diff --git a/litellm/litellm_core_utils/token_counter.py b/litellm/litellm_core_utils/token_counter.py index 858b078d626..ccfce0e4133 100644 --- a/litellm/litellm_core_utils/token_counter.py +++ b/litellm/litellm_core_utils/token_counter.py @@ -646,6 +646,24 @@ def _validate_anthropic_content(content: Mapping[str, Any]) -> type: return expected_cls +def _anthropic_image_source_data(source: Mapping[str, str]) -> str: + """ + Resolve an Anthropic image `source` to the data string `calculate_img_tokens` prices. + + Returns "" for a `file` source, whose bytes the proxy cannot resolve locally. + """ + source_type: Final = source.get("type") + if source_type == "base64": + data: Final = source.get("data") + if not data: + return "" + media_type: Final = source.get("media_type") or "image/png" + return f"data:{media_type};base64,{data}" + if source_type == "url": + return source.get("url") or "" + return "" + + def _count_anthropic_content( content: Mapping[str, Any], count_function: TokenCounterFunction, @@ -714,6 +732,13 @@ def _count_content_list( elif c["type"] == "image_url": image_url = c.get("image_url") num_tokens += _count_image_tokens(image_url, use_default_image_token_count) + elif c["type"] == "image": + source = c.get("source") + num_tokens += calculate_img_tokens( + data=_anthropic_image_source_data(source) if isinstance(source, dict) else "", + mode="auto", + use_default_image_token_count=use_default_image_token_count, + ) elif c["type"] in ("tool_use", "tool_result"): num_tokens += _count_anthropic_content( c, @@ -742,7 +767,8 @@ def _count_content_list( content_type = c.get("type", type(c).__name__) if isinstance(c, dict) else type(c).__name__ raise ValueError( f"Invalid content item type: {content_type}. " - f"Expected str or dict with 'type' field (text, image_url, tool_use, tool_result, thinking, tool_reference)." + f"Expected str or dict with 'type' field " + f"(text, image_url, image, tool_use, tool_result, thinking, tool_reference)." ) return num_tokens except Exception as e: diff --git a/tests/test_litellm/litellm_core_utils/test_token_counter.py b/tests/test_litellm/litellm_core_utils/test_token_counter.py index a2590dbca2d..701a1accd5f 100644 --- a/tests/test_litellm/litellm_core_utils/test_token_counter.py +++ b/tests/test_litellm/litellm_core_utils/test_token_counter.py @@ -1160,3 +1160,123 @@ def test_count_content_list_rejects_unknown_type(): message = str(exc_info.value) assert "Invalid content item type: totally_unknown_block" in message assert "tool_reference" in message + + +@pytest.mark.parametrize( + "source", + [ + {"type": "base64", "media_type": "image/png", "data": "iVBORw0KGgo="}, + {"type": "url", "url": "https://example.com/image.png"}, + {"type": "file", "file_id": "file-abc123"}, + ], + ids=["base64", "url", "file"], +) +def test_token_counter_with_anthropic_image_block(source): + """ + Anthropic-native `image` blocks must NOT raise, for every source variant. + + Before this fix `_count_content_list` raised + `Invalid content item type: image`. That 500s /v1/messages/count_tokens and + /utils/token_counter, and it makes the router's context-window pre-call + check swallow the error and return every deployment unfiltered, so an + oversized prompt carrying an image is dispatched upstream instead of being + rejected locally. + """ + from litellm.constants import DEFAULT_IMAGE_TOKEN_COUNT + + messages = [ + { + "role": "user", + "content": [ + {"type": "text", "text": "What is in this image?"}, + {"type": "image", "source": source}, + ], + } + ] + + tokens = token_counter( + model="anthropic/claude-sonnet-4-5-20250929", + messages=messages, + use_default_image_token_count=True, + ) + assert tokens > DEFAULT_IMAGE_TOKEN_COUNT, ( + f"Expected the image block to contribute tokens, got {tokens}" + ) + + +def test_anthropic_image_block_matches_equivalent_image_url(): + """ + An Anthropic `image` block must price identically to the OpenAI `image_url` + block carrying the same bytes, so the count does not depend on which + endpoint shape the caller used. + """ + anthropic_messages = [ + { + "role": "user", + "content": [ + { + "type": "image", + "source": { + "type": "base64", + "media_type": "image/png", + "data": "iVBORw0KGgo=", + }, + } + ], + } + ] + openai_messages = [ + { + "role": "user", + "content": [ + { + "type": "image_url", + "image_url": {"url": "data:image/png;base64,iVBORw0KGgo="}, + } + ], + } + ] + + anthropic_tokens = token_counter( + model="anthropic/claude-sonnet-4-5-20250929", messages=anthropic_messages + ) + openai_tokens = token_counter( + model="anthropic/claude-sonnet-4-5-20250929", messages=openai_messages + ) + assert anthropic_tokens == openai_tokens + + +def test_anthropic_image_block_nested_in_tool_result(): + """ + An `image` block nested inside a `tool_result.content` list must be counted + too. `_count_anthropic_content` recurses back into `_count_content_list`, so + the nested case failed for the same reason the top-level one did. + """ + messages = [ + { + "role": "user", + "content": [ + { + "type": "tool_result", + "tool_use_id": "toolu_01", + "content": [ + { + "type": "image", + "source": { + "type": "base64", + "media_type": "image/png", + "data": "iVBORw0KGgo=", + }, + } + ], + } + ], + } + ] + + tokens = token_counter( + model="anthropic/claude-sonnet-4-5-20250929", + messages=messages, + use_default_image_token_count=True, + ) + assert tokens > 0