docs: adjust graphrag doc

Signed-off-by: gitworkflows <[email protected]>

docs/docs/cookbook/rag/graph_rag_app_develop.md

@@ -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. GPT-DB 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 gptdb.model.proxy.llms.chatgpt import OpenAILLMClient
@@ -154,14 +154,11 @@ Then you can retrieve the knowledge from the knowledge graph, which is the same
 ```python
 import os
 
-import pytest
 
 from gptdb.configs.model_config import ROOT_PATH
 from gptdb.core import Chunk, HumanPromptTemplate, ModelMessage, ModelRequest
-from gptdb.model.proxy.llms.chatgpt import OpenAILLMClient
 from gptdb.rag import ChunkParameters
 from gptdb.rag.assembler import EmbeddingAssembler
-from gptdb.rag.embedding import DefaultEmbeddingFactory
 from gptdb.rag.knowledge import KnowledgeFactory
 from gptdb.rag.retriever import RetrieverStrategy