community: Add InMemoryVectorStore #19326
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Ɑ: vector store
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@cbornet would you mind moving this to: All in memory implementations are pretty fundamental -- useful as both reference implementations and for testing purposes cc @baskaryan |
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Standby! We're trying to figure whether it's langchain-core or langchain |
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Ok. Note that I’m using utility functions for cosine similarity and mmr. |
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Also the core would have to depend on numpy |
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But a no-numpy, zero-dep, less performant implementation could also probably be written. |
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Aah got it i didn't notice the numpy dependencies |
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OK we can merge as is for now. We're working on breaking langchain dependency on langchain community. Once that's broken, we're likely going to invert it with |
rahul-trip
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Mar 27, 2024
This is a basic VectorStore implementation using an in-memory dict to store the documents. It doesn't need any extra/optional dependency as it uses numpy which is already a dependency of langchain. This is useful for quick testing, demos, examples. Also it allows to write vendor-neutral tutorials, guides, etc...
bechbd
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Mar 29, 2024
This is a basic VectorStore implementation using an in-memory dict to store the documents. It doesn't need any extra/optional dependency as it uses numpy which is already a dependency of langchain. This is useful for quick testing, demos, examples. Also it allows to write vendor-neutral tutorials, guides, etc...
gkorland
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Mar 30, 2024
This is a basic VectorStore implementation using an in-memory dict to store the documents. It doesn't need any extra/optional dependency as it uses numpy which is already a dependency of langchain. This is useful for quick testing, demos, examples. Also it allows to write vendor-neutral tutorials, guides, etc...
chrispy-snps
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Mar 30, 2024
This is a basic VectorStore implementation using an in-memory dict to store the documents. It doesn't need any extra/optional dependency as it uses numpy which is already a dependency of langchain. This is useful for quick testing, demos, examples. Also it allows to write vendor-neutral tutorials, guides, etc...
chrispy-snps
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Mar 30, 2024
This is a basic VectorStore implementation using an in-memory dict to store the documents. It doesn't need any extra/optional dependency as it uses numpy which is already a dependency of langchain. This is useful for quick testing, demos, examples. Also it allows to write vendor-neutral tutorials, guides, etc...
hinthornw
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Apr 26, 2024
This is a basic VectorStore implementation using an in-memory dict to store the documents. It doesn't need any extra/optional dependency as it uses numpy which is already a dependency of langchain. This is useful for quick testing, demos, examples. Also it allows to write vendor-neutral tutorials, guides, etc...
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This is a basic VectorStore implementation using an in-memory dict to store the documents.
It doesn't need any extra/optional dependency as it uses numpy which is already a dependency of langchain.
This is useful for quick testing, demos, examples.
Also it allows to write vendor-neutral tutorials, guides, etc...