Add activity_options to all graph_api samples

Demonstrates per-node activity configuration using activity_options():

Direct node metadata (graphs using add_node directly):
- hello_world: Simple 30s timeout for process node
- reflection: 2min timeouts for LLM nodes, 30s for finalize
- deep_research: Varied timeouts (plan 2min, search 1min, synthesize 3min)
- agentic_rag: 1-2min timeouts for grading/generation nodes
- plan_and_execute: 2min for planning, 30s for evaluation
- activity_from_node: 30s for finalize activity node
- human_in_the_loop: 30s timeouts for approval nodes

Documentation for pre-built graphs (create_agent/create_supervisor):
- react_agent: Docstring shows per_node_activity_options usage
- supervisor: Docstring shows multi-agent configuration

Author: mfateev

langgraph_plugin/graph_api/activity_from_node/graph.py

@@ -86,7 +86,7 @@ def build_activity_from_node_graph() -> Any:
     The orchestrator node uses run_in_workflow=True to execute directly
     in the workflow context, allowing it to call Temporal activities.
     """
-    from temporalio.contrib.langgraph import temporal_node_metadata
+    from temporalio.contrib.langgraph import activity_options, temporal_node_metadata
 
     graph = StateGraph(ProcessingState)
 
@@ -97,8 +97,14 @@ def build_activity_from_node_graph() -> Any:
         metadata=temporal_node_metadata(run_in_workflow=True),
     )
 
-    # Finalize runs as a regular activity
-    graph.add_node("finalize", finalize_node)
+    # Finalize runs as a regular activity with timeout config
+    graph.add_node(
+        "finalize",
+        finalize_node,
+        metadata=activity_options(
+            start_to_close_timeout=timedelta(seconds=30),
+        ),
+    )
 
     graph.add_edge(START, "orchestrator")
     graph.add_edge("orchestrator", "finalize")

langgraph_plugin/graph_api/agentic_rag/graph.py

@@ -27,6 +27,7 @@
 """
 
 import os
+from datetime import timedelta
 from typing import Annotated, Any, Literal, Sequence, cast
 
 from langchain_core.documents import Document
@@ -39,6 +40,7 @@
 from langgraph.graph import END, START, StateGraph
 from langgraph.graph.message import add_messages
 from pydantic import BaseModel, Field
+from temporalio.contrib.langgraph import activity_options
 from typing_extensions import TypedDict
 
 from langchain.agents import create_agent
@@ -308,12 +310,31 @@ def rewrite(state: AgentState) -> dict[str, Any]:
     # Build the outer graph with grading logic
     workflow = StateGraph(AgentState)
 
-    # Add nodes
+    # Add nodes with activity options
     # retrieve_agent is a compiled graph from create_agent - inner nodes run as separate activities
+    # Use per_node_activity_options in LangGraphPlugin to configure its inner nodes
     workflow.add_node("retrieve_agent", retrieve_agent)
-    workflow.add_node("grade_documents", grade_documents)  # LLM grading as activity
-    workflow.add_node("generate", generate)
-    workflow.add_node("rewrite", rewrite)
+    workflow.add_node(
+        "grade_documents",
+        grade_documents,
+        metadata=activity_options(
+            start_to_close_timeout=timedelta(minutes=1),
+        ),
+    )
+    workflow.add_node(
+        "generate",
+        generate,
+        metadata=activity_options(
+            start_to_close_timeout=timedelta(minutes=2),
+        ),
+    )
+    workflow.add_node(
+        "rewrite",
+        rewrite,
+        metadata=activity_options(
+            start_to_close_timeout=timedelta(minutes=1),
+        ),
+    )
 
     # Add edges
     workflow.add_edge(START, "retrieve_agent")

langgraph_plugin/graph_api/deep_research/graph.py

@@ -23,6 +23,7 @@
 """
 
 import os
+from datetime import timedelta
 from typing import Annotated, Any, Literal, cast
 
 from langchain_community.tools import DuckDuckGoSearchRun
@@ -34,6 +35,7 @@
 from langgraph.graph import END, START, StateGraph
 from langgraph.graph.message import add_messages
 from pydantic import BaseModel, Field
+from temporalio.contrib.langgraph import activity_options
 from typing_extensions import TypedDict
 
 
@@ -287,11 +289,35 @@ def synthesize_report(state: ResearchState) -> dict[str, Any]:
     # Build the research graph
     workflow = StateGraph(ResearchState)
 
-    # Add nodes
-    workflow.add_node("plan", plan_research)
-    workflow.add_node("search", execute_search)
-    workflow.add_node("evaluate", evaluate_results)
-    workflow.add_node("synthesize", synthesize_report)
+    # Add nodes with activity options
+    workflow.add_node(
+        "plan",
+        plan_research,
+        metadata=activity_options(
+            start_to_close_timeout=timedelta(minutes=2),
+        ),
+    )
+    workflow.add_node(
+        "search",
+        execute_search,
+        metadata=activity_options(
+            start_to_close_timeout=timedelta(minutes=1),
+        ),
+    )
+    workflow.add_node(
+        "evaluate",
+        evaluate_results,
+        metadata=activity_options(
+            start_to_close_timeout=timedelta(seconds=30),
+        ),
+    )
+    workflow.add_node(
+        "synthesize",
+        synthesize_report,
+        metadata=activity_options(
+            start_to_close_timeout=timedelta(minutes=3),
+        ),
+    )
 
     # Add edges
     workflow.add_edge(START, "plan")

langgraph_plugin/graph_api/hello_world/graph.py

@@ -4,9 +4,11 @@
 It is imported only by the worker (not by the workflow).
 """
 
+from datetime import timedelta
 from typing import Any
 
 from langgraph.graph import END, START, StateGraph
+from temporalio.contrib.langgraph import activity_options
 from typing_extensions import TypedDict
 
 # =============================================================================
@@ -49,8 +51,14 @@ def build_hello_graph() -> Any:
     """
     graph = StateGraph(HelloState)
 
-    # Add a single processing node
-    graph.add_node("process", process_query)
+    # Add a single processing node with activity options
+    graph.add_node(
+        "process",
+        process_query,
+        metadata=activity_options(
+            start_to_close_timeout=timedelta(seconds=30),
+        ),
+    )
 
     # Define edges: START -> process -> END
     graph.add_edge(START, "process")

langgraph_plugin/graph_api/human_in_the_loop/approval_graph_interrupt/graph.py

@@ -9,10 +9,12 @@
 3. execute_action: Processes the approved request (or rejects it)
 """
 
+from datetime import timedelta
 from typing import Any
 
 from langgraph.graph import END, START, StateGraph
 from langgraph.types import interrupt
+from temporalio.contrib.langgraph import activity_options
 from typing_extensions import TypedDict
 
 
@@ -114,10 +116,28 @@ def build_approval_graph() -> Any:
     """
     graph = StateGraph(ApprovalState)
 
-    # Add nodes
-    graph.add_node("process_request", process_request)
-    graph.add_node("request_approval", request_approval)
-    graph.add_node("execute_action", execute_action)
+    # Add nodes with activity options
+    graph.add_node(
+        "process_request",
+        process_request,
+        metadata=activity_options(
+            start_to_close_timeout=timedelta(seconds=30),
+        ),
+    )
+    graph.add_node(
+        "request_approval",
+        request_approval,
+        metadata=activity_options(
+            start_to_close_timeout=timedelta(seconds=30),
+        ),
+    )
+    graph.add_node(
+        "execute_action",
+        execute_action,
+        metadata=activity_options(
+            start_to_close_timeout=timedelta(seconds=30),
+        ),
+    )
 
     # Define edges
     graph.add_edge(START, "process_request")

langgraph_plugin/graph_api/human_in_the_loop/approval_wait_condition/graph.py

@@ -14,6 +14,7 @@
 
 from langgraph.graph import END, START, StateGraph
 from temporalio import activity
+from temporalio.contrib.langgraph import activity_options
 from typing_extensions import TypedDict
 
 
@@ -190,15 +191,27 @@ def build_approval_graph() -> Any:
 
     graph = StateGraph(ApprovalState)
 
-    # Add nodes
-    graph.add_node("process_request", process_request)
+    # Add nodes with activity options
+    graph.add_node(
+        "process_request",
+        process_request,
+        metadata=activity_options(
+            start_to_close_timeout=timedelta(seconds=30),
+        ),
+    )
     # Mark request_approval as run_in_workflow - it can access Temporal operations
     graph.add_node(
         "request_approval",
         request_approval,
         metadata=temporal_node_metadata(run_in_workflow=True),
     )
-    graph.add_node("execute_action", execute_action)
+    graph.add_node(
+        "execute_action",
+        execute_action,
+        metadata=activity_options(
+            start_to_close_timeout=timedelta(seconds=30),
+        ),
+    )
 
     # Define edges
     graph.add_edge(START, "process_request")

langgraph_plugin/graph_api/plan_and_execute/graph.py

@@ -21,6 +21,7 @@
 """
 
 import os
+from datetime import timedelta
 from typing import Annotated, Any, Literal
 
 from langchain_core.messages import BaseMessage, HumanMessage, SystemMessage
@@ -31,6 +32,7 @@
 from langgraph.graph import END, START, StateGraph
 from langgraph.graph.message import add_messages
 from pydantic import BaseModel, Field
+from temporalio.contrib.langgraph import activity_options
 from typing_extensions import TypedDict
 
 from langchain.agents import create_agent
@@ -427,12 +429,37 @@ def respond(state: PlanExecuteState) -> dict[str, Any]:
     # Build the plan-and-execute graph
     workflow = StateGraph(PlanExecuteState)
 
-    # Add nodes
-    workflow.add_node("plan", create_plan)
+    # Add nodes with activity options
+    workflow.add_node(
+        "plan",
+        create_plan,
+        metadata=activity_options(
+            start_to_close_timeout=timedelta(minutes=2),
+        ),
+    )
+    # execute uses create_agent internally - configure via per_node_activity_options
     workflow.add_node("execute", execute_step)
-    workflow.add_node("evaluate", evaluate_progress)
-    workflow.add_node("replan", replan)
-    workflow.add_node("respond", respond)
+    workflow.add_node(
+        "evaluate",
+        evaluate_progress,
+        metadata=activity_options(
+            start_to_close_timeout=timedelta(seconds=30),
+        ),
+    )
+    workflow.add_node(
+        "replan",
+        replan,
+        metadata=activity_options(
+            start_to_close_timeout=timedelta(minutes=2),
+        ),
+    )
+    workflow.add_node(
+        "respond",
+        respond,
+        metadata=activity_options(
+            start_to_close_timeout=timedelta(minutes=1),
+        ),
+    )
 
     # Add edges
     workflow.add_edge(START, "plan")

langgraph_plugin/graph_api/react_agent/graph.py

@@ -35,6 +35,22 @@ def build_react_agent() -> Any:
     3. Observe: Feed tool results back to LLM
     4. Repeat until done
 
+    Activity Configuration:
+        Since create_agent() returns a pre-built graph, configure activity
+        options at the plugin level using per_node_activity_options:
+
+        ```python
+        from temporalio.contrib.langgraph import LangGraphPlugin, activity_options
+
+        plugin = LangGraphPlugin(
+            graphs={"react_agent": build_react_agent},
+            per_node_activity_options={
+                "agent": activity_options(start_to_close_timeout=timedelta(minutes=2)),
+                "tools": activity_options(start_to_close_timeout=timedelta(minutes=1)),
+            },
+        )
+        ```
+
     Returns:
         A compiled LangGraph that can be executed with ainvoke().
     """

langgraph_plugin/graph_api/reflection/graph.py

@@ -20,6 +20,7 @@
 """
 
 import os
+from datetime import timedelta
 from typing import Annotated, Any, Literal
 
 from langchain_core.messages import BaseMessage, HumanMessage
@@ -29,6 +30,7 @@
 from langgraph.graph import END, START, StateGraph
 from langgraph.graph.message import add_messages
 from pydantic import BaseModel, Field
+from temporalio.contrib.langgraph import activity_options
 from typing_extensions import TypedDict
 
 
@@ -307,11 +309,35 @@ def finalize(state: ReflectionState) -> dict[str, Any]:
     # Build the reflection graph
     workflow = StateGraph(ReflectionState)
 
-    # Add nodes
-    workflow.add_node("generate", generate)
-    workflow.add_node("reflect", reflect)
-    workflow.add_node("revise", revise)
-    workflow.add_node("finalize", finalize)
+    # Add nodes with activity options for LLM calls
+    workflow.add_node(
+        "generate",
+        generate,
+        metadata=activity_options(
+            start_to_close_timeout=timedelta(minutes=2),
+        ),
+    )
+    workflow.add_node(
+        "reflect",
+        reflect,
+        metadata=activity_options(
+            start_to_close_timeout=timedelta(minutes=2),
+        ),
+    )
+    workflow.add_node(
+        "revise",
+        revise,
+        metadata=activity_options(
+            start_to_close_timeout=timedelta(minutes=2),
+        ),
+    )
+    workflow.add_node(
+        "finalize",
+        finalize,
+        metadata=activity_options(
+            start_to_close_timeout=timedelta(seconds=30),
+        ),
+    )
 
     # Add edges
     workflow.add_edge(START, "generate")