fix: Fix the mypy check error

[yyhhyyyyyy]

Description

This PR attempts to fix the 'make mymp' error outlined in CONTRIBUTING.md that was introduced by PR #1359, particularly when submitting new PRs. Due to the lack of a Milvus environment on my end, I would kindly ask for testing before merging to ensure the issue with PR #1359 has been resolved. Apologies for the inconvenience.

How Has This Been Tested?

make fmt
make test
make mypy

Snapshots:

Due to working on an internal network, I cannot submit screenshots. Please proceed with direct testing.

Checklist:

• My code follows the style guidelines of this project
• I have already rebased the commits and make the commit message conform to the project standard.
• I have performed a self-review of my own code
• I have commented my code, particularly in hard-to-understand areas
• I have made corresponding changes to the documentation
• Any dependent changes have been merged and published in downstream modules

[csunny]

And when remove the code

if vector_store_config.embedding_fn is None:
    raise ValueError("embedding_fn is required for MilvusStore")

make mypy will raise an error.

dbgpt/storage/vector_store/milvus_store.py:181: error: Incompatible types in assignment (expression has type "Embeddings | None", variable has type "Embeddings")  [assignment]
Found 1 error in 1 file (checked 94 source files)
make: *** [mypy] Error 1

This issue should not fixed use remove embedding_fn config. @Aries-ckt

[csunny]

When we delete knowledge space at dbgpt/app/knowledge/service, Each knowledge space should have a saved embedding_fn model parameter. We can query this embedding_fn according to knowledge space when later embedding_fn is not equal to pre, we need to raise an error.

    def delete_space(self, space_name: str):
        """delete knowledge space
        Args:
            - space_name: knowledge space name
        """
        query = KnowledgeSpaceEntity(name=space_name)
        spaces = knowledge_space_dao.get_knowledge_space(query)
        if len(spaces) == 0:
            raise Exception(f"delete error, no space name:{space_name} in database")
        space = spaces[0]
        # TODO query embedding_fn according space.name
        config = VectorStoreConfig(name=space.name) 
        ...
        # delete vectors
        vector_store_connector.delete_vector_name(space.name)
        document_query = KnowledgeDocumentEntity(space=space.name)
        # delete chunks
        documents = knowledge_document_dao.get_documents(document_query)
        for document in documents:
            document_chunk_dao.raw_delete(document.id)
        # delete documents
        knowledge_document_dao.raw_delete(document_query)
        # delete space
        return knowledge_space_dao.delete_knowledge_space(space)

[yyhhyyyyyy]

Thanks @Aries-ckt for fixing the PR, it has been tested and confirmed resolved.
Also, thanks to @csunny for your insights.

[fangyinc]

LGTM.

[Aries-ckt]

r+

[fangyinc]

r+