BerriAI/litellm · error · ValueError

embedding_config is required in litellm_params for Milvus. Y

Error message

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'}

What it means

Error "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'}" thrown in BerriAI/litellm.

Source

Thrown at litellm/llms/milvus/vector_stores/transformation.py:146

        Transform search request for Azure AI Search API

        Generates embeddings using litellm.embeddings and constructs Azure AI Search request
        """
        # Convert query to string if it's a list
        if isinstance(query, list):
            query = " ".join(query)

        # Get embedding model from litellm_params (required)
        embedding_model: Final = litellm_params.get("litellm_embedding_model")
        if not embedding_model:
            raise ValueError(
                "embedding_model is required in litellm_params for Milvus. You can call any litellm embedding model."
                "Example: litellm_params['embedding_model'] = 'azure/text-embedding-3-large'"
            )

        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

View on GitHub (pinned to 6c2dcb801b)

Solutions

Set litellm_params['embedding_config'] for Milvus.

When it happens

Trigger: Thrown at litellm/llms/milvus/vector_stores/transformation.py:146 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/869fe011c0c09fa0. Report an issue: GitHub.