feat: Add tool support to AnthropicMultiModal (#17302)

llama-index-integrations/llms/llama-index-llms-bedrock/pyproject.toml

@@ -27,7 +27,7 @@ exclude = ["**/BUILD"]
 license = "MIT"
 name = "llama-index-llms-bedrock"
 readme = "README.md"
-version = "0.3.1"
+version = "0.3.2"
 
 [tool.poetry.dependencies]
 python = ">=3.9,<4.0"

llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-anthropic/llama_index/multi_modal_llms/anthropic/base.py

@@ -194,6 +194,7 @@ def _get_response_token_counts(self, raw_response: Any) -> dict:
     def _complete(
         self, prompt: str, image_documents: Sequence[ImageNode], **kwargs: Any
     ) -> CompletionResponse:
+        """Complete the prompt with image support and optional tool calls."""
         all_kwargs = self._get_model_kwargs(**kwargs)
         message_dict = self._get_multi_modal_chat_messages(
             prompt=prompt, role=MessageRole.USER, image_documents=image_documents
@@ -206,8 +207,17 @@ def _complete(
             **all_kwargs,
         )
 
+        # Handle both tool and text responses
+        content = response.content[0]
+        if hasattr(content, "input"):
+            # Tool response - convert to string for compatibility
+            text = str(content.input)
+        else:
+            # Standard text response
+            text = content.text
+
         return CompletionResponse(
-            text=response.content[0].text,
+            text=text,
             raw=response,
             additional_kwargs=self._get_response_token_counts(response),
         )

llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-anthropic/pyproject.toml

@@ -27,7 +27,7 @@ exclude = ["**/BUILD"]
 license = "MIT"
 name = "llama-index-multi-modal-llms-anthropic"
 readme = "README.md"
-version = "0.3.0"
+version = "0.3.1"
 
 [tool.poetry.dependencies]
 python = ">=3.9,<4.0"

llama-index-integrations/multi_modal_llms/llama-index-multi-modal-llms-anthropic/tests/test_multi-modal-llms_anthropic.py

@@ -1,5 +1,7 @@
+from unittest.mock import Mock, patch
 from llama_index.core.multi_modal_llms.base import MultiModalLLM
 from llama_index.multi_modal_llms.anthropic import AnthropicMultiModal
+from llama_index.core.base.llms.types import CompletionResponse
 
 
 def test_embedding_class():
@@ -10,3 +12,45 @@ def test_embedding_class():
 def test_init():
     m = AnthropicMultiModal(max_tokens=400)
     assert m.max_tokens == 400
+
+
+def test_tool_response():
+    """Test handling of tool responses."""
+    llm = AnthropicMultiModal(max_tokens=400)
+
+    # Create mock response with tool input
+    mock_content = Mock()
+    mock_content.input = {
+        "booking_number": "123",
+        "carrier": "Test Carrier",
+        "total_amount": 1000.0,
+    }
+    mock_response = Mock()
+    mock_response.content = [mock_content]
+
+    with patch.object(llm._client.messages, "create", return_value=mock_response):
+        response = llm.complete(
+            prompt="test prompt",
+            image_documents=[],
+            tools=[
+                {
+                    "name": "tms_order_payload",
+                    "description": "Test tool",
+                    "input_schema": {
+                        "type": "object",
+                        "properties": {
+                            "booking_number": {"type": "string"},
+                            "carrier": {"type": "string"},
+                            "total_amount": {"type": "number"},
+                        },
+                    },
+                }
+            ],
+            tool_choice={"type": "tool", "name": "tms_order_payload"},
+        )
+
+        assert isinstance(response, CompletionResponse)
+        assert isinstance(response.text, str)
+        assert "booking_number" in response.text
+        assert "123" in response.text
+        assert response.raw == mock_response