move straggler files and fix some important existing bugs

llama_toolchain/agentic_system/agent_instance.py

@@ -4,15 +4,17 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
+
+import copy
+import uuid
+from datetime import datetime
+from typing import AsyncGenerator, List, Optional
+
 from llama_toolchain.inference.api import Inference
 from llama_toolchain.safety.api import Safety
 
 from .api.endpoints import *  # noqa
 
-import uuid
-from datetime import datetime
-from typing import AsyncGenerator, List, Optional
-
 from llama_toolchain.inference.api import ChatCompletionRequest
 
 from llama_toolchain.inference.api.datatypes import (
@@ -219,13 +221,14 @@ class AgentInstance(ShieldRunnerMixin):
         )
         session.turns.append(turn)
 
-        yield AgenticSystemTurnResponseStreamChunk(
+        chunk = AgenticSystemTurnResponseStreamChunk(
             event=AgenticSystemTurnResponseEvent(
                 payload=AgenticSystemTurnResponseTurnCompletePayload(
                     turn=turn,
                 )
             )
         )
+        yield chunk
 
     async def run_shields_wrapper(
         self,
@@ -388,7 +391,10 @@ class AgentInstance(ShieldRunnerMixin):
             stop_reason = None
             async for chunk in self.inference_api.chat_completion(req):
                 event = chunk.event
-                if event.event_type != ChatCompletionResponseEventType.progress:
+                if event.event_type == ChatCompletionResponseEventType.start:
+                    continue
+                elif event.event_type == ChatCompletionResponseEventType.complete:
+                    stop_reason = StopReason.end_of_turn
                     continue
 
                 delta = event.delta
@@ -439,7 +445,12 @@ class AgentInstance(ShieldRunnerMixin):
                         step_type=StepType.inference.value,
                         step_id=step_id,
                         step_details=InferenceStep(
-                            step_id=step_id, turn_id=turn_id, model_response=message
+                            # somewhere deep, we are re-assigning message or closing over some
+                            # variable which causes message to mutate later on. fix with a
+                            # `deepcopy` for now, but this is symptomatic of a deeper issue.
+                            step_id=step_id,
+                            turn_id=turn_id,
+                            model_response=copy.deepcopy(message),
                         ),
                     )
                 )

llama_toolchain/agentic_system/event_logger.py

@@ -0,0 +1,166 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from typing import Optional
+
+from llama_models.llama3_1.api.datatypes import ToolResponseMessage
+from llama_models.llama3_1.api.tool_utils import ToolUtils
+
+from llama_toolchain.agentic_system.api import (
+    AgenticSystemTurnResponseEventType,
+    StepType,
+)
+
+from termcolor import cprint
+
+
+class LogEvent:
+    def __init__(
+        self,
+        role: Optional[str] = None,
+        content: str = "",
+        end: str = "\n",
+        color="white",
+    ):
+        self.role = role
+        self.content = content
+        self.color = color
+        self.end = "\n" if end is None else end
+
+    def __str__(self):
+        if self.role is not None:
+            return f"{self.role}> {self.content}"
+        else:
+            return f"{self.content}"
+
+    def print(self, flush=True):
+        cprint(f"{str(self)}", color=self.color, end=self.end, flush=flush)
+
+
+EventType = AgenticSystemTurnResponseEventType
+
+
+class EventLogger:
+    async def log(self, event_generator, stream=True):
+        previous_event_type = None
+        previous_step_type = None
+
+        async for chunk in event_generator:
+            if not hasattr(chunk, "event"):
+                # Need to check for custom tool first
+                # since it does not produce event but instead
+                # a Message
+                if isinstance(chunk, ToolResponseMessage):
+                    yield chunk, LogEvent(
+                        role="CustomTool", content=chunk.content, color="grey"
+                    )
+                continue
+
+            event = chunk.event
+            event_type = event.payload.event_type
+            if event_type in {
+                EventType.turn_start.value,
+                EventType.turn_complete.value,
+            }:
+                # Currently not logging any turn realted info
+                yield event, None
+                continue
+
+            step_type = event.payload.step_type
+            # handle safety
+            if (
+                step_type == StepType.shield_call
+                and event_type == EventType.step_complete.value
+            ):
+                response = event.payload.step_details.response
+                if not response.is_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}",
+                        color="red",
+                    )
+
+            # handle inference
+            if step_type == StepType.inference:
+                if stream:
+                    if event_type == EventType.step_start.value:
+                        # TODO: Currently this event is never received
+                        yield event, LogEvent(
+                            role=step_type, content="", end="", color="yellow"
+                        )
+                    elif event_type == EventType.step_progress.value:
+                        # HACK: if previous was not step/event was not inference's step_progress
+                        # this is the first time we are getting model inference response
+                        # aka equivalent to step_start for inference. Hence,
+                        # start with "Model>".
+                        if (
+                            previous_event_type != EventType.step_progress.value
+                            and previous_step_type != StepType.inference
+                        ):
+                            yield event, LogEvent(
+                                role=step_type, content="", end="", color="yellow"
+                            )
+
+                        if event.payload.tool_call_delta:
+                            if isinstance(event.payload.tool_call_delta.content, str):
+                                yield event, LogEvent(
+                                    role=None,
+                                    content=event.payload.tool_call_delta.content,
+                                    end="",
+                                    color="cyan",
+                                )
+                        else:
+                            yield event, LogEvent(
+                                role=None,
+                                content=event.payload.model_response_text_delta,
+                                end="",
+                                color="yellow",
+                            )
+                    else:
+                        # step_complete
+                        yield event, LogEvent(role=None, content="")
+
+                else:
+                    # Not streaming
+                    if event_type == EventType.step_complete.value:
+                        response = event.payload.step_details.model_response
+                        if response.tool_calls:
+                            content = ToolUtils.encode_tool_call(response.tool_calls[0])
+                        else:
+                            content = response.content
+                        yield event, LogEvent(
+                            role=step_type,
+                            content=content,
+                            color="yellow",
+                        )
+
+            # handle tool_execution
+            if (
+                step_type == StepType.tool_execution
+                and
+                # Only print tool calls and responses at the step_complete event
+                event_type == EventType.step_complete.value
+            ):
+                details = event.payload.step_details
+                for t in details.tool_calls:
+                    yield event, LogEvent(
+                        role=step_type,
+                        content=f"Tool:{t.tool_name} Args:{t.arguments}",
+                        color="green",
+                    )
+                for r in details.tool_responses:
+                    yield event, LogEvent(
+                        role=step_type,
+                        content=f"Tool:{r.tool_name} Response:{r.content}",
+                        color="green",
+                    )
+
+            preivous_event_type = event_type
+            previous_step_type = step_type

llama_toolchain/agentic_system/tools/execute.py

@@ -47,7 +47,6 @@ async def execute_with_custom_tools(
                 yield chunk
             else:
                 turn = chunk.event.payload.turn
-                break
 
         message = turn.output_message
         if len(message.tool_calls) == 0:

llama_toolchain/agentic_system/utils.py

@@ -0,0 +1,115 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+import uuid
+from typing import Any, List, Optional
+
+from llama_models.llama3_1.api.datatypes import BuiltinTool, Message, SamplingParams
+
+from llama_toolchain.agentic_system.api import (
+    AgenticSystemCreateRequest,
+    AgenticSystemInstanceConfig,
+    AgenticSystemSessionCreateRequest,
+    AgenticSystemToolDefinition,
+)
+from llama_toolchain.agentic_system.client import AgenticSystemClient
+
+from llama_toolchain.agentic_system.tools.execute import execute_with_custom_tools
+from llama_toolchain.safety.api.datatypes import BuiltinShield, ShieldDefinition
+
+
+class AgenticSystemClientWrapper:
+
+    def __init__(self, api, system_id, custom_tools):
+        self.api = api
+        self.system_id = system_id
+        self.custom_tools = custom_tools
+        self.session_id = None
+
+    async def create_session(self, name: str = None):
+        if name is None:
+            name = f"Session-{uuid.uuid4()}"
+
+        response = await self.api.create_agentic_system_session(
+            AgenticSystemSessionCreateRequest(
+                system_id=self.system_id,
+                session_name=name,
+            )
+        )
+        self.session_id = response.session_id
+        return self.session_id
+
+    async def run(self, messages: List[Message], stream: bool = True):
+        async for chunk in execute_with_custom_tools(
+            self.api,
+            self.system_id,
+            self.session_id,
+            messages,
+            self.custom_tools,
+            stream=stream,
+        ):
+            yield chunk
+
+
+async def get_agent_system_instance(
+    host: str,
+    port: int,
+    custom_tools: Optional[List[Any]] = None,
+    disable_safety: bool = False,
+    model: str = "Meta-Llama3.1-8B-Instruct",
+) -> AgenticSystemClientWrapper:
+    custom_tools = custom_tools or []
+
+    api = AgenticSystemClient(base_url=f"http://{host}:{port}")
+
+    tool_definitions = [
+        AgenticSystemToolDefinition(
+            tool_name=BuiltinTool.brave_search,
+        ),
+        AgenticSystemToolDefinition(
+            tool_name=BuiltinTool.wolfram_alpha,
+        ),
+        AgenticSystemToolDefinition(
+            tool_name=BuiltinTool.photogen,
+        ),
+        AgenticSystemToolDefinition(
+            tool_name=BuiltinTool.code_interpreter,
+        ),
+    ] + [t.get_tool_definition() for t in custom_tools]
+
+    if not disable_safety:
+        for t in tool_definitions:
+            t.input_shields = [ShieldDefinition(shield_type=BuiltinShield.llama_guard)]
+            t.output_shields = [
+                ShieldDefinition(shield_type=BuiltinShield.llama_guard),
+                ShieldDefinition(shield_type=BuiltinShield.injection_shield),
+            ]
+
+    create_request = AgenticSystemCreateRequest(
+        model=model,
+        instance_config=AgenticSystemInstanceConfig(
+            instructions="You are a helpful assistant",
+            available_tools=tool_definitions,
+            input_shields=(
+                []
+                if disable_safety
+                else [
+                    ShieldDefinition(shield_type=BuiltinShield.llama_guard),
+                    ShieldDefinition(shield_type=BuiltinShield.jailbreak_shield),
+                ]
+            ),
+            output_shields=(
+                []
+                if disable_safety
+                else [
+                    ShieldDefinition(shield_type=BuiltinShield.llama_guard),
+                ]
+            ),
+            sampling_params=SamplingParams(),
+        ),
+    )
+    create_response = await api.create_agentic_system(create_request)
+    return AgenticSystemClientWrapper(api, create_response.system_id, custom_tools)

llama_toolchain/distribution/server.py

@@ -233,9 +233,10 @@ def topological_sort(adapters: List[Adapter]) -> List[Adapter]:
     def dfs(a: Adapter, visited: Set[ApiSurface], stack: List[ApiSurface]):
         visited.add(a.api_surface)
 
-        for surface in a.adapter_dependencies:
+        if not isinstance(a, PassthroughApiAdapter):
-            if surface not in visited:
+            for surface in a.adapter_dependencies:
-                dfs(by_id[surface], visited, stack)
+                if surface not in visited:
+                    dfs(by_id[surface], visited, stack)
 
         stack.append(a.api_surface)