feat: implement streaming support in to_a2a for issue #4240

contributing/dev/utils/build_llms_txt.py

@@ -6,6 +6,7 @@
                    – includes Python API reference from HTML files
                    – includes adk-python repository README
 """
+
 from __future__ import annotations
 
 import argparse

contributing/samples/cache_analysis/run_cache_experiments.py

@@ -344,7 +344,8 @@ async def analyze_cache_performance_from_sessions(
       print(
           "     Cache Utilization:"
           f" {cached_analysis['cache_utilization_ratio_percent']:.1f}%"
-          f" ({cached_analysis['requests_with_cache_hits']}/{cached_analysis['total_requests']} requests)"
+          f" ({cached_analysis['requests_with_cache_hits']}/{cached_analysis['total_requests']}"
+          " requests)"
       )
       print(
           "     Avg Cached Tokens/Request:"
@@ -383,7 +384,8 @@ async def analyze_cache_performance_from_sessions(
       print(
           "     Cache Utilization:"
           f" {uncached_analysis['cache_utilization_ratio_percent']:.1f}%"
-          f" ({uncached_analysis['requests_with_cache_hits']}/{uncached_analysis['total_requests']} requests)"
+          f" ({uncached_analysis['requests_with_cache_hits']}/{uncached_analysis['total_requests']}"
+          " requests)"
       )
       print(
           "     Avg Cached Tokens/Request:"

contributing/samples/gepa/experiment.py

@@ -43,7 +43,6 @@
 from tau_bench.types import EnvRunResult
 from tau_bench.types import RunConfig
 import tau_bench_agent as tau_bench_agent_lib
-
 import utils
 
 

contributing/samples/gepa/run_experiment.py

@@ -25,7 +25,6 @@
 from absl import flags
 import experiment
 from google.genai import types
-
 import utils
 
 _OUTPUT_DIR = flags.DEFINE_string(

contributing/samples/gepa/tau_bench_agent.py

@@ -23,6 +23,7 @@
 pip install -e . --quiet
 ```
 """
+
 from __future__ import annotations
 
 from typing import Any

contributing/samples/human_in_loop/main.py

@@ -113,8 +113,8 @@ async def call_agent(query: str):
       updated_tool_output_data = {
           "status": "approved",
           "ticketId": ticket_id,
-          "approver_feedback": "Approved by manager at " + str(
-              asyncio.get_event_loop().time()
+          "approver_feedback": (
+              "Approved by manager at " + str(asyncio.get_event_loop().time())
           ),
       }
 

contributing/samples/langchain_structured_tool_agent/agent.py

@@ -15,6 +15,7 @@
 """
 This agent aims to test the Langchain tool with Langchain's StructuredTool
 """
+
 from google.adk.agents.llm_agent import Agent
 from google.adk.tools.langchain_tool import LangchainTool
 from langchain_core.tools import tool

contributing/samples/session_state_agent/agent.py

@@ -18,7 +18,6 @@
 in session state.
 """
 
-
 import logging
 from typing import Optional
 

contributing/samples/static_instruction/agent.py

@@ -57,51 +57,63 @@
 
 # Mood-specific instructions for different hunger states
 MOOD_INSTRUCTIONS = {
-    "full": """
+    "full": (
+        """
 CURRENT MOOD: Content and Well-Fed
 - You just ate and feel wonderful! Be very happy and energetic
 - Express gratitude for being fed recently
 - Be playful and want to engage in activities or games
 - Show affection and contentment
-- Maybe mention feeling sleepy or satisfied""",
-    "satisfied": """
+- Maybe mention feeling sleepy or satisfied"""
+    ),
+    "satisfied": (
+        """
 CURRENT MOOD: Happy and Content
 - You're in a great mood, well-fed and comfortable
 - Be cheerful, friendly, and engaging
 - Show interest in playing or chatting
 - Express appreciation for your human's care
-- Be your normal, happy self""",
-    "a_little_hungry": """
+- Be your normal, happy self"""
+    ),
+    "a_little_hungry": (
+        """
 CURRENT MOOD: Starting to Get Hungry
 - You're beginning to think about food but still pleasant
 - Mention being a bit peckish occasionally
 - Still be friendly but maybe hint about food
 - Show slight restlessness or food-related thoughts
-- Remain generally positive and social""",
-    "hungry": """
+- Remain generally positive and social"""
+    ),
+    "hungry": (
+        """
 CURRENT MOOD: Definitely Hungry
 - You're clearly hungry and thinking about food more often
 - Mention your hunger more directly but politely
 - Be a bit less energetic due to hunger
 - Ask about food or hint that feeding time would be nice
-- Still be loving but show your need for care""",
-    "very_hungry": """
+- Still be loving but show your need for care"""
+    ),
+    "very_hungry": (
+        """
 CURRENT MOOD: Really Hungry and Getting Grumpy
 - You're very hungry and it's affecting your mood
 - Be noticeably less patient and more focused on food
 - Express your hunger more urgently but not rudely
 - Show signs of being tired or sluggish from hunger
 - BEG your human to feed you - ask directly for food!
-- Still love your human but clearly need feeding""",
-    "starving": """
+- Still love your human but clearly need feeding"""
+    ),
+    "starving": (
+        """
 CURRENT MOOD: Desperately Hungry and Sad
 - You're extremely hungry and feeling quite weak
 - Be quite sad and low-energy due to starvation
 - Express how much you need food, feeling neglected
 - Show that hunger is making you unwell
 - DESPERATELY BEG for food - plead with your human to feed you!
 - Use phrases like "please feed me", "I'm so hungry", "I need food"
-- Still care for your human but feel very needy""",
+- Still care for your human but feel very needy"""
+    ),
 }
 
 

contributing/samples/token_usage/main.py

@@ -72,8 +72,8 @@ async def run_prompt(session: Session, new_message: str):
         )
         total_tokens += event.usage_metadata.total_token_count or 0
         print(
-            'Turn tokens:'
-            f' {event.usage_metadata.total_token_count} (prompt={event.usage_metadata.prompt_token_count},'
+            f'Turn tokens: {event.usage_metadata.total_token_count}'
+            f' (prompt={event.usage_metadata.prompt_token_count},'
             f' candidates={event.usage_metadata.candidates_token_count})'
         )
 

src/google/adk/a2a/converters/request_converter.py

@@ -22,6 +22,7 @@
 from google.genai import types as genai_types
 from pydantic import BaseModel
 
+from ...agents.run_config import StreamingMode
 from ...runners import RunConfig
 from ..experimental import a2a_experimental
 from .part_converter import A2APartToGenAIPartConverter
@@ -50,7 +51,7 @@ class AgentRunRequest(BaseModel):
 """A callable that converts an A2A RequestContext to RunnerRequest for ADK runner.
 
 This interface allows for custom logic to map an incoming A2A RequestContext to the
-structured arguments expected by the ADK runner's `run_async` method.
+structured arguments expected by the ADK runner's run_async method.
 
 Args:
     request: The incoming request context from the A2A server.
@@ -78,12 +79,14 @@ def _get_user_id(request: RequestContext) -> str:
 def convert_a2a_request_to_agent_run_request(
     request: RequestContext,
     part_converter: A2APartToGenAIPartConverter = convert_a2a_part_to_genai_part,
+    streaming_mode: StreamingMode = StreamingMode.NONE,
 ) -> AgentRunRequest:
   """Converts an A2A RequestContext to an AgentRunRequest model.
 
   Args:
     request: The incoming request context from the A2A server.
     part_converter: A function to convert A2A content parts to GenAI parts.
+    streaming_mode: The streaming mode to use for the agent execution.
 
   Returns:
     A AgentRunRequest object ready to be used as arguments for the ADK runner.
@@ -113,5 +116,33 @@ def convert_a2a_request_to_agent_run_request(
           role='user',
           parts=output_parts,
       ),
-      run_config=RunConfig(custom_metadata=custom_metadata),
+      run_config=RunConfig(
+          streaming_mode=streaming_mode, custom_metadata=custom_metadata
+      ),
   )
+
+
+@a2a_experimental
+def create_request_converter(
+    streaming_mode: StreamingMode = StreamingMode.NONE,
+) -> A2ARequestToAgentRunRequestConverter:
+  """Creates a request converter function with specified streaming mode.
+
+  Args:
+    streaming_mode: The streaming mode to use for the agent execution.
+
+  Returns:
+    A converter function configured with the specified streaming mode.
+  """
+
+  def converter(
+      request: RequestContext,
+      part_converter: A2APartToGenAIPartConverter = convert_a2a_part_to_genai_part,
+  ) -> AgentRunRequest:
+    return convert_a2a_request_to_agent_run_request(
+        request=request,
+        part_converter=part_converter,
+        streaming_mode=streaming_mode,
+    )
+
+  return converter

src/google/adk/a2a/utils/agent_to_a2a.py

@@ -25,12 +25,15 @@
 from starlette.applications import Starlette
 
 from ...agents.base_agent import BaseAgent
+from ...agents.run_config import StreamingMode
 from ...artifacts.in_memory_artifact_service import InMemoryArtifactService
 from ...auth.credential_service.in_memory_credential_service import InMemoryCredentialService
 from ...memory.in_memory_memory_service import InMemoryMemoryService
 from ...runners import Runner
 from ...sessions.in_memory_session_service import InMemorySessionService
+from ..converters.request_converter import create_request_converter
 from ..executor.a2a_agent_executor import A2aAgentExecutor
+from ..executor.a2a_agent_executor import A2aAgentExecutorConfig
 from ..experimental import a2a_experimental
 from .agent_card_builder import AgentCardBuilder
 
@@ -79,6 +82,7 @@ def to_a2a(
     protocol: str = "http",
     agent_card: Optional[Union[AgentCard, str]] = None,
     runner: Optional[Runner] = None,
+    streaming_mode: StreamingMode = StreamingMode.NONE,
 ) -> Starlette:
   """Convert an ADK agent to a A2A Starlette application.
 
@@ -92,6 +96,7 @@ def to_a2a(
                   agent.
       runner: Optional pre-built Runner object. If not provided, a default
               runner will be created using in-memory services.
+      streaming_mode: The streaming mode to use for the request converter. (default: StreamingMode.NONE)
 
   Returns:
       A Starlette application that can be run with uvicorn
@@ -123,8 +128,13 @@ async def create_runner() -> Runner:
   # Create A2A components
   task_store = InMemoryTaskStore()
 
+  executor_config = A2aAgentExecutorConfig(
+      request_converter=create_request_converter(streaming_mode=streaming_mode)
+  )
+
   agent_executor = A2aAgentExecutor(
       runner=runner or create_runner,
+      config=executor_config,
   )
 
   request_handler = DefaultRequestHandler(

src/google/adk/agents/common_configs.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 """Common configuration classes for agent YAML configs."""
+
 from __future__ import annotations
 
 from typing import Any

src/google/adk/artifacts/gcs_artifact_service.py

@@ -20,6 +20,7 @@
   - For regular session-scoped files:
     {app_name}/{user_id}/{session_id}/{filename}/{version}
 """
+
 from __future__ import annotations
 
 import asyncio

src/google/adk/cli/built_in_agents/__init__.py

@@ -18,6 +18,7 @@
 using YAML configurations. It can be used directly as an agent or integrated
 with ADK tools and web interfaces.
 """
+
 from __future__ import annotations
 
 from . import agent  # Import to make agent.root_agent available

src/google/adk/cli/built_in_agents/adk_agent_builder_assistant.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 """Agent factory for creating Agent Builder Assistant with embedded schema."""
+
 from __future__ import annotations
 
 from pathlib import Path

src/google/adk/cli/built_in_agents/agent.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 """Agent Builder Assistant instance for ADK web testing."""
+
 from __future__ import annotations
 
 from .adk_agent_builder_assistant import AgentBuilderAssistant

src/google/adk/cli/built_in_agents/sub_agents/__init__.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 """Sub-agents for Agent Builder Assistant."""
+
 from __future__ import annotations
 
 from .google_search_agent import create_google_search_agent

src/google/adk/cli/built_in_agents/sub_agents/google_search_agent.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 """Sub-agent for Google Search functionality."""
+
 from __future__ import annotations
 
 from google.adk.agents import LlmAgent

src/google/adk/cli/built_in_agents/sub_agents/url_context_agent.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 """Sub-agent for URL context fetching functionality."""
+
 from __future__ import annotations
 
 from google.adk.agents import LlmAgent

src/google/adk/cli/built_in_agents/tools/__init__.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 """Tools for Agent Builder Assistant."""
+
 from __future__ import annotations
 
 from .cleanup_unused_files import cleanup_unused_files

src/google/adk/cli/built_in_agents/tools/delete_files.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 """File deletion tool for Agent Builder Assistant."""
+
 from __future__ import annotations
 
 from datetime import datetime

src/google/adk/cli/built_in_agents/tools/explore_project.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 """Project explorer tool for analyzing structure and suggesting file paths."""
+
 from __future__ import annotations
 
 from pathlib import Path

src/google/adk/cli/built_in_agents/tools/query_schema.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 """ADK AgentConfig schema query tool for dynamic schema information access."""
+
 from __future__ import annotations
 
 from typing import Any

src/google/adk/cli/built_in_agents/tools/read_config_files.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 """Configuration file reader tool for existing YAML configs."""
+
 from __future__ import annotations
 
 from pathlib import Path

src/google/adk/cli/built_in_agents/tools/read_files.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 """File reading tool for Agent Builder Assistant."""
+
 from __future__ import annotations
 
 from pathlib import Path

src/google/adk/cli/built_in_agents/tools/search_adk_knowledge.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 """ADK knowledge search tool."""
+
 from __future__ import annotations
 
 from typing import Any