A macOS app that transforms RSS news feeds into an interactive knowledge graph, enabling semantic search and multi-hop reasoning across your news sources.
NewsComb retrieves articles from your RSS feeds and uses LLM-powered extraction to build a semantic hypergraph — a knowledge graph where entities (companies, people, products, technologies) are connected by relationships extracted from the news.
- RSS Feed Aggregation: Subscribe to multiple tech news feeds and automatically fetch new articles
- Knowledge Graph Construction: Extract entities and relationships using configurable LLM prompts
- Vector Search with sqlite-vec: Embeddings are stored locally using sqlite-vec, enabling fast cosine similarity search without external dependencies
- Multi-hop Reasoning Paths: Answer questions by traversing the hypergraph to find connections between concepts, even when they aren't directly linked
When you ask a question, NewsComb doesn't just search for keywords — it finds reasoning paths through the knowledge graph. For example, asking about AI chip competition might reveal paths like:
NVIDIA → competes with → AMD → partners with → Microsoft → invests in → OpenAI
These multi-hop connections surface relationships that wouldn't appear in a simple text search.
The "Dive Deeper" feature uses a multi-agent workflow to synthesize insights with academic-style citations and generate hypotheses for further investigation.
- Download the latest DMG from Releases
- Open the DMG and drag
NewsCombApp.appto your Applications folder - Eject the DMG
Since the app is not signed with an Apple Developer certificate, macOS will block it on first launch.
To open the app:
- Try to open
NewsCombApp.app— macOS will show a warning that it cannot verify the developer - Open System Settings → Privacy & Security
- Scroll down to find the message "NewsCombApp.app" was blocked to protect your Mac
- Click Open Anyway
- macOS will ask you to confirm twice more — click Open each time
After this one-time setup, the app will open normally.
NewsComb uses local embeddings for the knowledge graph. You need to install Ollama and download the nomic-embed-text model:
- Install Ollama
- Open Terminal and run:
ollama pull nomic-embed-text:v1.5
NewsComb uses two separate LLM configurations:
- Knowledge Extraction LLM — Used to extract entities and relationships from articles when building the knowledge graph
- Analysis LLM — Used for answering questions ("Ask Your News") and deep analysis ("Dive Deeper")
Both can be configured independently in Settings, allowing you to use different models for each task.
- Create an account at OpenRouter
- Generate an API key
- In NewsComb Settings:
- Knowledge Extraction: Select OpenRouter and use
meta-llama/llama-4-maverick - Analysis: Use the same model or a stronger one (e.g.,
openai/gpt-5.2for more nuanced reasoning)
- Knowledge Extraction: Select OpenRouter and use
The Llama 4 Maverick model provides an excellent balance of speed and quality for entity extraction. For analysis, you may want a more capable model if you need deeper reasoning, but Maverick works well for most use cases.
You can run LLMs locally with Ollama, but this will be significantly slower:
ollama pull qwen2.5:14bThen select Ollama as the provider in Settings and use qwen2.5:14b as the model for both extraction and analysis.
This project is inspired by and builds upon the hypergraph reasoning approach described in:
HyperGraphRAG: Hypergraph-Driven Reasoning and Affordable LLM-Based Knowledge Construction
Buehler, M.J. (2025). A novel approach using hypergraphs for knowledge organization and reasoning, enabling multi-hop traversal and affordable construction via small language models.
The original Python implementation is available at: lamm-mit/HyperGraphReasoning
- GRDBCustomSQLiteBuild — Invaluable guide for integrating sqlite-vec with GRDB in Swift, enabling local vector search without external services
MIT License — see LICENSE for details.