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<start_of_text>Generate Haystack DocumentSearchPipeline with EmbeddingRetriever and deepset cloud document store<response>{"version": "1.6.0", "components": [{"name": "deepset_cloud_document_store", "type": "DeepsetCloudDocumentStore", "params": {}}, {"name": "embedding_retriever", "type": "EmbeddingRetriever", "params": {}}], "pipelines": [{"name": "my_doc_search_pipeline", "nodes": [{"inputs": ["Query"], "name": "embedding_retriever"}, {"inputs": ["embedding_retriever"]}]}]}<end_of_text> |
<start_of_text>Generate Haystack search summarization pipeline consisting of TransformersSummarizer, EmbeddingRetriever and deepset cloud document store<response>{"version": "1.6.0", "components": [{"name": "deepset_cloud_document_store", "type": "DeepsetCloudDocumentStore", "params": {}}, {"name": "embedding_retriever", "type": "EmbeddingRetriever", "params": {}}, {"name": "transformers_summarizer", "type": "TransformersSummarizer", "params": {}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "embedding_retriever"}, {"inputs": ["embedding_retriever"], "name": "transformers_summarizer"}]}]}<end_of_text> |
<start_of_text>Generate Haystack generative qa system using ra generator, tfidf retriever and open search document store<response>{"version": "1.6.0", "components": [{"name": "open_search_document_store", "type": "OpenSearchDocumentStore", "params": {"scheme": "https", "username": "admin", "password": "admin", "port": 0, "index": "document", "label_index": "label", "content_field": "content", "name_field": "name", "embedding_field": "embedding", "embedding_dim": 768, "analyzer": "standard", "verify_certs": false, "recreate_index": false, "create_index": true, "refresh_type": "wait_for", "similarity": "dot_product", "timeout": 30, "return_embedding": false, "duplicate_documents": "overwrite", "index_type": "flat", "scroll": "1d", "skip_missing_embeddings": true, "synonym_type": "synonym", "use_system_proxy": false}}, {"name": "tfidf_retriever", "type": "TfidfRetriever", "params": {"top_k": 10}}, {"name": "ra_generator", "type": "RAGenerator", "params": {"model_name_or_path": "facebook/rag-token-nq", "generator_type": "token", "top_k": 2, "max_length": 200, "min_length": 2, "num_beams": 2, "embed_title": true, "use_gpu": true}}], "pipelines": [{"name": "my_generator_pipeline", "nodes": [{"inputs": ["Query"], "name": "tfidf_retriever"}, {"inputs": ["tfidf_retriever"], "name": "ra_generator"}]}]}<end_of_text> |
<start_of_text>Create question generation pipeline<response>{"version": "1.6.0", "components": [{"name": "QuestionGenerator", "params": {}, "type": "QuestionGenerator"}], "pipelines": [{"name": "query", "nodes": [{"inputs": ["Query"], "name": "QuestionGenerator"}]}]}<end_of_text> |
<start_of_text>Generate Haystack search summarization pipeline using TransformersSummarizer, bm25 retriever and InMemoryDocumentStore<response>{"version": "1.6.0", "components": [{"name": "in_memory_document_store", "type": "InMemoryDocumentStore", "params": {}}, {"name": "bm25_retriever", "type": "BM25Retriever", "params": {}}, {"name": "transformers_summarizer", "type": "TransformersSummarizer", "params": {}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "bm25_retriever"}, {"inputs": ["bm25_retriever"], "name": "transformers_summarizer"}]}]}<end_of_text> |
<start_of_text>Make Haystack search pipeline with filter retriever and elasticsearch document store<response>{"version": "1.6.0", "components": [{"name": "elasticsearch_document_store", "type": "ElasticsearchDocumentStore", "params": {"port": 0, "index": "document", "content_field": "content", "name_field": "name", "embedding_field": "embedding", "embedding_dim": 768, "analyzer": "standard", "scheme": "http", "verify_certs": true, "recreate_index": false, "create_index": true, "refresh_type": "wait_for", "similarity": "dot_product", "timeout": 30, "return_embedding": false, "duplicate_documents": "overwrite", "index_type": "flat", "scroll": "1d", "skip_missing_embeddings": true, "synonym_type": "synonym", "use_system_proxy": false}}, {"name": "filter_retriever", "type": "FilterRetriever", "params": {"all_terms_must_match": false, "scale_score": true}}], "pipelines": [{"name": "my_doc_search_pipeline", "nodes": [{"inputs": ["Query"], "name": "filter_retriever"}, {"inputs": ["filter_retriever"]}]}]}<end_of_text> |
<start_of_text>Generate Haystack extractive qa system using rci reader, BM25Retriever and PineconeDocumentStore<response>{"version": "1.6.0", "components": [{"name": "pinecone_document_store", "type": "PineconeDocumentStore", "params": {}}, {"name": "bm25_retriever", "type": "BM25Retriever", "params": {}}, {"name": "rci_reader", "type": "RCIReader", "params": {}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "bm25_retriever"}, {"inputs": ["bm25_retriever"], "name": "rci_reader"}]}]}<end_of_text> |
<start_of_text>Make Haystack question generation pipeline<response>{"version": "1.6.0", "components": [{"name": "QuestionGenerator", "params": {}, "type": "QuestionGenerator"}], "pipelines": [{"name": "query", "nodes": [{"inputs": ["Query"], "name": "QuestionGenerator"}]}]}<end_of_text> |
<start_of_text>Make faq search pipeline with TfidfRetriever and sql document store<response>{"version": "1.6.0", "components": [{"name": "sql_document_store", "type": "SQLDocumentStore", "params": {}}, {"name": "tfidf_retriever", "type": "TfidfRetriever", "params": {}}], "pipelines": [{"name": "my_doc_search_pipeline", "nodes": [{"inputs": ["Query"], "name": "tfidf_retriever"}, {"inputs": ["tfidf_retriever"]}]}]}<end_of_text> |
<start_of_text>Make question answer generation system using RCIReader and question generator<response>{"version": "1.6.0", "components": [{"name": "question_generator", "type": "QuestionGenerator", "params": {}}, {"name": "rci_reader", "type": "RCIReader", "params": {}}], "pipelines": [{"name": "my_question_answering_pipeline", "nodes": [{"inputs": ["Query"], "name": "question_generator"}, {"inputs": ["question_generator"], "name": "rci_reader"}]}]}<end_of_text> |
<start_of_text>Create Haystack question answer generation pipeline consisting of transformers reader and QuestionGenerator<response>{"version": "1.6.0", "components": [{"name": "question_generator", "type": "QuestionGenerator", "params": {}}, {"name": "transformers_reader", "type": "TransformersReader", "params": {}}], "pipelines": [{"name": "my_question_answering_pipeline", "nodes": [{"inputs": ["Query"], "name": "question_generator"}, {"inputs": ["question_generator"], "name": "transformers_reader"}]}]}<end_of_text> |
<start_of_text>Build generative qa system consisting of ra generator, elasticsearch retriever and PineconeDocumentStore<response>{"version": "1.6.0", "components": [{"name": "pinecone_document_store", "type": "PineconeDocumentStore", "params": {"environment": "us-west1-gcp", "sql_url": "sqlite:///pinecone_document_store.db", "embedding_dim": 768, "return_embedding": false, "index": "document", "similarity": "cosine", "replicas": 1, "shards": 1, "embedding_field": "embedding", "progress_bar": true, "duplicate_documents": "overwrite", "recreate_index": false, "validate_index_sync": true}}, {"name": "elasticsearch_retriever", "type": "ElasticsearchRetriever", "params": {"top_k": 10, "all_terms_must_match": false}}, {"name": "ra_generator", "type": "RAGenerator", "params": {"model_name_or_path": "facebook/rag-token-nq", "generator_type": "token", "top_k": 2, "max_length": 200, "min_length": 2, "num_beams": 2, "embed_title": true, "use_gpu": true}}], "pipelines": [{"name": "my_generator_pipeline", "nodes": [{"inputs": ["Query"], "name": "elasticsearch_retriever"}, {"inputs": ["elasticsearch_retriever"], "name": "ra_generator"}]}]}<end_of_text> |
<start_of_text>Make Haystack question generation pipeline<response>{"version": "1.6.0", "components": [{"name": "QuestionGenerator", "params": {}, "type": "QuestionGenerator"}], "pipelines": [{"name": "query", "nodes": [{"inputs": ["Query"], "name": "QuestionGenerator"}]}]}<end_of_text> |
<start_of_text>Generate Haystack SearchSummarizationPipeline using TransformersSummarizer, embedding retriever and sql document store<response>{"version": "1.6.0", "components": [{"name": "sql_document_store", "type": "SQLDocumentStore", "params": {}}, {"name": "embedding_retriever", "type": "EmbeddingRetriever", "params": {}}, {"name": "transformers_summarizer", "type": "TransformersSummarizer", "params": {}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "embedding_retriever"}, {"inputs": ["embedding_retriever"], "name": "transformers_summarizer"}]}]}<end_of_text> |
<start_of_text>Make Haystack search summarization consisting of transformers summarizer, BM25Retriever and weaviate document store<response>{"version": "1.6.0", "components": [{"name": "weaviate_document_store", "type": "WeaviateDocumentStore", "params": {"index": "Document", "progress_bar": true}}, {"name": "bm25_retriever", "type": "BM25Retriever", "params": {}}, {"name": "transformers_summarizer", "type": "TransformersSummarizer", "params": {}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "bm25_retriever"}, {"inputs": ["bm25_retriever"], "name": "transformers_summarizer"}]}]}<end_of_text> |
<start_of_text>Make Haystack generative qa using seq2 seq generator, TfidfRetriever and deepset cloud document store<response>{"version": "1.6.0", "components": [{"name": "deepset_cloud_document_store", "type": "DeepsetCloudDocumentStore", "params": {"workspace": "default", "duplicate_documents": "overwrite", "similarity": "dot_product", "return_embedding": false, "label_index": "default"}}, {"name": "tfidf_retriever", "type": "TfidfRetriever", "params": {"top_k": 10}}, {"name": "seq2_seq_generator", "type": "Seq2SeqGenerator", "params": {"top_k": 1, "max_length": 200, "min_length": 2, "num_beams": 8, "use_gpu": true}}], "pipelines": [{"name": "my_generator_pipeline", "nodes": [{"inputs": ["Query"], "name": "tfidf_retriever"}, {"inputs": ["tfidf_retriever"], "name": "seq2_seq_generator"}]}]}<end_of_text> |
<start_of_text>Make extractive qa with TransformersReader, elasticsearch retriever and sql document store<response>{"version": "1.6.0", "components": [{"name": "sql_document_store", "type": "SQLDocumentStore", "params": {"label_index": "label", "check_same_thread": false}}, {"name": "elasticsearch_retriever", "type": "ElasticsearchRetriever", "params": {}}, {"name": "transformers_reader", "type": "TransformersReader", "params": {"model_name_or_path": "distilbert-base-uncased-distilled-squad", "use_gpu": true, "top_k": 10, "top_k_per_candidate": 3, "max_seq_len": 256, "batch_size": 0}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "elasticsearch_retriever"}, {"inputs": ["elasticsearch_retriever"], "name": "transformers_reader"}]}]}<end_of_text> |
<start_of_text>Build faq search pipeline using tfidf retriever and open distro elasticsearch document store<response>{"version": "1.6.0", "components": [{"name": "open_distro_elasticsearch_document_store", "type": "OpenDistroElasticsearchDocumentStore", "params": {"password": "admin", "port": 0, "label_index": "label", "embedding_field": "embedding", "embedding_dim": 768, "recreate_index": false, "refresh_type": "wait_for", "return_embedding": false, "duplicate_documents": "overwrite", "skip_missing_embeddings": true, "synonym_type": "synonym"}}, {"name": "tfidf_retriever", "type": "TfidfRetriever", "params": {}}], "pipelines": [{"name": "my_doc_search_pipeline", "nodes": [{"inputs": ["Query"], "name": "tfidf_retriever"}, {"inputs": ["tfidf_retriever"]}]}]}<end_of_text> |
<start_of_text>Build generative qa pipeline consisting of ra generator, FilterRetriever and elasticsearch document store<response>{"version": "1.6.0", "components": [{"name": "elasticsearch_document_store", "type": "ElasticsearchDocumentStore", "params": {"port": 0, "index": "document", "label_index": "label", "content_field": "content", "name_field": "name", "embedding_field": "embedding", "embedding_dim": 768, "analyzer": "standard", "scheme": "http", "verify_certs": true, "recreate_index": false, "create_index": true, "refresh_type": "wait_for", "similarity": "dot_product", "timeout": 30, "return_embedding": false, "duplicate_documents": "overwrite", "index_type": "flat", "scroll": "1d", "skip_missing_embeddings": true, "synonym_type": "synonym", "use_system_proxy": false}}, {"name": "filter_retriever", "type": "FilterRetriever", "params": {"top_k": 10, "all_terms_must_match": false, "scale_score": true}}, {"name": "ra_generator", "type": "RAGenerator", "params": {"model_name_or_path": "facebook/rag-token-nq", "generator_type": "token", "top_k": 2, "max_length": 200, "min_length": 2, "num_beams": 2, "embed_title": true, "use_gpu": true}}], "pipelines": [{"name": "my_generator_pipeline", "nodes": [{"inputs": ["Query"], "name": "filter_retriever"}, {"inputs": ["filter_retriever"], "name": "ra_generator"}]}]}<end_of_text> |
<start_of_text>Create search summarization pipeline consisting of transformers summarizer, BM25Retriever and weaviate document store<response>{"version": "1.6.0", "components": [{"name": "weaviate_document_store", "type": "WeaviateDocumentStore", "params": {"index": "Document", "content_field": "content", "similarity": "cosine", "progress_bar": true, "duplicate_documents": "overwrite"}}, {"name": "bm25_retriever", "type": "BM25Retriever", "params": {}}, {"name": "transformers_summarizer", "type": "TransformersSummarizer", "params": {}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "bm25_retriever"}, {"inputs": ["bm25_retriever"], "name": "transformers_summarizer"}]}]}<end_of_text> |
<start_of_text>Create Haystack question generation pipeline<response>{"version": "1.6.0", "components": [{"name": "QuestionGenerator", "params": {}, "type": "QuestionGenerator"}], "pipelines": [{"name": "query", "nodes": [{"inputs": ["Query"], "name": "QuestionGenerator"}]}]}<end_of_text> |
<start_of_text>Generate document search system using elasticsearch filter only retriever and FAISSDocumentStore<response>{"version": "1.6.0", "components": [{"name": "faiss_document_store", "type": "FAISSDocumentStore", "params": {}}, {"name": "elasticsearch_filter_only_retriever", "type": "ElasticsearchFilterOnlyRetriever", "params": {}}], "pipelines": [{"name": "my_doc_search_pipeline", "nodes": [{"inputs": ["Query"], "name": "elasticsearch_filter_only_retriever"}, {"inputs": ["elasticsearch_filter_only_retriever"]}]}]}<end_of_text> |
<start_of_text>Generate question generation system<response>{"version": "1.6.0", "components": [{"name": "QuestionGenerator", "params": {}, "type": "QuestionGenerator"}], "pipelines": [{"name": "query", "nodes": [{"inputs": ["Query"], "name": "QuestionGenerator"}]}]}<end_of_text> |
<start_of_text>Build DocumentSearchPipeline consisting of multihop embedding retriever and ElasticsearchDocumentStore<response>{"version": "1.6.0", "components": [{"name": "elasticsearch_document_store", "type": "ElasticsearchDocumentStore", "params": {}}, {"name": "multihop_embedding_retriever", "type": "MultihopEmbeddingRetriever", "params": {}}], "pipelines": [{"name": "my_doc_search_pipeline", "nodes": [{"inputs": ["Query"], "name": "multihop_embedding_retriever"}, {"inputs": ["multihop_embedding_retriever"]}]}]}<end_of_text> |
<start_of_text>Make Haystack faq pipeline using elasticsearch retriever and SQLDocumentStore<response>{"version": "1.6.0", "components": [{"name": "sql_document_store", "type": "SQLDocumentStore", "params": {}}, {"name": "elasticsearch_retriever", "type": "ElasticsearchRetriever", "params": {}}], "pipelines": [{"name": "my_doc_search_pipeline", "nodes": [{"inputs": ["Query"], "name": "elasticsearch_retriever"}, {"inputs": ["elasticsearch_retriever"]}]}]}<end_of_text> |
<start_of_text>Generate faq pipeline consisting of BM25Retriever and SQLDocumentStore<response>{"version": "1.6.0", "components": [{"name": "sql_document_store", "type": "SQLDocumentStore", "params": {}}, {"name": "bm25_retriever", "type": "BM25Retriever", "params": {}}], "pipelines": [{"name": "my_doc_search_pipeline", "nodes": [{"inputs": ["Query"], "name": "bm25_retriever"}, {"inputs": ["bm25_retriever"]}]}]}<end_of_text> |
<start_of_text>Generate faq pipeline consisting of bm25 retriever and in memory document store<response>{"version": "1.6.0", "components": [{"name": "in_memory_document_store", "type": "InMemoryDocumentStore", "params": {}}, {"name": "bm25_retriever", "type": "BM25Retriever", "params": {}}], "pipelines": [{"name": "my_doc_search_pipeline", "nodes": [{"inputs": ["Query"], "name": "bm25_retriever"}, {"inputs": ["bm25_retriever"]}]}]}<end_of_text> |
<start_of_text>Make Haystack faq pipeline consisting of filter retriever and InMemoryDocumentStore<response>{"version": "1.6.0", "components": [{"name": "in_memory_document_store", "type": "InMemoryDocumentStore", "params": {}}, {"name": "filter_retriever", "type": "FilterRetriever", "params": {}}], "pipelines": [{"name": "my_doc_search_pipeline", "nodes": [{"inputs": ["Query"], "name": "filter_retriever"}, {"inputs": ["filter_retriever"]}]}]}<end_of_text> |
<start_of_text>Make Haystack document search system consisting of TfidfRetriever and deepset cloud document store<response>{"version": "1.6.0", "components": [{"name": "deepset_cloud_document_store", "type": "DeepsetCloudDocumentStore", "params": {}}, {"name": "tfidf_retriever", "type": "TfidfRetriever", "params": {}}], "pipelines": [{"name": "my_doc_search_pipeline", "nodes": [{"inputs": ["Query"], "name": "tfidf_retriever"}, {"inputs": ["tfidf_retriever"]}]}]}<end_of_text> |
<start_of_text>Generate Haystack generative qa consisting of seq2 seq generator, ElasticsearchRetriever and ElasticsearchDocumentStore<response>{"version": "1.6.0", "components": [{"name": "elasticsearch_document_store", "type": "ElasticsearchDocumentStore", "params": {"port": 0, "index": "document", "label_index": "label", "content_field": "content", "name_field": "name", "embedding_field": "embedding", "embedding_dim": 768, "analyzer": "standard", "scheme": "http", "verify_certs": true, "recreate_index": false, "create_index": true, "refresh_type": "wait_for", "similarity": "dot_product", "timeout": 30, "return_embedding": false, "duplicate_documents": "overwrite", "index_type": "flat", "scroll": "1d", "skip_missing_embeddings": true, "synonym_type": "synonym", "use_system_proxy": false}}, {"name": "elasticsearch_retriever", "type": "ElasticsearchRetriever", "params": {"top_k": 10, "all_terms_must_match": false}}, {"name": "seq2_seq_generator", "type": "Seq2SeqGenerator", "params": {"top_k": 1, "max_length": 200, "min_length": 2, "num_beams": 8, "use_gpu": true}}], "pipelines": [{"name": "my_generator_pipeline", "nodes": [{"inputs": ["Query"], "name": "elasticsearch_retriever"}, {"inputs": ["elasticsearch_retriever"], "name": "seq2_seq_generator"}]}]}<end_of_text> |
<start_of_text>Build Haystack QuestionGenerationPipeline<response>{"version": "1.6.0", "components": [{"name": "QuestionGenerator", "params": {}, "type": "QuestionGenerator"}], "pipelines": [{"name": "query", "nodes": [{"inputs": ["Query"], "name": "QuestionGenerator"}]}]}<end_of_text> |
<start_of_text>Generate generative pipeline consisting of Seq2SeqGenerator, elasticsearch retriever and elasticsearch document store<response>{"version": "1.6.0", "components": [{"name": "elasticsearch_document_store", "type": "ElasticsearchDocumentStore", "params": {"port": 0, "index": "document", "label_index": "label", "content_field": "content", "name_field": "name", "embedding_field": "embedding", "embedding_dim": 768, "analyzer": "standard", "scheme": "http", "verify_certs": true, "recreate_index": false, "create_index": true, "refresh_type": "wait_for", "similarity": "dot_product", "timeout": 30, "return_embedding": false, "duplicate_documents": "overwrite", "index_type": "flat", "scroll": "1d", "skip_missing_embeddings": true, "synonym_type": "synonym", "use_system_proxy": false}}, {"name": "elasticsearch_retriever", "type": "ElasticsearchRetriever", "params": {"top_k": 10, "all_terms_must_match": false}}, {"name": "seq2_seq_generator", "type": "Seq2SeqGenerator", "params": {"top_k": 1, "max_length": 200, "min_length": 2, "num_beams": 8, "use_gpu": true}}], "pipelines": [{"name": "my_generator_pipeline", "nodes": [{"inputs": ["Query"], "name": "elasticsearch_retriever"}, {"inputs": ["elasticsearch_retriever"], "name": "seq2_seq_generator"}]}]}<end_of_text> |
<start_of_text>Create Haystack SearchSummarizationPipeline with TransformersSummarizer, ElasticsearchFilterOnlyRetriever and deepset cloud document store<response>{"version": "1.6.0", "components": [{"name": "deepset_cloud_document_store", "type": "DeepsetCloudDocumentStore", "params": {}}, {"name": "elasticsearch_filter_only_retriever", "type": "ElasticsearchFilterOnlyRetriever", "params": {}}, {"name": "transformers_summarizer", "type": "TransformersSummarizer", "params": {}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "elasticsearch_filter_only_retriever"}, {"inputs": ["elasticsearch_filter_only_retriever"], "name": "transformers_summarizer"}]}]}<end_of_text> |
<start_of_text>Build extractive qa system using rci reader, ElasticsearchRetriever and faiss document store<response>{"version": "1.6.0", "components": [{"name": "faiss_document_store", "type": "FAISSDocumentStore", "params": {"sql_url": "sqlite:///faiss_document_store.db", "vector_dim": 0, "faiss_index_factory_str": "Flat", "index": "document", "similarity": "dot_product", "progress_bar": true, "duplicate_documents": "overwrite", "n_links": 64, "ef_search": 20, "ef_construction": 80, "validate_index_sync": true}}, {"name": "elasticsearch_retriever", "type": "ElasticsearchRetriever", "params": {}}, {"name": "rci_reader", "type": "RCIReader", "params": {"row_model_name_or_path": "michaelrglass/albert-base-rci-wikisql-row", "max_seq_len": 256}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "elasticsearch_retriever"}, {"inputs": ["elasticsearch_retriever"], "name": "rci_reader"}]}]}<end_of_text> |
<start_of_text>Generate qa pipeline with transformers reader, FilterRetriever and elasticsearch document store<response>{"version": "1.6.0", "components": [{"name": "elasticsearch_document_store", "type": "ElasticsearchDocumentStore", "params": {"index": "document", "label_index": "label", "content_field": "content", "name_field": "name", "embedding_field": "embedding", "embedding_dim": 768, "analyzer": "standard", "verify_certs": true, "recreate_index": false, "create_index": true, "refresh_type": "wait_for", "similarity": "dot_product", "timeout": 30, "return_embedding": false, "duplicate_documents": "overwrite", "index_type": "flat", "scroll": "1d", "skip_missing_embeddings": true, "synonym_type": "synonym", "use_system_proxy": false}}, {"name": "filter_retriever", "type": "FilterRetriever", "params": {"all_terms_must_match": false}}, {"name": "transformers_reader", "type": "TransformersReader", "params": {"model_name_or_path": "distilbert-base-uncased-distilled-squad", "use_gpu": true, "top_k": 10, "top_k_per_candidate": 3, "max_seq_len": 256, "doc_stride": 128, "batch_size": 0}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "filter_retriever"}, {"inputs": ["filter_retriever"], "name": "transformers_reader"}]}]}<end_of_text> |
<start_of_text>Build qa pipeline with table reader, tfidf retriever and OpenSearchDocumentStore<response>{"version": "1.6.0", "components": [{"name": "open_search_document_store", "type": "OpenSearchDocumentStore", "params": {"username": "admin", "port": 0, "content_field": "content", "verify_certs": false, "create_index": true, "similarity": "dot_product", "timeout": 30, "return_embedding": false, "duplicate_documents": "overwrite", "index_type": "flat", "scroll": "1d", "skip_missing_embeddings": true}}, {"name": "tfidf_retriever", "type": "TfidfRetriever", "params": {}}, {"name": "table_reader", "type": "TableReader", "params": {}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "tfidf_retriever"}, {"inputs": ["tfidf_retriever"], "name": "table_reader"}]}]}<end_of_text> |
<start_of_text>Build Haystack faq pipeline with bm25 retriever and in memory document store<response>{"version": "1.6.0", "components": [{"name": "in_memory_document_store", "type": "InMemoryDocumentStore", "params": {"index": "document", "label_index": "label", "embedding_dim": 768, "return_embedding": false, "similarity": "dot_product", "progress_bar": true, "duplicate_documents": "overwrite", "use_gpu": true, "scoring_batch_size": 500000}}, {"name": "bm25_retriever", "type": "BM25Retriever", "params": {"top_k": 10, "all_terms_must_match": false}}], "pipelines": [{"name": "my_doc_search_pipeline", "nodes": [{"inputs": ["Query"], "name": "bm25_retriever"}, {"inputs": ["bm25_retriever"]}]}]}<end_of_text> |
<start_of_text>Build faq pipeline using tfidf retriever and OpenDistroElasticsearchDocumentStore<response>{"version": "1.6.0", "components": [{"name": "open_distro_elasticsearch_document_store", "type": "OpenDistroElasticsearchDocumentStore", "params": {"scheme": "https", "username": "admin", "password": "admin", "port": 0, "index": "document", "label_index": "label", "name_field": "name", "embedding_field": "embedding", "embedding_dim": 768, "verify_certs": false, "recreate_index": false, "create_index": true, "refresh_type": "wait_for", "return_embedding": false, "duplicate_documents": "overwrite", "index_type": "flat", "scroll": "1d", "skip_missing_embeddings": true, "synonym_type": "synonym", "use_system_proxy": false}}, {"name": "tfidf_retriever", "type": "TfidfRetriever", "params": {}}], "pipelines": [{"name": "my_doc_search_pipeline", "nodes": [{"inputs": ["Query"], "name": "tfidf_retriever"}, {"inputs": ["tfidf_retriever"]}]}]}<end_of_text> |
<start_of_text>Build extractive qa system using transformers reader, bm25 retriever and sql document store<response>{"version": "1.6.0", "components": [{"name": "sql_document_store", "type": "SQLDocumentStore", "params": {"url": "sqlite://", "index": "document", "label_index": "label", "check_same_thread": false}}, {"name": "bm25_retriever", "type": "BM25Retriever", "params": {"top_k": 10, "all_terms_must_match": false}}, {"name": "transformers_reader", "type": "TransformersReader", "params": {"model_name_or_path": "distilbert-base-uncased-distilled-squad", "context_window_size": 70, "use_gpu": true, "top_k": 10, "top_k_per_candidate": 3, "return_no_answers": false, "doc_stride": 128, "batch_size": 0}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "bm25_retriever"}, {"inputs": ["bm25_retriever"], "name": "transformers_reader"}]}]}<end_of_text> |
<start_of_text>Build Haystack extractive qa system with FARMReader, ElasticsearchRetriever and OpenDistroElasticsearchDocumentStore<response>{"version": "1.6.0", "components": [{"name": "open_distro_elasticsearch_document_store", "type": "OpenDistroElasticsearchDocumentStore", "params": {"username": "admin", "password": "admin", "port": 0, "content_field": "content", "embedding_field": "embedding", "embedding_dim": 768, "analyzer": "standard", "verify_certs": false, "recreate_index": false, "refresh_type": "wait_for", "similarity": "cosine", "synonym_type": "synonym"}}, {"name": "elasticsearch_retriever", "type": "ElasticsearchRetriever", "params": {}}, {"name": "farm_reader", "type": "FARMReader", "params": {"context_window_size": 150, "top_k_per_sample": 1, "max_seq_len": 256, "doc_stride": 128}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "elasticsearch_retriever"}, {"inputs": ["elasticsearch_retriever"], "name": "farm_reader"}]}]}<end_of_text> |
<start_of_text>Create Haystack question generation pipeline<response>{"version": "1.6.0", "components": [{"name": "QuestionGenerator", "params": {}, "type": "QuestionGenerator"}], "pipelines": [{"name": "query", "nodes": [{"inputs": ["Query"], "name": "QuestionGenerator"}]}]}<end_of_text> |
<start_of_text>Make question answer generation system with transformers reader and QuestionGenerator<response>{"version": "1.6.0", "components": [{"name": "question_generator", "type": "QuestionGenerator", "params": {}}, {"name": "transformers_reader", "type": "TransformersReader", "params": {}}], "pipelines": [{"name": "my_question_answering_pipeline", "nodes": [{"inputs": ["Query"], "name": "question_generator"}, {"inputs": ["question_generator"], "name": "transformers_reader"}]}]}<end_of_text> |
<start_of_text>Make FAQPipeline consisting of multihop embedding retriever and deepset cloud document store<response>{"version": "1.6.0", "components": [{"name": "deepset_cloud_document_store", "type": "DeepsetCloudDocumentStore", "params": {}}, {"name": "multihop_embedding_retriever", "type": "MultihopEmbeddingRetriever", "params": {}}], "pipelines": [{"name": "my_doc_search_pipeline", "nodes": [{"inputs": ["Query"], "name": "multihop_embedding_retriever"}, {"inputs": ["multihop_embedding_retriever"]}]}]}<end_of_text> |
<start_of_text>Generate generative qa system consisting of seq2 seq generator, ElasticsearchRetriever and sql document store<response>{"version": "1.6.0", "components": [{"name": "sql_document_store", "type": "SQLDocumentStore", "params": {"url": "sqlite://", "index": "document", "label_index": "label", "duplicate_documents": "overwrite", "check_same_thread": false}}, {"name": "elasticsearch_retriever", "type": "ElasticsearchRetriever", "params": {"top_k": 10, "all_terms_must_match": false}}, {"name": "seq2_seq_generator", "type": "Seq2SeqGenerator", "params": {"top_k": 1, "max_length": 200, "min_length": 2, "num_beams": 8, "use_gpu": true}}], "pipelines": [{"name": "my_generator_pipeline", "nodes": [{"inputs": ["Query"], "name": "elasticsearch_retriever"}, {"inputs": ["elasticsearch_retriever"], "name": "seq2_seq_generator"}]}]}<end_of_text> |
<start_of_text>Create search pipeline with BM25Retriever and sql document store<response>{"version": "1.6.0", "components": [{"name": "sql_document_store", "type": "SQLDocumentStore", "params": {}}, {"name": "bm25_retriever", "type": "BM25Retriever", "params": {}}], "pipelines": [{"name": "my_doc_search_pipeline", "nodes": [{"inputs": ["Query"], "name": "bm25_retriever"}, {"inputs": ["bm25_retriever"]}]}]}<end_of_text> |
<start_of_text>Generate Haystack DocumentSearchPipeline consisting of FilterRetriever and open search document store<response>{"version": "1.6.0", "components": [{"name": "open_search_document_store", "type": "OpenSearchDocumentStore", "params": {"password": "admin", "index": "document", "refresh_type": "wait_for", "timeout": 30, "duplicate_documents": "overwrite", "scroll": "1d", "synonym_type": "synonym"}}, {"name": "filter_retriever", "type": "FilterRetriever", "params": {}}], "pipelines": [{"name": "my_doc_search_pipeline", "nodes": [{"inputs": ["Query"], "name": "filter_retriever"}, {"inputs": ["filter_retriever"]}]}]}<end_of_text> |
<start_of_text>Create extractive qa system using table reader, EmbeddingRetriever and InMemoryDocumentStore<response>{"version": "1.6.0", "components": [{"name": "in_memory_document_store", "type": "InMemoryDocumentStore", "params": {}}, {"name": "embedding_retriever", "type": "EmbeddingRetriever", "params": {}}, {"name": "table_reader", "type": "TableReader", "params": {}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "embedding_retriever"}, {"inputs": ["embedding_retriever"], "name": "table_reader"}]}]}<end_of_text> |
<start_of_text>Build generative pipeline using RAGenerator, tfidf retriever and open search document store<response>{"version": "1.6.0", "components": [{"name": "open_search_document_store", "type": "OpenSearchDocumentStore", "params": {"scheme": "https", "username": "admin", "password": "admin", "port": 0, "index": "document", "label_index": "label", "content_field": "content", "name_field": "name", "embedding_field": "embedding", "embedding_dim": 768, "analyzer": "standard", "verify_certs": false, "recreate_index": false, "create_index": true, "refresh_type": "wait_for", "similarity": "dot_product", "timeout": 30, "return_embedding": false, "duplicate_documents": "overwrite", "index_type": "flat", "scroll": "1d", "skip_missing_embeddings": true, "synonym_type": "synonym", "use_system_proxy": false}}, {"name": "tfidf_retriever", "type": "TfidfRetriever", "params": {"top_k": 10}}, {"name": "ra_generator", "type": "RAGenerator", "params": {"model_name_or_path": "facebook/rag-token-nq", "generator_type": "token", "top_k": 2, "max_length": 200, "min_length": 2, "num_beams": 2, "embed_title": true, "use_gpu": true}}], "pipelines": [{"name": "my_generator_pipeline", "nodes": [{"inputs": ["Query"], "name": "tfidf_retriever"}, {"inputs": ["tfidf_retriever"], "name": "ra_generator"}]}]}<end_of_text> |
<start_of_text>Build Haystack document search system with elasticsearch retriever and OpenDistroElasticsearchDocumentStore<response>{"version": "1.6.0", "components": [{"name": "open_distro_elasticsearch_document_store", "type": "OpenDistroElasticsearchDocumentStore", "params": {"scheme": "https", "username": "admin", "password": "admin", "port": 0, "index": "document", "content_field": "content", "name_field": "name", "create_index": true, "similarity": "cosine", "timeout": 30, "scroll": "1d", "synonym_type": "synonym", "use_system_proxy": false}}, {"name": "elasticsearch_retriever", "type": "ElasticsearchRetriever", "params": {}}], "pipelines": [{"name": "my_doc_search_pipeline", "nodes": [{"inputs": ["Query"], "name": "elasticsearch_retriever"}, {"inputs": ["elasticsearch_retriever"]}]}]}<end_of_text> |
<start_of_text>Create Haystack question generation system<response>{"version": "1.6.0", "components": [{"name": "QuestionGenerator", "params": {}, "type": "QuestionGenerator"}], "pipelines": [{"name": "query", "nodes": [{"inputs": ["Query"], "name": "QuestionGenerator"}]}]}<end_of_text> |
<start_of_text>Build Haystack search summarization pipeline consisting of TransformersSummarizer, FilterRetriever and pinecone document store<response>{"version": "1.6.0", "components": [{"name": "pinecone_document_store", "type": "PineconeDocumentStore", "params": {"environment": "us-west1-gcp", "return_embedding": false, "similarity": "cosine", "shards": 1, "recreate_index": false, "metadata_config": {}}}, {"name": "filter_retriever", "type": "FilterRetriever", "params": {}}, {"name": "transformers_summarizer", "type": "TransformersSummarizer", "params": {}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "filter_retriever"}, {"inputs": ["filter_retriever"], "name": "transformers_summarizer"}]}]}<end_of_text> |
<start_of_text>Create generative qa consisting of ra generator, FilterRetriever and OpenSearchDocumentStore<response>{"version": "1.6.0", "components": [{"name": "open_search_document_store", "type": "OpenSearchDocumentStore", "params": {"scheme": "https", "username": "admin", "password": "admin", "port": 0, "index": "document", "label_index": "label", "content_field": "content", "name_field": "name", "embedding_field": "embedding", "embedding_dim": 768, "analyzer": "standard", "verify_certs": false, "recreate_index": false, "create_index": true, "refresh_type": "wait_for", "similarity": "dot_product", "timeout": 30, "return_embedding": false, "duplicate_documents": "overwrite", "index_type": "flat", "scroll": "1d", "skip_missing_embeddings": true, "synonym_type": "synonym", "use_system_proxy": false}}, {"name": "filter_retriever", "type": "FilterRetriever", "params": {"top_k": 10, "all_terms_must_match": false, "scale_score": true}}, {"name": "ra_generator", "type": "RAGenerator", "params": {"model_name_or_path": "facebook/rag-token-nq", "generator_type": "token", "top_k": 2, "max_length": 200, "min_length": 2, "num_beams": 2, "embed_title": true, "use_gpu": true}}], "pipelines": [{"name": "my_generator_pipeline", "nodes": [{"inputs": ["Query"], "name": "filter_retriever"}, {"inputs": ["filter_retriever"], "name": "ra_generator"}]}]}<end_of_text> |
<start_of_text>Generate Haystack search summarization pipeline with transformers summarizer, TableTextRetriever and deepset cloud document store<response>{"version": "1.6.0", "components": [{"name": "deepset_cloud_document_store", "type": "DeepsetCloudDocumentStore", "params": {"return_embedding": false}}, {"name": "table_text_retriever", "type": "TableTextRetriever", "params": {"max_seq_len_passage": 256, "max_seq_len_table": 256, "top_k": 10, "use_gpu": true, "batch_size": 16, "use_fast_tokenizers": true, "infer_tokenizer_classes": false, "global_loss_buffer_size": 150000, "progress_bar": true, "scale_score": true}}, {"name": "transformers_summarizer", "type": "TransformersSummarizer", "params": {"use_gpu": true, "clean_up_tokenization_spaces": true, "separator_for_single_summary": " ", "generate_single_summary": false}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "table_text_retriever"}, {"inputs": ["table_text_retriever"], "name": "transformers_summarizer"}]}]}<end_of_text> |
<start_of_text>Create search summarization consisting of TransformersSummarizer, multihop embedding retriever and weaviate document store<response>{"version": "1.6.0", "components": [{"name": "weaviate_document_store", "type": "WeaviateDocumentStore", "params": {"port": 0, "timeout_config": [5, 15], "index": "Document", "embedding_dim": 768, "content_field": "content", "name_field": "name", "similarity": "cosine", "index_type": "hnsw", "embedding_field": "embedding", "progress_bar": true, "duplicate_documents": "overwrite", "recreate_index": false}}, {"name": "multihop_embedding_retriever", "type": "MultihopEmbeddingRetriever", "params": {"num_iterations": 2, "use_gpu": true, "batch_size": 32, "max_seq_len": 512, "model_format": "farm", "pooling_strategy": "reduce_mean", "emb_extraction_layer": -1, "top_k": 10, "use_auth_token": false, "scale_score": true}}, {"name": "transformers_summarizer", "type": "TransformersSummarizer", "params": {"model_name_or_path": "google/pegasus-xsum", "max_length": 200, "min_length": 5, "use_gpu": true, "clean_up_tokenization_spaces": true, "separator_for_single_summary": " ", "generate_single_summary": false}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "multihop_embedding_retriever"}, {"inputs": ["multihop_embedding_retriever"], "name": "transformers_summarizer"}]}]}<end_of_text> |
<start_of_text>Build ExtractiveQAPipeline with rci reader, elasticsearch filter only retriever and faiss document store<response>{"version": "1.6.0", "components": [{"name": "faiss_document_store", "type": "FAISSDocumentStore", "params": {"embedding_dim": 768}}, {"name": "elasticsearch_filter_only_retriever", "type": "ElasticsearchFilterOnlyRetriever", "params": {}}, {"name": "rci_reader", "type": "RCIReader", "params": {}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "elasticsearch_filter_only_retriever"}, {"inputs": ["elasticsearch_filter_only_retriever"], "name": "rci_reader"}]}]}<end_of_text> |
<start_of_text>Create Haystack faq search pipeline consisting of filter retriever and InMemoryDocumentStore<response>{"version": "1.6.0", "components": [{"name": "in_memory_document_store", "type": "InMemoryDocumentStore", "params": {}}, {"name": "filter_retriever", "type": "FilterRetriever", "params": {}}], "pipelines": [{"name": "my_doc_search_pipeline", "nodes": [{"inputs": ["Query"], "name": "filter_retriever"}, {"inputs": ["filter_retriever"]}]}]}<end_of_text> |
<start_of_text>Make Haystack search summarization with TransformersSummarizer, table text retriever and DeepsetCloudDocumentStore<response>{"version": "1.6.0", "components": [{"name": "deepset_cloud_document_store", "type": "DeepsetCloudDocumentStore", "params": {}}, {"name": "table_text_retriever", "type": "TableTextRetriever", "params": {}}, {"name": "transformers_summarizer", "type": "TransformersSummarizer", "params": {}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "table_text_retriever"}, {"inputs": ["table_text_retriever"], "name": "transformers_summarizer"}]}]}<end_of_text> |
<start_of_text>Make search pipeline with tfidf retriever and SQLDocumentStore<response>{"version": "1.6.0", "components": [{"name": "sql_document_store", "type": "SQLDocumentStore", "params": {"label_index": "label"}}, {"name": "tfidf_retriever", "type": "TfidfRetriever", "params": {}}], "pipelines": [{"name": "my_doc_search_pipeline", "nodes": [{"inputs": ["Query"], "name": "tfidf_retriever"}, {"inputs": ["tfidf_retriever"]}]}]}<end_of_text> |
<start_of_text>Build extractive qa pipeline with farm reader, table text retriever and DeepsetCloudDocumentStore<response>{"version": "1.6.0", "components": [{"name": "deepset_cloud_document_store", "type": "DeepsetCloudDocumentStore", "params": {}}, {"name": "table_text_retriever", "type": "TableTextRetriever", "params": {"top_k": 10}}, {"name": "farm_reader", "type": "FARMReader", "params": {"context_window_size": 150, "top_k_per_candidate": 3, "confidence_threshold": 0}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "table_text_retriever"}, {"inputs": ["table_text_retriever"], "name": "farm_reader"}]}]}<end_of_text> |
<start_of_text>Create document search pipeline with embedding retriever and sql document store<response>{"version": "1.6.0", "components": [{"name": "sql_document_store", "type": "SQLDocumentStore", "params": {}}, {"name": "embedding_retriever", "type": "EmbeddingRetriever", "params": {}}], "pipelines": [{"name": "my_doc_search_pipeline", "nodes": [{"inputs": ["Query"], "name": "embedding_retriever"}, {"inputs": ["embedding_retriever"]}]}]}<end_of_text> |
<start_of_text>Generate search pipeline consisting of filter retriever and OpenDistroElasticsearchDocumentStore<response>{"version": "1.6.0", "components": [{"name": "open_distro_elasticsearch_document_store", "type": "OpenDistroElasticsearchDocumentStore", "params": {"password": "admin", "content_field": "content", "embedding_dim": 768, "analyzer": "standard", "verify_certs": false, "create_index": true, "duplicate_documents": "overwrite", "index_type": "flat", "skip_missing_embeddings": true, "synonym_type": "synonym"}}, {"name": "filter_retriever", "type": "FilterRetriever", "params": {}}], "pipelines": [{"name": "my_doc_search_pipeline", "nodes": [{"inputs": ["Query"], "name": "filter_retriever"}, {"inputs": ["filter_retriever"]}]}]}<end_of_text> |
<start_of_text>Create extractive qa system using farm reader, table text retriever and DeepsetCloudDocumentStore<response>{"version": "1.6.0", "components": [{"name": "deepset_cloud_document_store", "type": "DeepsetCloudDocumentStore", "params": {}}, {"name": "table_text_retriever", "type": "TableTextRetriever", "params": {}}, {"name": "farm_reader", "type": "FARMReader", "params": {}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "table_text_retriever"}, {"inputs": ["table_text_retriever"], "name": "farm_reader"}]}]}<end_of_text> |
<start_of_text>Make Haystack generative qa system using RAGenerator, embedding retriever and SQLDocumentStore<response>{"version": "1.6.0", "components": [{"name": "sql_document_store", "type": "SQLDocumentStore", "params": {"url": "sqlite://", "index": "document", "label_index": "label", "duplicate_documents": "overwrite", "check_same_thread": false}}, {"name": "embedding_retriever", "type": "EmbeddingRetriever", "params": {"use_gpu": true, "batch_size": 32, "max_seq_len": 512, "pooling_strategy": "reduce_mean", "emb_extraction_layer": -1, "top_k": 10, "progress_bar": true, "use_auth_token": false, "scale_score": true}}, {"name": "ra_generator", "type": "RAGenerator", "params": {"model_name_or_path": "facebook/rag-token-nq", "generator_type": "token", "top_k": 2, "max_length": 200, "min_length": 2, "num_beams": 2, "embed_title": true, "use_gpu": true}}], "pipelines": [{"name": "my_generator_pipeline", "nodes": [{"inputs": ["Query"], "name": "embedding_retriever"}, {"inputs": ["embedding_retriever"], "name": "ra_generator"}]}]}<end_of_text> |
<start_of_text>Build search summarization system using TransformersSummarizer, embedding retriever and WeaviateDocumentStore<response>{"version": "1.6.0", "components": [{"name": "weaviate_document_store", "type": "WeaviateDocumentStore", "params": {}}, {"name": "embedding_retriever", "type": "EmbeddingRetriever", "params": {}}, {"name": "transformers_summarizer", "type": "TransformersSummarizer", "params": {}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "embedding_retriever"}, {"inputs": ["embedding_retriever"], "name": "transformers_summarizer"}]}]}<end_of_text> |
<start_of_text>Generate Haystack search summarization system consisting of TransformersSummarizer, TableTextRetriever and DeepsetCloudDocumentStore<response>{"version": "1.6.0", "components": [{"name": "deepset_cloud_document_store", "type": "DeepsetCloudDocumentStore", "params": {}}, {"name": "table_text_retriever", "type": "TableTextRetriever", "params": {"top_k": 10, "use_fast_tokenizers": true, "global_loss_buffer_size": 150000, "progress_bar": true}}, {"name": "transformers_summarizer", "type": "TransformersSummarizer", "params": {}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "table_text_retriever"}, {"inputs": ["table_text_retriever"], "name": "transformers_summarizer"}]}]}<end_of_text> |
<start_of_text>Generate Haystack question generation pipeline<response>{"version": "1.6.0", "components": [{"name": "QuestionGenerator", "params": {}, "type": "QuestionGenerator"}], "pipelines": [{"name": "query", "nodes": [{"inputs": ["Query"], "name": "QuestionGenerator"}]}]}<end_of_text> |
<start_of_text>Create Haystack search summarization system consisting of transformers summarizer, TableTextRetriever and DeepsetCloudDocumentStore<response>{"version": "1.6.0", "components": [{"name": "deepset_cloud_document_store", "type": "DeepsetCloudDocumentStore", "params": {}}, {"name": "table_text_retriever", "type": "TableTextRetriever", "params": {}}, {"name": "transformers_summarizer", "type": "TransformersSummarizer", "params": {}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "table_text_retriever"}, {"inputs": ["table_text_retriever"], "name": "transformers_summarizer"}]}]}<end_of_text> |
<start_of_text>Make Haystack search pipeline using elasticsearch retriever and OpenDistroElasticsearchDocumentStore<response>{"version": "1.6.0", "components": [{"name": "open_distro_elasticsearch_document_store", "type": "OpenDistroElasticsearchDocumentStore", "params": {}}, {"name": "elasticsearch_retriever", "type": "ElasticsearchRetriever", "params": {}}], "pipelines": [{"name": "my_doc_search_pipeline", "nodes": [{"inputs": ["Query"], "name": "elasticsearch_retriever"}, {"inputs": ["elasticsearch_retriever"]}]}]}<end_of_text> |
<start_of_text>Make Haystack question answer generation system consisting of FARMReader and QuestionGenerator<response>{"version": "1.6.0", "components": [{"name": "question_generator", "type": "QuestionGenerator", "params": {}}, {"name": "farm_reader", "type": "FARMReader", "params": {"context_window_size": 150, "batch_size": 50, "use_gpu": true, "no_ans_boost": 0.0, "return_no_answer": false, "top_k_per_candidate": 3, "top_k_per_sample": 1, "num_processes": 0, "max_seq_len": 256, "doc_stride": 128, "progress_bar": true, "duplicate_filtering": 0, "use_confidence_scores": true, "confidence_threshold": 0, "use_auth_token": false}}], "pipelines": [{"name": "my_question_answering_pipeline", "nodes": [{"inputs": ["Query"], "name": "question_generator"}, {"inputs": ["question_generator"], "name": "farm_reader"}]}]}<end_of_text> |
<start_of_text>Build FAQPipeline using ElasticsearchRetriever and open search document store<response>{"version": "1.6.0", "components": [{"name": "open_search_document_store", "type": "OpenSearchDocumentStore", "params": {"label_index": "label", "name_field": "name", "create_index": true}}, {"name": "elasticsearch_retriever", "type": "ElasticsearchRetriever", "params": {}}], "pipelines": [{"name": "my_doc_search_pipeline", "nodes": [{"inputs": ["Query"], "name": "elasticsearch_retriever"}, {"inputs": ["elasticsearch_retriever"]}]}]}<end_of_text> |
<start_of_text>Create generative qa system using seq2 seq generator, TableTextRetriever and faiss document store<response>{"version": "1.6.0", "components": [{"name": "faiss_document_store", "type": "FAISSDocumentStore", "params": {"sql_url": "sqlite:///faiss_document_store.db", "vector_dim": 0, "embedding_dim": 768, "faiss_index_factory_str": "Flat", "return_embedding": false, "index": "document", "similarity": "dot_product", "embedding_field": "embedding", "progress_bar": true, "duplicate_documents": "overwrite", "n_links": 64, "ef_search": 20, "ef_construction": 80, "validate_index_sync": true}}, {"name": "table_text_retriever", "type": "TableTextRetriever", "params": {"max_seq_len_query": 64, "max_seq_len_passage": 256, "max_seq_len_table": 256, "top_k": 10, "use_gpu": true, "batch_size": 16, "embed_meta_fields": ["name", "section_title", "caption"], "use_fast_tokenizers": true, "infer_tokenizer_classes": false, "similarity_function": "dot_product", "global_loss_buffer_size": 150000, "progress_bar": true, "use_auth_token": false, "scale_score": true}}, {"name": "seq2_seq_generator", "type": "Seq2SeqGenerator", "params": {"top_k": 1, "max_length": 200, "min_length": 2, "num_beams": 8, "use_gpu": true}}], "pipelines": [{"name": "my_generator_pipeline", "nodes": [{"inputs": ["Query"], "name": "table_text_retriever"}, {"inputs": ["table_text_retriever"], "name": "seq2_seq_generator"}]}]}<end_of_text> |
<start_of_text>Generate Haystack extractive qa system using TransformersReader, elasticsearch filter only retriever and weaviate document store<response>{"version": "1.6.0", "components": [{"name": "weaviate_document_store", "type": "WeaviateDocumentStore", "params": {"port": 0, "timeout_config": [5, 15], "embedding_dim": 768, "content_field": "content", "name_field": "name", "similarity": "cosine", "index_type": "hnsw", "return_embedding": false, "progress_bar": true, "duplicate_documents": "overwrite", "recreate_index": false}}, {"name": "elasticsearch_filter_only_retriever", "type": "ElasticsearchFilterOnlyRetriever", "params": {}}, {"name": "transformers_reader", "type": "TransformersReader", "params": {"context_window_size": 70, "use_gpu": true, "top_k": 10, "top_k_per_candidate": 3, "return_no_answers": false, "max_seq_len": 256, "doc_stride": 128}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "elasticsearch_filter_only_retriever"}, {"inputs": ["elasticsearch_filter_only_retriever"], "name": "transformers_reader"}]}]}<end_of_text> |
<start_of_text>Build Haystack question generation system<response>{"version": "1.6.0", "components": [{"name": "QuestionGenerator", "params": {}, "type": "QuestionGenerator"}], "pipelines": [{"name": "query", "nodes": [{"inputs": ["Query"], "name": "QuestionGenerator"}]}]}<end_of_text> |
<start_of_text>Create extractive qa system using TransformersReader, bm25 retriever and SQLDocumentStore<response>{"version": "1.6.0", "components": [{"name": "sql_document_store", "type": "SQLDocumentStore", "params": {}}, {"name": "bm25_retriever", "type": "BM25Retriever", "params": {}}, {"name": "transformers_reader", "type": "TransformersReader", "params": {}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "bm25_retriever"}, {"inputs": ["bm25_retriever"], "name": "transformers_reader"}]}]}<end_of_text> |
<start_of_text>Generate Haystack search pipeline using bm25 retriever and elasticsearch document store<response>{"version": "1.6.0", "components": [{"name": "elasticsearch_document_store", "type": "ElasticsearchDocumentStore", "params": {"content_field": "content", "similarity": "dot_product", "return_embedding": false, "duplicate_documents": "overwrite", "index_type": "flat"}}, {"name": "bm25_retriever", "type": "BM25Retriever", "params": {}}], "pipelines": [{"name": "my_doc_search_pipeline", "nodes": [{"inputs": ["Query"], "name": "bm25_retriever"}, {"inputs": ["bm25_retriever"]}]}]}<end_of_text> |
<start_of_text>Create generative qa pipeline consisting of seq2 seq generator, TableTextRetriever and faiss document store<response>{"version": "1.6.0", "components": [{"name": "faiss_document_store", "type": "FAISSDocumentStore", "params": {"sql_url": "sqlite:///faiss_document_store.db", "vector_dim": 0, "embedding_dim": 768, "faiss_index_factory_str": "Flat", "return_embedding": false, "index": "document", "similarity": "dot_product", "embedding_field": "embedding", "progress_bar": true, "duplicate_documents": "overwrite", "n_links": 64, "ef_search": 20, "ef_construction": 80, "validate_index_sync": true}}, {"name": "table_text_retriever", "type": "TableTextRetriever", "params": {"max_seq_len_query": 64, "max_seq_len_passage": 256, "max_seq_len_table": 256, "top_k": 10, "use_gpu": true, "batch_size": 16, "embed_meta_fields": ["name", "section_title", "caption"], "use_fast_tokenizers": true, "infer_tokenizer_classes": false, "similarity_function": "dot_product", "global_loss_buffer_size": 150000, "progress_bar": true, "use_auth_token": false, "scale_score": true}}, {"name": "seq2_seq_generator", "type": "Seq2SeqGenerator", "params": {"top_k": 1, "max_length": 200, "min_length": 2, "num_beams": 8, "use_gpu": true}}], "pipelines": [{"name": "my_generator_pipeline", "nodes": [{"inputs": ["Query"], "name": "table_text_retriever"}, {"inputs": ["table_text_retriever"], "name": "seq2_seq_generator"}]}]}<end_of_text> |
<start_of_text>Build Haystack document search system with dense passage retriever and PineconeDocumentStore<response>{"version": "1.6.0", "components": [{"name": "pinecone_document_store", "type": "PineconeDocumentStore", "params": {"embedding_dim": 768, "recreate_index": false, "validate_index_sync": true}}, {"name": "dense_passage_retriever", "type": "DensePassageRetriever", "params": {"max_seq_len_query": 64, "infer_tokenizer_classes": false, "use_auth_token": false}}], "pipelines": [{"name": "my_doc_search_pipeline", "nodes": [{"inputs": ["Query"], "name": "dense_passage_retriever"}, {"inputs": ["dense_passage_retriever"]}]}]}<end_of_text> |
<start_of_text>Make QuestionAnswerGenerationPipeline with rci reader and question generator<response>{"version": "1.6.0", "components": [{"name": "question_generator", "type": "QuestionGenerator", "params": {}}, {"name": "rci_reader", "type": "RCIReader", "params": {}}], "pipelines": [{"name": "my_question_answering_pipeline", "nodes": [{"inputs": ["Query"], "name": "question_generator"}, {"inputs": ["question_generator"], "name": "rci_reader"}]}]}<end_of_text> |
<start_of_text>Generate GenerativeQAPipeline using seq2 seq generator, ElasticsearchRetriever and elasticsearch document store<response>{"version": "1.6.0", "components": [{"name": "elasticsearch_document_store", "type": "ElasticsearchDocumentStore", "params": {"port": 0, "index": "document", "label_index": "label", "content_field": "content", "name_field": "name", "embedding_field": "embedding", "embedding_dim": 768, "analyzer": "standard", "scheme": "http", "verify_certs": true, "recreate_index": false, "create_index": true, "refresh_type": "wait_for", "similarity": "dot_product", "timeout": 30, "return_embedding": false, "duplicate_documents": "overwrite", "index_type": "flat", "scroll": "1d", "skip_missing_embeddings": true, "synonym_type": "synonym", "use_system_proxy": false}}, {"name": "elasticsearch_retriever", "type": "ElasticsearchRetriever", "params": {"top_k": 10, "all_terms_must_match": false}}, {"name": "seq2_seq_generator", "type": "Seq2SeqGenerator", "params": {"top_k": 1, "max_length": 200, "min_length": 2, "num_beams": 8, "use_gpu": true}}], "pipelines": [{"name": "my_generator_pipeline", "nodes": [{"inputs": ["Query"], "name": "elasticsearch_retriever"}, {"inputs": ["elasticsearch_retriever"], "name": "seq2_seq_generator"}]}]}<end_of_text> |
<start_of_text>Make Haystack FAQPipeline consisting of bm25 retriever and sql document store<response>{"version": "1.6.0", "components": [{"name": "sql_document_store", "type": "SQLDocumentStore", "params": {"label_index": "label", "duplicate_documents": "overwrite", "check_same_thread": false}}, {"name": "bm25_retriever", "type": "BM25Retriever", "params": {"all_terms_must_match": false}}], "pipelines": [{"name": "my_doc_search_pipeline", "nodes": [{"inputs": ["Query"], "name": "bm25_retriever"}, {"inputs": ["bm25_retriever"]}]}]}<end_of_text> |
<start_of_text>Build extractive qa pipeline using RCIReader, BM25Retriever and FAISSDocumentStore<response>{"version": "1.6.0", "components": [{"name": "faiss_document_store", "type": "FAISSDocumentStore", "params": {"sql_url": "sqlite:///faiss_document_store.db", "embedding_field": "embedding"}}, {"name": "bm25_retriever", "type": "BM25Retriever", "params": {}}, {"name": "rci_reader", "type": "RCIReader", "params": {}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "bm25_retriever"}, {"inputs": ["bm25_retriever"], "name": "rci_reader"}]}]}<end_of_text> |
<start_of_text>Build search summarization using TransformersSummarizer, MultihopEmbeddingRetriever and weaviate document store<response>{"version": "1.6.0", "components": [{"name": "weaviate_document_store", "type": "WeaviateDocumentStore", "params": {}}, {"name": "multihop_embedding_retriever", "type": "MultihopEmbeddingRetriever", "params": {}}, {"name": "transformers_summarizer", "type": "TransformersSummarizer", "params": {}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "multihop_embedding_retriever"}, {"inputs": ["multihop_embedding_retriever"], "name": "transformers_summarizer"}]}]}<end_of_text> |
<start_of_text>Make document search pipeline with dense passage retriever and OpenSearchDocumentStore<response>{"version": "1.6.0", "components": [{"name": "open_search_document_store", "type": "OpenSearchDocumentStore", "params": {"username": "admin", "password": "admin", "verify_certs": false, "refresh_type": "wait_for", "skip_missing_embeddings": true, "synonym_type": "synonym"}}, {"name": "dense_passage_retriever", "type": "DensePassageRetriever", "params": {}}], "pipelines": [{"name": "my_doc_search_pipeline", "nodes": [{"inputs": ["Query"], "name": "dense_passage_retriever"}, {"inputs": ["dense_passage_retriever"]}]}]}<end_of_text> |
<start_of_text>Build Haystack search summarization system using TransformersSummarizer, MultihopEmbeddingRetriever and InMemoryDocumentStore<response>{"version": "1.6.0", "components": [{"name": "in_memory_document_store", "type": "InMemoryDocumentStore", "params": {}}, {"name": "multihop_embedding_retriever", "type": "MultihopEmbeddingRetriever", "params": {}}, {"name": "transformers_summarizer", "type": "TransformersSummarizer", "params": {}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "multihop_embedding_retriever"}, {"inputs": ["multihop_embedding_retriever"], "name": "transformers_summarizer"}]}]}<end_of_text> |
<start_of_text>Make search summarization pipeline consisting of TransformersSummarizer, table text retriever and open search document store<response>{"version": "1.6.0", "components": [{"name": "open_search_document_store", "type": "OpenSearchDocumentStore", "params": {"username": "admin", "password": "admin", "port": 0, "index": "document", "label_index": "label", "content_field": "content", "name_field": "name", "embedding_field": "embedding", "embedding_dim": 768, "analyzer": "standard", "verify_certs": false, "recreate_index": false, "create_index": true, "refresh_type": "wait_for", "timeout": 30, "duplicate_documents": "overwrite", "index_type": "flat", "scroll": "1d", "skip_missing_embeddings": true, "synonym_type": "synonym", "use_system_proxy": false}}, {"name": "table_text_retriever", "type": "TableTextRetriever", "params": {"max_seq_len_query": 64, "max_seq_len_passage": 256, "max_seq_len_table": 256, "top_k": 10, "use_gpu": true, "batch_size": 16, "embed_meta_fields": ["name", "section_title", "caption"], "use_fast_tokenizers": true, "infer_tokenizer_classes": false, "similarity_function": "dot_product", "use_auth_token": false}}, {"name": "transformers_summarizer", "type": "TransformersSummarizer", "params": {"model_name_or_path": "google/pegasus-xsum", "min_length": 5, "use_gpu": true, "generate_single_summary": false, "batch_size": 0}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "table_text_retriever"}, {"inputs": ["table_text_retriever"], "name": "transformers_summarizer"}]}]}<end_of_text> |
<start_of_text>Generate Haystack question generation system<response>{"version": "1.6.0", "components": [{"name": "QuestionGenerator", "params": {}, "type": "QuestionGenerator"}], "pipelines": [{"name": "query", "nodes": [{"inputs": ["Query"], "name": "QuestionGenerator"}]}]}<end_of_text> |
<start_of_text>Build Haystack extractive qa system consisting of rci reader, multihop embedding retriever and open search document store<response>{"version": "1.6.0", "components": [{"name": "open_search_document_store", "type": "OpenSearchDocumentStore", "params": {}}, {"name": "multihop_embedding_retriever", "type": "MultihopEmbeddingRetriever", "params": {}}, {"name": "rci_reader", "type": "RCIReader", "params": {}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "multihop_embedding_retriever"}, {"inputs": ["multihop_embedding_retriever"], "name": "rci_reader"}]}]}<end_of_text> |
<start_of_text>Make extractive qa consisting of TransformersReader, bm25 retriever and SQLDocumentStore<response>{"version": "1.6.0", "components": [{"name": "sql_document_store", "type": "SQLDocumentStore", "params": {}}, {"name": "bm25_retriever", "type": "BM25Retriever", "params": {}}, {"name": "transformers_reader", "type": "TransformersReader", "params": {}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "bm25_retriever"}, {"inputs": ["bm25_retriever"], "name": "transformers_reader"}]}]}<end_of_text> |
<start_of_text>Make Haystack question generation pipeline<response>{"version": "1.6.0", "components": [{"name": "QuestionGenerator", "params": {}, "type": "QuestionGenerator"}], "pipelines": [{"name": "query", "nodes": [{"inputs": ["Query"], "name": "QuestionGenerator"}]}]}<end_of_text> |
<start_of_text>Create question generation system<response>{"version": "1.6.0", "components": [{"name": "QuestionGenerator", "params": {}, "type": "QuestionGenerator"}], "pipelines": [{"name": "query", "nodes": [{"inputs": ["Query"], "name": "QuestionGenerator"}]}]}<end_of_text> |
<start_of_text>Generate SearchSummarizationPipeline consisting of TransformersSummarizer, elasticsearch filter only retriever and OpenSearchDocumentStore<response>{"version": "1.6.0", "components": [{"name": "open_search_document_store", "type": "OpenSearchDocumentStore", "params": {"index": "document", "analyzer": "standard", "recreate_index": false, "refresh_type": "wait_for"}}, {"name": "elasticsearch_filter_only_retriever", "type": "ElasticsearchFilterOnlyRetriever", "params": {}}, {"name": "transformers_summarizer", "type": "TransformersSummarizer", "params": {}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "elasticsearch_filter_only_retriever"}, {"inputs": ["elasticsearch_filter_only_retriever"], "name": "transformers_summarizer"}]}]}<end_of_text> |
<start_of_text>Create FAQPipeline using FilterRetriever and DeepsetCloudDocumentStore<response>{"version": "1.6.0", "components": [{"name": "deepset_cloud_document_store", "type": "DeepsetCloudDocumentStore", "params": {}}, {"name": "filter_retriever", "type": "FilterRetriever", "params": {}}], "pipelines": [{"name": "my_doc_search_pipeline", "nodes": [{"inputs": ["Query"], "name": "filter_retriever"}, {"inputs": ["filter_retriever"]}]}]}<end_of_text> |
<start_of_text>Make Haystack generative qa system consisting of ra generator, filter retriever and open search document store<response>{"version": "1.6.0", "components": [{"name": "open_search_document_store", "type": "OpenSearchDocumentStore", "params": {"scheme": "https", "username": "admin", "password": "admin", "port": 0, "index": "document", "label_index": "label", "content_field": "content", "name_field": "name", "embedding_field": "embedding", "embedding_dim": 768, "analyzer": "standard", "verify_certs": false, "recreate_index": false, "create_index": true, "refresh_type": "wait_for", "similarity": "dot_product", "timeout": 30, "return_embedding": false, "duplicate_documents": "overwrite", "index_type": "flat", "scroll": "1d", "skip_missing_embeddings": true, "synonym_type": "synonym", "use_system_proxy": false}}, {"name": "filter_retriever", "type": "FilterRetriever", "params": {"top_k": 10, "all_terms_must_match": false, "scale_score": true}}, {"name": "ra_generator", "type": "RAGenerator", "params": {"model_name_or_path": "facebook/rag-token-nq", "generator_type": "token", "top_k": 2, "max_length": 200, "min_length": 2, "num_beams": 2, "embed_title": true, "use_gpu": true}}], "pipelines": [{"name": "my_generator_pipeline", "nodes": [{"inputs": ["Query"], "name": "filter_retriever"}, {"inputs": ["filter_retriever"], "name": "ra_generator"}]}]}<end_of_text> |
<start_of_text>Build FAQPipeline consisting of TfidfRetriever and sql document store<response>{"version": "1.6.0", "components": [{"name": "sql_document_store", "type": "SQLDocumentStore", "params": {}}, {"name": "tfidf_retriever", "type": "TfidfRetriever", "params": {}}], "pipelines": [{"name": "my_doc_search_pipeline", "nodes": [{"inputs": ["Query"], "name": "tfidf_retriever"}, {"inputs": ["tfidf_retriever"]}]}]}<end_of_text> |
<start_of_text>Create SearchSummarizationPipeline consisting of transformers summarizer, embedding retriever and deepset cloud document store<response>{"version": "1.6.0", "components": [{"name": "deepset_cloud_document_store", "type": "DeepsetCloudDocumentStore", "params": {}}, {"name": "embedding_retriever", "type": "EmbeddingRetriever", "params": {"use_gpu": true, "batch_size": 32, "top_k": 10, "scale_score": true}}, {"name": "transformers_summarizer", "type": "TransformersSummarizer", "params": {"model_name_or_path": "google/pegasus-xsum", "min_length": 5, "generate_single_summary": false}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "embedding_retriever"}, {"inputs": ["embedding_retriever"], "name": "transformers_summarizer"}]}]}<end_of_text> |
<start_of_text>Create Haystack faq search pipeline using tfidf retriever and OpenDistroElasticsearchDocumentStore<response>{"version": "1.6.0", "components": [{"name": "open_distro_elasticsearch_document_store", "type": "OpenDistroElasticsearchDocumentStore", "params": {"recreate_index": false}}, {"name": "tfidf_retriever", "type": "TfidfRetriever", "params": {}}], "pipelines": [{"name": "my_doc_search_pipeline", "nodes": [{"inputs": ["Query"], "name": "tfidf_retriever"}, {"inputs": ["tfidf_retriever"]}]}]}<end_of_text> |
<start_of_text>Make SearchSummarizationPipeline using transformers summarizer, bm25 retriever and weaviate document store<response>{"version": "1.6.0", "components": [{"name": "weaviate_document_store", "type": "WeaviateDocumentStore", "params": {"index": "Document", "embedding_dim": 768, "content_field": "content", "similarity": "cosine", "progress_bar": true, "duplicate_documents": "overwrite"}}, {"name": "bm25_retriever", "type": "BM25Retriever", "params": {}}, {"name": "transformers_summarizer", "type": "TransformersSummarizer", "params": {"model_name_or_path": "google/pegasus-xsum"}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "bm25_retriever"}, {"inputs": ["bm25_retriever"], "name": "transformers_summarizer"}]}]}<end_of_text> |
<start_of_text>Make search summarization system using transformers summarizer, DensePassageRetriever and sql document store<response>{"version": "1.6.0", "components": [{"name": "sql_document_store", "type": "SQLDocumentStore", "params": {}}, {"name": "dense_passage_retriever", "type": "DensePassageRetriever", "params": {"use_gpu": true, "similarity_function": "dot_product"}}, {"name": "transformers_summarizer", "type": "TransformersSummarizer", "params": {}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "dense_passage_retriever"}, {"inputs": ["dense_passage_retriever"], "name": "transformers_summarizer"}]}]}<end_of_text> |
<start_of_text>Make GenerativeQAPipeline with RAGenerator, TfidfRetriever and OpenSearchDocumentStore<response>{"version": "1.6.0", "components": [{"name": "open_search_document_store", "type": "OpenSearchDocumentStore", "params": {"scheme": "https", "username": "admin", "password": "admin", "port": 0, "index": "document", "label_index": "label", "content_field": "content", "name_field": "name", "embedding_field": "embedding", "embedding_dim": 768, "analyzer": "standard", "verify_certs": false, "recreate_index": false, "create_index": true, "refresh_type": "wait_for", "similarity": "dot_product", "timeout": 30, "return_embedding": false, "duplicate_documents": "overwrite", "index_type": "flat", "scroll": "1d", "skip_missing_embeddings": true, "synonym_type": "synonym", "use_system_proxy": false}}, {"name": "tfidf_retriever", "type": "TfidfRetriever", "params": {"top_k": 10}}, {"name": "ra_generator", "type": "RAGenerator", "params": {"model_name_or_path": "facebook/rag-token-nq", "generator_type": "token", "top_k": 2, "max_length": 200, "min_length": 2, "num_beams": 2, "embed_title": true, "use_gpu": true}}], "pipelines": [{"name": "my_generator_pipeline", "nodes": [{"inputs": ["Query"], "name": "tfidf_retriever"}, {"inputs": ["tfidf_retriever"], "name": "ra_generator"}]}]}<end_of_text> |
<start_of_text>Generate extractive qa system using rci reader, bm25 retriever and PineconeDocumentStore<response>{"version": "1.6.0", "components": [{"name": "pinecone_document_store", "type": "PineconeDocumentStore", "params": {"embedding_dim": 768, "shards": 1, "embedding_field": "embedding", "progress_bar": true, "recreate_index": false, "metadata_config": {}}}, {"name": "bm25_retriever", "type": "BM25Retriever", "params": {}}, {"name": "rci_reader", "type": "RCIReader", "params": {}}], "pipelines": [{"name": "my_query_pipeline", "nodes": [{"inputs": ["Query"], "name": "bm25_retriever"}, {"inputs": ["bm25_retriever"], "name": "rci_reader"}]}]}<end_of_text> |
Subsets and Splits