feat(anthropic): auto append relevant beta headers for computer use (#34117)

in addition to documenting it


https://platform.claude.com/docs/en/agents-and-tools/tool-use/computer-use-tool

libs/partners/anthropic/langchain_anthropic/chat_models.py

@@ -138,6 +138,8 @@ _TOOL_TYPE_TO_BETA: dict[str, str] = {
     "code_execution_20250522": "code-execution-2025-05-22",
     "code_execution_20250825": "code-execution-2025-08-25",
     "memory_20250818": "context-management-2025-06-27",
+    "computer_20250124": "computer-use-2025-01-24",
+    "computer_20251124": "computer-use-2025-11-24",
     "tool_search_tool_regex_20251119": "advanced-tool-use-2025-11-20",
     "tool_search_tool_bm25_20251119": "advanced-tool-use-2025-11-20",
 }
@@ -2531,6 +2533,60 @@ class ChatAnthropic(BaseChatModel):
             )
             ```
 
+        ??? example "Computer use tool"
+
+            Claude supports computer use capabilities, allowing it to interact with
+            desktop environments through screenshots, mouse control, and keyboard input.
+
+            !!! warning "Execution environment required"
+
+                LangChain handles the API integration, but **you must provide**:
+
+                - A sandboxed computing environment (Docker, VM, etc.)
+                - A virtual display (e.g., Xvfb)
+                - Code to execute tool calls (screenshot, clicks, typing)
+                - An agent loop to pass results back to Claude
+
+                Anthropic provides a [reference implementation](https://github.com/anthropics/anthropic-quickstarts/tree/main/computer-use-demo).
+
+            !!! note
+
+                Computer use requires:
+
+                - Claude Opus 4.5, Claude 4, or Claude Sonnet 3.7
+                - A sandboxed computing environment with virtual display
+
+            See the [Claude docs](https://platform.claude.com/docs/en/agents-and-tools/tool-use/computer-use-tool)
+            for setup instructions, model capability, and best practices.
+
+            ```python
+            from langchain_anthropic import ChatAnthropic
+
+            model = ChatAnthropic(model="claude-sonnet-4-5-20250929")
+
+            # LangChain handles the API call and tool binding
+            computer_tool = {
+                "type": "computer_20250124",
+                "name": "computer",
+                "display_width_px": 1024,
+                "display_height_px": 768,
+                "display_number": 1,
+            }
+
+            model_with_computer = model.bind_tools([computer_tool])
+            response = model_with_computer.invoke("Take a screenshot to see what's on the screen")
+
+            # response.tool_calls contains the action Claude wants to perform
+            # You must execute this action in your environment and pass the result back
+            ```
+
+            !!! note "Automatic beta header"
+
+                The required beta header is automatically appended based on the tool
+                version. For `computer_20250124` and `computer_20251124`, the respective
+                `computer-use-2025-01-24` and `computer-use-2025-11-24` beta header is
+                added automatically.
+
         ??? example "Strict tool use"
 
             Strict tool use guarantees that tool names and arguments are validated

libs/partners/anthropic/langchain_anthropic/data/_profiles.py

@@ -118,6 +118,23 @@ _PROFILES: dict[str, dict[str, Any]] = {
         "image_tool_message": True,
         "structured_output": False,
     },
+    "claude-opus-4-5": {
+        "max_input_tokens": 200000,
+        "max_output_tokens": 64000,
+        "image_inputs": True,
+        "audio_inputs": False,
+        "video_inputs": False,
+        "image_outputs": False,
+        "audio_outputs": False,
+        "video_outputs": False,
+        "reasoning_output": True,
+        "tool_calling": True,
+        "image_url_inputs": True,
+        "pdf_inputs": True,
+        "pdf_tool_message": True,
+        "image_tool_message": True,
+        "structured_output": False,
+    },
     "claude-3-opus-20240229": {
         "max_input_tokens": 200000,
         "max_output_tokens": 4096,

libs/partners/anthropic/tests/integration_tests/test_chat_models.py

@@ -582,6 +582,47 @@ def test_builtin_tools_text_editor() -> None:
     assert content_blocks[1]["name"] == "str_replace_based_edit_tool"
 
 
+def test_builtin_tools_computer_use() -> None:
+    """Test computer use tool integration.
+
+    Beta header should be automatically appended based on tool type.
+
+    This test only verifies tool call generation.
+    """
+    llm = ChatAnthropic(
+        model="claude-sonnet-4-5-20250929",  # type: ignore[call-arg]
+    )
+    tool = {
+        "type": "computer_20250124",
+        "name": "computer",
+        "display_width_px": 1024,
+        "display_height_px": 768,
+        "display_number": 1,
+    }
+    llm_with_tools = llm.bind_tools([tool])
+    response = llm_with_tools.invoke(
+        "Can you take a screenshot to see what's on the screen?",
+    )
+    assert isinstance(response, AIMessage)
+    assert response.tool_calls
+
+    content_blocks = response.content_blocks
+    assert len(content_blocks) >= 2
+    assert content_blocks[0]["type"] == "text"
+    assert content_blocks[0]["text"]
+
+    # Check that we have a tool_call for computer use
+    tool_call_blocks = [b for b in content_blocks if b["type"] == "tool_call"]
+    assert len(tool_call_blocks) >= 1
+    assert tool_call_blocks[0]["name"] == "computer"
+
+    # Verify tool call has expected action (screenshot in this case)
+    tool_call = response.tool_calls[0]
+    assert tool_call["name"] == "computer"
+    assert "action" in tool_call["args"]
+    assert tool_call["args"]["action"] == "screenshot"
+
+
 class GenerateUsername(BaseModel):
     """Get a username based on someone's name and hair color."""