Implementing the MMR algorithm for OLAP vector storage

[fkzhao]

Thank you for contributing to LangChain!

• Implementing the MMR algorithm for OLAP vector storage:

• Support Apache Doris and StarRocks OLAP database.

• Example: "vectorstore.as_retriever(search_type="mmr", search_kwargs={"k": 10})"

• Implementing the MMR algorithm for OLAP vector storage:

  • **Apache Doris
  • **StarRocks
  • Dependencies: any dependencies required for this change
  • Twitter handle: if your PR gets announced, and you'd like a mention, we'll gladly shout you out!

• Add tests and docs:

  • Example: "vectorstore.as_retriever(search_type="mmr", search_kwargs={"k": 10})"

• Lint and test: Run make format, make lint and make test from the root of the package(s) you've modified. See contribution guidelines for more: https://python.langchain.com/docs/contributing/

Additional guidelines:

• Make sure optional dependencies are imported within a function.
• Please do not add dependencies to pyproject.toml files (even optional ones) unless they are required for unit tests.
• Most PRs should not touch more than one package.
• Changes should be backwards compatible.
• If you are adding something to community, do not re-import it in langchain.

If no one reviews your PR within a few days, please @-mention one of baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17.

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