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Build Haystack question answer generation pipeline using TableReader and question generator
{"version": "1.8.0", "components": [{"name": "question_generator", "type": "QuestionGenerator", "params": {"sep_token": "<sep>", "batch_size": 16, "progress_bar": true, "use_auth_token": false}}, {"name": "table_reader", "type": "TableReader", "params": {"model_name_or_path": "google/tapas-base-finetuned-wtq", "use_gpu...
Build search pipeline using PineconeDocumentStore and ElasticsearchRetriever
{"version": "1.8.0", "components": [{"name": "pinecone_document_store", "type": "PineconeDocumentStore", "params": {"environment": "us-west1-gcp", "embedding_dim": 768, "return_embedding": false, "index": "document", "similarity": "cosine", "replicas": 1, "shards": 1, "embedding_field": "embedding", "progress_bar": tru...
Make faq system consisting of WeaviateDocumentStore and table text retriever
{"version": "1.8.0", "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", "return_embedding": false, ...
Build extractive qa pipeline using bm25 retriever, pinecone document store and rci reader
{"version": "1.8.0", "components": [{"name": "pinecone_document_store", "type": "PineconeDocumentStore", "params": {"environment": "us-west1-gcp", "embedding_dim": 768, "return_embedding": false, "index": "document", "similarity": "cosine", "replicas": 1, "shards": 1, "embedding_field": "embedding", "progress_bar": tru...
Create QuestionGenerationPipeline
{"version": "1.8.0", "components": [{"name": "QuestionGenerator", "params": {}, "type": "QuestionGenerator"}], "pipelines": [{"name": "query", "nodes": [{"inputs": ["Query"], "name": "QuestionGenerator"}]}]}
Build Haystack qa system with SQLDocumentStore, table reader and TableTextRetriever
{"version": "1.8.0", "components": [{"name": "sql_document_store", "type": "SQLDocumentStore", "params": {"url": "sqlite://", "index": "document", "label_index": "label", "duplicate_documents": "overwrite", "check_same_thread": false}}, {"name": "table_text_retriever", "type": "TableTextRetriever", "params": {"max_seq_...
Generate generative pipeline with seq2 seq generator, ElasticsearchRetriever and OpenDistroElasticsearchDocumentStore
{"version": "1.8.0", "components": [{"name": "open_distro_elasticsearch_document_store", "type": "OpenDistroElasticsearchDocumentStore", "params": {"scheme": "https", "username": "admin", "password": "admin", "port": 0, "index": "document", "label_index": "label", "content_field": "content", "name_field": "name", "embe...
Make Haystack ExtractiveQAPipeline using TfidfRetriever, faiss document store and FARMReader
{"version": "1.8.0", "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_...
Build QuestionAnswerGenerationPipeline with question generator and TransformersReader
{"version": "1.8.0", "components": [{"name": "question_generator", "type": "QuestionGenerator", "params": {"sep_token": "<sep>", "batch_size": 16, "progress_bar": true, "use_auth_token": false}}, {"name": "transformers_reader", "type": "TransformersReader", "params": {"model_name_or_path": "distilbert-base-uncased-dist...
Generate GenerativeQAPipeline using tfidf retriever, InMemoryDocumentStore and ra generator
{"version": "1.8.0", "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, "scor...
Make document search pipeline with in memory document store and ElasticsearchRetriever
{"version": "1.8.0", "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, "scor...
Generate GenerativeQAPipeline consisting of SQLDocumentStore, seq2 seq generator and DensePassageRetriever
{"version": "1.8.0", "components": [{"name": "sql_document_store", "type": "SQLDocumentStore", "params": {"url": "sqlite://", "index": "document", "label_index": "label", "duplicate_documents": "overwrite", "check_same_thread": false}}, {"name": "dense_passage_retriever", "type": "DensePassageRetriever", "params": {"ma...
Build Haystack GenerativeQAPipeline with PineconeDocumentStore, TfidfRetriever and open ai answer generator
{"version": "1.8.0", "components": [{"name": "pinecone_document_store", "type": "PineconeDocumentStore", "params": {"environment": "us-west1-gcp", "embedding_dim": 768, "return_embedding": false, "index": "document", "similarity": "cosine", "replicas": 1, "shards": 1, "embedding_field": "embedding", "progress_bar": tru...
Create FAQPipeline using FAISSDocumentStore and bm25 retriever
{"version": "1.8.0", "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_...
Generate Haystack generative qa pipeline using seq2 seq generator, SQLDocumentStore and TableTextRetriever
{"version": "1.8.0", "components": [{"name": "sql_document_store", "type": "SQLDocumentStore", "params": {"url": "sqlite://", "index": "document", "label_index": "label", "duplicate_documents": "overwrite", "check_same_thread": false}}, {"name": "table_text_retriever", "type": "TableTextRetriever", "params": {"max_seq_...
Generate faq pipeline using EmbeddingRetriever and OpenDistroElasticsearchDocumentStore
{"version": "1.8.0", "components": [{"name": "open_distro_elasticsearch_document_store", "type": "OpenDistroElasticsearchDocumentStore", "params": {"scheme": "https", "username": "admin", "password": "admin", "port": 0, "index": "document", "label_index": "label", "content_field": "content", "name_field": "name", "embe...
Generate Haystack QuestionGenerationPipeline
{"version": "1.8.0", "components": [{"name": "QuestionGenerator", "params": {}, "type": "QuestionGenerator"}], "pipelines": [{"name": "query", "nodes": [{"inputs": ["Query"], "name": "QuestionGenerator"}]}]}
Make Haystack FAQPipeline with WeaviateDocumentStore and MultihopEmbeddingRetriever
{"version": "1.8.0", "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", "return_embedding": false, ...
Build FAQPipeline using open search document store and table text retriever
{"version": "1.8.0", "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", ...
Generate FAQPipeline using DeepsetCloudDocumentStore and ElasticsearchRetriever
{"version": "1.8.0", "components": [{"name": "deepset_cloud_document_store", "type": "DeepsetCloudDocumentStore", "params": {"workspace": "default", "duplicate_documents": "overwrite", "similarity": "dot_product", "return_embedding": false, "label_index": "default", "embedding_dim": 768}}, {"name": "elasticsearch_retri...
Create Haystack generative pipeline consisting of embedding retriever, Seq2SeqGenerator and DeepsetCloudDocumentStore
{"version": "1.8.0", "components": [{"name": "deepset_cloud_document_store", "type": "DeepsetCloudDocumentStore", "params": {"workspace": "default", "duplicate_documents": "overwrite", "similarity": "dot_product", "return_embedding": false, "label_index": "default", "embedding_dim": 768}}, {"name": "embedding_retriever...
Generate qa pipeline using elasticsearch document store, filter retriever and rci reader
{"version": "1.8.0", "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": ...
Create Haystack extractive qa system using TableReader, TableTextRetriever and OpenSearchDocumentStore
{"version": "1.8.0", "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", ...
Build Haystack qa pipeline with FARMReader, WeaviateDocumentStore and MultihopEmbeddingRetriever
{"version": "1.8.0", "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", "return_embedding": false, ...
Create Haystack generative qa system with TfidfRetriever, pinecone document store and OpenAIAnswerGenerator
{"version": "1.8.0", "components": [{"name": "pinecone_document_store", "type": "PineconeDocumentStore", "params": {"environment": "us-west1-gcp", "embedding_dim": 768, "return_embedding": false, "index": "document", "similarity": "cosine", "replicas": 1, "shards": 1, "embedding_field": "embedding", "progress_bar": tru...
Make Haystack faq pipeline consisting of FilterRetriever and InMemoryDocumentStore
{"version": "1.8.0", "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, "scor...
Generate Haystack QuestionAnswerGenerationPipeline using question generator and transformers reader
{"version": "1.8.0", "components": [{"name": "question_generator", "type": "QuestionGenerator", "params": {"sep_token": "<sep>", "batch_size": 16, "progress_bar": true, "use_auth_token": false}}, {"name": "transformers_reader", "type": "TransformersReader", "params": {"model_name_or_path": "distilbert-base-uncased-dist...
Build Haystack question generation pipeline
{"version": "1.8.0", "components": [{"name": "QuestionGenerator", "params": {}, "type": "QuestionGenerator"}], "pipelines": [{"name": "query", "nodes": [{"inputs": ["Query"], "name": "QuestionGenerator"}]}]}
Build question answer generation pipeline with question generator and rci reader
{"version": "1.8.0", "components": [{"name": "question_generator", "type": "QuestionGenerator", "params": {"sep_token": "<sep>", "batch_size": 16, "progress_bar": true, "use_auth_token": false}}, {"name": "rci_reader", "type": "RCIReader", "params": {"row_model_name_or_path": "michaelrglass/albert-base-rci-wikisql-row"...
Generate Haystack QuestionAnswerGenerationPipeline using TableReader and question generator
{"version": "1.8.0", "components": [{"name": "question_generator", "type": "QuestionGenerator", "params": {"sep_token": "<sep>", "batch_size": 16, "progress_bar": true, "use_auth_token": false}}, {"name": "table_reader", "type": "TableReader", "params": {"model_name_or_path": "google/tapas-base-finetuned-wtq", "use_gpu...
Create QuestionGenerationPipeline
{"version": "1.8.0", "components": [{"name": "QuestionGenerator", "params": {}, "type": "QuestionGenerator"}], "pipelines": [{"name": "query", "nodes": [{"inputs": ["Query"], "name": "QuestionGenerator"}]}]}
Make Haystack question answer generation pipeline using TableReader and question generator
{"version": "1.8.0", "components": [{"name": "question_generator", "type": "QuestionGenerator", "params": {"sep_token": "<sep>", "batch_size": 16, "progress_bar": true, "use_auth_token": false}}, {"name": "table_reader", "type": "TableReader", "params": {"model_name_or_path": "google/tapas-base-finetuned-wtq", "use_gpu...
Make faq system with multihop embedding retriever and weaviate document store
{"version": "1.8.0", "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", "return_embedding": false, ...
Make search summarization system using TransformersSummarizer, pinecone document store and bm25 retriever
{"version": "1.8.0", "components": [{"name": "pinecone_document_store", "type": "PineconeDocumentStore", "params": {"environment": "us-west1-gcp", "embedding_dim": 768, "return_embedding": false, "index": "document", "similarity": "cosine", "replicas": 1, "shards": 1, "embedding_field": "embedding", "progress_bar": tru...
Create generative qa system using DeepsetCloudDocumentStore, OpenAIAnswerGenerator and TfidfRetriever
{"version": "1.8.0", "components": [{"name": "deepset_cloud_document_store", "type": "DeepsetCloudDocumentStore", "params": {"workspace": "default", "duplicate_documents": "overwrite", "similarity": "dot_product", "return_embedding": false, "label_index": "default", "embedding_dim": 768}}, {"name": "tfidf_retriever", "...
Make Haystack question answer generation system with TransformersReader and question generator
{"version": "1.8.0", "components": [{"name": "question_generator", "type": "QuestionGenerator", "params": {"sep_token": "<sep>", "batch_size": 16, "progress_bar": true, "use_auth_token": false}}, {"name": "transformers_reader", "type": "TransformersReader", "params": {"model_name_or_path": "distilbert-base-uncased-dist...
Create Haystack document search system consisting of FAISSDocumentStore and elasticsearch retriever
{"version": "1.8.0", "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_...
Build extractive qa using transformers reader, MultihopEmbeddingRetriever and SQLDocumentStore
{"version": "1.8.0", "components": [{"name": "sql_document_store", "type": "SQLDocumentStore", "params": {"url": "sqlite://", "index": "document", "label_index": "label", "duplicate_documents": "overwrite", "check_same_thread": false}}, {"name": "multihop_embedding_retriever", "type": "MultihopEmbeddingRetriever", "par...
Create Haystack generative pipeline consisting of DensePassageRetriever, SQLDocumentStore and RAGenerator
{"version": "1.8.0", "components": [{"name": "sql_document_store", "type": "SQLDocumentStore", "params": {"url": "sqlite://", "index": "document", "label_index": "label", "duplicate_documents": "overwrite", "check_same_thread": false}}, {"name": "dense_passage_retriever", "type": "DensePassageRetriever", "params": {"ma...
Create Haystack generative pipeline with open search document store, FilterRetriever and ra generator
{"version": "1.8.0", "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", ...
Make Haystack document search system consisting of TfidfRetriever and open distro elasticsearch document store
{"version": "1.8.0", "components": [{"name": "open_distro_elasticsearch_document_store", "type": "OpenDistroElasticsearchDocumentStore", "params": {"scheme": "https", "username": "admin", "password": "admin", "port": 0, "index": "document", "label_index": "label", "content_field": "content", "name_field": "name", "embe...
Generate faq system consisting of pinecone document store and FilterRetriever
{"version": "1.8.0", "components": [{"name": "pinecone_document_store", "type": "PineconeDocumentStore", "params": {"environment": "us-west1-gcp", "embedding_dim": 768, "return_embedding": false, "index": "document", "similarity": "cosine", "replicas": 1, "shards": 1, "embedding_field": "embedding", "progress_bar": tru...
Generate Haystack ExtractiveQAPipeline with weaviate document store, table reader and filter retriever
{"version": "1.8.0", "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", "return_embedding": false, ...
Generate Haystack faq search pipeline using deepset cloud document store and table text retriever
{"version": "1.8.0", "components": [{"name": "deepset_cloud_document_store", "type": "DeepsetCloudDocumentStore", "params": {"workspace": "default", "duplicate_documents": "overwrite", "similarity": "dot_product", "return_embedding": false, "label_index": "default", "embedding_dim": 768}}, {"name": "table_text_retrieve...
Create Haystack QuestionAnswerGenerationPipeline using farm reader and QuestionGenerator
{"version": "1.8.0", "components": [{"name": "question_generator", "type": "QuestionGenerator", "params": {"sep_token": "<sep>", "batch_size": 16, "progress_bar": true, "use_auth_token": false}}, {"name": "farm_reader", "type": "FARMReader", "params": {"context_window_size": 150, "batch_size": 50, "use_gpu": true, "no_...
Create Haystack search summarization pipeline with transformers summarizer, elasticsearch filter only retriever and in memory document store
{"version": "1.8.0", "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, "scor...
Build search pipeline consisting of pinecone document store and ElasticsearchRetriever
{"version": "1.8.0", "components": [{"name": "pinecone_document_store", "type": "PineconeDocumentStore", "params": {"environment": "us-west1-gcp", "embedding_dim": 768, "return_embedding": false, "index": "document", "similarity": "cosine", "replicas": 1, "shards": 1, "embedding_field": "embedding", "progress_bar": tru...
Generate Haystack faq system with TableTextRetriever and weaviate document store
{"version": "1.8.0", "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", "return_embedding": false, ...