fix: make telemetry optional for agents (#3705)

# What does this PR do?

there is a lot of code in the agents API using the telemetry API and its
helpers without checking if that API is even enabled.

This is the only API besides inference actively using telemetry code, so
after this telemetry can be optional for the entire stack


resolves #3665


## Test Plan

existing agent tests.

Signed-off-by: Charlie Doern <cdoern@redhat.com>

llama_stack/providers/inline/agents/meta_reference/__init__.py

@@ -22,6 +22,7 @@ async def get_provider_impl(config: MetaReferenceAgentsImplConfig, deps: dict[Ap
         deps[Api.tool_runtime],
         deps[Api.tool_groups],
         policy,
+        Api.telemetry in deps,
     )
     await impl.initialize()
     return impl

llama_stack/providers/inline/agents/meta_reference/agent_instance.py

@@ -110,6 +110,7 @@ class ChatAgent(ShieldRunnerMixin):
         persistence_store: KVStore,
         created_at: str,
         policy: list[AccessRule],
+        telemetry_enabled: bool = False,
     ):
         self.agent_id = agent_id
         self.agent_config = agent_config
@@ -120,6 +121,7 @@ class ChatAgent(ShieldRunnerMixin):
         self.tool_runtime_api = tool_runtime_api
         self.tool_groups_api = tool_groups_api
         self.created_at = created_at
+        self.telemetry_enabled = telemetry_enabled
 
         ShieldRunnerMixin.__init__(
             self,
@@ -188,28 +190,30 @@ class ChatAgent(ShieldRunnerMixin):
 
     async def create_and_execute_turn(self, request: AgentTurnCreateRequest) -> AsyncGenerator:
         turn_id = str(uuid.uuid4())
-        span = tracing.get_current_span()
-        if span:
-            span.set_attribute("session_id", request.session_id)
-            span.set_attribute("agent_id", self.agent_id)
-            span.set_attribute("request", request.model_dump_json())
-            span.set_attribute("turn_id", turn_id)
-            if self.agent_config.name:
-                span.set_attribute("agent_name", self.agent_config.name)
+        if self.telemetry_enabled:
+            span = tracing.get_current_span()
+            if span is not None:
+                span.set_attribute("session_id", request.session_id)
+                span.set_attribute("agent_id", self.agent_id)
+                span.set_attribute("request", request.model_dump_json())
+                span.set_attribute("turn_id", turn_id)
+                if self.agent_config.name:
+                    span.set_attribute("agent_name", self.agent_config.name)
 
         await self._initialize_tools(request.toolgroups)
         async for chunk in self._run_turn(request, turn_id):
             yield chunk
 
     async def resume_turn(self, request: AgentTurnResumeRequest) -> AsyncGenerator:
-        span = tracing.get_current_span()
-        if span:
-            span.set_attribute("agent_id", self.agent_id)
-            span.set_attribute("session_id", request.session_id)
-            span.set_attribute("request", request.model_dump_json())
-            span.set_attribute("turn_id", request.turn_id)
-            if self.agent_config.name:
-                span.set_attribute("agent_name", self.agent_config.name)
+        if self.telemetry_enabled:
+            span = tracing.get_current_span()
+            if span is not None:
+                span.set_attribute("agent_id", self.agent_id)
+                span.set_attribute("session_id", request.session_id)
+                span.set_attribute("request", request.model_dump_json())
+                span.set_attribute("turn_id", request.turn_id)
+                if self.agent_config.name:
+                    span.set_attribute("agent_name", self.agent_config.name)
 
         await self._initialize_tools()
         async for chunk in self._run_turn(request):
@@ -395,9 +399,12 @@ class ChatAgent(ShieldRunnerMixin):
         touchpoint: str,
     ) -> AsyncGenerator:
         async with tracing.span("run_shields") as span:
-            span.set_attribute("input", [m.model_dump_json() for m in messages])
+            if self.telemetry_enabled and span is not None:
+                span.set_attribute("input", [m.model_dump_json() for m in messages])
+                if len(shields) == 0:
+                    span.set_attribute("output", "no shields")
+
             if len(shields) == 0:
-                span.set_attribute("output", "no shields")
                 return
 
             step_id = str(uuid.uuid4())
@@ -430,7 +437,8 @@ class ChatAgent(ShieldRunnerMixin):
                         )
                     )
                 )
-                span.set_attribute("output", e.violation.model_dump_json())
+                if self.telemetry_enabled and span is not None:
+                    span.set_attribute("output", e.violation.model_dump_json())
 
                 yield CompletionMessage(
                     content=str(e),
@@ -453,7 +461,8 @@ class ChatAgent(ShieldRunnerMixin):
                     )
                 )
             )
-            span.set_attribute("output", "no violations")
+            if self.telemetry_enabled and span is not None:
+                span.set_attribute("output", "no violations")
 
     async def _run(
         self,
@@ -518,8 +527,9 @@ class ChatAgent(ShieldRunnerMixin):
             stop_reason: StopReason | None = None
 
             async with tracing.span("inference") as span:
-                if self.agent_config.name:
-                    span.set_attribute("agent_name", self.agent_config.name)
+                if self.telemetry_enabled and span is not None:
+                    if self.agent_config.name:
+                        span.set_attribute("agent_name", self.agent_config.name)
 
                 def _serialize_nested(value):
                     """Recursively serialize nested Pydantic models to dicts."""
@@ -637,18 +647,19 @@ class ChatAgent(ShieldRunnerMixin):
                     else:
                         raise ValueError(f"Unexpected delta type {type(delta)}")
 
-                span.set_attribute("stop_reason", stop_reason or StopReason.end_of_turn)
-                span.set_attribute(
-                    "input",
-                    json.dumps([json.loads(m.model_dump_json()) for m in input_messages]),
-                )
-                output_attr = json.dumps(
-                    {
-                        "content": content,
-                        "tool_calls": [json.loads(t.model_dump_json()) for t in tool_calls],
-                    }
-                )
-                span.set_attribute("output", output_attr)
+                if self.telemetry_enabled and span is not None:
+                    span.set_attribute("stop_reason", stop_reason or StopReason.end_of_turn)
+                    span.set_attribute(
+                        "input",
+                        json.dumps([json.loads(m.model_dump_json()) for m in input_messages]),
+                    )
+                    output_attr = json.dumps(
+                        {
+                            "content": content,
+                            "tool_calls": [json.loads(t.model_dump_json()) for t in tool_calls],
+                        }
+                    )
+                    span.set_attribute("output", output_attr)
 
             n_iter += 1
             await self.storage.set_num_infer_iters_in_turn(session_id, turn_id, n_iter)
@@ -756,7 +767,9 @@ class ChatAgent(ShieldRunnerMixin):
                         {
                             "tool_name": tool_call.tool_name,
                             "input": message.model_dump_json(),
-                        },
+                        }
+                        if self.telemetry_enabled
+                        else {},
                     ) as span:
                         tool_execution_start_time = datetime.now(UTC).isoformat()
                         tool_result = await self.execute_tool_call_maybe(
@@ -771,7 +784,8 @@ class ChatAgent(ShieldRunnerMixin):
                             call_id=tool_call.call_id,
                             content=tool_result.content,
                         )
-                        span.set_attribute("output", result_message.model_dump_json())
+                        if self.telemetry_enabled and span is not None:
+                            span.set_attribute("output", result_message.model_dump_json())
 
                         # Store tool execution step
                         tool_execution_step = ToolExecutionStep(

llama_stack/providers/inline/agents/meta_reference/agents.py

@@ -64,6 +64,7 @@ class MetaReferenceAgentsImpl(Agents):
         tool_runtime_api: ToolRuntime,
         tool_groups_api: ToolGroups,
         policy: list[AccessRule],
+        telemetry_enabled: bool = False,
     ):
         self.config = config
         self.inference_api = inference_api
@@ -71,6 +72,7 @@ class MetaReferenceAgentsImpl(Agents):
         self.safety_api = safety_api
         self.tool_runtime_api = tool_runtime_api
         self.tool_groups_api = tool_groups_api
+        self.telemetry_enabled = telemetry_enabled
 
         self.in_memory_store = InmemoryKVStoreImpl()
         self.openai_responses_impl: OpenAIResponsesImpl | None = None
@@ -135,6 +137,7 @@ class MetaReferenceAgentsImpl(Agents):
             ),
             created_at=agent_info.created_at,
             policy=self.policy,
+            telemetry_enabled=self.telemetry_enabled,
         )
 
     async def create_agent_session(

llama_stack/providers/registry/agents.py

@@ -36,6 +36,9 @@ def available_providers() -> list[ProviderSpec]:
                 Api.tool_runtime,
                 Api.tool_groups,
             ],
+            optional_api_dependencies=[
+                Api.telemetry,
+            ],
             description="Meta's reference implementation of an agent system that can use tools, access vector databases, and perform complex reasoning tasks.",
         ),
     ]