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1、首先使用uv新增一个Graphrag项目

uv init graphrag

2、切换进项目目录

cd graphrag

3、激活项目

source .venv/bin/activate

4、安装graphrag依赖

uv pip install graphrag

5、新增目录存在用于存放graphrag ,并且把微软的测试数据下载到目录下

 mkdir -p ./openl/inputcurl https://www.gutenberg.org/cache/epub/24022/pg24022 -o ./openl/input/book.txt

6、初始化项目

graphrag init --root ./openl

7、修改./openl 目录下的settings.yaml 和 .env 文件（只要一个key，改成自己即可），标红部分属于修改或者添加

models:default_chat_model:type: openai_chat # or azure_openai_chatapi_base: https://dashscope.aliyuncs.com/compatible-mode/v1# api_version: 2024-05-01-previewauth_type: api_key # or azure_managed_identityapi_key: ${GRAPHRAG_API_KEY} # set this in the generated .env file# audience: "https://cognitiveservices.azure.com/.default"# organization: <organization_id>encoding_model: cl100k_base  # 关键参数，适配阿里百炼encodingmodel: qwen-plus #修改成千问的市场模型# deployment_name: <azure_model_deployment_name># encoding_model: cl100k_base # automatically set by tiktoken if left undefinedmodel_supports_json: true # recommended if this is available for your model.concurrent_requests: 25 # max number of simultaneous LLM requests allowedasync_mode: threaded # or asyncioretry_strategy: nativemax_retries: -1                   # set to -1 for dynamic retry logic (most optimal setting based on server response)tokens_per_minute: 0              # set to 0 to disable rate limitingrequests_per_minute: 0            # set to 0 to disable rate limiting

embedding_model 配置修改

  default_embedding_model:type: openai_embedding # or azure_openai_embeddingapi_base: https://dashscope.aliyuncs.com/compatible-mode/v1# api_version: 2024-05-01-previewauth_type: api_key # or azure_managed_identityapi_key: ${GRAPHRAG_API_KEY}# audience: "https://cognitiveservices.azure.com/.default"# organization: <organization_id>encoding_model: cl100k_base  # 显式指定编码器model: text-embedding-v3     # 使用阿里云官方的嵌入模型名称# deployment_name: <azure_model_deployment_name># encoding_model: cl100k_base # automatically set by tiktoken if left undefinedmodel_supports_json: true # recommended if this is available for your model.concurrent_requests: 25 # max number of simultaneous LLM requests allowedasync_mode: threaded # or asyncioretry_strategy: nativemax_retries: -1                   # set to -1 for dynamic retry logic (most optimal setting based on server response)tokens_per_minute: 0              # set to 0 to disable rate limitingrequests_per_minute: 0            # set to 0 to disable rate limiting

就修改这个地方，执行索引，代码就能运行起来

graphrag index --root ./openl

最后结果是失败的