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version: ignore components: # define all the building-blocks for Pipeline - name: DocumentStore type: ElasticsearchDocumentStore # consider using MilvusDocumentStore or WeaviateDocumentStore for scaling to large number of documents params: host: localhost - name: Retriever type: DensePassageRetriever params: document_store: DocumentStore # params can reference other components defined in the YAML top_k: 5 - name: Reader # custom-name for the component; helpful for visualization & debugging type: FARMReader # Haystack Class name for the component params: model_name_or_path: deepset/roberta-base-squad2 context_window_size: 1000 return_no_answer: true - name: TextFileConverter type: TextConverter - name: PDFFileConverter type: PDFToTextConverter - name: Preprocessor type: PreProcessor params: split_by: word split_length: 1000 - name: FileTypeClassifier type: FileTypeClassifier - name: Generator type: Seq2SeqGenerator params: model_name_or_path: vblagoje/bart_lfqa pipelines: - name: query # a sample extractive-qa Pipeline nodes: - name: Retriever inputs: [Query] - name: Reader inputs: [Retriever] - name: Generator inputs: [Reader] - name: indexing nodes: - name: FileTypeClassifier inputs: [File] - name: TextFileConverter inputs: [FileTypeClassifier.output_1] - name: PDFFileConverter inputs: [FileTypeClassifier.output_2] - name: Preprocessor inputs: [PDFFileConverter, TextFileConverter] - name: Retriever inputs: [Preprocessor] - name: DocumentStore inputs: [Retriever]
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