Fix vector store filter not work (#4065)

* Fix vector store filter not work

* Update ExtractMetadataRetriever.ts

* Update HydeRetriever.ts

* Update MultiQueryRetriever.ts

* Update SimilarityThresholdRetriever.ts

---------

Co-authored-by: Henry Heng <henryheng@flowiseai.com>

packages/components/nodes/retrievers/ExtractMetadataRetriever/ExtractMetadataRetriever.ts

@@ -150,6 +150,7 @@ class ExtractMetadataRetriever_Retrievers implements INode {
             prompt: dynamicMetadataFilterRetrieverPrompt,
             topK: topK ? parseInt(topK, 10) : (vectorStore as any)?.k ?? 4
         })
+        retriever.filter = vectorStore?.lc_kwargs?.filter ?? (vectorStore as any).filter
 
         if (output === 'retriever') return retriever
         else if (output === 'document') return await retriever.getRelevantDocuments(finalInputQuery)

packages/components/nodes/retrievers/HydeRetriever/HydeRetriever.ts

@@ -172,6 +172,7 @@ Passage:`
         else if (promptKey) obj.promptTemplate = promptKey
 
         const retriever = new HydeRetriever(obj)
+        retriever.filter = vectorStore?.lc_kwargs?.filter ?? (vectorStore as any).filter
 
         if (output === 'retriever') return retriever
         else if (output === 'document') return await retriever.getRelevantDocuments(query ? query : input)

packages/components/nodes/retrievers/MultiQueryRetriever/MultiQueryRetriever.ts

@@ -71,7 +71,7 @@ class MultiQueryRetriever_Retrievers implements INode {
 
         const retriever = MultiQueryRetriever.fromLLM({
             llm: model,
-            retriever: vectorStore.asRetriever(),
+            retriever: vectorStore.asRetriever({ filter: vectorStore?.lc_kwargs?.filter ?? vectorStore?.filter }),
             verbose: process.env.DEBUG === 'true',
             // @ts-ignore
             prompt: PromptTemplate.fromTemplate(prompt)

packages/components/nodes/retrievers/RRFRetriever/ReciprocalRankFusion.ts

@@ -50,7 +50,7 @@ export class ReciprocalRankFusion extends BaseDocumentCompressor {
         })
         const docList: Document<Record<string, any>>[][] = []
         for (let i = 0; i < queries.length; i++) {
-            const resultOne = await this.baseRetriever.vectorStore.similaritySearch(queries[i], 5)
+            const resultOne = await this.baseRetriever.vectorStore.similaritySearch(queries[i], 5, this.baseRetriever.filter)
             const docs: any[] = []
             resultOne.forEach((doc) => {
                 docs.push(doc)

packages/components/nodes/retrievers/SimilarityThresholdRetriever/SimilarityThresholdRetriever.ts

@@ -100,6 +100,7 @@ class SimilarityThresholdRetriever_Retrievers implements INode {
             maxK: maxK ? parseInt(maxK, 10) : 100,
             kIncrement: kIncrement ? parseInt(kIncrement, 10) : 2
         })
+        retriever.filter = vectorStore?.lc_kwargs?.filter ?? (vectorStore as any).filter
 
         if (output === 'retriever') return retriever
         else if (output === 'document') return await retriever.getRelevantDocuments(query ? query : input)