prompt stringlengths 31 149 | pipeline stringlengths 473 1.03k |
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Make Haystack search pipeline consisting of DensePassageRetriever and DeepsetCloudDocumentStore | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "deepset_cloud_document_store",
"type": "DeepsetCloudDocumentStore",
"params": {}
},
{
"name": "dense_passage_retriever",
"type": "DensePassageRetriever",
"params"... |
Build generative pipeline using Seq2SeqGenerator, TfidfRetriever and InMemoryDocumentStore | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "in_memory_document_store",
"type": "InMemoryDocumentStore",
"params": {}
},
{
"name": "tfidf_retriever",
"type": "TfidfRetriever",
"params": {}
},
... |
Build Haystack FAQPipeline using bm25 retriever and deepset cloud document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "deepset_cloud_document_store",
"type": "DeepsetCloudDocumentStore",
"params": {}
},
{
"name": "bm25_retriever",
"type": "BM25Retriever",
"params": {}
}
... |
Make question answer generation system using TableReader and QuestionGenerator | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "question_generator",
"type": "QuestionGenerator",
"params": {}
},
{
"name": "table_reader",
"type": "TableReader",
"params": {}
}
],
"pipelines": ... |
Generate question answer generation system with table reader and QuestionGenerator | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "question_generator",
"type": "QuestionGenerator",
"params": {}
},
{
"name": "table_reader",
"type": "TableReader",
"params": {}
}
],
"pipelines": ... |
Create Haystack faq search pipeline consisting of TableTextRetriever and InMemoryDocumentStore | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "in_memory_document_store",
"type": "InMemoryDocumentStore",
"params": {}
},
{
"name": "table_text_retriever",
"type": "TableTextRetriever",
"params": {}
}... |
Generate extractive qa pipeline with transformers reader, elasticsearch filter only retriever and DeepsetCloudDocumentStore | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "deepset_cloud_document_store",
"type": "DeepsetCloudDocumentStore",
"params": {}
},
{
"name": "elasticsearch_filter_only_retriever",
"type": "ElasticsearchFilterOnlyRetriever... |
Generate Haystack question answer generation pipeline with rci reader and QuestionGenerator | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "question_generator",
"type": "QuestionGenerator",
"params": {}
},
{
"name": "rci_reader",
"type": "RCIReader",
"params": {}
}
],
"pipelines": [
... |
Build Haystack generative qa system using seq2 seq generator, tfidf retriever and FAISSDocumentStore | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "faiss_document_store",
"type": "FAISSDocumentStore",
"params": {}
},
{
"name": "tfidf_retriever",
"type": "TfidfRetriever",
"params": {}
},
{
... |
Create QuestionAnswerGenerationPipeline using rci reader and question generator | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "question_generator",
"type": "QuestionGenerator",
"params": {}
},
{
"name": "rci_reader",
"type": "RCIReader",
"params": {}
}
],
"pipelines": [
... |
Generate Haystack GenerativeQAPipeline using Seq2SeqGenerator, MultihopEmbeddingRetriever and elasticsearch document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "elasticsearch_document_store",
"type": "ElasticsearchDocumentStore",
"params": {}
},
{
"name": "multihop_embedding_retriever",
"type": "MultihopEmbeddingRetriever",
... |
Build generative qa pipeline using ra generator, TfidfRetriever and ElasticsearchDocumentStore | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "elasticsearch_document_store",
"type": "ElasticsearchDocumentStore",
"params": {}
},
{
"name": "tfidf_retriever",
"type": "TfidfRetriever",
"params": {}
}... |
Build Haystack qa system using RCIReader, FilterRetriever and in memory document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "in_memory_document_store",
"type": "InMemoryDocumentStore",
"params": {}
},
{
"name": "filter_retriever",
"type": "FilterRetriever",
"params": {}
},
... |
Build search pipeline using MultihopEmbeddingRetriever and DeepsetCloudDocumentStore | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "deepset_cloud_document_store",
"type": "DeepsetCloudDocumentStore",
"params": {}
},
{
"name": "multihop_embedding_retriever",
"type": "MultihopEmbeddingRetriever",
... |
Make Haystack search summarization using transformers summarizer, embedding retriever and WeaviateDocumentStore | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "weaviate_document_store",
"type": "WeaviateDocumentStore",
"params": {}
},
{
"name": "embedding_retriever",
"type": "EmbeddingRetriever",
"params": {}
},
... |
Build Haystack generative qa pipeline with seq2 seq generator, EmbeddingRetriever and FAISSDocumentStore | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "faiss_document_store",
"type": "FAISSDocumentStore",
"params": {}
},
{
"name": "embedding_retriever",
"type": "EmbeddingRetriever",
"params": {}
},
... |
Build Haystack generative qa using ra generator, bm25 retriever and elasticsearch document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "elasticsearch_document_store",
"type": "ElasticsearchDocumentStore",
"params": {}
},
{
"name": "bm25_retriever",
"type": "BM25Retriever",
"params": {}
},
... |
Create FAQPipeline with ElasticsearchFilterOnlyRetriever and OpenSearchDocumentStore | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "open_search_document_store",
"type": "OpenSearchDocumentStore",
"params": {}
},
{
"name": "elasticsearch_filter_only_retriever",
"type": "ElasticsearchFilterOnlyRetriever",
... |
Generate search pipeline using bm25 retriever and sql document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "sql_document_store",
"type": "SQLDocumentStore",
"params": {}
},
{
"name": "bm25_retriever",
"type": "BM25Retriever",
"params": {}
}
],
"pipelines... |
Build ExtractiveQAPipeline consisting of transformers reader, filter retriever and ElasticsearchDocumentStore | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "elasticsearch_document_store",
"type": "ElasticsearchDocumentStore",
"params": {}
},
{
"name": "filter_retriever",
"type": "FilterRetriever",
"params": {}
... |
Generate Haystack QuestionAnswerGenerationPipeline with RCIReader and QuestionGenerator | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "question_generator",
"type": "QuestionGenerator",
"params": {}
},
{
"name": "rci_reader",
"type": "RCIReader",
"params": {}
}
],
"pipelines": [
... |
Build Haystack qa pipeline using rci reader, ElasticsearchRetriever and faiss document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "faiss_document_store",
"type": "FAISSDocumentStore",
"params": {}
},
{
"name": "elasticsearch_retriever",
"type": "ElasticsearchRetriever",
"params": {}
}... |
Create QuestionGenerationPipeline | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "QuestionGenerator",
"params": {},
"type": "QuestionGenerator"
}
],
"pipelines": [
{
"name": "query",
"nodes": [
{
"inputs": [
... |
Create question answer generation pipeline with transformers reader and question generator | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "question_generator",
"type": "QuestionGenerator",
"params": {}
},
{
"name": "transformers_reader",
"type": "TransformersReader",
"params": {}
}
],
... |
Generate document search system using EmbeddingRetriever and weaviate document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "weaviate_document_store",
"type": "WeaviateDocumentStore",
"params": {}
},
{
"name": "embedding_retriever",
"type": "EmbeddingRetriever",
"params": {}
}
... |
Generate Haystack question generation system | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "QuestionGenerator",
"params": {},
"type": "QuestionGenerator"
}
],
"pipelines": [
{
"name": "query",
"nodes": [
{
"inputs": [
... |
Generate SearchSummarizationPipeline consisting of TransformersSummarizer, table text retriever and ElasticsearchDocumentStore | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "elasticsearch_document_store",
"type": "ElasticsearchDocumentStore",
"params": {}
},
{
"name": "table_text_retriever",
"type": "TableTextRetriever",
"params": {}
... |
Build DocumentSearchPipeline using tfidf retriever and elasticsearch document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "elasticsearch_document_store",
"type": "ElasticsearchDocumentStore",
"params": {}
},
{
"name": "tfidf_retriever",
"type": "TfidfRetriever",
"params": {}
}... |
Generate document search pipeline consisting of dense passage retriever and WeaviateDocumentStore | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "weaviate_document_store",
"type": "WeaviateDocumentStore",
"params": {}
},
{
"name": "dense_passage_retriever",
"type": "DensePassageRetriever",
"params": {}
... |
Generate question generation system | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "QuestionGenerator",
"params": {},
"type": "QuestionGenerator"
}
],
"pipelines": [
{
"name": "query",
"nodes": [
{
"inputs": [
... |
Generate GenerativeQAPipeline with seq2 seq generator, TfidfRetriever and InMemoryDocumentStore | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "in_memory_document_store",
"type": "InMemoryDocumentStore",
"params": {}
},
{
"name": "tfidf_retriever",
"type": "TfidfRetriever",
"params": {}
},
... |
Create Haystack question answer generation pipeline using table reader and QuestionGenerator | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "question_generator",
"type": "QuestionGenerator",
"params": {}
},
{
"name": "table_reader",
"type": "TableReader",
"params": {}
}
],
"pipelines": ... |
Build Haystack QuestionAnswerGenerationPipeline using farm reader and question generator | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "question_generator",
"type": "QuestionGenerator",
"params": {}
},
{
"name": "farm_reader",
"type": "FARMReader",
"params": {}
}
],
"pipelines": [
... |
Build generative qa pipeline consisting of Seq2SeqGenerator, tfidf retriever and DeepsetCloudDocumentStore | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "deepset_cloud_document_store",
"type": "DeepsetCloudDocumentStore",
"params": {}
},
{
"name": "tfidf_retriever",
"type": "TfidfRetriever",
"params": {}
},... |
Make Haystack generative pipeline consisting of seq2 seq generator, tfidf retriever and DeepsetCloudDocumentStore | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "deepset_cloud_document_store",
"type": "DeepsetCloudDocumentStore",
"params": {}
},
{
"name": "tfidf_retriever",
"type": "TfidfRetriever",
"params": {}
},... |
Create Haystack GenerativeQAPipeline using seq2 seq generator, TfidfRetriever and faiss document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "faiss_document_store",
"type": "FAISSDocumentStore",
"params": {}
},
{
"name": "tfidf_retriever",
"type": "TfidfRetriever",
"params": {}
},
{
... |
Create Haystack search pipeline using filter retriever and elasticsearch document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "elasticsearch_document_store",
"type": "ElasticsearchDocumentStore",
"params": {}
},
{
"name": "filter_retriever",
"type": "FilterRetriever",
"params": {}
... |
Create faq pipeline using TfidfRetriever and sql document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "sql_document_store",
"type": "SQLDocumentStore",
"params": {}
},
{
"name": "tfidf_retriever",
"type": "TfidfRetriever",
"params": {}
}
],
"pipelin... |
Build Haystack extractive qa system consisting of TableReader, filter retriever and open distro elasticsearch document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "open_distro_elasticsearch_document_store",
"type": "OpenDistroElasticsearchDocumentStore",
"params": {}
},
{
"name": "filter_retriever",
"type": "FilterRetriever",
... |
Build search pipeline with multihop embedding retriever and deepset cloud document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "deepset_cloud_document_store",
"type": "DeepsetCloudDocumentStore",
"params": {}
},
{
"name": "multihop_embedding_retriever",
"type": "MultihopEmbeddingRetriever",
... |
Build QuestionAnswerGenerationPipeline using RCIReader and QuestionGenerator | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "question_generator",
"type": "QuestionGenerator",
"params": {}
},
{
"name": "rci_reader",
"type": "RCIReader",
"params": {}
}
],
"pipelines": [
... |
Create QuestionAnswerGenerationPipeline using transformers reader and question generator | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "question_generator",
"type": "QuestionGenerator",
"params": {}
},
{
"name": "transformers_reader",
"type": "TransformersReader",
"params": {}
}
],
... |
Create Haystack document search system using BM25Retriever and elasticsearch document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "elasticsearch_document_store",
"type": "ElasticsearchDocumentStore",
"params": {}
},
{
"name": "bm25_retriever",
"type": "BM25Retriever",
"params": {}
}
... |
Generate Haystack search summarization consisting of transformers summarizer, elasticsearch retriever and open distro elasticsearch document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "open_distro_elasticsearch_document_store",
"type": "OpenDistroElasticsearchDocumentStore",
"params": {}
},
{
"name": "elasticsearch_retriever",
"type": "ElasticsearchRetrieve... |
Build faq search pipeline using table text retriever and OpenDistroElasticsearchDocumentStore | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "open_distro_elasticsearch_document_store",
"type": "OpenDistroElasticsearchDocumentStore",
"params": {}
},
{
"name": "table_text_retriever",
"type": "TableTextRetriever",
... |
Make search summarization consisting of transformers summarizer, multihop embedding retriever and open search document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "open_search_document_store",
"type": "OpenSearchDocumentStore",
"params": {}
},
{
"name": "multihop_embedding_retriever",
"type": "MultihopEmbeddingRetriever",
"p... |
Generate DocumentSearchPipeline consisting of DensePassageRetriever and DeepsetCloudDocumentStore | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "deepset_cloud_document_store",
"type": "DeepsetCloudDocumentStore",
"params": {}
},
{
"name": "dense_passage_retriever",
"type": "DensePassageRetriever",
"params"... |
Generate extractive qa pipeline using transformers reader, BM25Retriever and sql document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "sql_document_store",
"type": "SQLDocumentStore",
"params": {}
},
{
"name": "bm25_retriever",
"type": "BM25Retriever",
"params": {}
},
{
... |
Generate Haystack extractive qa using RCIReader, bm25 retriever and FAISSDocumentStore | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "faiss_document_store",
"type": "FAISSDocumentStore",
"params": {}
},
{
"name": "bm25_retriever",
"type": "BM25Retriever",
"params": {}
},
{
... |
Generate Haystack question answer generation pipeline with RCIReader and QuestionGenerator | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "question_generator",
"type": "QuestionGenerator",
"params": {}
},
{
"name": "rci_reader",
"type": "RCIReader",
"params": {}
}
],
"pipelines": [
... |
Create QuestionAnswerGenerationPipeline with rci reader and question generator | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "question_generator",
"type": "QuestionGenerator",
"params": {}
},
{
"name": "rci_reader",
"type": "RCIReader",
"params": {}
}
],
"pipelines": [
... |
Build document search system with dense passage retriever and DeepsetCloudDocumentStore | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "deepset_cloud_document_store",
"type": "DeepsetCloudDocumentStore",
"params": {}
},
{
"name": "dense_passage_retriever",
"type": "DensePassageRetriever",
"params"... |
Make search pipeline with BM25Retriever and sql document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "sql_document_store",
"type": "SQLDocumentStore",
"params": {}
},
{
"name": "bm25_retriever",
"type": "BM25Retriever",
"params": {}
}
],
"pipelines... |
Generate ExtractiveQAPipeline consisting of transformers reader, ElasticsearchFilterOnlyRetriever and elasticsearch document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "elasticsearch_document_store",
"type": "ElasticsearchDocumentStore",
"params": {}
},
{
"name": "elasticsearch_filter_only_retriever",
"type": "ElasticsearchFilterOnlyRetrieve... |
Generate question answer generation pipeline with FARMReader and question generator | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "question_generator",
"type": "QuestionGenerator",
"params": {}
},
{
"name": "farm_reader",
"type": "FARMReader",
"params": {}
}
],
"pipelines": [
... |
Make Haystack QuestionAnswerGenerationPipeline with transformers reader and QuestionGenerator | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "question_generator",
"type": "QuestionGenerator",
"params": {}
},
{
"name": "transformers_reader",
"type": "TransformersReader",
"params": {}
}
],
... |
Generate Haystack QuestionAnswerGenerationPipeline consisting of rci reader and question generator | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "question_generator",
"type": "QuestionGenerator",
"params": {}
},
{
"name": "rci_reader",
"type": "RCIReader",
"params": {}
}
],
"pipelines": [
... |
Create faq system with embedding retriever and DeepsetCloudDocumentStore | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "deepset_cloud_document_store",
"type": "DeepsetCloudDocumentStore",
"params": {}
},
{
"name": "embedding_retriever",
"type": "EmbeddingRetriever",
"params": {}
... |
Make generative qa consisting of RAGenerator, TfidfRetriever and open search document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "open_search_document_store",
"type": "OpenSearchDocumentStore",
"params": {}
},
{
"name": "tfidf_retriever",
"type": "TfidfRetriever",
"params": {}
},
... |
Create document search system consisting of embedding retriever and SQLDocumentStore | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "sql_document_store",
"type": "SQLDocumentStore",
"params": {}
},
{
"name": "embedding_retriever",
"type": "EmbeddingRetriever",
"params": {}
}
],
... |
Build Haystack extractive qa system with farm reader, multihop embedding retriever and weaviate document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "weaviate_document_store",
"type": "WeaviateDocumentStore",
"params": {}
},
{
"name": "multihop_embedding_retriever",
"type": "MultihopEmbeddingRetriever",
"params... |
Build search pipeline using ElasticsearchRetriever and InMemoryDocumentStore | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "in_memory_document_store",
"type": "InMemoryDocumentStore",
"params": {}
},
{
"name": "elasticsearch_retriever",
"type": "ElasticsearchRetriever",
"params": {}
... |
Make Haystack question answer generation pipeline consisting of rci reader and question generator | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "question_generator",
"type": "QuestionGenerator",
"params": {}
},
{
"name": "rci_reader",
"type": "RCIReader",
"params": {}
}
],
"pipelines": [
... |
Make Haystack document search system with MultihopEmbeddingRetriever and elasticsearch document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "elasticsearch_document_store",
"type": "ElasticsearchDocumentStore",
"params": {}
},
{
"name": "multihop_embedding_retriever",
"type": "MultihopEmbeddingRetriever",
... |
Create faq pipeline consisting of elasticsearch retriever and open search document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "open_search_document_store",
"type": "OpenSearchDocumentStore",
"params": {}
},
{
"name": "elasticsearch_retriever",
"type": "ElasticsearchRetriever",
"params": {... |
Make qa system consisting of transformers reader, bm25 retriever and sql document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "sql_document_store",
"type": "SQLDocumentStore",
"params": {}
},
{
"name": "bm25_retriever",
"type": "BM25Retriever",
"params": {}
},
{
... |
Create document search pipeline using DensePassageRetriever and pinecone document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "pinecone_document_store",
"type": "PineconeDocumentStore",
"params": {}
},
{
"name": "dense_passage_retriever",
"type": "DensePassageRetriever",
"params": {}
... |
Generate Haystack QuestionGenerationPipeline | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "QuestionGenerator",
"params": {},
"type": "QuestionGenerator"
}
],
"pipelines": [
{
"name": "query",
"nodes": [
{
"inputs": [
... |
Create Haystack question answer generation pipeline using rci reader and QuestionGenerator | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "question_generator",
"type": "QuestionGenerator",
"params": {}
},
{
"name": "rci_reader",
"type": "RCIReader",
"params": {}
}
],
"pipelines": [
... |
Build extractive qa pipeline with FARMReader, table text retriever and deepset cloud document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "deepset_cloud_document_store",
"type": "DeepsetCloudDocumentStore",
"params": {}
},
{
"name": "table_text_retriever",
"type": "TableTextRetriever",
"params": {}
... |
Make search summarization using transformers summarizer, multihop embedding retriever and WeaviateDocumentStore | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "weaviate_document_store",
"type": "WeaviateDocumentStore",
"params": {}
},
{
"name": "multihop_embedding_retriever",
"type": "MultihopEmbeddingRetriever",
"params... |
Make Haystack document search pipeline consisting of ElasticsearchFilterOnlyRetriever and pinecone document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "pinecone_document_store",
"type": "PineconeDocumentStore",
"params": {}
},
{
"name": "elasticsearch_filter_only_retriever",
"type": "ElasticsearchFilterOnlyRetriever",
... |
Generate Haystack document search system using BM25Retriever and sql document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "sql_document_store",
"type": "SQLDocumentStore",
"params": {}
},
{
"name": "bm25_retriever",
"type": "BM25Retriever",
"params": {}
}
],
"pipelines... |
Generate generative qa pipeline with Seq2SeqGenerator, ElasticsearchRetriever and sql document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "sql_document_store",
"type": "SQLDocumentStore",
"params": {}
},
{
"name": "elasticsearch_retriever",
"type": "ElasticsearchRetriever",
"params": {}
},
... |
Build Haystack extractive qa pipeline with transformers reader, ElasticsearchFilterOnlyRetriever and elasticsearch document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "elasticsearch_document_store",
"type": "ElasticsearchDocumentStore",
"params": {}
},
{
"name": "elasticsearch_filter_only_retriever",
"type": "ElasticsearchFilterOnlyRetrieve... |
Make ExtractiveQAPipeline with rci reader, elasticsearch retriever and FAISSDocumentStore | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "faiss_document_store",
"type": "FAISSDocumentStore",
"params": {}
},
{
"name": "elasticsearch_retriever",
"type": "ElasticsearchRetriever",
"params": {}
}... |
Build search summarization with TransformersSummarizer, TableTextRetriever and open search document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "open_search_document_store",
"type": "OpenSearchDocumentStore",
"params": {}
},
{
"name": "table_text_retriever",
"type": "TableTextRetriever",
"params": {}
... |
Create Haystack qa system consisting of table reader, TfidfRetriever and open search document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "open_search_document_store",
"type": "OpenSearchDocumentStore",
"params": {}
},
{
"name": "tfidf_retriever",
"type": "TfidfRetriever",
"params": {}
},
... |
Build Haystack question answer generation pipeline with TransformersReader and QuestionGenerator | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "question_generator",
"type": "QuestionGenerator",
"params": {}
},
{
"name": "transformers_reader",
"type": "TransformersReader",
"params": {}
}
],
... |
Make Haystack QuestionGenerationPipeline | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "QuestionGenerator",
"params": {},
"type": "QuestionGenerator"
}
],
"pipelines": [
{
"name": "query",
"nodes": [
{
"inputs": [
... |
Build Haystack faq search pipeline using TableTextRetriever and InMemoryDocumentStore | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "in_memory_document_store",
"type": "InMemoryDocumentStore",
"params": {}
},
{
"name": "table_text_retriever",
"type": "TableTextRetriever",
"params": {}
}... |
Create search summarization with transformers summarizer, table text retriever and elasticsearch document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "elasticsearch_document_store",
"type": "ElasticsearchDocumentStore",
"params": {}
},
{
"name": "table_text_retriever",
"type": "TableTextRetriever",
"params": {}
... |
Generate search summarization pipeline with transformers summarizer, ElasticsearchFilterOnlyRetriever and pinecone document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "pinecone_document_store",
"type": "PineconeDocumentStore",
"params": {}
},
{
"name": "elasticsearch_filter_only_retriever",
"type": "ElasticsearchFilterOnlyRetriever",
... |
Make FAQPipeline with TableTextRetriever and in memory document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "in_memory_document_store",
"type": "InMemoryDocumentStore",
"params": {}
},
{
"name": "table_text_retriever",
"type": "TableTextRetriever",
"params": {}
}... |
Make Haystack ExtractiveQAPipeline consisting of table reader, filter retriever and OpenDistroElasticsearchDocumentStore | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "open_distro_elasticsearch_document_store",
"type": "OpenDistroElasticsearchDocumentStore",
"params": {}
},
{
"name": "filter_retriever",
"type": "FilterRetriever",
... |
Generate extractive qa using TransformersReader, elasticsearch filter only retriever and deepset cloud document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "deepset_cloud_document_store",
"type": "DeepsetCloudDocumentStore",
"params": {}
},
{
"name": "elasticsearch_filter_only_retriever",
"type": "ElasticsearchFilterOnlyRetriever... |
Create faq system with BM25Retriever and pinecone document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "pinecone_document_store",
"type": "PineconeDocumentStore",
"params": {}
},
{
"name": "bm25_retriever",
"type": "BM25Retriever",
"params": {}
}
],
... |
Make faq system consisting of filter retriever and deepset cloud document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "deepset_cloud_document_store",
"type": "DeepsetCloudDocumentStore",
"params": {}
},
{
"name": "filter_retriever",
"type": "FilterRetriever",
"params": {}
... |
Create search pipeline consisting of tfidf retriever and sql document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "sql_document_store",
"type": "SQLDocumentStore",
"params": {}
},
{
"name": "tfidf_retriever",
"type": "TfidfRetriever",
"params": {}
}
],
"pipelin... |
Build question answer generation system consisting of FARMReader and question generator | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "question_generator",
"type": "QuestionGenerator",
"params": {}
},
{
"name": "farm_reader",
"type": "FARMReader",
"params": {}
}
],
"pipelines": [
... |
Build Haystack question generation pipeline | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "QuestionGenerator",
"params": {},
"type": "QuestionGenerator"
}
],
"pipelines": [
{
"name": "query",
"nodes": [
{
"inputs": [
... |
Build question answer generation system with transformers reader and question generator | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "question_generator",
"type": "QuestionGenerator",
"params": {}
},
{
"name": "transformers_reader",
"type": "TransformersReader",
"params": {}
}
],
... |
Create Haystack search summarization pipeline with TransformersSummarizer, TableTextRetriever and open distro elasticsearch document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "open_distro_elasticsearch_document_store",
"type": "OpenDistroElasticsearchDocumentStore",
"params": {}
},
{
"name": "table_text_retriever",
"type": "TableTextRetriever",
... |
Make Haystack search summarization system using TransformersSummarizer, elasticsearch filter only retriever and DeepsetCloudDocumentStore | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "deepset_cloud_document_store",
"type": "DeepsetCloudDocumentStore",
"params": {}
},
{
"name": "elasticsearch_filter_only_retriever",
"type": "ElasticsearchFilterOnlyRetriever... |
Make document search pipeline consisting of ElasticsearchFilterOnlyRetriever and PineconeDocumentStore | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "pinecone_document_store",
"type": "PineconeDocumentStore",
"params": {}
},
{
"name": "elasticsearch_filter_only_retriever",
"type": "ElasticsearchFilterOnlyRetriever",
... |
Create Haystack FAQPipeline using elasticsearch retriever and OpenSearchDocumentStore | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "open_search_document_store",
"type": "OpenSearchDocumentStore",
"params": {}
},
{
"name": "elasticsearch_retriever",
"type": "ElasticsearchRetriever",
"params": {... |
Create FAQPipeline with filter retriever and InMemoryDocumentStore | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "in_memory_document_store",
"type": "InMemoryDocumentStore",
"params": {}
},
{
"name": "filter_retriever",
"type": "FilterRetriever",
"params": {}
}
],... |
Create Haystack SearchSummarizationPipeline consisting of transformers summarizer, bm25 retriever and faiss document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "faiss_document_store",
"type": "FAISSDocumentStore",
"params": {}
},
{
"name": "bm25_retriever",
"type": "BM25Retriever",
"params": {}
},
{
... |
Create extractive qa pipeline consisting of transformers reader, filter retriever and ElasticsearchDocumentStore | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "elasticsearch_document_store",
"type": "ElasticsearchDocumentStore",
"params": {}
},
{
"name": "filter_retriever",
"type": "FilterRetriever",
"params": {}
... |
Generate qa pipeline with FARMReader, ElasticsearchFilterOnlyRetriever and sql document store | <SOS>{
"version": "1.6.0",
"components": [
{
"name": "sql_document_store",
"type": "SQLDocumentStore",
"params": {}
},
{
"name": "elasticsearch_filter_only_retriever",
"type": "ElasticsearchFilterOnlyRetriever",
"par... |
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