feat(cli): add Temporal + LangGraph agent template and example

examples/tutorials/10_async/10_temporal/130_langgraph/.dockerignore

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+# 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
+
+# Environments
+.env**
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# IDE
+.idea/
+.vscode/
+*.swp
+*.swo
+
+# Git
+.git
+.gitignore
+
+# Misc
+.DS_Store 

examples/tutorials/10_async/10_temporal/130_langgraph/.env.example

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+# at130-langgraph - Environment Variables
+# Copy this file to .env and fill in the values
+
+# API key for your LLM provider
+LITELLM_API_KEY=
+
+# LLM base URL (optional - override to use a different provider)
+# OPENAI_BASE_URL=
+
+# SGP Configuration (optional - for tracing)
+# SGP_API_KEY=
+# SGP_ACCOUNT_ID=
+# SGP_CLIENT_BASE_URL=

examples/tutorials/10_async/10_temporal/130_langgraph/Dockerfile

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+# syntax=docker/dockerfile:1.3
+FROM python:3.12-slim
+COPY --from=ghcr.io/astral-sh/uv:0.6.4 /uv /uvx /bin/
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y \
+    htop \
+    vim \
+    curl \
+    tar \
+    python3-dev \
+    postgresql-client \
+    build-essential \
+    libpq-dev \
+    gcc \
+    cmake \
+    netcat-openbsd \
+    && apt-get clean \
+    && rm -rf /var/lib/apt/lists/*
+
+RUN uv pip install --system --upgrade pip setuptools wheel
+
+ENV UV_HTTP_TIMEOUT=1000
+
+COPY 10_async/10_temporal/130_langgraph/pyproject.toml /app/130_langgraph/pyproject.toml
+COPY 10_async/10_temporal/130_langgraph/README.md /app/130_langgraph/README.md
+
+WORKDIR /app/130_langgraph
+
+COPY 10_async/10_temporal/130_langgraph/project /app/130_langgraph/project
+COPY 10_async/10_temporal/130_langgraph/tests /app/130_langgraph/tests
+COPY test_utils /app/test_utils
+
+RUN uv pip install --system .[dev]
+
+ENV PYTHONPATH=/app
+
+ENV AGENT_NAME=at130-langgraph
+
+CMD ["uvicorn", "project.acp:acp", "--host", "0.0.0.0", "--port", "8000"]
+
+# When we deploy the worker, we will replace the CMD with the following
+# CMD ["python", "-m", "run_worker"]

examples/tutorials/10_async/10_temporal/130_langgraph/README.md

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+# at130-langgraph — AgentEx Temporal + LangGraph
+
+A minimal Temporal-backed [LangGraph](https://langchain-ai.github.io/langgraph/)
+agent. It uses the official [`temporalio.contrib.langgraph`](https://docs.temporal.io/develop/python/integrations/langgraph)
+plugin so each LangGraph node runs as a durable **Temporal activity** (the LLM
+`agent` node) or inline in the **workflow** (the `tools` node) — set per node
+with `execute_in`. *Temporal is the runtime; LangGraph is the agent framework.*
+
+> The Temporal LangGraph plugin is currently **experimental**.
+
+## The graph
+
+```
+START → agent → (tool calls?) → tools → agent
+             → (no tool calls?) → END
+```
+
+- `agent` (`execute_in="activity"`): the LLM call — a retried, observable Temporal activity.
+- `tools` (`execute_in="workflow"`): runs the tool calls inline in the workflow.
+
+The router and tools are `async` so LangGraph awaits them directly (a sync
+callable is offloaded via `run_in_executor`, which Temporal workflows forbid).
+
+## Project structure
+
+```
+130_langgraph/
+├── project/
+│   ├── acp.py          # Thin async ACP server; registers the LangGraphPlugin
+│   ├── workflow.py     # Runs the graph each turn; keeps multi-turn memory
+│   ├── graph.py        # LangGraph graph; nodes tagged execute_in activity/workflow
+│   └── tools.py        # Async tool(s)
+└── run_worker.py is project/run_worker.py
+```
+
+## Running
+
+```bash
+agentex agents run --manifest manifest.yaml
+```
+
+Open the Temporal UI at http://localhost:8080 to watch the workflow and the
+`agent` activity execute. Use `dev.ipynb` to create a task and send messages.
+
+## Adding tools
+
+Define an **async** `@tool` in `project/tools.py` and add it to `TOOLS`. The
+model is bound with `TOOLS` and the tool node runs them by name.
+
+For a fuller version with human-in-the-loop approval and graph-introspection
+queries, scaffold the `temporal-langgraph` template via `agentex init`.
+
+## Tests
+
+- `tests/test_graph_temporal.py` — hermetic ReAct-loop test with a stub model,
+  plus a live end-to-end run through the real Temporal plugin (skipped unless
+  `LITELLM_API_KEY` is set).
+- `tests/test_agent.py` — live integration against a running agent.

examples/tutorials/10_async/10_temporal/130_langgraph/dev.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "36834357",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from agentex import Agentex\n",
+    "\n",
+    "client = Agentex(base_url=\"http://localhost:5003\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d1c309d6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "AGENT_NAME = \"at130-langgraph\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9f6e6ef0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# (REQUIRED) Create a new task. For Async agents, you must create a task for messages to be associated with.\n",
+    "import uuid\n",
+    "\n",
+    "rpc_response = client.agents.create_task(\n",
+    "    agent_name=AGENT_NAME,\n",
+    "    params={\n",
+    "        \"name\": f\"{str(uuid.uuid4())[:8]}-task\",\n",
+    "        \"params\": {}\n",
+    "    }\n",
+    ")\n",
+    "\n",
+    "task = rpc_response.result\n",
+    "print(task)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b03b0d37",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Send an event to the agent\n",
+    "\n",
+    "# The response is expected to be a list of TaskMessage objects, which is a union of the following types:\n",
+    "# - TextContent: A message with just text content   \n",
+    "# - DataContent: A message with JSON-serializable data content\n",
+    "# - ToolRequestContent: A message with a tool request, which contains a JSON-serializable request to call a tool\n",
+    "# - ToolResponseContent: A message with a tool response, which contains response object from a tool call in its content\n",
+    "\n",
+    "# When processing the message/send response, if you are expecting more than TextContent, such as DataContent, ToolRequestContent, or ToolResponseContent, you can process them as well\n",
+    "\n",
+    "rpc_response = client.agents.send_event(\n",
+    "    agent_name=AGENT_NAME,\n",
+    "    params={\n",
+    "        \"content\": {\"type\": \"text\", \"author\": \"user\", \"content\": \"Hello what can you do?\"},\n",
+    "        \"task_id\": task.id,\n",
+    "    }\n",
+    ")\n",
+    "\n",
+    "event = rpc_response.result\n",
+    "print(event)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a6927cc0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Subscribe to the async task messages produced by the agent\n",
+    "from agentex.lib.utils.dev_tools import subscribe_to_async_task_messages\n",
+    "\n",
+    "task_messages = subscribe_to_async_task_messages(\n",
+    "    client=client,\n",
+    "    task=task, \n",
+    "    only_after_timestamp=event.created_at, \n",
+    "    print_messages=True,\n",
+    "    rich_print=True,\n",
+    "    timeout=5,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4864e354",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/tutorials/10_async/10_temporal/130_langgraph/environments.yaml

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+# Agent Environment Configuration
+# ------------------------------
+# This file defines environment-specific settings for your agent.
+# This DIFFERS from the manifest.yaml file in that it is used to program things that are ONLY per environment.
+
+# ********** EXAMPLE **********
+# schema_version: "v1" # This is used to validate the file structure and is not used by the agentex CLI
+# environments:
+#   dev:
+#     auth:
+#       principal:
+#         user_id: "1234567890"
+#         user_name: "John Doe"
+#         user_email: "john.doe@example.com"
+#         user_role: "admin"
+#       user_permissions: "read, write, delete"
+#     helm_overrides: # This is used to override the global helm values.yaml file in the agentex-agent helm charts
+#       replicas: 3
+#       resources:
+#         requests:
+#           cpu: "1000m"
+#           memory: "2Gi"
+#         limits:
+#           cpu: "2000m"
+#           memory: "4Gi"
+#       env:
+#         - name: LOG_LEVEL
+#           value: "DEBUG"
+#         - name: ENVIRONMENT
+#           value: "staging"
+#
+#     kubernetes: 
+#       # OPTIONAL - Otherwise it will be derived from separately. However, this can be used to override the derived
+#       #   namespace and deploy it with in the same namespace that already exists for a separate agent.
+#       namespace: "team-at130-langgraph"
+# ********** END EXAMPLE **********
+
+schema_version: "v1" # This is used to validate the file structure and is not used by the agentex CLI
+environments:
+  dev:
+    auth:
+      principal:
+        user_id: # TODO: Fill in
+        account_id: # TODO: Fill in
+    helm_overrides: 
+      # This is used to override the global helm values.yaml file in the agentex-agent helm charts
+      replicaCount: 2
+      resources:
+        requests:
+          cpu: "500m"
+          memory: "1Gi"
+        limits:
+          cpu: "1000m"
+          memory: "2Gi"
+      temporal-worker:
+        enabled: true
+        replicaCount: 2
+        resources:
+          requests:
+            cpu: "500m"
+            memory: "1Gi"
+          limits:
+            cpu: "1000m"
+            memory: "2Gi"