Changes being requested

Add defensive null/undefined checks for malformed embedding responses to prevent runtime crashes when using third-party OpenAI-compatible endpoints.

Core changes:

• Add null/undefined validation for embedding objects and data
• Skip null embedding objects gracefully during processing
• Throw meaningful OpenAIError with context for missing embedding data
• Maintain full backward compatibility with existing functionality

Test coverage:

• Add 5 new test cases covering null/undefined scenarios
• Add helper function makeClientWithCustomResponse for custom mock responses
• Verify error messages include proper context (item index)
• Ensure existing functionality remains unaffected

Additional context & links

Bug: #1542

This addresses potential runtime errors when third-party providers (Ollama, LM Studio) return malformed responses with null/undefined embedding data. The current code lacks defensive checks:

// Before (vulnerable to runtime errors)
response.data.forEach((embeddingBase64Obj) => {
  const embeddingBase64Str = embeddingBase64Obj.embedding as unknown as string;
  embeddingBase64Obj.embedding = toFloat32Array(embeddingBase64Str);
});

// After (defensive with meaningful errors)
response.data.forEach((embeddingBase64Obj) => {
  if (!embeddingBase64Obj) return; // Skip null/undefined items

  const embeddingBase64Str = embeddingBase64Obj.embedding as unknown;
  if (embeddingBase64Str == null) {
    throw new OpenAIError(`Missing embedding data for item at index ${embeddingBase64Obj.index ?? 'unknown'}`);
  }
  embeddingBase64Obj.embedding = toFloat32Array(embeddingBase64Str as string);
});

Impact:

• ✅ Prevents runtime crashes from malformed third-party responses
• ✅ Provides meaningful error messages for debugging
• ✅ Maintains full backward compatibility
• ✅ No performance impact on normal operations

✅ I understand that this repository is auto-generated, and my pull request may not be merged