feat: add AG-UI (AGUI) as fourth first-class protocol mode

src/assets/python/a2a/googleadk/base/main.py

@@ -6,14 +6,16 @@
 from bedrock_agentcore.runtime import serve_a2a
 from model.load import load_model
 
+load_model()  # Sets GOOGLE_API_KEY env var (returns None)
+
 
 def add_numbers(a: int, b: int) -> int:
     """Return the sum of two numbers."""
     return a + b
 
 
 agent = Agent(
-    model=load_model(),
+    model="gemini-2.5-flash",
     name="{{ name }}",
     description="A helpful assistant that can use tools.",
     instruction="You are a helpful assistant. Use tools when appropriate.",

src/assets/python/agui/googleadk/base/README.md

@@ -0,0 +1,30 @@
+# {{ name }}
+
+An AG-UI agent deployed on Amazon Bedrock AgentCore using Google ADK.
+
+## Overview
+
+This agent implements the AG-UI protocol using Google's Agent Development Kit, enabling rich agent-user interaction via the AG-UI event stream.
+
+## Local Development
+
+```bash
+uv sync
+uv run python main.py
+```
+
+The agent starts on port 8080 and serves requests at `/invocations`.
+
+## Health Check
+
+```
+GET /ping
+```
+
+Returns `{"status": "healthy"}`.
+
+## Deploy
+
+```bash
+agentcore deploy
+```

src/assets/python/agui/googleadk/base/gitignore.template

@@ -0,0 +1,41 @@
+# Environment variables
+.env
+
+# Python
+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+
+# Virtual environments
+.venv/
+venv/
+ENV/
+env/
+
+# IDE
+.vscode/
+.idea/
+*.swp
+*.swo
+*~
+
+# OS
+.DS_Store
+Thumbs.db

src/assets/python/agui/googleadk/base/main.py

@@ -0,0 +1,31 @@
+import uvicorn
+from google.adk.agents import LlmAgent
+from ag_ui_adk import ADKAgent, AGUIToolset, create_adk_app
+from model.load import load_model
+
+load_model()
+
+agent = LlmAgent(
+    name="{{ name }}",
+    model="gemini-2.5-flash",
+    instruction="You are a helpful assistant.",
+    tools=[AGUIToolset()],
+)
+
+adk_agent = ADKAgent(
+    adk_agent=agent,
+    app_name="{{ name }}",
+    user_id="default-user",
+    use_in_memory_services=True,
+)
+
+app = create_adk_app(adk_agent, path="/invocations")
+
+
+@app.get("/ping")
+async def ping():
+    return {"status": "healthy"}
+
+
+if __name__ == "__main__":
+    uvicorn.run(app, host="0.0.0.0", port=8080)

src/assets/python/agui/googleadk/base/model/__init__.py

@@ -0,0 +1 @@
+# Package marker

src/assets/python/agui/googleadk/base/model/load.py

@@ -0,0 +1,41 @@
+import os
+from bedrock_agentcore.identity.auth import requires_api_key
+
+IDENTITY_PROVIDER_NAME = "{{identityProviders.[0].name}}"
+IDENTITY_ENV_VAR = "{{identityProviders.[0].envVarName}}"
+
+
+@requires_api_key(provider_name=IDENTITY_PROVIDER_NAME)
+def _agentcore_identity_api_key_provider(api_key: str) -> str:
+    """Fetch API key from AgentCore Identity."""
+    return api_key
+
+
+def _get_api_key() -> str:
+    """
+    Uses AgentCore Identity for API key management in deployed environments.
+    For local development, run via 'agentcore dev' which loads agentcore/.env.
+    """
+    if os.getenv("LOCAL_DEV") == "1":
+        api_key = os.getenv(IDENTITY_ENV_VAR)
+        if not api_key:
+            raise RuntimeError(
+                f"{IDENTITY_ENV_VAR} not found. Add {IDENTITY_ENV_VAR}=your-key to .env.local"
+            )
+        return api_key
+    return _agentcore_identity_api_key_provider()
+
+
+def load_model() -> None:
+    """
+    Set up Gemini API key authentication.
+    Uses AgentCore Identity for API key management in deployed environments,
+    and falls back to .env file for local development.
+    Sets the GOOGLE_API_KEY environment variable for the Google ADK.
+    """
+    api_key = _get_api_key()
+    # Use Google AI Studios API Key Authentication.
+    # https://google.github.io/adk-docs/agents/models/#google-ai-studio
+    os.environ["GOOGLE_API_KEY"] = api_key
+    # Set to TRUE is using Google Vertex AI, Set to FALSE for Google AI Studio
+    os.environ["GOOGLE_GENAI_USE_VERTEXAI"] = "FALSE"

src/assets/python/agui/googleadk/base/pyproject.toml

@@ -0,0 +1,22 @@
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
+[project]
+name = "{{ name }}"
+version = "0.1.0"
+description = "AgentCore AG-UI Agent using Google ADK"
+readme = "README.md"
+requires-python = ">=3.10"
+dependencies = [
+    "ag-ui-adk >= 0.6.0",
+    "ag-ui-protocol >= 0.1.10",
+    "bedrock-agentcore >= 1.0.3",
+    "fastapi >= 0.115.12",
+    "google-adk >= 1.16.0",
+    "google-genai >= 1.0.0",
+    "uvicorn >= 0.34.3",
+]
+
+[tool.hatch.build.targets.wheel]
+packages = ["."]

src/assets/python/agui/langchain_langgraph/base/README.md

@@ -0,0 +1,22 @@
+# {{ name }}
+
+An AG-UI agent deployed on Amazon Bedrock AgentCore using LangChain + LangGraph.
+
+## Overview
+
+This agent implements the AG-UI protocol using LangGraph, enabling seamless frontend-to-agent communication with support for streaming, tool calls, and frontend-injected tools.
+
+## Local Development
+
+```bash
+uv sync
+uv run python main.py
+```
+
+The agent starts on port 8080.
+
+## Deploy
+
+```bash
+agentcore deploy
+```

src/assets/python/agui/langchain_langgraph/base/gitignore.template

@@ -0,0 +1,41 @@
+# Environment variables
+.env
+
+# Python
+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+
+# Virtual environments
+.venv/
+venv/
+ENV/
+env/
+
+# IDE
+.vscode/
+.idea/
+*.swp
+*.swo
+*~
+
+# OS
+.DS_Store
+Thumbs.db

src/assets/python/agui/langchain_langgraph/base/main.py

@@ -0,0 +1,71 @@
+import os
+
+os.environ["LANGGRAPH_FAST_API"] = "true"
+
+import uvicorn
+from typing import Any, List
+from fastapi import FastAPI
+from fastapi.middleware.cors import CORSMiddleware
+from langgraph.graph import StateGraph, END, START
+from langgraph.graph.message import MessagesState
+from langgraph.checkpoint.memory import MemorySaver
+from langgraph.prebuilt import ToolNode, tools_condition
+from langchain_core.tools import tool
+from ag_ui_langgraph import LangGraphAgent, add_langgraph_fastapi_endpoint
+from model.load import load_model
+
+
+@tool
+def add_numbers(a: int, b: int) -> int:
+    """Return the sum of two numbers."""
+    return a + b
+
+
+backend_tools = [add_numbers]
+model = load_model()
+
+
+class AgentState(MessagesState):
+    tools: List[Any]
+
+
+def chat_node(state: AgentState):
+    bound_model = model.bind_tools(
+        [*state.get("tools", []), *backend_tools],
+    )
+    response = bound_model.invoke(state["messages"])
+    return {"messages": [response]}
+
+
+builder = StateGraph(AgentState)
+builder.add_node("chat", chat_node)
+builder.add_node("tools", ToolNode(tools=backend_tools))
+builder.add_edge(START, "chat")
+builder.add_conditional_edges("chat", tools_condition)
+builder.add_edge("tools", "chat")
+graph = builder.compile(checkpointer=MemorySaver())
+
+agent = LangGraphAgent(
+    name="{{ name }}",
+    graph=graph,
+    description="A helpful assistant",
+)
+
+app = FastAPI()
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+add_langgraph_fastapi_endpoint(app=app, agent=agent, path="/invocations")
+
+
+@app.get("/ping")
+async def ping():
+    return {"status": "healthy"}
+
+
+if __name__ == "__main__":
+    uvicorn.run(app, host="0.0.0.0", port=8080)

src/assets/python/agui/langchain_langgraph/base/model/__init__.py

@@ -0,0 +1 @@
+# Package marker