Add models configuration object to init()#164
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Braintrust eval reportAutoevals (models-config-1771613247)
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Olmo Maldonado (ibolmo)
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py/autoevals/ragas.py
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| def _get_ragas_embedding_model(user_model): | ||
| """Get embedding model with RAGAS-specific default fallback. | ||
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| Priority: | ||
| 1. Explicitly provided user_model parameter | ||
| 2. User-configured global embedding default (via init()) | ||
| 3. RAGAS-specific default (text-embedding-3-small) | ||
| """ | ||
| if user_model is not None: | ||
| return user_model | ||
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| # Check if user has explicitly configured a global embedding default | ||
| configured_default = _default_embedding_model_var.get(None) | ||
| if configured_default is not None: | ||
| return configured_default | ||
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| # Fall back to RAGAS-specific default | ||
| return DEFAULT_RAGAS_EMBEDDING_MODEL |
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This exists because (for some reason) Python and TypeScript are inconsistent about the embedding model to use here. Python has its own fallback to text-embedding-3-small while TypeScript delegates to the EmbeddingSimilarity default which will use text-embedding-ada-002. Should we just be switching everywhere to text-embedding-3-small though?
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Olmo Maldonado (ibolmo)
| return DEFAULT_RAGAS_MODEL | ||
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| DEFAULT_RAGAS_EMBEDDING_MODEL = "text-embedding-3-small" |
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is this important for backwards compat?
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Not sure. I have another comment about that in another part of the PR--the TypeScript code does not do this and, as far as I can tell it's an accident that the Python code differs, but I'm not 100% certain about that or if the model change would constitute a breaking change.
Matt Perpick (clutchski)
approved these changes
Jan 27, 2026
Introduces a new `models` parameter to init() that allows configuring
default models for different evaluation types:
```typescript
init({
models: {
completion: 'claude-3-5-sonnet-20241022',
embedding: 'text-embedding-3-large',
}
})
```
Changes:
- Added `models` parameter to init() in both JS and Python
- Models object supports:
- `completion`: Default model for LLM-as-a-judge evaluations
- `embedding`: Default model for embedding-based evaluations
- `models.completion` takes precedence over deprecated `defaultModel`
- All embedding scorers now use configured default embedding model
- Added getDefaultEmbeddingModel() function
- Maintains backward compatibility with existing `defaultModel` parameter
- Added comprehensive tests for both languages
Default values:
- Completion: "gpt-4o" (unchanged)
- Embedding: "text-embedding-ada-002"
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
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The ContextRecall test occasionally fails in CI due to LLM response variability, returning a score of 0.0 instead of the expected 1.0. This is similar to the ContextRelevancy test which is already marked as can_fail=True. Marking this test as potentially flaky allows CI to pass while still running the test. Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Braintrust eval report
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Introduces a new
modelsparameter to init() that allows configuring default models for different evaluation types:Changes:
modelsparameter to init() in both JS and Pythoncompletion: Default model for LLM-as-a-judge evaluationsembedding: Default model for embedding-based evaluationsmodels.completiontakes precedence over deprecateddefaultModeldefaultModelparameterDefault values: