feat(api): adds support for Claude Opus 4.5, Effort, Advance Tool Use Features, Autocompaction, and Computer Use v5

Author: stainless-app[bot]

.stats.yml

@@ -1,4 +1,4 @@
 configured_endpoints: 34
-openapi_spec_url: https://storage.googleapis.com/stainless-sdk-openapi-specs/anthropic%2Fanthropic-2f35b2ff9174d526a6d35796d2703490bfa5692312af67cbdfa4500283dabe31.yml
-openapi_spec_hash: dc52b25c487e97d355ef645644aa13e7
-config_hash: d23c4d678fcf7ff829a2891b3196edb6
+openapi_spec_url: https://storage.googleapis.com/stainless-sdk-openapi-specs/anthropic%2Fanthropic-a49e89deec4e00d1da490808099d66e2001531b12d8666a7f5d0b496f760440d.yml
+openapi_spec_hash: c93ef3808c58e233b01966ff154f31ce
+config_hash: 7e9dfe17ab5c80abee5372ce746a926e

api.md

@@ -256,6 +256,7 @@ from anthropic.types.beta import (
     BetaContextManagementConfig,
     BetaContextManagementResponse,
     BetaCountTokensContextManagementResponse,
+    BetaDirectCaller,
     BetaDocumentBlock,
     BetaFileDocumentSource,
     BetaFileImageSource,
@@ -264,9 +265,12 @@ from anthropic.types.beta import (
     BetaInputTokensClearAtLeast,
     BetaInputTokensTrigger,
     BetaJSONOutputFormat,
+    BetaMCPToolConfig,
+    BetaMCPToolDefaultConfig,
     BetaMCPToolResultBlock,
     BetaMCPToolUseBlock,
     BetaMCPToolUseBlockParam,
+    BetaMCPToolset,
     BetaMemoryTool20250818,
     BetaMemoryTool20250818Command,
     BetaMemoryTool20250818CreateCommand,
@@ -280,6 +284,7 @@ from anthropic.types.beta import (
     BetaMessageParam,
     BetaMessageTokensCount,
     BetaMetadata,
+    BetaOutputConfig,
     BetaPlainTextSource,
     BetaRawContentBlockDelta,
     BetaRawContentBlockDeltaEvent,
@@ -296,6 +301,7 @@ from anthropic.types.beta import (
     BetaRequestMCPServerURLDefinition,
     BetaRequestMCPToolResultBlockParam,
     BetaSearchResultBlockParam,
+    BetaServerToolCaller,
     BetaServerToolUsage,
     BetaServerToolUseBlock,
     BetaServerToolUseBlockParam,
@@ -335,7 +341,18 @@ from anthropic.types.beta import (
     BetaToolChoiceTool,
     BetaToolComputerUse20241022,
     BetaToolComputerUse20250124,
+    BetaToolComputerUse20251124,
+    BetaToolReferenceBlock,
+    BetaToolReferenceBlockParam,
     BetaToolResultBlockParam,
+    BetaToolSearchToolBm25_20251119,
+    BetaToolSearchToolRegex20251119,
+    BetaToolSearchToolResultBlock,
+    BetaToolSearchToolResultBlockParam,
+    BetaToolSearchToolResultError,
+    BetaToolSearchToolResultErrorParam,
+    BetaToolSearchToolSearchResultBlock,
+    BetaToolSearchToolSearchResultBlockParam,
     BetaToolTextEditor20241022,
     BetaToolTextEditor20250124,
     BetaToolTextEditor20250429,

examples/auto_compaction.py

@@ -0,0 +1,77 @@
+"""Show the full summary content after compaction"""
+
+import json
+
+from anthropic import Anthropic
+from anthropic.lib.tools import beta_tool
+
+
+@beta_tool
+def search(query: str) -> str:
+    """Search for information."""
+    return json.dumps(
+        {
+            "results": [
+                {"title": f"Result for {query}", "content": "Lorem ipsum " * 100},
+                {"title": f"More on {query}", "content": "Detailed info " * 100},
+            ]
+        }
+    )
+
+
+@beta_tool
+def done(summary: str) -> str:  # noqa: ARG001
+    """Call when finished."""
+    return "Complete"
+
+
+client = Anthropic()
+
+runner = client.beta.messages.tool_runner(
+    model="claude-sonnet-4-20250514",
+    max_tokens=4096,
+    tools=[search, done],
+    messages=[
+        {
+            "role": "user",
+            "content": "You MUST search for EACH of these animals ONE BY ONE: dogs, cats, birds, fish, horses, elephants, lions, tigers, bears, wolves. After searching for ALL of them, call done.",
+        }
+    ],
+    compaction_control={
+        "enabled": True,
+        "context_token_threshold": 3000,  # Even lower threshold
+    },
+)
+
+prev_msg_count = 0
+for i, message in enumerate(runner):
+    curr_msg_count = len(list(runner._params["messages"]))
+    print(f"Turn {i + 1}: {message.usage.input_tokens} input tokens, {curr_msg_count} messages")
+
+    if curr_msg_count < prev_msg_count:
+        print("=" * 70)
+        print("🔄 COMPACTION OCCURRED!")
+        print("=" * 70)
+        print(f"Messages went from {prev_msg_count} → {curr_msg_count}")
+        print(f"Input tokens: {message.usage.input_tokens}")
+        print("\nNEW MESSAGES LIST:")
+        print("-" * 70)
+
+        for msg in runner._params["messages"]:
+            role = msg.get("role", "?")
+            content = msg.get("content", "")
+
+            if isinstance(content, list):
+                for block in content:
+                    if isinstance(block, dict) and block.get("type") == "text":
+                        print(f"\n[{role}] TEXT BLOCK:")
+                        print(block.get("text", ""))
+            elif isinstance(content, str):
+                print(f"\n[{role}]:")
+                print(content)
+
+        print("-" * 70)
+
+    prev_msg_count = curr_msg_count
+
+print("\n✅ Done!")

examples/tools_runner_search_tool.py

@@ -0,0 +1,80 @@
+import json
+from typing import Any, List
+from typing_extensions import Literal
+
+import rich
+
+from anthropic import Anthropic, beta_tool
+from anthropic.lib.tools import BetaFunctionTool, BetaFunctionToolResultType
+from anthropic.types.beta import BetaToolReferenceBlockParam
+
+client = Anthropic()
+
+
+@beta_tool(defer_loading=True)
+def get_weather(location: str, units: Literal["c", "f"]) -> str:
+    """Lookup the weather for a given city in either celsius or fahrenheit
+
+    Args:
+        location: The city and state, e.g. San Francisco, CA
+        units: Unit for the output, either 'c' for celsius or 'f' for fahrenheit
+    Returns:
+        A dictionary containing the location, temperature, and weather condition.
+    """
+    # Simulate a weather API call
+    print(f"Fetching weather for {location} in {units}")
+
+    # Here you would typically make an API call to a weather service
+    # For demonstration, we return a mock response
+    if units == "c":
+        return json.dumps(
+            {
+                "location": location,
+                "temperature": "20°C",
+                "condition": "Sunny",
+            }
+        )
+    else:
+        return json.dumps(
+            {
+                "location": location,
+                "temperature": "68°F",
+                "condition": "Sunny",
+            }
+        )
+
+
+def make_tool_searcher(tools: List[BetaFunctionTool[Any]]) -> BetaFunctionTool[Any]:
+    """Returns a tool that Claude can use to search through all available tools"""
+
+    @beta_tool
+    def search_available_tools(*, keyword: str) -> BetaFunctionToolResultType:
+        """Search for useful tools using a query string"""
+
+        results: list[BetaToolReferenceBlockParam] = []
+        for tool in tools:
+            if keyword in json.dumps(tool.to_dict()):
+                results.append({"type": "tool_reference", "tool_name": tool.name})
+
+        return results
+
+    return search_available_tools
+
+
+def main() -> None:
+    tools: list[BetaFunctionTool[Any]] = [
+        get_weather,
+        # ... many more tools
+    ]
+    runner = client.beta.messages.tool_runner(
+        max_tokens=1024,
+        model="claude-sonnet-4-5-20250929",
+        tools=[*tools, make_tool_searcher(tools)],
+        messages=[{"role": "user", "content": "What is the weather in SF?"}],
+        betas=["tool-search-tool-2025-10-19"],
+    )
+    for message in runner:
+        rich.print(message)
+
+
+main()

pyproject.toml

@@ -160,7 +160,7 @@ show_error_codes = true
 #
 # We also exclude our `tests` as mypy doesn't always infer
 # types correctly and Pyright will still catch any type errors.
-exclude = ['src/anthropic/_files.py', '_dev/.*.py', 'tests/.*', 'examples/mcp_server_weather.py', 'examples/tools_with_mcp.py', 'examples/memory/basic.py', 'src/anthropic/lib/_parse/_transform.py']
+exclude = ['src/anthropic/_files.py', '_dev/.*.py', 'tests/.*', 'examples/mcp_server_weather.py', 'examples/tools_with_mcp.py', 'examples/memory/basic.py', 'src/anthropic/lib/_parse/_transform.py', 'src/anthropic/lib/tools/_beta_functions.py']
 
 strict_equality = true
 implicit_reexport = true

src/anthropic/lib/streaming/_beta_messages.py

@@ -468,7 +468,7 @@ def accumulate_event(
         current_snapshot.content.append(
             cast(
                 Any,  # Pydantic does not support generic unions at runtime
-                construct_type(type_=ParsedBetaContentBlock, value=event.content_block.model_dump()),
+                construct_type(type_=ParsedBetaContentBlock, value=event.content_block.to_dict()),
             ),
         )
     elif event.type == "content_block_delta":

src/anthropic/lib/tools/_beta_compaction_control.py

@@ -0,0 +1,48 @@
+from typing import TypedDict
+from typing_extensions import Required
+
+DEFAULT_SUMMARY_PROMPT = """You have been working on the task described above but have not yet completed it. Write a continuation summary that will allow you (or another instance of yourself) to resume work efficiently in a future context window where the conversation history will be replaced with this summary. Your summary should be structured, concise, and actionable. Include:
+1. Task Overview
+The user's core request and success criteria
+Any clarifications or constraints they specified
+2. Current State
+What has been completed so far
+Files created, modified, or analyzed (with paths if relevant)
+Key outputs or artifacts produced
+3. Important Discoveries
+Technical constraints or requirements uncovered
+Decisions made and their rationale
+Errors encountered and how they were resolved
+What approaches were tried that didn't work (and why)
+4. Next Steps
+Specific actions needed to complete the task
+Any blockers or open questions to resolve
+Priority order if multiple steps remain
+5. Context to Preserve
+User preferences or style requirements
+Domain-specific details that aren't obvious
+Any promises made to the user
+Be concise but complete—err on the side of including information that would prevent duplicate work or repeated mistakes. Write in a way that enables immediate resumption of the task.
+Wrap your summary in <summary></summary> tags."""
+
+DEFAULT_THRESHOLD = 100_000
+
+
+class CompactionControl(TypedDict, total=False):
+    context_token_threshold: int
+    """The context token threshold at which to trigger compaction.
+    
+    When the cumulative token count (input + output) across all messages exceeds this threshold,
+    the message history will be automatically summarized and compressed. Defaults to 150,000 tokens.
+    """
+
+    model: str
+    """
+    The model to use for generating the compaction summary.
+    If not specified, defaults to the same model used for the tool runner.
+    """
+
+    summary_prompt: str
+    """The prompt used to instruct the model on how to generate the summary."""
+
+    enabled: Required[bool]