docs: updated the configuratino examples for graph-based RAG
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@@ -199,7 +199,7 @@ rag_chunk_size: null # Defines the size of chunks for document proce
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rag_chunk_overlap: null # Defines the overlap between chunks
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rag_extractor_model: null # LLM model for graph-based entity/relationship extraction; when set, enables a graph RAG signal alongside vector and BM25
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rag_extractor_prompt: null # Custom extraction prompt template; must contain __CHUNK__ placeholder; defaults to built-in prompt when null
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rag_graph_hops: 1 # Number of hops to expand from matched entities at query time (1 = direct neighbors; increase for denser graphs)
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rag_graph_hops: 1 # Number of hops to expand from matched entities at query time (0 = seed nodes only; 1 = direct neighbors; increase for denser graphs)
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# Defines the query structure using variables like __CONTEXT__, __SOURCES__, and __INPUT__ to tailor searches to specific needs
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rag_template: |
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Answer the query based on the context while respecting the rules. (user query, some textual context and rules, all inside xml tags)
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@@ -227,7 +227,7 @@ nodes:
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reranker_model: null # Optional reranker for hybrid-search results
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extractor_model: null # Optional chat model for graph-based entity/relationship extraction; enables graph RAG signal when set
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extractor_prompt: null # Optional custom extraction prompt; must contain __CHUNK__ placeholder; uses built-in prompt when null
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graph_hops: 1 # Graph expansion depth at query time (1 = direct neighbors; increase for denser knowledge graphs)
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graph_hops: 1 # Graph expansion depth at query time (0 = seed nodes only; 1 = direct neighbors; increase for denser knowledge graphs)
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batch_size: 100 # Optional embedding-request batch size
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state_updates: # {{output}} = { context: <str>, sources: [<path>, ...] }
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context: "{{output.context}}" # writes `context` -> `reducers.context = concat`
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