chore: import upstream snapshot with attribution

examples/integrations/agentcore/agents/langgraph-single-agent/Dockerfile

@@ -0,0 +1,36 @@
+# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+FROM ghcr.io/astral-sh/uv:python3.13-bookworm-slim
+
+WORKDIR /app
+
+# Configure UV for container environment
+ENV UV_SYSTEM_PYTHON=1 \
+    UV_COMPILE_BYTECODE=1 \
+    DOCKER_CONTAINER=1 \
+    OTEL_PYTHON_LOG_CORRELATION=true \
+    PYTHONUNBUFFERED=1
+
+# Copy and install agent-specific requirements first
+COPY agents/langgraph-single-agent/requirements.txt requirements.txt
+RUN uv pip install --no-cache -r requirements.txt && \
+    uv pip install --no-cache aws-opentelemetry-distro==0.16.0
+
+# Create non-root user
+RUN useradd -m -u 1000 bedrock_agentcore
+USER bedrock_agentcore
+
+EXPOSE 8080
+
+# Copy agent code, tools, and shared utilities
+COPY agents/langgraph-single-agent/langgraph_agent.py .
+COPY agents/langgraph-single-agent/tools/ tools/
+COPY agents/utils/ utils/
+
+# Healthcheck using Python (no extra dependencies needed)
+HEALTHCHECK --interval=30s --timeout=3s --start-period=5s --retries=3 \
+  CMD python -c "import urllib.request; urllib.request.urlopen('http://localhost:8080/ping', timeout=2)" || exit 1
+
+# Start agent with OpenTelemetry instrumentation
+CMD ["opentelemetry-instrument", "python", "-m", "langgraph_agent"]

examples/integrations/agentcore/agents/langgraph-single-agent/langgraph_agent.py

@@ -0,0 +1,159 @@
+# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+from __future__ import annotations
+
+import logging
+import os
+
+from ag_ui.core import RunAgentInput, RunErrorEvent
+from bedrock_agentcore.identity.auth import requires_access_token
+from bedrock_agentcore.runtime import BedrockAgentCoreApp, RequestContext
+from copilotkit import (
+    CopilotKitMiddleware,
+    LangGraphAGUIAgent,
+    StateStreamingMiddleware,
+    StateItem,
+)
+from langchain.agents import create_agent
+from langchain_aws import ChatBedrock
+from langchain_mcp_adapters.client import MultiServerMCPClient
+from langgraph_checkpoint_aws import AgentCoreMemorySaver
+
+from utils.auth import extract_user_id_from_context
+from utils.ssm import get_ssm_parameter
+from tools import query_data, AgentState, todo_tools
+
+app = BedrockAgentCoreApp()
+
+ACTOR_ID_KEYS = ("actor_id", "actorId", "user_id", "userId", "sub")
+
+SYSTEM_PROMPT = """You are a helpful assistant with access to tools via the Gateway and built-in data tools.
+
+When demonstrating charts, always call the query_data tool first to fetch data from the database before calling any chart tool.
+When managing todos, use manage_todos to update the list and get_todos to read the current list.
+When asked about your tools, list them and explain what they do."""
+
+
+@requires_access_token(
+    provider_name=os.environ["GATEWAY_CREDENTIAL_PROVIDER_NAME"],
+    auth_flow="M2M",
+    scopes=[],
+)
+async def _fetch_gateway_token(access_token: str) -> str:
+    return access_token
+
+
+async def create_gateway_mcp_client() -> MultiServerMCPClient:
+    stack_name = os.environ.get("STACK_NAME")
+    if not stack_name:
+        raise ValueError("STACK_NAME environment variable is required")
+
+    if not stack_name.replace("-", "").replace("_", "").isalnum():
+        raise ValueError("Invalid STACK_NAME format")
+
+    gateway_url = get_ssm_parameter(f"/{stack_name}/gateway_url")
+    fresh_token = await _fetch_gateway_token()
+
+    return MultiServerMCPClient(
+        {
+            "gateway": {
+                "transport": "streamable_http",
+                "url": gateway_url,
+                "headers": {
+                    "Authorization": f"Bearer {fresh_token}",
+                },
+            }
+        }
+    )
+
+
+def _build_model(streaming: bool) -> ChatBedrock:
+    return ChatBedrock(
+        model_id="us.anthropic.claude-sonnet-4-5-20250929-v1:0",
+        temperature=0.1,
+        max_tokens=16384,
+        streaming=streaming,
+        beta_use_converse_api=True,
+    )
+
+
+def _build_checkpointer() -> AgentCoreMemorySaver:
+    memory_id = os.environ.get("MEMORY_ID")
+    if not memory_id:
+        raise ValueError("MEMORY_ID environment variable is required")
+
+    return AgentCoreMemorySaver(
+        memory_id=memory_id,
+        region_name=os.environ.get("AWS_DEFAULT_REGION", "us-east-1"),
+    )
+
+
+@app.entrypoint
+async def invocations(payload: dict, context: RequestContext):
+    input_data = RunAgentInput.model_validate(payload)
+
+    # Extract actor identity securely from the validated JWT token.
+    try:
+        actor_id = extract_user_id_from_context(context)
+    except ValueError:
+        # Fall back to forwarded props if JWT extraction fails (e.g. local dev).
+        forwarded = (
+            input_data.forwarded_props
+            if isinstance(input_data.forwarded_props, dict)
+            else {}
+        )
+        actor_id = next(
+            (forwarded[k] for k in ACTOR_ID_KEYS if k in forwarded and forwarded[k]),
+            None,
+        )
+
+    if not actor_id:
+        raise ValueError(
+            "Missing actor identity. Provide forwardedProps.actor_id/user_id "
+            "or include sub claim in the bearer token."
+        )
+
+    try:
+        try:
+            mcp_client = await create_gateway_mcp_client()
+            gateway_tools = await mcp_client.get_tools()
+        except Exception as gw_err:
+            logging.warning("Gateway tools unavailable (running locally?): %s", gw_err)
+            gateway_tools = []
+
+        graph = create_agent(
+            model=_build_model(streaming=True),
+            tools=[*gateway_tools, query_data, *todo_tools],
+            checkpointer=_build_checkpointer(),
+            middleware=[
+                CopilotKitMiddleware(),
+                StateStreamingMiddleware(
+                    StateItem(
+                        state_key="todos", tool="manage_todos", tool_argument="todos"
+                    )
+                ),
+            ],
+            system_prompt=SYSTEM_PROMPT,
+            state_schema=AgentState,
+        )
+
+        agent = LangGraphAGUIAgent(
+            name="LangGraphSingleAgent",
+            description="LangGraph single agent exposed via AG-UI",
+            graph=graph,
+            config={"configurable": {"actor_id": actor_id}},
+        )
+        async for event in agent.run(input_data):
+            if event is not None:
+                yield event.model_dump(mode="json", by_alias=True, exclude_none=True)
+    except Exception as exc:
+        logging.exception("Agent run failed")
+        yield RunErrorEvent(
+            message=str(exc) or type(exc).__name__,
+            code=type(exc).__name__,
+        ).model_dump(mode="json", by_alias=True, exclude_none=True)
+
+
+if __name__ == "__main__":
+    app.run()

examples/integrations/agentcore/agents/langgraph-single-agent/requirements.txt

@@ -0,0 +1,14 @@
+# LangGraph agent dependencies with pinned versions
+fastapi==0.115.12
+uvicorn==0.34.2
+ag-ui-protocol>=0.1.15
+ag-ui-langgraph==0.0.33
+copilotkit==0.1.87
+partialjson>=0.0.8
+langgraph==1.0.10rc1
+langchain>=0.3.0
+langchain-aws==1.0.0
+langchain-mcp-adapters==0.1.13
+langgraph-checkpoint-aws==1.0.5
+mcp==1.23.1
+bedrock-agentcore==1.0.6

examples/integrations/agentcore/agents/langgraph-single-agent/tools/__init__.py

@@ -0,0 +1,8 @@
+# patterns/langgraph-single-agent/tools/__init__.py
+# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+from .query_data import query_data
+from .todos import AgentState, todo_tools
+
+__all__ = ["query_data", "AgentState", "todo_tools"]

examples/integrations/agentcore/agents/langgraph-single-agent/tools/db.csv

@@ -0,0 +1,16 @@
+date,category,amount,type
+2026-01-05,Food,42.50,expense
+2026-01-10,Transport,15.00,expense
+2026-01-15,Salary,3500.00,income
+2026-01-20,Entertainment,80.00,expense
+2026-01-25,Utilities,120.00,expense
+2026-02-03,Food,55.20,expense
+2026-02-08,Freelance,800.00,income
+2026-02-14,Dining,65.00,expense
+2026-02-20,Transport,22.50,expense
+2026-02-28,Salary,3500.00,income
+2026-03-05,Groceries,95.40,expense
+2026-03-10,Gym,40.00,expense
+2026-03-15,Salary,3500.00,income
+2026-03-18,Coffee,18.75,expense
+2026-03-22,Books,35.00,expense

examples/integrations/agentcore/agents/langgraph-single-agent/tools/query_data.py

@@ -0,0 +1,25 @@
+# patterns/langgraph-single-agent/tools/query_data.py
+# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+import csv
+from pathlib import Path
+
+from langchain.tools import tool
+
+# Read at module load time — avoids file I/O on every tool invocation.
+_csv_path = Path(__file__).parent / "db.csv"
+try:
+    with open(_csv_path) as _f:
+        _cached_data = list(csv.DictReader(_f))
+except (FileNotFoundError, OSError) as e:
+    raise RuntimeError(f"query_data: cannot load sample data from {_csv_path}") from e
+
+
+@tool
+def query_data(query: str) -> list[dict]:
+    """
+    Query the database. Accepts natural language.
+    Always call this tool before displaying a chart or graph.
+    """
+    return _cached_data

examples/integrations/agentcore/agents/langgraph-single-agent/tools/todos.py

@@ -0,0 +1,66 @@
+# patterns/langgraph-single-agent/tools/todos.py
+# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+import uuid
+from typing import Literal, TypedDict
+
+from langchain.agents import AgentState as BaseAgentState
+from langchain.tools import ToolRuntime, tool
+from langchain_core.messages import ToolMessage
+from langgraph.types import Command
+
+# ToolRuntime is confirmed available at langchain.tools (langchain >= 1.2).
+# If you see an ImportError, verify your langchain version is >= 0.3.
+
+
+class Todo(TypedDict):
+    id: str
+    title: str
+    description: str
+    emoji: str
+    status: Literal["pending", "completed"]
+
+
+class AgentState(BaseAgentState):
+    todos: list[Todo]
+
+
+def _assign_ids(todos: list[dict]) -> list[dict]:
+    """Assign a uuid4 to any todo that has a missing or empty 'id'."""
+    for todo in todos:
+        if not todo.get("id"):
+            todo["id"] = str(uuid.uuid4())
+    return todos
+
+
+@tool
+def manage_todos(todos: list[Todo], runtime: ToolRuntime) -> Command:
+    """
+    Manage the current todos. Replaces the entire todo list.
+    Assigns a unique UUID to any todo that is missing one.
+    """
+    _assign_ids(todos)  # type: ignore[arg-type]
+
+    return Command(
+        update={
+            "todos": todos,
+            "messages": [
+                ToolMessage(
+                    content="Successfully updated todos",
+                    tool_call_id=runtime.tool_call_id,
+                )
+            ],
+        }
+    )
+
+
+@tool
+def get_todos(runtime: ToolRuntime) -> list[Todo]:
+    """
+    Get the current todo list from agent state.
+    """
+    return runtime.state.get("todos", [])
+
+
+todo_tools = [manage_todos, get_todos]