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Response transformation crashed with TypeError when counting tokens for multimodal (dict-shaped) embedding inputs, since encoding.encode() was called directly on the dict instead of its text parts. Also removed a dead, equally-buggy duplicate of the same loop in _transform_response. Separately, the embeddings guardrail handler silently skipped multimodal dict inputs instead of scanning them, letting prohibited text/image content bypass the configured guardrail. It now extracts and scans the text parts while leaving image parts untouched. |
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| .. | ||
| rag | ||
| base_vector_store_test.py | ||
| conftest.py | ||
| test_azure_ai_vector_store.py | ||
| test_azure_vector_store.py | ||
| test_bedrock_vector_store.py | ||
| test_gemini_vector_store.py | ||
| test_milvus_vector_store.py | ||
| test_openai_vector_store.py | ||
| test_ragflow_vector_store.py | ||
| test_s3_vectors_vector_store.py | ||
| test_vertex_ai_search_api_vector_store.py | ||
| test_vertex_ai_vector_store.py | ||