Update main.py
Browse files
main.py
CHANGED
@@ -69,7 +69,7 @@ def Retriever(categorie):
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if categorie != "year":
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retriever = vectorstore.as_retriever(search_type="similarity_score_threshold", search_kwargs={"score_threshold": .7, "k": 150,"filter": {'categorie': {'$eq': categorie}}})
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else:
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retriever = vectorstore.as_retriever(search_type="similarity_score_threshold", search_kwargs={"score_threshold": .7, "k":
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#search = vectorstore.similarity_search(query,k=50, filter={"categorie": {"$eq": "bibliographie-OPP-DGDIN"}, 'Source': {'$eq': 'Source : Persée'}})
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return retriever
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@@ -95,8 +95,8 @@ def Search(input, categorie):
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for i in range(0,len(search)):
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if count <= 15:
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count = count + 1
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sources_text = sources_text + str(count) + ". " + search[i].metadata['title'] + ' (JDLP : ' + str(search[i].metadata['year']) + '), ' + search[i].metadata['author'] + ', ' + search[i].metadata['file'] + "\n"
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verbatim_text = verbatim_text + "<p>" + str(count) + ". JDLP : " + search[i].metadata['jdlp'] + "</p><p>" + search[i].
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results = [sources_text, verbatim_text]
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return results
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if categorie != "year":
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retriever = vectorstore.as_retriever(search_type="similarity_score_threshold", search_kwargs={"score_threshold": .7, "k": 150,"filter": {'categorie': {'$eq': categorie}}})
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else:
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retriever = vectorstore.as_retriever(search_type="similarity_score_threshold", search_kwargs={"score_threshold": .7, "k": 6,"filter": {'year': {'$gte': 2019}}})
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#search = vectorstore.similarity_search(query,k=50, filter={"categorie": {"$eq": "bibliographie-OPP-DGDIN"}, 'Source': {'$eq': 'Source : Persée'}})
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return retriever
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for i in range(0,len(search)):
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if count <= 15:
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count = count + 1
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sources_text = sources_text + str(count) + ". " + search[i].metadata['title'] + ' (JDLP : ' + str(search[i].metadata['year']) + '), ' + search[i].metadata['author'] + ', https://cipen.univ-gustave-eiffel.fr/fileadmin/CIPEN/OPP/' + search[i].metadata['file'] + "\n"
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verbatim_text = verbatim_text + "<p>" + str(count) + ". JDLP : " + search[i].metadata['jdlp'] + "</p><p>" + search[i].page_content + "</p>"
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results = [sources_text, verbatim_text]
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return results
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