Address vector dimension mismatch when using ollama with Azure AI Search #6001
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Azure AI Search may fail to ingest new data if the vector dimensionality mismatches. This may cause an issue if you have data from prior runs with a different embedding model.
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PR Overview
This PR addresses the vector dimension mismatch when using ollama with Azure AI Search by conditionally setting the vector size and updating the README with an index deletion note.
- Added a compilation condition to set a vector dimension of 384 for ollama versus 1536 for the OpenAI model.
- Inserted a warning note in the README for users to potentially delete an old index if switching models.
Reviewed Changes
| File | Description |
|---|---|
| src/ProjectTemplates/Microsoft.Extensions.AI.Templates/src/ChatWithCustomData/ChatWithCustomData.Web/Services/SemanticSearchRecord.cs | Added conditional attribute to set vector dimension based on the ollama compilation symbol. |
| src/ProjectTemplates/Microsoft.Extensions.AI.Templates/src/ChatWithCustomData/ChatWithCustomData.Web/README.md | Updated the documentation with a note regarding potential index deletion due to vector dimension mismatch. |
Copilot reviewed 2 out of 2 changed files in this pull request and generated 1 comment.
...es/Microsoft.Extensions.AI.Templates/src/ChatWithCustomData/ChatWithCustomData.Web/README.md
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Co-authored-by: Copilot <[email protected]>
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