BerriAI/litellm · error · ValueError

Embedding batch records do not have a chat-completion equiva

Error message

Embedding batch records do not have a chat-completion equivalent

What it means

Error "Embedding batch records do not have a chat-completion equivalent" thrown in BerriAI/litellm.

Source

Thrown at litellm/llms/bedrock/files/transformation.py:710

    @staticmethod
    def _transform_batch_body_to_chat_body(
        openai_request_body: _OpenAIBatchRecordBody,
        record_kind: BedrockBatchRecordKind,
    ) -> Mapping[str, object]:
        """
        Normalize a non-embedding batch body to the Chat Completions shape the
        per-provider Bedrock transformations expect.
        """
        match record_kind:
            case BedrockBatchRecordKind.TEXT_COMPLETION:
                return BedrockFilesConfig._transform_text_completion_body_to_chat_body(openai_request_body)
            case BedrockBatchRecordKind.RESPONSES:
                return BedrockFilesConfig._transform_responses_body_to_chat_body(openai_request_body)
            case BedrockBatchRecordKind.CHAT:
                return openai_request_body
            case BedrockBatchRecordKind.EMBEDDING:
                raise ValueError("Embedding batch records do not have a chat-completion equivalent")

    def _map_openai_to_bedrock_params(
        self,
        openai_request_body: Mapping[str, Any],
        model: str,
        provider: str | None = None,
    ) -> dict[str, object]:
        """
        Transform OpenAI request body to Bedrock-compatible modelInput
        parameters using existing transformation logic.

        Routes to the correct per-provider transformation so that the
        resulting dict matches the InvokeModel body that Bedrock expects
        for batch inference.
        """
        from litellm.types.utils import LlmProviders

        messages: Final = openai_request_body.get("messages", [])

View on GitHub (pinned to 6c2dcb801b)

Solutions

1. Embedding batch records cannot be converted to chat-completion format; use an embedding route.

When it happens

Trigger: Thrown at litellm/llms/bedrock/files/transformation.py:710 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/a751f78456fe6397. Report an issue: GitHub.