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Update sample code and README

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yangdx
2025-04-20 14:33:16 +08:00
parent 4ae5246a7e
commit 5f2cd871a8
3 changed files with 63 additions and 47 deletions
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README.md
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@@ -71,21 +71,6 @@
## Installation
### Install LightRAG Core
* Install from source (Recommend)
```bash
cd LightRAG
pip install -e .
```
* Install from PyPI
```bash
pip install lightrag-hku
```
### Install LightRAG Server
The LightRAG Server is designed to provide Web UI and API support. The Web UI facilitates document indexing, knowledge graph exploration, and a simple RAG query interface. LightRAG Server also provide an Ollama compatible interfaces, aiming to emulate LightRAG as an Ollama chat model. This allows AI chat bot, such as Open WebUI, to access LightRAG easily.
@@ -104,17 +89,40 @@ pip install "lightrag-hku[api]"
pip install -e ".[api]"
```
**For more information about LightRAG Server, please refer to [LightRAG Server](./lightrag/api/README.md).**
### Install LightRAG Core
## Quick Start for LightRAG core only
* [Video demo](https://www.youtube.com/watch?v=g21royNJ4fw) of running LightRAG locally.
* All the code can be found in the `examples`.
* Set OpenAI API key in environment if using OpenAI models: `export OPENAI_API_KEY="sk-...".`
* Download the demo text "A Christmas Carol by Charles Dickens":
* Install from source (Recommend)
```bash
cd LightRAG
pip install -e .
```
* Install from PyPI
```bash
pip install lightrag-hku
```
## Quick Start
### Quick Start for LightRAG Server
For more information about LightRAG Server, please refer to [LightRAG Server](./lightrag/api/README.md).
### Quick Start for LightRAG core
To get started with LightRAG core, refer to the sample codes available in the `examples` folder. Additionally, a [video demo](https://www.youtube.com/watch?v=g21royNJ4fw) demonstration is provided to guide you through the local setup process. If you already possess an OpenAI API key, you can run the demo right away:
```bash
### you should run the demo code with project folder
cd LightRAG
### provide your API-KEY for OpenAI
export OPENAI_API_KEY="sk-...your_opeai_key..."
### download the demo document of "A Christmas Carol" by Charles Dickens
curl https://raw.githubusercontent.com/gusye1234/nano-graphrag/main/tests/mock_data.txt > ./book.txt
### run the demo code
python examples/lightrag_openai_demo.py
```
## Query
@@ -836,7 +844,7 @@ For production level scenarios you will most likely want to leverage an enterpri
create INDEX CONCURRENTLY entity_idx_node_id ON dickens."Entity" (ag_catalog.agtype_access_operator(properties, '"node_id"'::agtype));
CREATE INDEX CONCURRENTLY entity_node_id_gin_idx ON dickens."Entity" using gin(properties);
ALTER TABLE dickens."DIRECTED" CLUSTER ON directed_sid_idx;
-- drop if necessary
drop INDEX entity_p_idx;
drop INDEX vertex_p_idx;