You can resolve embedding mismatches in LlamaIndex by re-embedding nodes using a consistent embedding model and updating the index accordingly.
Here is the code snippet below:

In the above code we are using the following key points:
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Reloading the existing index using load_index_from_storage.
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Applying a uniform HuggingFaceEmbedding model for consistency.
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Recomputing embeddings for each node to fix mismatches.
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Rebuilding and persisting the updated index.
Hence, re-embedding with a unified model ensures alignment and consistency in your LlamaIndex-based pipelines.