Update README
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@@ -127,9 +127,9 @@ python examples/lightrag_openai_demo.py
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For a streaming response implementation example, please see `examples/lightrag_openai_compatible_demo.py`. Prior to execution, ensure you modify the sample code’s LLM and embedding configurations accordingly.
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**Note**: When running the demo program, please be aware that different test scripts may use different embedding models. If you switch to a different embedding model, you must clear the data directory (`./dickens`); otherwise, the program may encounter errors. If you wish to retain the LLM cache, you can preserve the `kv_store_llm_response_cache.json` file while clearing the data directory.
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**Note 1**: When running the demo program, please be aware that different test scripts may use different embedding models. If you switch to a different embedding model, you must clear the data directory (`./dickens`); otherwise, the program may encounter errors. If you wish to retain the LLM cache, you can preserve the `kv_store_llm_response_cache.json` file while clearing the data directory.
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Integrate Using LightRAG core object
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**Note 2**: Only `lightrag_openai_demo.py` and `lightrag_openai_compatible_demo.py` are officially supported sample codes. Other sample files are community contributions that haven't undergone full testing and optimization.
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## Programing with LightRAG Core
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@@ -847,7 +847,7 @@ 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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