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docs: adjust graphrag doc (#2027)

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Florian 2024-09-18 20:10:18 +08:00 committed by GitHub
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docs/docs/cookbook/rag/graph_rag_app_develop.md
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@ -21,7 +21,7 @@ Visit github repository of TuGraph to view [Quick Start](https://tugraph-db.read
```
docker pull tugraph/tugraph-runtime-centos7:latest
docker run -d -p 7070:7070 -p 7687:7687 -p 9090:9090 --name tugraph_demo reg.docker.alibaba-inc.com/fma/tugraph-runtime-centos7:latest lgraph_server -d run --enable_plugin true
docker run -d -p 7070:7070 -p 7687:7687 -p 9090:9090 --name tugraph_demo tugraph/tugraph-runtime-centos7:latest lgraph_server -d run --enable_plugin true
```
The default port for the bolt protocol is `7687`.
@ -120,7 +120,7 @@ GRAPH_COMMUNITY_SUMMARY_ENABLED=True
When using a graph database as the underlying knowledge storage platform, it is necessary to build a knowledge graph to facilitate the archiving and retrieval of documents. DB-GPT leverages the capabilities of large language models to implement an integrated knowledge graph, while still maintaining the flexibility to freely connect to other knowledge graph systems and graph database systems.
To maintain compatibility with existing conventional RAG frameworks, we continue to access the knowledge graph through the `VectorStoreConnector` interface. Simply set the `vector_store_type` to `KnowledgeGraph` to enable this connection.
We created a knowledge graph with graph community summaries based on `CommunitySummaryKnowledgeGraph`.
```python
from dbgpt.model.proxy.llms.chatgpt import OpenAILLMClient
@ -154,14 +154,10 @@ Then you can retrieve the knowledge from the knowledge graph, which is the same
```python
import os
import pytest
from dbgpt.configs.model_config import ROOT_PATH
from dbgpt.core import Chunk, HumanPromptTemplate, ModelMessage, ModelRequest
from dbgpt.model.proxy.llms.chatgpt import OpenAILLMClient
from dbgpt.rag import ChunkParameters
from dbgpt.rag.assembler import EmbeddingAssembler
from dbgpt.rag.embedding import DefaultEmbeddingFactory
from dbgpt.rag.knowledge import KnowledgeFactory
from dbgpt.rag.retriever import RetrieverStrategy