https://github.com/raphaelsty/kgsearch
Query and visualize knowledge graphs
https://github.com/raphaelsty/kgsearch
3d-graph graph information-retrieval knowledge-graph visualization
Last synced: 7 months ago
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Query and visualize knowledge graphs
- Host: GitHub
- URL: https://github.com/raphaelsty/kgsearch
- Owner: raphaelsty
- License: mit
- Created: 2022-08-11T04:09:05.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2025-03-21T12:57:46.000Z (about 1 year ago)
- Last Synced: 2025-10-08T19:23:54.470Z (7 months ago)
- Topics: 3d-graph, graph, information-retrieval, knowledge-graph, visualization
- Language: Python
- Homepage:
- Size: 6.02 MB
- Stars: 59
- Watchers: 1
- Forks: 7
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
KGSearch
KGSearch is a minimalist tool for searching and viewing entities in a graph and is dedicated to a local environment. The application provides a Python client with three distinct terminal commands: `add, start, open`. The application default proposes to search through the knowledge graph [Countries](https://www.aaai.org/ocs/index.php/SSS/SSS15/paper/view/10257/10026). You can explore the borders we must cross to get from one country to another and see how small the 🌍 is.
## Installation
```sh
pip install git+https://github.com/raphaelsty/kgsearch
```
## ✅ Quick Start
The `start` command starts the API and opens the user interface:
```sh
kg start
```
## ⭐️ Query
KGSearch suggests performing multiple queries via the `;` separator.
The query `france;germany;china` will be divided into three subqueries `france`, `germany`, and `china` to visualize the interactions between the entities of our choice.
The `top K` field allows selecting the number of candidate entities retrieved by the search engine (1 by default).
The `neighbours` field selects the number of neighbors to be displayed (1 by default).
The `prune` field removes entities that have fewer than `prune` connections to other entities (1 by default).
## 🤖 Custom KG
We can add our graph to KGSearch via the command:
```sh
kg add -f data.csv
```
The graph must be saved in CSV format and structured as triples (head, relation, tail) with a comma separator and without column names. Here is an example of a compatible CSV file:
```sh
senegal,neighbor,gambia
senegal,neighbor,mauritania
senegal,neighbor,mali
senegal,neighbor,guinea-bissau
senegal,neighbor,guinea
```
We can also add custom metadata for each entity to be displayed in the user interface using `meta -f`:
```sh
kg meta -f metadata.json
```
where the `metadata.json` file has the label of the entity as a key and a set of characteristics:
```json
{
"senegal": {"url": "https://en.wikipedia.org/wiki/senegal"},
"gambia": {"url": "https://en.wikipedia.org/wiki/gambia"},
"mauritania": {"url": "https://en.wikipedia.org/wiki/gambia"},
"mali": {"url": "https://en.wikipedia.org/wiki/mali"},
}
```
## 📑 Notes
If you have already started the application, you can reopen a window with the open command:
```sh
kg open
```
The library [Cherche](https://github.com/raphaelsty/cherche) provides the entity search engine. KGSearch relies on a local flask API. The user interface is developed in React and uses the [3D Force-Directed Graph](https://github.com/vasturiano/3d-force-graph) library.