Improve provider-specific errors in vectorizer _set_model_dims()
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enhancement
- Dominant language
- Python
- Stars
- 427
- Forks
- 101
- Avg merge
- 6d 3h
- Merged PRs (30d)
- 20
Description
Summary
Replace generic fallback exceptions in vectorizer _set_model_dims() with provider-specific, actionable errors.
Level: Beginner
Current State
- Several vectorizer implementations catch broad
Exceptionwith TODO comments. - Resulting messages are vague and slow down troubleshooting.
Proposed Change
- Update
_set_model_dims()error handling in:redisvl/utils/vectorize/text/openai.pyredisvl/utils/vectorize/text/cohere.pyredisvl/utils/vectorize/text/mistral.pyredisvl/utils/vectorize/text/azureopenai.pyredisvl/utils/vectorize/text/huggingface.pyredisvl/utils/vectorize/bedrock.pyredisvl/utils/vectorize/vertexai.pyredisvl/utils/vectorize/voyageai.py
- Catch known provider/network/auth cases and include remediation hints.
Definition of Done
- TODO fallback comments are removed.
- Errors include provider/model context and useful next-step guidance.
- Existing tests pass; add targeted tests where needed.
Out of Scope
- Refactoring vectorizer architecture or retry policy behavior.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Read the _set_model_dims() implementations and TODO fallback paths in the eight listed provider files, then inspect the existing vectorizer tests before running them. Done means removing those TODO fallbacks, adding provider/model context and actionable guidance for known provider, network, and authentication cases, and keeping existing tests passing.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100