chore(trace): updated semantic conventions with tool mappings

poshinchen · poshinchen · commit 22fa807b2a2f · 2025-10-08T16:44:05.000-04:00
diff --git a/src/strands/telemetry/tracer.py b/src/strands/telemetry/tracer.py
@@ -316,7 +316,7 @@ def end_model_invoke_span(
                         [
                             {
                                 "role": message["role"],
-                                "parts": [{"type": "text", "content": message["content"]}],
+                                "parts": self._map_content_blocks_to_otel_parts(message["content"]),
                                 "finish_reason": str(stop_reason),
                             }
                         ]
@@ -371,7 +371,7 @@ def start_tool_call_span(self, tool: ToolUse, parent_span: Optional[Span] = None
                                         "type": "tool_call",
                                         "name": tool["name"],
                                         "id": tool["toolUseId"],
-                                        "arguments": [{"content": tool["input"]}],
+                                        "arguments": tool["input"],
                                     }
                                 ],
                             }
@@ -426,7 +426,7 @@ def end_tool_call_span(
                                         {
                                             "type": "tool_call_response",
                                             "id": tool_result.get("toolUseId", ""),
-                                            "result": tool_result.get("content"),
+                                            "response": tool_result.get("content"),
                                         }
                                     ],
                                 }
@@ -513,7 +513,7 @@ def end_event_loop_cycle_span(
                             [
                                 {
                                     "role": tool_result_message["role"],
-                                    "parts": [{"type": "text", "content": tool_result_message["content"]}],
+                                    "parts": self._map_content_blocks_to_otel_parts(tool_result_message["content"]),
                                 }
                             ]
                         )
@@ -727,7 +727,7 @@ def _add_event_messages(self, span: Span, messages: Messages) -> None:
             input_messages: list = []
             for message in messages:
                 input_messages.append(
-                    {"role": message["role"], "parts": [{"type": "text", "content": message["content"]}]}
+                    {"role": message["role"], "parts": self._map_content_blocks_to_otel_parts(message["content"])}
                 )
             self._add_event(
                 span, "gen_ai.client.inference.operation.details", {"gen_ai.input.messages": serialize(input_messages)}
@@ -740,6 +740,41 @@ def _add_event_messages(self, span: Span, messages: Messages) -> None:
                     {"content": serialize(message["content"])},
                 )
 
+    def _map_content_blocks_to_otel_parts(self, content_blocks: list[ContentBlock]) -> list[dict[str, Any]]:
+        """Map ContentBlock objects to OpenTelemetry parts format."""
+        parts: list[dict[str, Any]] = []
+
+        for block in content_blocks:
+            if "text" in block:
+                # Standard TextPart
+                parts.append({"type": "text", "content": block["text"]})
+            elif "toolUse" in block:
+                # Standard ToolCallRequestPart
+                tool_use = block["toolUse"]
+                parts.append(
+                    {
+                        "type": "tool_call",
+                        "name": tool_use["name"],
+                        "id": tool_use["toolUseId"],
+                        "arguments": tool_use["input"],
+                    }
+                )
+            elif "toolResult" in block:
+                # Standard ToolCallResponsePart
+                tool_result = block["toolResult"]
+                parts.append(
+                    {
+                        "type": "tool_call_response",
+                        "id": tool_result["toolUseId"],
+                        "response": tool_result["content"],
+                    }
+                )
+            else:
+                # For all other ContentBlock types, use the key as type and value as content
+                for key, value in block.items():
+                    parts.append({"type": key, "content": value})
+        return parts
+
 
 # Singleton instance for global access
 _tracer_instance = None
diff --git a/tests/strands/telemetry/test_tracer.py b/tests/strands/telemetry/test_tracer.py
@@ -191,7 +191,7 @@ def test_start_model_invoke_span_latest_conventions(mock_tracer):
                     [
                         {
                             "role": messages[0]["role"],
-                            "parts": [{"type": "text", "content": messages[0]["content"]}],
+                            "parts": [{"type": "text", "content": "Hello"}],
                         }
                     ]
                 )
@@ -255,7 +255,7 @@ def test_end_model_invoke_span_latest_conventions(mock_span):
                     [
                         {
                             "role": "assistant",
-                            "parts": [{"type": "text", "content": message["content"]}],
+                            "parts": [{"type": "text", "content": "Response"}],
                             "finish_reason": "end_turn",
                         }
                     ]
@@ -324,7 +324,7 @@ def test_start_tool_call_span_latest_conventions(mock_tracer):
                                     "type": "tool_call",
                                     "name": tool["name"],
                                     "id": tool["toolUseId"],
-                                    "arguments": [{"content": tool["input"]}],
+                                    "arguments": tool["input"],
                                 }
                             ],
                         }
@@ -508,7 +508,7 @@ def test_end_tool_call_span_latest_conventions(mock_span):
                             {
                                 "type": "tool_call_response",
                                 "id": tool_result.get("toolUseId", ""),
-                                "result": tool_result.get("content"),
+                                "response": tool_result.get("content"),
                             }
                         ],
                     }
@@ -564,9 +564,7 @@ def test_start_event_loop_cycle_span_latest_conventions(mock_tracer):
         mock_span.add_event.assert_any_call(
             "gen_ai.client.inference.operation.details",
             attributes={
-                "gen_ai.input.messages": serialize(
-                    [{"role": "user", "parts": [{"type": "text", "content": messages[0]["content"]}]}]
-                )
+                "gen_ai.input.messages": serialize([{"role": "user", "parts": [{"type": "text", "content": "Hello"}]}])
             },
         )
         assert span is not None
@@ -576,7 +574,12 @@ def test_end_event_loop_cycle_span(mock_span):
     """Test ending an event loop cycle span."""
     tracer = Tracer()
     message = {"role": "assistant", "content": [{"text": "Response"}]}
-    tool_result_message = {"role": "assistant", "content": [{"toolResult": {"response": "Success"}}]}
+    tool_result_message = {
+        "role": "assistant",
+        "content": [
+            {"toolResult": {"toolUseId": "123", "status": "success", "content": [{"text": "Weather is sunny"}]}}
+        ],
+    }
 
     tracer.end_event_loop_cycle_span(mock_span, message, tool_result_message)
 
@@ -596,7 +599,12 @@ def test_end_event_loop_cycle_span_latest_conventions(mock_span):
     tracer = Tracer()
     tracer.use_latest_genai_conventions = True
     message = {"role": "assistant", "content": [{"text": "Response"}]}
-    tool_result_message = {"role": "assistant", "content": [{"toolResult": {"response": "Success"}}]}
+    tool_result_message = {
+        "role": "assistant",
+        "content": [
+            {"toolResult": {"toolUseId": "123", "status": "success", "content": [{"text": "Weather is sunny"}]}}
+        ],
+    }
 
     tracer.end_event_loop_cycle_span(mock_span, message, tool_result_message)
 
@@ -607,7 +615,13 @@ def test_end_event_loop_cycle_span_latest_conventions(mock_span):
                 [
                     {
                         "role": "assistant",
-                        "parts": [{"type": "text", "content": tool_result_message["content"]}],
+                        "parts": [
+                            {
+                                "type": "tool_call_response",
+                                "id": "123",
+                                "response": [{"text": "Weather is sunny"}],
+                            }
+                        ],
                     }
                 ]
             )
@@ -682,7 +696,7 @@ def test_start_agent_span_latest_conventions(mock_tracer):
             "gen_ai.client.inference.operation.details",
             attributes={
                 "gen_ai.input.messages": serialize(
-                    [{"role": "user", "parts": [{"type": "text", "content": [{"text": "test prompt"}]}]}]
+                    [{"role": "user", "parts": [{"type": "text", "content": "test prompt"}]}]
                 )
             },
         )

Original file line number	Diff line number	Diff line change
`@@ -316,7 +316,7 @@ def end_model_invoke_span(`
`316`	`316`	`[`
`317`	`317`	`{`
`318`	`318`	`"role": message["role"],`
`319`		`- "parts": [{"type": "text", "content": message["content"]}],`
	`319`	`+ "parts": self._map_content_blocks_to_otel_parts(message["content"]),`
`320`	`320`	`"finish_reason": str(stop_reason),`
`321`	`321`	`}`
`322`	`322`	`]`
`@@ -371,7 +371,7 @@ def start_tool_call_span(self, tool: ToolUse, parent_span: Optional[Span] = None`
`371`	`371`	`"type": "tool_call",`
`372`	`372`	`"name": tool["name"],`
`373`	`373`	`"id": tool["toolUseId"],`
`374`		`- "arguments": [{"content": tool["input"]}],`
	`374`	`+ "arguments": tool["input"],`
`375`	`375`	`}`
`376`	`376`	`],`
`377`	`377`	`}`
`@@ -426,7 +426,7 @@ def end_tool_call_span(`
`426`	`426`	`{`
`427`	`427`	`"type": "tool_call_response",`
`428`	`428`	`"id": tool_result.get("toolUseId", ""),`
`429`		`- "result": tool_result.get("content"),`
	`429`	`+ "response": tool_result.get("content"),`
`430`	`430`	`}`
`431`	`431`	`],`
`432`	`432`	`}`
`@@ -513,7 +513,7 @@ def end_event_loop_cycle_span(`
`513`	`513`	`[`
`514`	`514`	`{`
`515`	`515`	`"role": tool_result_message["role"],`
`516`		`- "parts": [{"type": "text", "content": tool_result_message["content"]}],`
	`516`	`+ "parts": self._map_content_blocks_to_otel_parts(tool_result_message["content"]),`
`517`	`517`	`}`
`518`	`518`	`]`
`519`	`519`	`)`
`@@ -727,7 +727,7 @@ def _add_event_messages(self, span: Span, messages: Messages) -> None:`
`727`	`727`	`input_messages: list = []`
`728`	`728`	`for message in messages:`
`729`	`729`	`input_messages.append(`
`730`		`- {"role": message["role"], "parts": [{"type": "text", "content": message["content"]}]}`
	`730`	`+ {"role": message["role"], "parts": self._map_content_blocks_to_otel_parts(message["content"])}`
`731`	`731`	`)`
`732`	`732`	`self._add_event(`
`733`	`733`	`span, "gen_ai.client.inference.operation.details", {"gen_ai.input.messages": serialize(input_messages)}`
`@@ -740,6 +740,41 @@ def _add_event_messages(self, span: Span, messages: Messages) -> None:`
`740`	`740`	`{"content": serialize(message["content"])},`
`741`	`741`	`)`
`742`	`742`
	`743`	`+ def _map_content_blocks_to_otel_parts(self, content_blocks: list[ContentBlock]) -> list[dict[str, Any]]:`
	`744`	`+ """Map ContentBlock objects to OpenTelemetry parts format."""`
	`745`	`+ parts: list[dict[str, Any]] = []`
	`746`	`+`
	`747`	`+ for block in content_blocks:`
	`748`	`+ if "text" in block:`
	`749`	`+ # Standard TextPart`
	`750`	`+ parts.append({"type": "text", "content": block["text"]})`
	`751`	`+ elif "toolUse" in block:`
	`752`	`+ # Standard ToolCallRequestPart`
	`753`	`+ tool_use = block["toolUse"]`
	`754`	`+ parts.append(`
	`755`	`+ {`
	`756`	`+ "type": "tool_call",`
	`757`	`+ "name": tool_use["name"],`
	`758`	`+ "id": tool_use["toolUseId"],`
	`759`	`+ "arguments": tool_use["input"],`
	`760`	`+ }`
	`761`	`+ )`
	`762`	`+ elif "toolResult" in block:`
	`763`	`+ # Standard ToolCallResponsePart`
	`764`	`+ tool_result = block["toolResult"]`
	`765`	`+ parts.append(`
	`766`	`+ {`
	`767`	`+ "type": "tool_call_response",`
	`768`	`+ "id": tool_result["toolUseId"],`
	`769`	`+ "response": tool_result["content"],`
	`770`	`+ }`
	`771`	`+ )`
	`772`	`+ else:`
	`773`	`+ # For all other ContentBlock types, use the key as type and value as content`
	`774`	`+ for key, value in block.items():`
	`775`	`+ parts.append({"type": key, "content": value})`
	`776`	`+ return parts`
	`777`	`+`
`743`	`778`
`744`	`779`	`# Singleton instance for global access`
`745`	`780`	`_tracer_instance = None`
Original file line number	Diff line number	Diff line change
`@@ -191,7 +191,7 @@ def test_start_model_invoke_span_latest_conventions(mock_tracer):`
`191`	`191`	`[`
`192`	`192`	`{`
`193`	`193`	`"role": messages[0]["role"],`
`194`		`- "parts": [{"type": "text", "content": messages[0]["content"]}],`
	`194`	`+ "parts": [{"type": "text", "content": "Hello"}],`
`195`	`195`	`}`
`196`	`196`	`]`
`197`	`197`	`)`
`@@ -255,7 +255,7 @@ def test_end_model_invoke_span_latest_conventions(mock_span):`
`255`	`255`	`[`
`256`	`256`	`{`
`257`	`257`	`"role": "assistant",`
`258`		`- "parts": [{"type": "text", "content": message["content"]}],`
	`258`	`+ "parts": [{"type": "text", "content": "Response"}],`
`259`	`259`	`"finish_reason": "end_turn",`
`260`	`260`	`}`
`261`	`261`	`]`
`@@ -324,7 +324,7 @@ def test_start_tool_call_span_latest_conventions(mock_tracer):`
`324`	`324`	`"type": "tool_call",`
`325`	`325`	`"name": tool["name"],`
`326`	`326`	`"id": tool["toolUseId"],`
`327`		`- "arguments": [{"content": tool["input"]}],`
	`327`	`+ "arguments": tool["input"],`
`328`	`328`	`}`
`329`	`329`	`],`
`330`	`330`	`}`
`@@ -508,7 +508,7 @@ def test_end_tool_call_span_latest_conventions(mock_span):`
`508`	`508`	`{`
`509`	`509`	`"type": "tool_call_response",`
`510`	`510`	`"id": tool_result.get("toolUseId", ""),`
`511`		`- "result": tool_result.get("content"),`
	`511`	`+ "response": tool_result.get("content"),`
`512`	`512`	`}`
`513`	`513`	`],`
`514`	`514`	`}`
`@@ -564,9 +564,7 @@ def test_start_event_loop_cycle_span_latest_conventions(mock_tracer):`
`564`	`564`	`mock_span.add_event.assert_any_call(`
`565`	`565`	`"gen_ai.client.inference.operation.details",`
`566`	`566`	`attributes={`
`567`		`- "gen_ai.input.messages": serialize(`
`568`		`- [{"role": "user", "parts": [{"type": "text", "content": messages[0]["content"]}]}]`
`569`		`- )`
	`567`	`+ "gen_ai.input.messages": serialize([{"role": "user", "parts": [{"type": "text", "content": "Hello"}]}])`
`570`	`568`	`},`
`571`	`569`	`)`
`572`	`570`	`assert span is not None`
`@@ -576,7 +574,12 @@ def test_end_event_loop_cycle_span(mock_span):`
`576`	`574`	`"""Test ending an event loop cycle span."""`
`577`	`575`	`tracer = Tracer()`
`578`	`576`	`message = {"role": "assistant", "content": [{"text": "Response"}]}`
`579`		`- tool_result_message = {"role": "assistant", "content": [{"toolResult": {"response": "Success"}}]}`
	`577`	`+ tool_result_message = {`
	`578`	`+ "role": "assistant",`
	`579`	`+ "content": [`
	`580`	`+ {"toolResult": {"toolUseId": "123", "status": "success", "content": [{"text": "Weather is sunny"}]}}`
	`581`	`+ ],`
	`582`	`+ }`
`580`	`583`
`581`	`584`	`tracer.end_event_loop_cycle_span(mock_span, message, tool_result_message)`
`582`	`585`
`@@ -596,7 +599,12 @@ def test_end_event_loop_cycle_span_latest_conventions(mock_span):`
`596`	`599`	`tracer = Tracer()`
`597`	`600`	`tracer.use_latest_genai_conventions = True`
`598`	`601`	`message = {"role": "assistant", "content": [{"text": "Response"}]}`
`599`		`- tool_result_message = {"role": "assistant", "content": [{"toolResult": {"response": "Success"}}]}`
	`602`	`+ tool_result_message = {`
	`603`	`+ "role": "assistant",`
	`604`	`+ "content": [`
	`605`	`+ {"toolResult": {"toolUseId": "123", "status": "success", "content": [{"text": "Weather is sunny"}]}}`
	`606`	`+ ],`
	`607`	`+ }`
`600`	`608`
`601`	`609`	`tracer.end_event_loop_cycle_span(mock_span, message, tool_result_message)`
`602`	`610`
`@@ -607,7 +615,13 @@ def test_end_event_loop_cycle_span_latest_conventions(mock_span):`
`607`	`615`	`[`
`608`	`616`	`{`
`609`	`617`	`"role": "assistant",`
`610`		`- "parts": [{"type": "text", "content": tool_result_message["content"]}],`
	`618`	`+ "parts": [`
	`619`	`+ {`
	`620`	`+ "type": "tool_call_response",`
	`621`	`+ "id": "123",`
	`622`	`+ "response": [{"text": "Weather is sunny"}],`
	`623`	`+ }`
	`624`	`+ ],`
`611`	`625`	`}`
`612`	`626`	`]`
`613`	`627`	`)`
`@@ -682,7 +696,7 @@ def test_start_agent_span_latest_conventions(mock_tracer):`
`682`	`696`	`"gen_ai.client.inference.operation.details",`
`683`	`697`	`attributes={`
`684`	`698`	`"gen_ai.input.messages": serialize(`
`685`		`- [{"role": "user", "parts": [{"type": "text", "content": [{"text": "test prompt"}]}]}]`
	`699`	`+ [{"role": "user", "parts": [{"type": "text", "content": "test prompt"}]}]`
`686`	`700`	`)`
`687`	`701`	`},`
`688`	`702`	`)`