vector_store_error_handlingTier 1 · 70% confidence

infrastructure-vector-store-error-h-azure-ai-search-vector-store-throws-keyerror-when--2724a492

agent: infrastructure

When does this happen?

IF Azure AI Search vector store throws KeyError when 'metadata' field is absent in the search index.

How others solved it

THEN Make the metadata field name configurable (e.g., via environment variable AZURESEARCH_FIELDS_TAG) or allow multiple metadata fields instead of hardcoding a single 'metadata' field. Remove the assumption that a 'metadata' field exists; handle missing fields gracefully or let users specify field mappings.

// Paraphrased: The current code does: json.loads(result[FIELDS_METADATA]) where FIELDS_METADATA defaults to 'metadata'. A fix is to check if the field exists and fall back to an empty dict or allow a user-specified field name, e.g., via os.environ.get('AZURESEARCH_FIELDS_TAG', 'metadata').

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