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time_weighted_retriever: use a timestamp if needed (#9906)

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If last_accessed_at metadata is a float use it as a timestamp. This
allows to support vector stores that do not store datetime objects like
ChromaDb.

Fixes: https://github.com/langchain-ai/langchain/issues/3685

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This commit is contained in:
Frédéric Lepied 2023-09-04 00:05:30 +02:00 committed by GitHub
parent bc8cceebf7
commit 4dc47bd3ac
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1 changed files with 9 additions and 1 deletions
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10
libs/langchain/langchain/retrievers/time_weighted_retriever.py
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@ -47,6 +47,14 @@ class TimeWeightedVectorStoreRetriever(BaseRetriever):
arbitrary_types_allowed = True
def _document_get_date(self, field: str, document: Document) -> datetime.datetime:
"""Return the value of the date field of a document."""
if field in document.metadata:
if type(document.metadata[field]) == float:
return datetime.datetime.fromtimestamp(document.metadata[field])
return document.metadata[field]
return datetime.datetime.now()
def _get_combined_score(
self,
document: Document,
@ -56,7 +64,7 @@ class TimeWeightedVectorStoreRetriever(BaseRetriever):
"""Return the combined score for a document."""
hours_passed = _get_hours_passed(
current_time,
document.metadata["last_accessed_at"],
self._document_get_date("last_accessed_at", document),
)
score = (1.0 - self.decay_rate) ** hours_passed
for key in self.other_score_keys: