Repository: vllm-project/vllm
File: vllm/entrypoints/anthropic/serving.py (Python)

Code before:
            "stop": "end_turn",
            "length": "max_tokens",
            "tool_calls": "tool_use",
        }

    @staticmethod
    def _convert_image_source_to_url(source: dict[str, Any]) -> str:
        """Convert an Anthropic image source to an OpenAI-compatible URL.

        Anthropic supports two image source types:
        - base64: {"type": "base64", "media_type": "image/jpeg", "data": "..."}
        - url: {"type": "url", "url": "https://..."}

        For base64 sources, this constructs a proper data URI that
        downstream processors (e.g. vLLM's media connector) can handle.
        """
        source_type = source.get("type")
        if source_type == "url":
            return source.get("url", "")
        else:
            # Default to base64 processing if type is "base64"
            # or missing, ensuring a proper data URI is always
            # constructed for non-URL sources.
            media_type = source.get("media_type", "image/jpeg")
            data = source.get("data", "")
            return f"data:{media_type};base64,{data}"

    def _convert_anthropic_to_openai_request(
        self, anthropic_request: AnthropicMessagesRequest
    ) -> ChatCompletionRequest:
        """Convert Anthropic message format to OpenAI format"""
        openai_messages = []

        # Add system message if provided
        if anthropic_request.system:
            if isinstance(anthropic_request.system, str):
                openai_messages.append(
                    {"role": "system", "content": anthropic_request.system}
                )
            else:
                system_prompt = ""
                for block in anthropic_request.system:
                    if block.type == "text" and block.text:
                        system_prompt += block.text
                openai_messages.append({"role": "system", "content": system_prompt})

        for msg in anthropic_request.messages:
            openai_msg: dict[str, Any] = {"role": msg.role}  # type: ignore
            if isinstance(msg.content, str):
                openai_msg["content"] = msg.content
            else:

Review comment (suggestion):
```suggestion

        # Default to base64 processing if type is "base64"
        # or missing, ensuring a proper data URI is always
        # constructed for non-URL sources.
        media_type = source.get("media_type", "image/jpeg")
        data = source.get("data", "")
        return f"data:{media_type};base64,{data}"
```
Nit

Code after:
        self.stop_reason_map = {
            "stop": "end_turn",
            "length": "max_tokens",
            "tool_calls": "tool_use",
        }

    @staticmethod
    def _convert_image_source_to_url(source: dict[str, Any]) -> str:
        """Convert an Anthropic image source to an OpenAI-compatible URL.

        Anthropic supports two image source types:
        - base64: {"type": "base64", "media_type": "image/jpeg", "data": "..."}
        - url: {"type": "url", "url": "https://..."}

        For base64 sources, this constructs a proper data URI that
        downstream processors (e.g. vLLM's media connector) can handle.
        """
        source_type = source.get("type")
        if source_type == "url":
            return source.get("url", "")
        # Default to base64 processing if type is "base64"
        # or missing, ensuring a proper data URI is always
        # constructed for non-URL sources.
        media_type = source.get("media_type", "image/jpeg")
        data = source.get("data", "")
        return f"data:{media_type};base64,{data}"

    @classmethod
    def _convert_anthropic_to_openai_request(
        cls, anthropic_request: AnthropicMessagesRequest
    ) -> ChatCompletionRequest:
        """Convert Anthropic message format to OpenAI format"""
        openai_messages = []

        # Add system message if provided
        if anthropic_request.system:
            if isinstance(anthropic_request.system, str):
                openai_messages.append(
                    {"role": "system", "content": anthropic_request.system}
                )
            else:
                system_prompt = ""
                for block in anthropic_request.system:
                    if block.type == "text" and block.text:
                        system_prompt += block.text
                openai_messages.append({"role": "system", "content": system_prompt})

        for msg in anthropic_request.messages:
            openai_msg: dict[str, Any] = {"role": msg.role}  # type: ignore
            if isinstance(msg.content, str):
                openai_msg["content"] = msg.content