[ENH] add query config on collection configuration, splade, and bm25 efs

[jairad26]

Description of changes

This PR adds a new function embed_query on the base embeddingfunction type to allow embedding functions to define a secondary path to embed documents for query path. by default this will invoke the call method.

this also adds a new protocol for SparseEmbeddingFunctions, and 2 new embedding functions: huggingface_sparse_embedding_function and fastembed_sparse_embedding_function

Test plan

How are these changes tested?

• Tests pass locally with pytest for python, yarn test for js, cargo test for rust

Documentation Changes

Are all docstrings for user-facing APIs updated if required? Do we need to make documentation changes in the docs section?

[jairad26]

• [ENH] Add nomic embedding function #4911
• [ENH] add query config on collection configuration, splade, and bm25 efs #4901 👈 (View in Graphite)
• main

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[github-actions]

Reviewer Checklist

Please leverage this checklist to ensure your code review is thorough before approving

Testing, Bugs, Errors, Logs, Documentation

• Can you think of any use case in which the code does not behave as intended? Have they been tested?
• Can you think of any inputs or external events that could break the code? Is user input validated and safe? Have they been tested?
• If appropriate, are there adequate property based tests?
• If appropriate, are there adequate unit tests?
• Should any logging, debugging, tracing information be added or removed?
• Are error messages user-friendly?
• Have all documentation changes needed been made?
• Have all non-obvious changes been commented?

System Compatibility

• Are there any potential impacts on other parts of the system or backward compatibility?
• Does this change intersect with any items on our roadmap, and if so, is there a plan for fitting them together?

Quality

• Is this code of a unexpectedly high quality (Readability, Modularity, Intuitiveness)

[Sicheng-Pan]

this works, but just for discussion an alternative approach is to have separate methods for read and write paths. any idea here?

[HammadB]

Yeah +1

[Sicheng-Pan]

How does this work for all embedding functions we support?

[jairad26]

since theres a default that assumes query config doesnt exist, none of the existing efs will break.

[Sicheng-Pan]

Lgtm

[propel-code-bot]

Add Query Config for Embedding Functions, Introduce Sparse Embedding Support

This PR introduces major extensibility to the embedding function API by adding a standardized embed_query method and optional query_config parameter to embedding functions. The change enables different code paths or configurations for query-time versus document-time embedding, improving support for multi-vector models and sparse embedding scenarios. Additionally, the PR implements a new SparseEmbeddingFunction protocol and provides initial integrations with HuggingFace SPLADE and FastEmbed, supporting sparse vector representations. Various core files are updated to propagate and use the new embed_query method and protocol, and extensive new and updated tests validate this extended configuration support.

Key Changes

• Added embed_query method to the EmbeddingFunction and new SparseEmbeddingFunction protocol in chromadb/api/types.py.
• Introduced support and full protocol for declaring sparse embedding functions along with validation utilities.
• Implemented new embedding function classes: HuggingFaceSparseEmbeddingFunction and FastembedSparseEmbeddingFunction, supporting model/parameter selection and query/document disambiguation.
• Expanded and refactored tests in chromadb/test/configurations/test_collection_configuration.py for serialization, deserialization, config propagation, and behavior of embedding functions with/without query_config.
• Updated CollectionCommon.py to call embed_query for query operations (when appropriate), ensuring backward compatibility with legacy embeddings.
• Modified core configuration loading, registration, and serialization paths to handle legacy and modern function signatures, properly propagate query_config, and support new types.
• Extended JinaEmbeddingFunction and related tests to support query_config.
• Added sparse embedding validation utilities and improved embedding function interface robustness.
• Updated initialization and registry in chromadb/utils/embedding_functions/__init__.py and related test coverage for new sparse classes.

Affected Areas

• chromadb/api/types.py (embedding interfaces and core validation)
• chromadb/api/models/CollectionCommon.py (embedding pathways, handling of query/document logic)
• chromadb/utils/embedding_functions/ (embedding function classes, registry, imports)
• chromadb/test/configurations/test_collection_configuration.py (tests for embedding function configs and serialization)
• chromadb/test/ef/test_ef.py (import-level embedding function coverage)
• chromadb/api/collection_configuration.py and related code (config load/store/validation)

This summary was automatically generated by @propel-code-bot

[Sicheng-Pan]

nit: maybe put a list of models for common use cases somewhere