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PYTHON-4679 Fixes all Langchain Tests #39
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@@ -46,3 +46,7 @@ mongo-c-driver-* | |
# Benchmark and test output files | ||
results/* | ||
xunit-results/ | ||
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# Miscellaneous | ||
.DS_Store | ||
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[] |
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[] |
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[] |
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{ | ||
"fields": [ | ||
{ | ||
"numDimensions": 1536, | ||
"path": "embedding", | ||
"similarity": "cosine", | ||
"type": "vector" | ||
} | ||
], | ||
"name": "langchain-test-chain-example-vector-index", | ||
"type": "vectorSearch", | ||
"database": "langchain_test_db", | ||
"collectionName": "langchain_test_chain_example" | ||
} |
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{ | ||
"fields": [ | ||
{ | ||
"numDimensions": 5, | ||
"path": "embedding", | ||
"similarity": "cosine", | ||
"type": "vector" | ||
} | ||
], | ||
"name": "langchain-test-index-from-documents", | ||
"type": "vectorSearch", | ||
"database": "langchain_test_db", | ||
"collectionName": "langchain_test_from_documents" | ||
} |
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{ | ||
"mappings": { | ||
"dynamic": false, | ||
"fields": { | ||
"text": [ | ||
{ | ||
"type": "string" | ||
} | ||
] | ||
} | ||
}, | ||
"name": "text_index", | ||
"type": "search", | ||
"database": "langchain_test_db", | ||
"collectionName": "langchain_test_retrievers" | ||
} |
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{ | ||
"fields": [ | ||
{ | ||
"numDimensions": 1536, | ||
"path": "embedding", | ||
"similarity": "dotProduct", | ||
"type": "vector" | ||
}, | ||
{ | ||
"path": "c", | ||
"type": "filter" | ||
} | ||
], | ||
"name": "vector_index", | ||
"type": "vectorSearch", | ||
"database": "langchain_test_db", | ||
"collectionName": "langchain_test_retrievers" | ||
} |
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{ | ||
"fields": [ | ||
{ | ||
"numDimensions": 5, | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. I see some tests now have 5 dimensions whilst others have 1536. Any hesitation to making them all use 5? There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. The ones that use 5 are that way because we're not testing the quality of the search. If not, anything to make it faster. |
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"path": "embedding", | ||
"similarity": "dotProduct", | ||
"type": "vector" | ||
}, | ||
{ | ||
"path": "c", | ||
"type": "filter" | ||
} | ||
], | ||
"name": "langchain-test-index-from-texts", | ||
"type": "vectorSearch", | ||
"database": "langchain_test_db", | ||
"collectionName": "langchain_test_from_texts" | ||
} |
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Choose a reason for hiding this comment
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could you add your LangChain PR to the JIRA ticket?