Article List)

- [Home Page](https://hyper-news-git-main-hypermode.vercel.app/)

The main interface displays a curated list of the latest articles from your knowledge graph. Each article card shows:

- Article title and abstract
- Direct links to read the full article
- Quick access to discuss the article with the AI assistant
- Metadata including article ID for reference

### Chat Interface (/chat)

- [Chat Interface](https://hyper-news-git-main-hypermode.vercel.app/chat)

An interactive AI-powered chat interface powered by a [Modus Agent](https://docs.hypermode.com/modus/agents) that allows you to:

- **Search for specific articles**: "Find articles about climate change"
- **Analyze trends and topics**: "What are the trending topics this week?"
- **Get article summaries**: "Summarize the article about money laundering"
- **Location-based queries**: "Show me news from Cambodia"
- **Organization analysis**: "Find articles mentioning Tesla"
- **Ask follow-up questions**: Have natural conversations about the news content

The AI assistant has access to the full knowledge graph and can perform vector similarity searches, topic analysis, and provide detailed insights about the interconnected news data.

## Architecture

- Multi-modal GraphRAG approach
- Dgraph knowledge graph for structured data storage
- [Modus runtime](https://docs.hypermode.com/modus/overview) for embeddings, vector similarity search, and AI agents
- [Modus Agent](https://docs.hypermode.com/modus/agents) powering the interactive chat interface
- Next.js frontend for chat interface and graph/map visualization
- Vector embeddings for semantic search capabilities

## Create Your Hypermode Graph

1. Navigate to [Hypermode](https://hypermode.com) and sign up for a free account
2. Create a new graph

![create new graph](https://raw.githubusercontent.com/johnymontana/hyper-news/main/img/hypermode-1.png)

3. Copy the `dgraph://` connection string, you'll use this to connect to your Hypermode Graph instance

![dgraph connection string](https://raw.githubusercontent.com/johnymontana/hyper-news/main/img/hypermode-2.png)

4. Navigate to ratel.hypermode.com and connect to your Hypermode Graph instance using the `dgraph://` connection string

![connect to graph](https://raw.githubusercontent.com/johnymontana/hyper-news/main/img/hypermode-3.png)

5. Update the graph schema

![update graph schema](https://raw.githubusercontent.com/johnymontana/hyper-news/main/img/ratel-update-schema.png)

Select "Schema" from Ratel's left navigation, then select "Bulk Edit" and copy and paste the following graph schema to replace the default schema, then select "Apply

<Summary>Copy this DQL schema to update your graph schema</Summary>

```dql
<Article.abstract>: string @index(term) .
<Article.embedding>: float32vector @index(hnsw(metric:"euclidean")) .
<Article.geo>: [uid] @reverse .
<Article.org>: [uid] .
<Article.person>: [uid] .
<Article.published>: datetime .
<Article.title>: default .
<Article.topic>: [uid] @reverse .
<Article.uri>: default .
<Article.url>: default .
<Author.article>: [uid] @reverse .
<Author.name>: default .
<Geo.location>: geo @index(geo) .
<Geo.name>: default .
<Image.article>: [uid] .
<Image.caption>: default .
<Image.url>: default .
<Organization.name>: default .
<Person.name>: default .
<Topic.name>: string @index(fulltext) .
<dgraph.drop.op>: string .
<dgraph.graphql.p_query>: string @index(sha256) .
<dgraph.graphql.schema>: string .
<dgraph.graphql.xid>: string @index(exact) @upsert .
type <dgraph.graphql> {
	dgraph.graphql.schema
	dgraph.graphql.xid
}
type <dgraph.graphql.persisted_query> {
	dgraph.graphql.p_query
}
```

</details>

6. Import the sample data into your graph

Load RDF data into your graph, navigate to the [Ratel](https://ratel.hypermode.com) interface and connect to your graph using the Dgraph connection string. Then run the following mutation in Ratel (be sure to select the Mutate tab):

<details>

<summary>Copy this DQL mutation to load sample data</summary>

```dql
{
  set {
    _:89285c4b-ab8b-424c-9563-3236d425c2c8 <dgraph.type> "Article" .
_:89285c4b-ab8b-424c-9563-3236d425c2c8 <Article.title> "The Scammer's Manual: How to Launder Money and Get Away With It" .
_:89285c4b-ab8b-424c-9563-3236d425c2c8 <Article.abstract> "Documents and insiders reveal how one of the world's major money laundering networks operates." .
_:89285c4b-ab8b-424c-9563-3236d425c2c8 <Article.uri> "nyt://article/6ff00f2a-405a-5b74-99e6-f98f9a409884" .
_:89285c4b-ab8b-424c-9563-3236d425c2c8 <Article.url> "https://www.nytimes.com/2025/03/23/world/asia/cambodia-money-laundering-huione.html" .
_:89285c4b-ab8b-424c-9563-3236d425c2c8 <Article.published> "2025-03-23"^^<xs:dateTime> .
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_:bd5ff24a-4ec2-4066-9652-5171f57ef771 <dgraph.type> "Author" .
_:bd5ff24a-4ec2-4066-9652-5171f57ef771 <Author.name> "Selam Gebrekidan" .
_:bd5ff24a-4ec2-4066-9652-5171f57ef771 <Author.article> _:89285c4b-ab8b-424c-9563-3236d425c2c8 .
_:e2476b0a-133c-4685-a8d8-a1b98236c346 <dgraph.type> "Author" .
_:e2476b0a-133c-4685-a8d8-a1b98236c346 <Author.name> "Joy Dong" .
_:e2476b0a-133c-4685-a8d8-a1b98236c346 <Author.article> _:89285c4b-ab8b-424c-9563-3236d425c2c8 .
_:824a5abb-4454-4115-a940-7dee8fa0fc60 <dgraph.type> "Author" .
_:824a5abb-4454-4115-a940-7dee8fa0fc60 <Author.name> "Chang W. Lee" .
_:824a5abb-4454-4115-a940-7dee8fa0fc60 <Author.article> _:89285c4b-ab8b-424c-9563-3236d425c2c8 .
_:e2cdac1e-7a47-4cd8-8fd9-897bd20f1c80 <dgraph.type> "Author" .
_:e2cdac1e-7a47-4cd8-8fd9-897bd20f1c80 <Author.name> "Weiyi Cai" .
_:e2cdac1e-7a47-4cd8-8fd9-897bd20f1c80 <Author.article> _:89285c4b-ab8b-424c-9563-3236d425c2c8 .
_:11e2c957-ab09-47cb-9754-150657c615ba <dgraph.type> "Topic" .
_:11e2c957-ab09-47cb-9754-150657c615ba <Topic.name> "Frauds and Swindling" .
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_:Article_100000010064414 <Article.title> "It’s Trump vs. the Courts, and It Won’t End Well for Trump" .
_:Article_100000010064414 <Article.abstract> "The judiciary will never surrender to the president its constitutional role to interpret the Constitution." .
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_:Article_100000009988576 <Article.title> "The Scammer’s Manual: How to Launder Money and Get Away With It" .
_:Article_100000009988576 <Article.abstract> "Documents and insiders reveal how one of the world’s major money laundering networks operates." .
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_:Article_100000009988576 <Article.uri> "nyt://article/6ff00f2a-405a-5b74-99e6-f98f9a409884" .
_:Article_100000009988576 <Article.url> "https://www.nytimes.com/2025/03/23/world/asia/cambodia-money-laundering-huione.html" .
_:Article_100000009988576 <Article.published> "2025-03-23"^^<xs:dateTime> .
_:Author_SelamGebrekidan <dgraph.type> "Author" .
_:Author_SelamGebrekidan <Author.name> "Selam Gebrekidan" .
_:Author_SelamGebrekidan <Author.article> _:Article_100000009988576 .
_:Author_JoyDong <dgraph.type> "Author" .
_:Author_JoyDong <Author.name> "Joy Dong" .
_:Author_JoyDong <Author.article> _:Article_100000009988576 .
_:Author_ChangWLee <dgraph.type> "Author" .
_:Author_ChangWLee <Author.name> "Chang W. Lee" .
_:Author_ChangWLee <Author.article> _:Article_100000009988576 .
_:Author_WeiyiCai <dgraph.type> "Author" .
_:Author_WeiyiCai <Author.name> "Weiyi Cai" .
_:Author_WeiyiCai <Author.article> _:Article_100000009988576 .
_:Topic_FraudsandSwindling <dgraph.type> "Topic" .
_:Topic_FraudsandSwindling <Topic.name> "Frauds and Swindling" .
_:Article_100000009988576 <Article.topic> _:Topic_FraudsandSwindling .
_:Topic_MoneyLaundering <dgraph.type> "Topic" .
_:Topic_MoneyLaundering <Topic.name> "Money Laundering" .
_:Article_100000009988576 <Article.topic> _:Topic_MoneyLaundering .
_:Topic_BankingandFinancialInstitutions <dgraph.type> "Topic" .
_:Topic_BankingandFinancialInstitutions <Topic.name> "Banking and Financial Institutions" .
_:Article_100000009988576 <Article.topic> _:Topic_BankingandFinancialInstitutions .
_:Topic_RobberiesandThefts <dgraph.type> "Topic" .
_:Topic_RobberiesandThefts <Topic.name> "Robberies and Thefts" .
_:Article_100000009988576 <Article.topic> _:Topic_RobberiesandThefts .
_:Topic_VirtualCurrency <dgraph.type> "Topic" .
_:Topic_VirtualCurrency <Topic.name> "Virtual Currency" .
_:Article_100000009988576 <Article.topic> _:Topic_VirtualCurrency .
_:Topic_ComputersandtheInternet <dgraph.type> "Topic" .
_:Topic_ComputersandtheInternet <Topic.name> "Computers and the Internet" .
_:Article_100000009988576 <Article.topic> _:Topic_ComputersandtheInternet .
_:Topic_audioneutralimmersive <dgraph.type> "Topic" .
_:Topic_audioneutralimmersive <Topic.name> "audio-neutral-immersive" .
_:Article_100000009988576 <Article.topic> _:Topic_audioneutralimmersive .
_:Topic_audioneutralsuspenseful <dgraph.type> "Topic" .
_:Topic_audioneutralsuspenseful <Topic.name> "audio-neutral-suspenseful" .
_:Article_100000009988576 <Article.topic> _:Topic_audioneutralsuspenseful .
_:Organization_HuioneGroup <dgraph.type> "Organization" .
_:Organization_HuioneGroup <Organization.name> "Huione Group" .
_:Article_100000009988576 <Article.org> _:Organization_HuioneGroup .
_:Organization_TetherOperationsLtd <dgraph.type> "Organization" .
_:Organization_TetherOperationsLtd <Organization.name> "Tether Operations Ltd" .
_:Article_100000009988576 <Article.org> _:Organization_TetherOperationsLtd .
_:Organization_TelegramLLC <dgraph.type> "Organization" .
_:Organization_TelegramLLC <Organization.name> "Telegram LLC" .
_:Article_100000009988576 <Article.org> _:Organization_TelegramLLC .
_:Geo_PhnomPenhCambodia <dgraph.type> "Geo" .
_:Geo_PhnomPenhCambodia <Geo.name> "Phnom Penh (Cambodia)" .
_:Geo_PhnomPenhCambodia <Geo.location> "{'type': 'Point', 'coordinates': [104.929, 11.549]}"^^<geo:geojson> .
_:Article_100000009988576 <Article.geo> _:Geo_PhnomPenhCambodia .
_:Geo_Cambodia <dgraph.type> "Geo" .
_:Geo_Cambodia <Geo.name> "Cambodia" .
_:Geo_Cambodia <Geo.location> "{'type': 'Point', 'coordinates': [104.9254, 11.5633]}"^^<geo:geojson> .
_:Article_100000009988576 <Article.geo> _:Geo_Cambodia .
_:caa44a94-9490-496b-be29-cc0e8e8ddaeb <dgraph.type> "Image" .
_:caa44a94-9490-496b-be29-cc0e8e8ddaeb <Image.caption> "Huione is a constellation of affiliates. The headquarters of one of its companies, Huione Pay, is in Phnom Penh, Cambodia." .
_:caa44a94-9490-496b-be29-cc0e8e8ddaeb <Image.url> "https://static01.nyt.com/images/2025/03/10/multimedia/00int-moneylaundering-03-hpgl/00int-moneylaundering-03-hpgl-thumbStandard.jpg" .
_:caa44a94-9490-496b-be29-cc0e8e8ddaeb <Image.article> _:Article_100000009988576 .
_:Article_100000010036616 <dgraph.type> "Article" .
_:Article_100000010036616 <Article.title> "Why Dads Take Their Gay Sons to Hooters" .
_:Article_100000010036616 <Article.abstract> "Many fathers and grandfathers take their gay sons to the bar. It’s become a place of refuge — and how that happened is a curious story." .
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_:Article_100000010036616 <Article.uri> "nyt://article/70c88a70-e850-57ce-b62b-b5ccd5c7c939" .
_:Article_100000010036616 <Article.url> "https://www.nytimes.com/2025/03/23/opinion/hooters-gay-family.html" .
_:Article_100000010036616 <Article.published> "2025-03-23"^^<xs:dateTime> .
_:Author_PeterRothpletz <dgraph.type> "Author" .
_:Author_PeterRothpletz <Author.name> "Peter Rothpletz" .
_:Author_PeterRothpletz <Author.article> _:Article_100000010036616 .
_:Topic_HomosexualityandBisexuality <dgraph.type> "Topic" .
_:Topic_HomosexualityandBisexuality <Topic.name> "Homosexuality and Bisexuality" .
_:Article_100000010036616 <Article.topic> _:Topic_HomosexualityandBisexuality .
_:Topic_MenandBoys <dgraph.type> "Topic" .
_:Topic_MenandBoys <Topic.name> "Men and Boys" .
_:Article_100000010036616 <Article.topic> _:Topic_MenandBoys .
_:Topic_Minorities <dgraph.type> "Topic" .
_:Topic_Minorities <Topic.name> "Minorities" .
_:Article_100000010036616 <Article.topic> _:Topic_Minorities .
_:Topic_Grandparents <dgraph.type> "Topic" .
_:Topic_Grandparents <Topic.name> "Grandparents" .
_:Article_100000010036616 <Article.topic> _:Topic_Grandparents .
_:Topic_BarsandNightclubs <dgraph.type> "Topic" .
_:Topic_BarsandNightclubs <Topic.name> "Bars and Nightclubs" .
_:Article_100000010036616 <Article.topic> _:Topic_BarsandNightclubs .
_:Topic_Discrimination <dgraph.type> "Topic" .
_:Topic_Discrimination <Topic.name> "Discrimination" .
_:Article_100000010036616 <Article.topic> _:Topic_Discrimination .
_:Topic_WaitersandWaitresses <dgraph.type> "Topic" .
_:Topic_WaitersandWaitresses <Topic.name> "Waiters and Waitresses" .
_:Article_100000010036616 <Article.topic> _:Topic_WaitersandWaitresses .
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_:Topic_CustomerRelations <Topic.name> "Customer Relations" .
_:Article_100000010036616 <Article.topic> _:Topic_CustomerRelations .
_:Topic_Restaurants <dgraph.type> "Topic" .
_:Topic_Restaurants <Topic.name> "Restaurants" .
_:Article_100000010036616 <Article.topic> _:Topic_Restaurants .
_:Organization_Hooters <dgraph.type> "Organization" .
_:Organization_Hooters <Organization.name> "Hooters" .
_:Article_100000010036616 <Article.org> _:Organization_Hooters .
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_:0769f696-2e07-4fa9-9ee7-9992ec28ecb7 <Image.caption> "" .
_:0769f696-2e07-4fa9-9ee7-9992ec28ecb7 <Image.url> "https://static01.nyt.com/images/2025/03/23/opinion/23rothpletz-image/23rothpletz-image-thumbStandard.jpg" .
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_:Article_100000010065487 <dgraph.type> "Article" .
_:Article_100000010065487 <Article.title> "Keir Starmer on Putin, Trump and Europe’s Challenge: ‘We’ve Known This Moment Was Coming’" .
_:Article_100000010065487 <Article.abstract> "The British prime minister said in a series of conversations that the tectonic shifts in America’s relationship with Europe and Russia had to be a ‘galvanizing moment.’" .
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  }
}
```

</details>

![import sample data](https://raw.githubusercontent.com/johnymontana/hyper-news/main/img/hypermode-4.png)

Or using curl to upload the `data/articles/nyt_example_article.rdf` file:

```bash
curl -v -X POST https://<YOUR_HYPERMODE_GRAPH>.hypermode.host/dgraph/mutate \
    --header "Authorization: Bearer <YOUR_HYPERMODE_TOKEN>" \
    --header "Content-Type: application/rdf" \
    --data-binary "@data/articles/nyt_articles_versions.rdf"
```

## Modus Agent Architecture

The chat interface is powered by a [Modus Agent](https://docs.hypermode.com/modus/agents) that provides sophisticated news analysis capabilities. The agent implements several specialized tools for news exploration:

```go
// HyperNewsChatAgent implements the core chat functionality
type HyperNewsChatAgent struct {
    agents.AgentBase
    conversationId string
    items          []interface{}
    chatHistory    []openai.RequestMessage
    lastActivity   time.Time
}

// Available news analysis tools
func (c *HyperNewsChatAgent) getNewsTools() []openai.Tool {
    return []openai.Tool{
        openai.NewToolForFunction("search_articles", "Search for news articles in the HyperNews database").
            WithParameter("query", "string", "Search query for articles").
            WithParameter("limit", "number", "Maximum number of articles to return (default: 5)"),

openai.NewToolForFunction("analyze_topics", "Analyze trending topics in recent articles").
            WithParameter("days", "number", "Number of days to look back (default: 7)").
            WithParameter("limit", "number", "Maximum number of topics to return (default: 10)"),

openai.NewToolForFunction("get_articles_by_location", "Find articles related to a specific location").
            WithParameter("location", "string", "Geographic location to search for").
            WithParameter("limit", "number", "Maximum number of articles to return (default: 5)"),

openai.NewToolForFunction("get_articles_by_organization", "Find articles mentioning specific organizations").
            WithParameter("organization", "string", "Organization name to search for").
            WithParameter("limit", "number", "Maximum number of articles to return (default: 5)"),

openai.NewToolForFunction("summarize_article", "Generate a summary of an article").
            WithParameter("article_id", "string", "The ID of the article to summarize"),
    }
}
```

The agent integrates with the Dgraph knowledge graph through [Modus Functions](https://docs.hypermode.com/modus/functions) to provide real-time analysis and semantic search capabilities. Each tool executes DQL (Dgraph Query Language) queries to extract relevant information from the interconnected news data.

## Data

This project uses data from the [New York Times developer API.](https://developer.nytimes.com/docs/most-popular-product/1/overview) Sample data is provided in the `data/articles/nyt_example_article.rdf` file.

To Register for a free NYTimes developer account, create an API key, then fetch article data:

```bash
wget --directory-prefix=data/articles/nyt/article_versions -O data/articles/nyt/article_versions/data.json https://api.nytimes.com/svc/mostpopular/v2/viewed/1.json?api-key=yourkey
```

Then use the included Python script to convert article JSON data to RDF N-Quad format to import into Dgraph

First create a venv in the root of the project:

```bash
python3 -m venv venv
```

Then you can enter the venv and install the requirements:

Enter venv:

```bash
source venv/bin/activate
```

Then run the script to convert the JSON data to RDF:

```bash
cd ./data/articles && python3 article_json_to_rdf.py
```

This will output `nyt_articles_versions.rdf` in the `data/articles/` directory.

## Local Dgraph (Optional)

Launch a local Dgraph cluster using Docker or create a free hosted [Hypermode Graph.](https://hypermode.com)

```bash
cd dgraph
docker-compose up
```

Then to open a shell in the Dgraph Alpha container:

```bash
docker exec -it news_graph_alpha /bin/bash
```

To load the RDF generated in the previous step:

```bash
dgraph live -f /data/articles/nyt_articles_versions.rdf --zero zero:5080
```

Open [ratel.hypermode.com](https://ratel.hypermode.com), connect to `http://localhost:8080` then query your graph:

```dql
{
  articles(func:type(Article),first:100) {
	Article.title
    Article.uri
    Article.url
    Article.published
    Article.abstract
    Article.topic {
      Topic.name
    }
    Article.org {
      Organization.name
    }
    Article.geo {
      Geo.name
    }
  }
}
```

![querying the graph using Ratel](https://raw.githubusercontent.com/johnymontana/hyper-news/main/img/ratel-query.png)

### Update Dgraph schema

```bash
curl -X POST localhost:8080/alter --data-binary '@schema.dql'
```

## Modus Runtime

Update the modus `.env` file with your Dgraph connection string. See `modus/.env.example` for an example.

Install [Modus CLI](https://docs.hypermode.com/modus/overview):

```bash
npm i -g @hypermode/modus-cli
```

Start the Modus runtime:

```bash
modus dev
```

### Embeddings

![chunking the articles](https://raw.githubusercontent.com/johnymontana/hyper-news/main/img/chunks.png)

## Vector Similarity Search

```dql
 query vector_search($embedding: string, $limit: int) {
          articles(func: similar_to(Article.embedding, $limit, $embedding)) {
            uid
            Article.title
            Article.abstract
            score
          }
        }
```

---

<p align="center" style="margin-top: 4em; margin-bottom: 4em;">
  
  <strong>Built with <a href="https://hypermode.com">Hypermode</a></strong>
</p>

<p align="center">
  
  <img src="img/banner.png" alt="Hypermode - The AI Development Platform" width="100%">
</p>

hyper-news

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