prashant
commited on
Commit
•
dd2ab07
1
Parent(s):
d7ce857
remove keybert
Browse files- requirements.txt +0 -1
- utils/semantic_search.py +6 -2
requirements.txt
CHANGED
@@ -2,7 +2,6 @@ farm-haystack == 1.10
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farm-haystack[ocr]==1.10.0
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spacy==3.2.0
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https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.2.0/en_core_web_sm-3.2.0.tar.gz#egg=en_core_web_sm
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-
keybert==0.5.1
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matplotlib==3.5.1
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nltk==3.7
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numpy==1.22.1
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farm-haystack[ocr]==1.10.0
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spacy==3.2.0
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https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.2.0/en_core_web_sm-3.2.0.tar.gz#egg=en_core_web_sm
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matplotlib==3.5.1
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nltk==3.7
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numpy==1.22.1
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utils/semantic_search.py
CHANGED
@@ -254,7 +254,7 @@ def semanticSearchPipeline(documents:List[Document], embedding_model:Text = Non
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reader = FARMReader(model_name_or_path=reader_model,
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top_k = reader_top_k, use_gpu=True)
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semantic_search_pipeline = Pipeline()
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-
if useQueryCheck:
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querycheck = QueryCheck()
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semantic_search_pipeline.add_node(component = querycheck, name = "QueryCheck",
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inputs = ["Query"])
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@@ -262,11 +262,15 @@ def semanticSearchPipeline(documents:List[Document], embedding_model:Text = Non
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inputs = ["QueryCheck.output_1"])
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semantic_search_pipeline.add_node(component = reader, name = "FARMReader",
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inputs= ["EmbeddingRetriever"])
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-
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semantic_search_pipeline.add_node(component = retriever, name = "EmbeddingRetriever",
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inputs = ["Query"])
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semantic_search_pipeline.add_node(component = reader, name = "FARMReader",
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inputs= ["EmbeddingRetriever"])
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return semantic_search_pipeline, document_store
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reader = FARMReader(model_name_or_path=reader_model,
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top_k = reader_top_k, use_gpu=True)
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semantic_search_pipeline = Pipeline()
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+
if useQueryCheck and reader_model:
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querycheck = QueryCheck()
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semantic_search_pipeline.add_node(component = querycheck, name = "QueryCheck",
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inputs = ["Query"])
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inputs = ["QueryCheck.output_1"])
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semantic_search_pipeline.add_node(component = reader, name = "FARMReader",
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inputs= ["EmbeddingRetriever"])
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+
elif reader_model :
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semantic_search_pipeline.add_node(component = retriever, name = "EmbeddingRetriever",
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inputs = ["Query"])
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semantic_search_pipeline.add_node(component = reader, name = "FARMReader",
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inputs= ["EmbeddingRetriever"])
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+
else:
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+
semantic_search_pipeline.add_node(component = retriever, name = "EmbeddingRetriever",
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inputs = ["Query"])
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+
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return semantic_search_pipeline, document_store
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