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Posted to commits@hugegraph.apache.org by ji...@apache.org on 2024/09/20 07:08:43 UTC
(incubator-hugegraph-ai) branch main updated: docs: enhance user friendly for README (#82)
This is an automated email from the ASF dual-hosted git repository.
jin pushed a commit to branch main
in repository https://gitbox.apache.org/repos/asf/incubator-hugegraph-ai.git
The following commit(s) were added to refs/heads/main by this push:
new 8ff1319 docs: enhance user friendly for README (#82)
8ff1319 is described below
commit 8ff13195662407fcc80dd3f6d9687090cb397875
Author: chenzihong <58...@users.noreply.github.com>
AuthorDate: Fri Sep 20 15:08:39 2024 +0800
docs: enhance user friendly for README (#82)
---------
Co-authored-by: imbajin <ji...@apache.org>
---
hugegraph-llm/README.md | 21 +++++++++++++--------
1 file changed, 13 insertions(+), 8 deletions(-)
diff --git a/hugegraph-llm/README.md b/hugegraph-llm/README.md
index c6cb192..04b766f 100644
--- a/hugegraph-llm/README.md
+++ b/hugegraph-llm/README.md
@@ -12,18 +12,18 @@ With this project, we aim to reduce the cost of using graph systems, and decreas
building knowledge graphs. This project will offer more applications and integration solutions for
graph systems and large language models.
1. Construct knowledge graph by LLM + HugeGraph
-2. Use natural language to operate graph databases (gremlin)
-3. Knowledge graph supplements answer context (RAG)
+2. Use natural language to operate graph databases (Gremlin/Cypher)
+3. Knowledge graph supplements answer context (GraphRAG)
## Environment Requirements
- python 3.9+
-- hugegraph-server 1.0+
+- hugegraph-server 1.2+
## Preparation
-1. Start the HugeGraph database, you can do it via Docker/[Binary packages](https://hugegraph.apache.org/docs/download/download/).
-Refer to [docker-link](https://hub.docker.com/r/hugegraph/hugegraph) & [deploy-doc](https://hugegraph.apache.org/docs/quickstart/hugegraph-server/#31-use-docker-container-convenient-for-testdev) for guidance
+1. Start the HugeGraph database, you can run it via [Docker](https://hub.docker.com/r/hugegraph/hugegraph)/[Binary Package](https://hugegraph.apache.org/docs/download/download/).
+Refer to detailed [doc](https://hugegraph.apache.org/docs/quickstart/hugegraph-server/#31-use-docker-container-convenient-for-testdev) for more guidance (PS: Graph visualization in step8)
2. Clone this project
```bash
git clone https://github.com/apache/incubator-hugegraph-ai.git
@@ -39,7 +39,7 @@ Refer to [docker-link](https://hub.docker.com/r/hugegraph/hugegraph) & [deploy-d
cd ./hugegraph-llm/src
```
-5. Start the gradio interactive demo of **Graph RAG**, you can start with the following command, and open http://127.0.0.1:8001 after starting
+5. Start the gradio interactive demo of **Graph RAG**, you can run with the following command, and open http://127.0.0.1:8001 after starting
```bash
python3 -m hugegraph_llm.demo.rag_demo.app
```
@@ -48,17 +48,22 @@ Refer to [docker-link](https://hub.docker.com/r/hugegraph/hugegraph) & [deploy-d
python3 -m hugegraph_llm.demo.rag_demo.app --host 127.0.0.1 --port 18001
```
-6. Or start the gradio interactive demo of **Text2Gremlin**, you can start with the following command, and open http://127.0.0.1:8002 after starting. You can also change the default host `0.0.0.0` and port `8002` as above. (🚧ing)
+6. Or start the gradio interactive demo of **Text2Gremlin**, you can run with the following command, and open http://127.0.0.1:8002 after starting. You can also change the default host `0.0.0.0` and port `8002` as above. (🚧ing)
```bash
python3 -m hugegraph_llm.demo.gremlin_generate_web_demo
```
-7. After starting the web demo, the config file `.env` will be automatically generated. You can modify its content on the web page. Or modify the file directly and restart the web application.
+7. After running the web demo, the config file `.env` will be automatically generated. You can modify its content on the web page. Or modify the file directly and restart the web application.
(Optional)To regenerate the config file, you can use `config.generate` with `-u` or `--update`.
```bash
python3 -m hugegraph_llm.config.generate --update
```
+
+8. (__Optional__) You could use
+[hugegraph-hubble](https://hugegraph.apache.org/docs/quickstart/hugegraph-hubble/#21-use-docker-convenient-for-testdev)
+to visit the graph data, could run it via [Docker/Docker-Compose](https://hub.docker.com/r/hugegraph/hubble)
+for guidance. (Hubble is a graph-analysis dashboard include data loading/schema management/graph traverser/display).
## Examples