Update README
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@@ -164,6 +164,10 @@ class QueryParam:
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"""本地检索中实体描述的最大令牌分配。"""
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ids: list[str] | None = None # 仅支持PG向量数据库
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"""用于过滤RAG的ID列表。"""
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model_func: Callable[..., object] | None = None
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"""查询使用的LLM模型函数。如果提供了此选项,它将代替LightRAG全局模型函数。
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这允许为不同的查询模式使用不同的模型。
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"""
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...
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```
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@@ -764,7 +768,7 @@ 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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-- 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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@@ -194,6 +194,11 @@ class QueryParam:
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"""Maximum number of tokens allocated for entity descriptions in local retrieval."""
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ids: list[str] | None = None # ONLY SUPPORTED FOR PG VECTOR DBs
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"""List of ids to filter the RAG."""
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model_func: Callable[..., object] | None = None
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"""Optional override for the LLM model function to use for this specific query.
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If provided, this will be used instead of the global model function.
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This allows using different models for different query modes.
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"""
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...
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```
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@@ -761,7 +766,7 @@ 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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-- 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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