Bump sentence-transformers from 5.1.0 to 5.1.1 in /backend-agent

[dependabot]

Bumps sentence-transformers from 5.1.0 to 5.1.1.

Release notes

Sourced from sentence-transformers's releases.

v5.1.1 - Explicit incorrect arguments, fixes for multi-GPU, evaluator, and hard negative

This patch makes Sentence Transformers more explicit with incorrect arguments and introduces some fixes for multi-GPU processing, evaluators, and hard negatives mining.

Install this version with

# Training + Inference
pip install sentence-transformers[train]==5.1.1
Inference only, use one of:
pip install sentence-transformers==5.1.1
pip install sentence-transformers[onnx-gpu]==5.1.1
pip install sentence-transformers[onnx]==5.1.1
pip install sentence-transformers[openvino]==5.1.1

Error if unused kwargs is passed & get_model_kwargs (#3500)

Some SentenceTransformer or SparseEncoder models support custom model-specific keyword arguments, such as jinaai/jina-embeddings-v4. As of this release, calling model.encode with keyword arguments that aren't used by the model will result in an error.

>>> from sentence_transformers import SentenceTransformer
>>> model = SentenceTransformer("all-MiniLM-L6-v2")
>>> model.encode("Who is Amelia Earhart?", normalize=True)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "[sic]/torch/utils/_contextlib.py", line 116, in decorate_context
    return func(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^
  File "[sic]/SentenceTransformer.py", line 983, in encode
    raise ValueError(
ValueError: SentenceTransformer.encode() has been called with additional keyword arguments that this model does not use: ['normalize']. As per SentenceTransformer.get_model_kwargs(), this model does not accept any additional keyword arguments.

Quite useful when you, for example, accidentally forget that the parameter to get normalized embeddings is normalize_embeddings. Prior to this version, this parameter would simply quietly be ignored.

To check which custom extra keyword arguments may be used for your model, you can call the new get_model_kwargs method:

>>> from sentence_transformers import SentenceTransformer, SparseEncoder
>>> SentenceTransformer("all-MiniLM-L6-v2").get_model_kwargs()
[]
>>> SentenceTransformer("jinaai/jina-embeddings-v4", trust_remote_code=True).get_model_kwargs()
['task', 'truncate_dim']
>>> SparseEncoder("opensearch-project/opensearch-neural-sparse-encoding-doc-v3-distill").get_model_kwargs()
['task']

Note: You can always pass the task parameter, it's the only model-specific parameter that will be quietly ignored. This means that you can always use model.encode(..., task="query") and model.encode(..., task="document").

Minor Features

... (truncated)

Commits

• 22ff509 Release v5.1.1
• 5ad8a44 Merge branch 'master' into v5.1-release
• 1def8d3 Fix the number of missing negatives in mine_hard_negatives (#3504)
• 2e077fb fix: add makedirs to informationretrievalevaluator (#3516)
• 20c4820 Fix:Import SentenceTransformer class explicitly in losses module (#3521)
• 7240b33 [feat] add get_model_kwargs method; throw error if unused kwarg is passed (...
• 560cc33 always pass input_ids, attention_mask, token_type_ids, inputs_embeds ...
• bd91098 Update rasyosef/splade-mini MSMARCO and BEIR-13 benchmark scores in pretraine...
• ad8d27d Add Support for Knowledgeable Passage Retriever (KPR) (#3495)
• 5b18f36 [feat] Use encode_document and encode_query in mine_hard_negatives (#3502)
• Additional commits viewable in compare view

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[github-actions]

The change makes a small version update to the sentence-transformers dependency from version 5.1.0 to 5.1.1 in the backend-agent project configuration file.

Walkthrough

• Chore: Updated the sentence-transformers library to version 5.1.1, ensuring compatibility with the latest version without introducing breaking changes.
• Impact: This update might include bug fixes or minor improvements from the library's latest version, potentially enhancing stability or performance, but no direct new feature or user-visible impact is apparent from this change alone.

_{Model: gpt-4o | Prompt Tokens: 300 | Completion Tokens: 120}

[github-actions]

Here's a thoughtful code review enhanced by AI assistance. These insights offer suggestions and patterns we've identified, though your expertise and context matter most. Consider what aligns with your goals and project needs—you're the decision-maker, and AI simply provides additional perspective to support your work.

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_{Model: anthropic--claude-4-sonnet | Prompt Tokens: 856 | Completion Tokens: 257}

[github-actions]

Good practice to keep dependencies up to date! The sentence-transformers version bump from 5.1.0 to 5.1.1 is likely a patch release with bug fixes or security improvements. Consider checking the changelog to understand what improvements this version brings.

For better dependency management, you might want to consider:

# Pin major.minor versions but allow patch updates
'sentence-transformers>=5.1.0,<5.2.0',

This approach allows automatic patch updates while preventing potentially breaking minor/major version changes.