chore: 更新graphrag集成文档

src/demo/README.md

@@ -1,11 +1,18 @@
 ---
-title: Features demo
+title: Demo demonstration
 index: false
 icon: laptop-code
 category:
-  - Guide
+  - User Guide
 ---
 
-to be supplemented
+You can [view detailed usage instructions](../guide/README.md) here.
 
-You can [view instructions for use here](../guide/README.md).
+## graphrag integration
+
+graphrag is a structured, layered Retrieval-Augmented Generation (RAG) method developed by Microsoft.
+
+- [Github](https://github.com/microsoft/graphrag)
+- [How to integrate](graphrag.md)
+
+If you have good integration methods or ideas, feel free to submit a PR!

src/demo/graphrag.md

@@ -0,0 +1,101 @@
+---
+title: Integration of graphrag
+category:
+  - Guide
+icon: diagram-project
+---
+
+## Install and configure the corresponding libraries
+
+To avoid unnecessary trouble, please use a virtual environment:
+- [miniconda3](https://docs.anaconda.com/miniconda/), the minimal installation version of conda, of course, you can also directly use Anaconda.
+- [uv](https://github.com/astral-sh/uv), a very fast package installer and resolver built with Rust.
+
+::: code-tabs#python
+
+@tab conda
+
+```bash
+conda create -n rag python=3.12
+conda activate rag
+pip install --upgrade pdfdeal graphrag
+```
+
+@tab uv
+
+```bash
+uv venv
+source .venv/bin/activate # For Linux
+source .venv/Scripts/activate # For Windows
+uv pip install --upgrade graphrag pdfdeal
+```
+
+:::
+
+## Step1: Convert PDF
+
+Create two folders to store the PDFs before processing and the txt files after processing:
+
+```zsh
+mkdir ./pdf
+mkdir -p ./ragtest/input
+```
+
+Put the PDFs to be processed into the pdf folder, here using graphrag's [own paper](https://arxiv.org/pdf/2404.16130) and it's [references](https://arxiv.org/pdf/2306.04136).
+
+Go to [Doc2X](https://doc2x.com/), click on identity information, and copy your identity token as a key.
+
+Use `pdfdeal`'s CLI tool `doc2x` for batch processing, please add the long flag `--graphrag` to enable special adaptation for graphrag:
+
+```zsh
+doc2x -k "Your Key Here" -o ./ragtest/input -p --graphrag ./pdf
+```
+
+![](../images/demo/graphrag/doc2x.png)
+
+Wait for it to complete processing:
+
+![](../images/demo/graphrag/tree.png)
+
+## Step2: Build knowledge graph
+
+```zsh
+python -m graphrag.index --init --root ./ragtest
+```
+
+Modify `settings.yaml` and `.env` files, then build:
+
+```zsh
+python -m graphrag.index --root ./ragtest
+```
+
+![](../images/demo/graphrag/build.png)
+
+After building is complete, you can start asking questions to graphrag using different answering strategies:
+
+::: code-tabs
+
+@tab global
+
+```bash
+python -m graphrag.query \
+--root ./ragtest \
+--method global \
+"Q"
+```
+
+@tab local
+
+```bash
+python -m graphrag.query \
+--root ./ragtest \
+--method local \
+"Q"
+```
+
+:::
+
+## See Also
+
+- [graphrag official website](https://microsoft.github.io/graphrag/)
+- [将PDF知识图谱化：graphrag+Doc2X+DeepSeek](https://blog.menghuan1918.com/posts/graphrag_doc2x_deepseek.html)