BerriAI/litellm · error · Exception

Failed to generate embedding for query: {e}

Error message

Failed to generate embedding for query: {e}

What it means

Error "Failed to generate embedding for query: {e}" thrown in BerriAI/litellm.

Source

Thrown at litellm/llms/milvus/vector_stores/transformation.py:161

        embedding_config: Final = litellm_params.get("litellm_embedding_config", {})
        if not embedding_config:
            raise ValueError(
                "embedding_config is required in litellm_params for Milvus. You can call any litellm embedding model."
                "Example: litellm_params['embedding_config'] = {'api_base': 'https://krris-mh44uf7y-eastus2.cognitiveservices.azure.com/', 'api_key': 'os.environ/AZURE_API_KEY', 'api_version': '2025-09-01'}"
            )

        # Get top_k (number of results to return)
        # Generate embedding for the query using litellm.embeddings
        try:
            embedding_response: Final = litellm.embedding(
                model=embedding_model,
                input=[query],
                **embedding_config,
            )
            query_vector: Final = embedding_response.data[0]["embedding"]
        except Exception as e:
            raise Exception(f"Failed to generate embedding for query: {e}")

        # Azure AI Search endpoint for search
        index_name: Final = vector_store_id  # vector_store_id is the index name
        url: Final = f"{api_base}/v2/vectordb/entities/search"

        # Build the request body for Azure AI Search with vector search
        request_body: Final[dict[str, Any]] = {
            "collectionName": index_name,
            "data": [query_vector],
            "annsField": "book_intro_vector",
            **vector_store_search_optional_params,
        }

        db_name: Final = litellm_params.get("milvus_db_name")
        if db_name:
            request_body["dbName"] = db_name

        partition_names: Final = litellm_params.get("milvus_partition_names")

View on GitHub (pinned to 6c2dcb801b)

Solutions

1. Check the embedding model configuration; see the wrapped exception.

When it happens

Trigger: Thrown at litellm/llms/milvus/vector_stores/transformation.py:161 when the library encounters an invalid state.

Common situations: See trigger scenarios.

AI-assisted analysis of BerriAI/litellm@6c2dcb801b (2026-08-15). Data as JSON: /api/errors/bd328f6a3d511e54. Report an issue: GitHub.