fix(anthropic): classify server tool message parts

instrumentation/opentelemetry-instrumentation-genai-anthropic/.changelog/699.fixed

@@ -0,0 +1 @@
+Represent Anthropic server tool calls and results with server tool message parts.

instrumentation/opentelemetry-instrumentation-genai-anthropic/src/opentelemetry/instrumentation/genai/anthropic/utils.py

@@ -9,7 +9,7 @@
 import json
 from collections.abc import Mapping
 from dataclasses import dataclass
-from typing import TYPE_CHECKING, Any, cast
+from typing import TYPE_CHECKING, cast
 
 from anthropic.types import (
     InputJSONDelta,
@@ -20,18 +20,28 @@
     ThinkingBlock,
     ThinkingDelta,
     ToolUseBlock,
-    WebSearchToolResultBlock,
 )
 
 from opentelemetry.util.genai.types import (
     BlobPart,
     MessagePart,
     ReasoningPart,
+    ServerToolCallPart,
+    ServerToolCallResponsePart,
     TextPart,
     ToolCallRequestPart,
     ToolCallResponsePart,
 )
 
+_SERVER_TOOL_RESULT_TYPES = {
+    "web_search_tool_result": "web_search",
+    "web_fetch_tool_result": "web_fetch",
+    "code_execution_tool_result": "code_execution",
+    "bash_code_execution_tool_result": "bash_code_execution",
+    "text_editor_code_execution_tool_result": "text_editor_code_execution",
+    "tool_search_tool_result": "tool_search",
+}
+
 if TYPE_CHECKING:
     from collections.abc import Iterable
 
@@ -120,7 +130,7 @@ def _extract_base64_blob(source: object, modality: str) -> BlobPart | None:
 
 
 def _convert_dict_block_to_part(
-    block: Mapping[str, Any],
+    block: Mapping[str, object],
 ) -> MessagePart | None:
     """Convert a request-param content block (TypedDict/dict) to a MessagePart."""
     block_type = block.get("type")
@@ -137,12 +147,42 @@ def _convert_dict_block_to_part(
             id=str(block.get("id", "")),
         )
 
+    if block_type == "server_tool_use":
+        name = str(block.get("name", ""))
+        server_tool_call = {
+            key: value
+            for key, value in block.items()
+            if key not in ("id", "name", "type")
+        }
+        server_tool_call["type"] = name
+        block_id = block.get("id")
+        return ServerToolCallPart(
+            name=name,
+            server_tool_call=server_tool_call,
+            id=str(block_id) if block_id is not None else None,
+        )
+
     if block_type == "tool_result":
         return ToolCallResponsePart(
             response=block.get("content"),
             id=str(block.get("tool_use_id", "")),
         )
 
+    if isinstance(block_type, str) and (
+        server_tool_name := _SERVER_TOOL_RESULT_TYPES.get(block_type)
+    ):
+        server_tool_call_response = {
+            key: value
+            for key, value in block.items()
+            if key not in ("tool_use_id", "type")
+        }
+        server_tool_call_response["type"] = server_tool_name
+        tool_use_id = block.get("tool_use_id")
+        return ServerToolCallResponsePart(
+            server_tool_call_response=server_tool_call_response,
+            id=str(tool_use_id) if tool_use_id is not None else None,
+        )
+
     if block_type in ("thinking", "redacted_thinking"):
         thinking = block.get("thinking") or block.get("data")
         return ReasoningPart(
@@ -159,29 +199,32 @@ def _convert_content_block_to_part(
     block: ContentBlock | ContentBlockParam,
 ) -> MessagePart | None:
     """Convert an Anthropic content block to a MessagePart."""
+    if isinstance(block, Mapping):
+        return _convert_dict_block_to_part(cast(Mapping[str, object], block))
+
     if isinstance(block, TextBlock):
         return TextPart(content=block.text)
 
-    if isinstance(block, (ToolUseBlock, ServerToolUseBlock)):
+    if isinstance(block, ToolUseBlock):
         return ToolCallRequestPart(
             arguments=block.input, name=block.name, id=block.id
         )
 
+    if isinstance(block, ServerToolUseBlock):
+        return _convert_dict_block_to_part(block.model_dump(exclude_none=True))
+
     if isinstance(block, (ThinkingBlock, RedactedThinkingBlock)):
         content = (
             block.thinking if isinstance(block, ThinkingBlock) else block.data
         )
         return ReasoningPart(content=content)
 
-    if isinstance(block, WebSearchToolResultBlock):
-        return ToolCallResponsePart(
-            response=block.model_dump().get("content"),
-            id=block.tool_use_id,
+    if block.type in _SERVER_TOOL_RESULT_TYPES:
+        return _convert_dict_block_to_part(
+            cast(Mapping[str, object], block.model_dump(exclude_none=True))
         )
 
-    if not hasattr(block, "get"):
-        return None
-    return _convert_dict_block_to_part(cast(Mapping[str, Any], block))
+    return None
 
 
 def convert_content_to_parts(

instrumentation/opentelemetry-instrumentation-genai-anthropic/tests/cassettes/server_tool_calling_conformance.yaml

@@ -0,0 +1,58 @@
+# TODO: this is generated by AI, re-record
+interactions:
+- request:
+    body: |-
+      {"max_tokens":256,"messages":[{"role":"user","content":"Search for OpenTelemetry."}],"model":"claude-sonnet-4-20250514","tools":[{"type":"web_search_20250305","name":"web_search","max_uses":1}]}
+    headers:
+      accept:
+      - application/json
+      content-type:
+      - application/json
+      host:
+      - api.anthropic.com
+      x-api-key:
+      - test_anthropic_api_key
+    method: POST
+    uri: https://api.anthropic.com/v1/messages
+  response:
+    body:
+      string: |-
+        {
+          "id": "msg_server_tool",
+          "type": "message",
+          "role": "assistant",
+          "model": "claude-sonnet-4-20250514",
+          "content": [
+            {
+              "type": "server_tool_use",
+              "id": "srvtoolu_01",
+              "name": "web_search",
+              "input": {"query": "OpenTelemetry"}
+            },
+            {
+              "type": "web_search_tool_result",
+              "tool_use_id": "srvtoolu_01",
+              "content": {
+                "type": "web_search_tool_result_error",
+                "error_code": "unavailable"
+              }
+            },
+            {
+              "type": "text",
+              "text": "Search was unavailable."
+            }
+          ],
+          "stop_reason": "end_turn",
+          "stop_sequence": null,
+          "usage": {
+            "input_tokens": 20,
+            "output_tokens": 15
+          }
+        }
+    headers:
+      Content-Type:
+      - application/json
+    status:
+      code: 200
+      message: OK
+version: 1

instrumentation/opentelemetry-instrumentation-genai-anthropic/tests/conformance/server_tool_calling.py

@@ -0,0 +1,102 @@
+# Copyright The OpenTelemetry Authors
+# SPDX-License-Identifier: Apache-2.0
+
+"""Conformance scenario: Anthropic chat with server-side tool calls."""
+
+from __future__ import annotations
+
+import json
+import os
+from typing import Any
+from unittest import mock
+
+from anthropic import Anthropic
+
+from opentelemetry.instrumentation.genai.anthropic import AnthropicInstrumentor
+from opentelemetry.sdk._logs import LoggerProvider
+from opentelemetry.sdk.metrics import MeterProvider
+from opentelemetry.sdk.trace import TracerProvider
+from opentelemetry.test.weaver_live_check import LiveCheckReport
+from opentelemetry.test_util_genai.conformance import Scenario
+from opentelemetry.test_util_genai.instrumentor import instrument
+
+
+class ServerToolCallingScenario(Scenario):
+    expected_spans = {"chat": 1}
+    expected_metrics = (
+        "gen_ai.client.operation.duration",
+        "gen_ai.client.token.usage",
+    )
+
+    def validate(self, report: LiveCheckReport) -> None:
+        super().validate(report)
+        output_messages = [
+            json.loads(attribute["value"])
+            for entry in report["samples"]
+            if "span" in entry
+            for attribute in entry["span"]["attributes"]
+            if attribute["name"] == "gen_ai.output.messages"
+        ]
+        assert len(output_messages) == 1
+        assert output_messages[0][0]["parts"][:2] == [
+            {
+                "name": "web_search",
+                "server_tool_call": {
+                    "input": {"query": "OpenTelemetry"},
+                    "type": "web_search",
+                },
+                "id": "srvtoolu_01",
+                "type": "server_tool_call",
+            },
+            {
+                "server_tool_call_response": {
+                    "content": {
+                        "error_code": "unavailable",
+                        "type": "web_search_tool_result_error",
+                    },
+                    "type": "web_search",
+                },
+                "id": "srvtoolu_01",
+                "type": "server_tool_call_response",
+            },
+        ]
+
+    def run(
+        self,
+        *,
+        tracer_provider: TracerProvider,
+        meter_provider: MeterProvider,
+        logger_provider: LoggerProvider,
+        vcr: Any,
+    ) -> None:
+        key_override = (
+            {}
+            if os.getenv("ANTHROPIC_API_KEY")
+            else {"ANTHROPIC_API_KEY": "test_anthropic_api_key"}
+        )
+        with mock.patch.dict(os.environ, key_override):
+            with instrument(
+                AnthropicInstrumentor(),
+                tracer_provider=tracer_provider,
+                logger_provider=logger_provider,
+                meter_provider=meter_provider,
+                content_capture="SPAN_ONLY",
+            ):
+                with vcr.use_cassette("server_tool_calling_conformance.yaml"):
+                    Anthropic().messages.create(
+                        model="claude-sonnet-4-20250514",
+                        max_tokens=256,
+                        messages=[
+                            {
+                                "role": "user",
+                                "content": "Search for OpenTelemetry.",
+                            }
+                        ],
+                        tools=[
+                            {
+                                "type": "web_search_20250305",
+                                "name": "web_search",
+                                "max_uses": 1,
+                            }
+                        ],
+                    )

instrumentation/opentelemetry-instrumentation-genai-anthropic/tests/test_conformance.py

@@ -24,6 +24,7 @@
     InferenceRawResponseStreamingScenario,
 )
 from .conformance.inference_streaming import InferenceStreamingScenario
+from .conformance.server_tool_calling import ServerToolCallingScenario
 from .conformance.tool_calling import ToolCallingScenario
 
 
@@ -35,6 +36,7 @@
         InferenceRawResponseScenario(),
         InferenceRawResponseStreamingScenario(),
         ToolCallingScenario(),
+        ServerToolCallingScenario(),
     ],
     ids=lambda s: type(s).__name__,
 )