fix: Updated some flows to run on BaseAgent instances where supported, made request processor execution consistent with response processors

PiperOrigin-RevId: 797421115

Author: google-genai-bot

src/google/adk/agents/readonly_context.py

@@ -14,17 +14,23 @@
 
 from __future__ import annotations
 
+import copy
 from types import MappingProxyType
 from typing import Any
+from typing import List
 from typing import Optional
 from typing import TYPE_CHECKING
+from typing import TypeVar
 
 if TYPE_CHECKING:
   from google.genai import types
 
   from .invocation_context import InvocationContext
 
 
+Event = TypeVar('Event')
+
+
 class ReadonlyContext:
 
   def __init__(
@@ -52,3 +58,8 @@ def agent_name(self) -> str:
   def state(self) -> MappingProxyType[str, Any]:
     """The state of the current session. READONLY field."""
     return MappingProxyType(self._invocation_context.session.state)
+
+  @property
+  def events(self) -> List[Event]:
+    """Historical events from the current session."""
+    return copy.deepcopy(self._invocation_context.session.events)

src/google/adk/auth/auth_preprocessor.py

@@ -44,7 +44,7 @@ async def run_async(
     from ..agents.llm_agent import LlmAgent
 
     agent = invocation_context.agent
-    if not isinstance(agent, LlmAgent):
+    if not hasattr(agent, 'canonical_tools'):
       return
     events = invocation_context.session.events
     if not events:
@@ -110,7 +110,7 @@ async def run_async(
               event,
               {
                   tool.name: tool
-                  for tool in await agent.canonical_tools(
+                  for tool in await getattr(agent, 'canonical_tools')(
                       ReadonlyContext(invocation_context)
                   )
               },

src/google/adk/flows/llm_flows/base_llm_flow.py

@@ -401,17 +401,19 @@ async def _preprocess_async(
     from ...agents.llm_agent import LlmAgent
 
     agent = invocation_context.agent
-    if not isinstance(agent, LlmAgent):
-      return
 
     # Runs processors.
     for processor in self.request_processors:
+      logging.debug('Running processor: %s', type(processor).__name__)
       async with Aclosing(
           processor.run_async(invocation_context, llm_request)
       ) as agen:
         async for event in agen:
           yield event
 
+    if not isinstance(agent, LlmAgent):
+      return
+
     # Run processors for tools.
     for tool_union in agent.tools:
       tool_context = ToolContext(invocation_context)

src/google/adk/flows/llm_flows/basic.py

@@ -17,7 +17,6 @@
 from __future__ import annotations
 
 from typing import AsyncGenerator
-from typing import Generator
 
 from google.genai import types
 from typing_extensions import override
@@ -36,26 +35,7 @@ async def run_async(
   ) -> AsyncGenerator[Event, None]:
     from ...agents.llm_agent import LlmAgent
 
-    agent = invocation_context.agent
-    if not isinstance(agent, LlmAgent):
-      return
-
-    llm_request.model = (
-        agent.canonical_model
-        if isinstance(agent.canonical_model, str)
-        else agent.canonical_model.model
-    )
-    llm_request.config = (
-        agent.generate_content_config.model_copy(deep=True)
-        if agent.generate_content_config
-        else types.GenerateContentConfig()
-    )
-    # Only set output_schema if no tools are specified. as of now, model don't
-    # support output_schema and tools together. we have a workaround to support
-    # both outoput_schema and tools at the same time. see
-    # _output_schema_processor.py for details
-    if agent.output_schema and not agent.tools:
-      llm_request.set_output_schema(agent.output_schema)
+    llm_request.config = types.GenerateContentConfig()
 
     llm_request.live_connect_config.response_modalities = (
         invocation_context.run_config.response_modalities
@@ -81,6 +61,23 @@ async def run_async(
     llm_request.live_connect_config.session_resumption = (
         invocation_context.run_config.session_resumption
     )
+    agent = invocation_context.agent
+    if not isinstance(agent, LlmAgent):
+      return
+
+    llm_request.model = (
+        agent.canonical_model
+        if isinstance(agent.canonical_model, str)
+        else agent.canonical_model.model
+    )
+    # Only set output_schema if no tools are specified. as of now, model don't
+    # support output_schema and tools together. we have a workaround to support
+    # both outoput_schema and tools at the same time. see
+    # _output_schema_processor.py for details
+    if agent.output_schema and not agent.tools:
+      llm_request.set_output_schema(agent.output_schema)
+    if agent.generate_content_config:
+      llm_request.config = agent.generate_content_config.model_copy(deep=True)
 
     # TODO: handle tool append here, instead of in BaseTool.process_llm_request.
 

src/google/adk/flows/llm_flows/contents.py

@@ -33,22 +33,24 @@
 class _ContentLlmRequestProcessor(BaseLlmRequestProcessor):
   """Builds the contents for the LLM request."""
 
+  def __init__(self, mutating: bool):
+    self.mutating = mutating
+
   @override
   async def run_async(
       self, invocation_context: InvocationContext, llm_request: LlmRequest
   ) -> AsyncGenerator[Event, None]:
     from ...agents.llm_agent import LlmAgent
 
     agent = invocation_context.agent
-    if not isinstance(agent, LlmAgent):
-      return
 
-    if agent.include_contents == 'default':
+    if not isinstance(agent, LlmAgent) or agent.include_contents == 'default':
       # Include full conversation history
       llm_request.contents = _get_contents(
           invocation_context.branch,
           invocation_context.session.events,
           agent.name,
+          self.mutating,
       )
     else:
       # Include current turn context only (no conversation history)
@@ -63,7 +65,8 @@ async def run_async(
       yield  # This is a no-op but maintains generator structure
 
 
-request_processor = _ContentLlmRequestProcessor()
+request_processor = _ContentLlmRequestProcessor(mutating=True)
+non_mutating_request_processor = _ContentLlmRequestProcessor(mutating=False)
 
 
 def _rearrange_events_for_async_function_responses_in_history(
@@ -203,7 +206,10 @@ def _rearrange_events_for_latest_function_response(
 
 
 def _get_contents(
-    current_branch: Optional[str], events: list[Event], agent_name: str = ''
+    current_branch: Optional[str],
+    events: list[Event],
+    agent_name: str = '',
+    mutating: bool = True,
 ) -> list[types.Content]:
   """Get the contents for the LLM request.
 
@@ -213,6 +219,7 @@ def _get_contents(
     current_branch: The current branch of the agent.
     events: Events to process.
     agent_name: The name of the agent.
+    mutating: Whether to rewrite all conversation turns as user verbalizations.
 
   Returns:
     A list of processed contents.
@@ -240,7 +247,7 @@ def _get_contents(
       continue
     filtered_events.append(
         _convert_foreign_event(event)
-        if _is_other_agent_reply(agent_name, event)
+        if mutating and _is_other_agent_reply(agent_name, event)
         else event
     )
 
@@ -313,7 +320,6 @@ def _convert_foreign_event(event: Event) -> Event:
 
   Returns:
     The converted event.
-
   """
   if not event.content or not event.content.parts:
     return event

src/google/adk/tools/agent_tool.py

@@ -47,11 +47,19 @@ class AgentTool(BaseTool):
   Attributes:
     agent: The agent to wrap.
     skip_summarization: Whether to skip summarization of the agent output.
+    include_conversational_context: Whether to pass conversation history through
+      to the sub-agent.
   """
 
-  def __init__(self, agent: BaseAgent, skip_summarization: bool = False):
+  def __init__(
+      self,
+      agent: BaseAgent,
+      skip_summarization: bool = False,
+      include_conversational_context: bool = False,
+  ):
     self.agent = agent
-    self.skip_summarization: bool = skip_summarization
+    self.skip_summarization = skip_summarization
+    self.include_conversational_context = include_conversational_context
 
     super().__init__(name=agent.name, description=agent.description)
 
@@ -141,6 +149,10 @@ async def run_async(
         state=tool_context.state.to_dict(),
     )
 
+    if self.include_conversational_context:
+      for event in tool_context.events[:-1]:
+        await runner.session_service.append_event(session, event)
+
     last_event = None
     async with Aclosing(
         runner.run_async(