Add Sentence Transformers for embeddings

[oidebrett]

Hi there, I'm Ivo and I am loving the project,

This PR introduces support for Sentence Transformers (documentation here) as an embedding option. I've followed the documentation here.

To test, set the code/config/config_embedding.yaml to be preferred_provider: sentence-transformers and redo the db_load python -m tools.db_load https://feeds.libsyn.com/121695/rss Behind-the-Tech.

I reset the code/config/config_embedding.yaml to be preferred_provider: azure_openai as per the repo

Looking forward to your feedback!

[oidebrett]

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[Copilot]

Pull Request Overview

This PR adds support for the Sentence Transformers framework as a new local embedding provider, including docs, dependency updates, and integration in the embedding factory.

• Add documentation for the new provider
• Introduce the sentence-transformers dependency and implementation
• Register provider in factory, update config and README

Reviewed Changes

Copilot reviewed 6 out of 6 changed files in this pull request and generated 5 comments.

Show a summary per file

File	Description
docs/SentenceTransformers.md	New guide on using Sentence Transformers embeddings
code/requirements.txt	Add sentence-transformers package requirement
code/embedding/sentence_transformer_embedding.py	Implement SentenceTransformer-based embedding functions
code/embedding/embedding.py	Register sentence-transformers provider and locks
code/config/config_embedding.yaml	Add provider config for sentence-transformers
code/README.md	Include new embedding module in project README

[Copilot]

There are two identical "snowflake": threading.Lock(), entries; remove the duplicate to avoid key override.

Suggested change

"snowflake": threading.Lock(),

[Copilot]

The model parameter is accepted but never used; update get_sentence_transformer_embedding to pass this override to get_embedding_model or remove the unused argument.

[Copilot]

Calling the blocking encode method in an async function can block the event loop; consider running it via loop.run_in_executor or a thread pool.

Suggested change

	embedding = model_instance.encode(text.replace("\n", " "), convert_to_numpy=True).tolist()
	loop = asyncio.get_running_loop()
	embedding = await loop.run_in_executor(
	None,
	lambda: model_instance.encode(text.replace("\n", " "), convert_to_numpy=True).tolist()
	)

[Copilot]

Config key sentence-transformers does not match the lookup in get_model_name() which uses sentence_transformer; unify the provider identifier to ensure overrides work.

Suggested change

	sentence-transformers:
	sentence_transformer:

[Copilot]

[nitpick] The README entry for sentence_transformer_embedding.py has an empty comment; add a brief description of the module’s purpose.

Suggested change

	| ├── sentence_transformer_embedding.py #
	| ├── sentence_transformer_embedding.py # Embedding generation using Sentence Transformers

[toloco]

Using a version of this PR, I get this error:
SentenceTransformer("all-MiniLM-L6-v2")

@oidebrett have you come with the same issue?

ValueError: shapes (848,384) and (1024,) not aligned: 384 (dim 1) != 1024 (dim 0)

[shnax0210]

I believe the name should be: "sentence-transformers/all-MiniLM-L6-v2" instead of just "all-MiniLM-L6-v2"

[oidebrett]

Hi, I think the issue is the vector size/dimensions. If you already used embeddings then they are likely different sizing. I deleted all my embeddings and started fresh and that worked fine

…

On Wed 11 Jun 2025, 17:53 Tolo Palmer, ***@***.***> wrote: *toloco* left a comment (microsoft/NLWeb#142) <#142 (comment)> Using a version of this PR, I get this error: SentenceTransformer("all-MiniLM-L6-v2") @oidebrett <https://github.com/oidebrett> have you come with the same issue? ValueError: shapes (848,384) and (1024,) not aligned: 384 (dim 1) != 1024 (dim 0) — Reply to this email directly, view it on GitHub <#142 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AHUTNEMDXX3GRUCCRKUPVX33DBGGNAVCNFSM6AAAAAB56HTYF6VHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDSNRTGIYTSMRQGA> . You are receiving this because you were mentioned.Message ID: ***@***.***>

[toloco]

Thanks!, silly me didn't get I've run another embedding model before...