Further bug fixes

llama_stack/apis/agents/event_logger.py

@@ -9,10 +9,10 @@ from typing import Optional
 from llama_models.llama3.api.datatypes import *  # noqa: F403
 from llama_models.llama3.api.tool_utils import ToolUtils
 
-from llama_stack.apis.agents import AgentTurnResponseEventType, StepType
-
 from termcolor import cprint
 
+from llama_stack.apis.agents import AgentTurnResponseEventType, StepType
+
 
 class LogEvent:
     def __init__(
@@ -77,15 +77,15 @@ class EventLogger:
                 step_type == StepType.shield_call
                 and event_type == EventType.step_complete.value
             ):
-                response = event.payload.step_details.response
-                if not response.is_violation:
+                violation = event.payload.step_details.violation
+                if not violation:
                     yield event, LogEvent(
                         role=step_type, content="No Violation", color="magenta"
                     )
                 else:
                     yield event, LogEvent(
                         role=step_type,
-                        content=f"{response.violation_type} {response.violation_return_message}",
+                        content=f"{violation.metadata} {violation.user_message}",
                         color="red",
                     )
 

llama_stack/apis/inference/client.py

@@ -10,21 +10,14 @@ from typing import Any, AsyncGenerator
 
 import fire
 import httpx
-
-from llama_stack.distribution.datatypes import RemoteProviderConfig
 from pydantic import BaseModel
 from termcolor import cprint
 
+from llama_stack.distribution.datatypes import RemoteProviderConfig
+
 from .event_logger import EventLogger
 
-from .inference import (
-    ChatCompletionRequest,
-    ChatCompletionResponse,
-    ChatCompletionResponseStreamChunk,
-    CompletionRequest,
-    Inference,
-    UserMessage,
-)
+from llama_stack.apis.inference import *  # noqa: F403
 
 
 async def get_client_impl(config: RemoteProviderConfig, _deps: Any) -> Inference:
@@ -48,7 +41,27 @@ class InferenceClient(Inference):
     async def completion(self, request: CompletionRequest) -> AsyncGenerator:
         raise NotImplementedError()
 
-    async def chat_completion(self, request: ChatCompletionRequest) -> AsyncGenerator:
+    async def chat_completion(
+        self,
+        model: str,
+        messages: List[Message],
+        sampling_params: Optional[SamplingParams] = SamplingParams(),
+        tools: Optional[List[ToolDefinition]] = None,
+        tool_choice: Optional[ToolChoice] = ToolChoice.auto,
+        tool_prompt_format: Optional[ToolPromptFormat] = ToolPromptFormat.json,
+        stream: Optional[bool] = False,
+        logprobs: Optional[LogProbConfig] = None,
+    ) -> AsyncGenerator:
+        request = ChatCompletionRequest(
+            model=model,
+            messages=messages,
+            sampling_params=sampling_params,
+            tools=tools or [],
+            tool_choice=tool_choice,
+            tool_prompt_format=tool_prompt_format,
+            stream=stream,
+            logprobs=logprobs,
+        )
         async with httpx.AsyncClient() as client:
             async with client.stream(
                 "POST",

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

@@ -248,7 +248,7 @@ class ChatAgent(ShieldRunnerMixin):
         self,
         turn_id: str,
         messages: List[Message],
-        shields: List[ShieldDefinition],
+        shields: List[str],
         touchpoint: str,
     ) -> AsyncGenerator:
         if len(shields) == 0:
@@ -608,7 +608,6 @@ class ChatAgent(ShieldRunnerMixin):
             else:
                 return True
 
-        print(f"{enabled_tools=}")
         return AgentTool.memory.value in enabled_tools
 
     def _memory_tool_definition(self) -> Optional[MemoryToolDefinition]: