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Update README.md

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  1. README-zh.md +8 -8
  2. README.md +5 -5
README-zh.md CHANGED
@@ -532,20 +532,20 @@ response = rag.query(
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  )
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  ```
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- ### 自定义用户提示词
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- 自定义用户提示词不影响查询内容,仅仅用于向LLM指示如何处理查询结果。以下是使用方法:
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  ```python
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- # 创建查询参数
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  query_param = QueryParam(
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- mode = "hybrid", # 或其他模式:"local"、"global"、"hybrid"、"mix"和"naive"
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- user_prompt = "Please create the diagram using the Mermaid syntax"
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  )
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- # 查询和处理
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  response_default = rag.query(
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- "Please draw a character relationship diagram for Scrooge",
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  param=query_param
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  )
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  print(response_default)
@@ -755,7 +755,7 @@ rag = LightRAG(
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  create INDEX CONCURRENTLY entity_idx_node_id ON dickens."Entity" (ag_catalog.agtype_access_operator(properties, '"node_id"'::agtype));
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  CREATE INDEX CONCURRENTLY entity_node_id_gin_idx ON dickens."Entity" using gin(properties);
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  ALTER TABLE dickens."DIRECTED" CLUSTER ON directed_sid_idx;
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-
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  -- 如有必要可以删除
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  drop INDEX entity_p_idx;
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  drop INDEX vertex_p_idx;
 
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  )
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  ```
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+ ### 用户提示词 vs. 查询内容
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+ 当使用LightRAG查询内容的时候,不要把内容查询和与查询结果无关的输出加工写在一起。因为把两者混在一起会严重影响查询的效果。Query Param中的`user_prompt`就是为解决这一问题而设计的。`user_prompt`中的内容不参与RAG中的查询过程,它仅会在获得查询结果之后,与查询结果一起送给LLM,指导LLM如何处理查询结果。以下是使用方法:
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  ```python
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+ # Create query parameters
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  query_param = QueryParam(
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+ mode = "hybrid", # Other modes:local, global, hybrid, mix, naive
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+ user_prompt = "如需画图使用mermaid格式,节点名称用英文或拼音,显示名称用中文",
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  )
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+ # Query and process
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  response_default = rag.query(
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+ "请画出 Scrooge 的人物关系图谱",
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  param=query_param
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  )
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  print(response_default)
 
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  create INDEX CONCURRENTLY entity_idx_node_id ON dickens."Entity" (ag_catalog.agtype_access_operator(properties, '"node_id"'::agtype));
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  CREATE INDEX CONCURRENTLY entity_node_id_gin_idx ON dickens."Entity" using gin(properties);
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  ALTER TABLE dickens."DIRECTED" CLUSTER ON directed_sid_idx;
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+
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  -- 如有必要可以删除
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  drop INDEX entity_p_idx;
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  drop INDEX vertex_p_idx;
README.md CHANGED
@@ -570,15 +570,15 @@ response = rag.query(
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  </details>
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- ### Custom User Prompt Support
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- Custom user prompts do not affect the query content; they are only used to instruct the LLM on how to handle the query results. Here's how to use it:
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  ```python
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  # Create query parameters
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  query_param = QueryParam(
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- mode = "hybrid", # 或其他模式:"local"、"global"、"hybrid"、"mix"和"naive"
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- user_prompt = "Please create the diagram using the Mermaid syntax"
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  )
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  # Query and process
@@ -759,7 +759,7 @@ For production level scenarios you will most likely want to leverage an enterpri
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  create INDEX CONCURRENTLY entity_idx_node_id ON dickens."Entity" (ag_catalog.agtype_access_operator(properties, '"node_id"'::agtype));
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  CREATE INDEX CONCURRENTLY entity_node_id_gin_idx ON dickens."Entity" using gin(properties);
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  ALTER TABLE dickens."DIRECTED" CLUSTER ON directed_sid_idx;
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-
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  -- drop if necessary
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  drop INDEX entity_p_idx;
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  drop INDEX vertex_p_idx;
 
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  </details>
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+ ### User Prompt vs. Query
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+ When using LightRAG for content queries, avoid combining the search process with unrelated output processing, as this significantly impacts query effectiveness. The `user_prompt` parameter in Query Param is specifically designed to address this issue — it does not participate in the RAG retrieval phase, but rather guides the LLM on how to process the retrieved results after the query is completed. Here's how to use it:
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  ```python
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  # Create query parameters
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  query_param = QueryParam(
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+ mode = "hybrid", # Other modes:local, global, hybrid, mix, naive
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+ user_prompt = "For diagrams, use mermaid format with English/Pinyin node names and Chinese display labels",
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  )
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  # Query and process
 
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  create INDEX CONCURRENTLY entity_idx_node_id ON dickens."Entity" (ag_catalog.agtype_access_operator(properties, '"node_id"'::agtype));
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  CREATE INDEX CONCURRENTLY entity_node_id_gin_idx ON dickens."Entity" using gin(properties);
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  ALTER TABLE dickens."DIRECTED" CLUSTER ON directed_sid_idx;
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+
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  -- drop if necessary
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  drop INDEX entity_p_idx;
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  drop INDEX vertex_p_idx;