migrate agentic system

llama_toolchain/agentic_system/api/api.py

@@ -416,7 +416,16 @@ class AgenticSystem(Protocol):
     @webmethod(route="/agentic_system/turn/create")
     async def create_agentic_system_turn(
         self,
-        request: AgenticSystemTurnCreateRequest,
+        agent_id: str,
+        session_id: str,
+        messages: List[
+            Union[
+                UserMessage,
+                ToolResponseMessage,
+            ]
+        ],
+        attachments: Optional[List[Attachment]] = None,
+        stream: Optional[bool] = False,
     ) -> AgenticSystemTurnResponseStreamChunk: ...
 
     @webmethod(route="/agentic_system/turn/get")

llama_toolchain/agentic_system/client.py

@@ -73,9 +73,7 @@ class AgenticSystemClient(AgenticSystem):
             async with client.stream(
                 "POST",
                 f"{self.base_url}/agentic_system/turn/create",
-                json={
+                json=encodable_dict(request),
-                    "request": encodable_dict(request),
-                },
                 headers={"Content-Type": "application/json"},
                 timeout=20,
             ) as response:
@@ -134,7 +132,7 @@ async def run_main(host: str, port: int):
     api = AgenticSystemClient(f"http://{host}:{port}")
 
     tool_definitions = [
-        SearchToolDefinition(engine=SearchEngineType.bing),
+        SearchToolDefinition(engine=SearchEngineType.brave),
         WolframAlphaToolDefinition(),
         CodeInterpreterToolDefinition(),
     ]

llama_toolchain/agentic_system/meta_reference/agent_instance.py

@@ -400,7 +400,7 @@ class ChatAgent(ShieldRunnerMixin):
             tool_calls = []
             content = ""
             stop_reason = None
-            async for chunk in self.inference_api.chat_completion(req):
+            async for chunk in self.inference_api.chat_completion_impl(req):
                 event = chunk.event
                 if event.event_type == ChatCompletionResponseEventType.start:
                     continue

llama_toolchain/agentic_system/meta_reference/agentic_system.py

@@ -114,8 +114,26 @@ class MetaReferenceAgenticSystemImpl(AgenticSystem):
 
     async def create_agentic_system_turn(
         self,
-        request: AgenticSystemTurnCreateRequest,
+        agent_id: str,
+        session_id: str,
+        messages: List[
+            Union[
+                UserMessage,
+                ToolResponseMessage,
+            ]
+        ],
+        attachments: Optional[List[Attachment]] = None,
+        stream: Optional[bool] = False,
     ) -> AsyncGenerator:
+        # wrapper request to make it easier to pass around (internal only, not exposed to API)
+        request = AgenticSystemTurnCreateRequest(
+            agent_id=agent_id,
+            session_id=session_id,
+            messages=messages,
+            attachments=attachments,
+            stream=stream,
+        )
+
         agent_id = request.agent_id
         assert agent_id in AGENT_INSTANCES_BY_ID, f"System {agent_id} not found"
         agent = AGENT_INSTANCES_BY_ID[agent_id]

llama_toolchain/inference/meta_reference/inference.py

@@ -77,6 +77,13 @@ class MetaReferenceInferenceImpl(Inference):
             logprobs=logprobs,
         )
 
+        return self._chat_completion(request)
+
+    async def chat_completion_impl(
+        self, request: ChatCompletionRequest
+    ) -> AsyncIterator[
+        Union[ChatCompletionResponseStreamChunk, ChatCompletionResponse]
+    ]:
         messages = prepare_messages(request)
         model = resolve_model(request.model)
         if model is None: