multi hitl with new hash pattern

libs/langgraph/langgraph/constants.py

@@ -102,6 +102,8 @@ CONF = cast(Literal["configurable"], sys.intern("configurable"))
 # key for the configurable dict in RunnableConfig
 NULL_TASK_ID = sys.intern("00000000-0000-0000-0000-000000000000")
 # the task_id to use for writes that are not associated with a task
+CONFIG_KEY_RESUME_MAP = sys.intern("__pregel_resume_map")
+# holds a mapping of task ns -> resume value for resuming tasks
 
 RESERVED = {
     TAG_HIDDEN,

libs/langgraph/langgraph/pregel/algo.py

@@ -40,6 +40,7 @@ from langgraph.constants import (
     CONFIG_KEY_CHECKPOINTER,
     CONFIG_KEY_PREVIOUS,
     CONFIG_KEY_READ,
+    CONFIG_KEY_RESUME_MAP,
     CONFIG_KEY_SCRATCHPAD,
     CONFIG_KEY_SEND,
     CONFIG_KEY_STORE,
@@ -594,6 +595,8 @@ def prepare_single_task(
                             config[CONF].get(CONFIG_KEY_SCRATCHPAD),
                             pending_writes,
                             task_id,
+                            xxh3_128_hexdigest(task_checkpoint_ns.encode()),
+                            config[CONF].get(CONFIG_KEY_RESUME_MAP),
                         ),
                     },
                 ),
@@ -704,6 +707,8 @@ def prepare_single_task(
                                 config[CONF].get(CONFIG_KEY_SCRATCHPAD),
                                 pending_writes,
                                 task_id,
+                                xxh3_128_hexdigest(task_checkpoint_ns.encode()),
+                                config[CONF].get(CONFIG_KEY_RESUME_MAP),
                             ),
                             CONFIG_KEY_PREVIOUS: checkpoint["channel_values"].get(
                                 PREVIOUS, None
@@ -830,6 +835,8 @@ def prepare_single_task(
                                     config[CONF].get(CONFIG_KEY_SCRATCHPAD),
                                     pending_writes,
                                     task_id,
+                                    xxh3_128_hexdigest(task_checkpoint_ns.encode()),
+                                    config[CONF].get(CONFIG_KEY_RESUME_MAP),
                                 ),
                                 CONFIG_KEY_PREVIOUS: checkpoint["channel_values"].get(
                                     PREVIOUS, None
@@ -881,6 +888,8 @@ def _scratchpad(
     parent_scratchpad: Optional[PregelScratchpad],
     pending_writes: list[PendingWrite],
     task_id: str,
+    namespace_hash: str,
+    resume_map: Optional[dict[str, Any]],
 ) -> PregelScratchpad:
     if len(pending_writes) > 0:
         # find global resume value
@@ -892,17 +901,24 @@ def _scratchpad(
             # None cannot be used as a resume value, because it would be difficult to
             # distinguish from missing when used over http
             null_resume_write = None
-        # find task-specific resume value
-        for w in pending_writes:
-            if w[0] == task_id and w[1] == RESUME:
-                task_resume_write = w[2]
-                if not isinstance(task_resume_write, list):
-                    task_resume_write = [task_resume_write]
-                break
+
+        # find namespace and task-specific resume value
+        if resume_map and namespace_hash in resume_map:
+            task_resume_write = resume_map[namespace_hash]
+            if not isinstance(task_resume_write, list):
+                task_resume_write = [task_resume_write]
         else:
-            task_resume_write = []
-        # clear var
-        del w
+            # find task-specific resume value
+            for w in pending_writes:
+                if w[0] == task_id and w[1] == RESUME:
+                    task_resume_write = w[2]
+                    if not isinstance(task_resume_write, list):
+                        task_resume_write = [task_resume_write]
+                    break
+            else:
+                task_resume_write = []
+            # clear var
+            del w
     else:
         null_resume_write = None
         task_resume_write = []

libs/langgraph/langgraph/pregel/loop.py

@@ -47,6 +47,7 @@ from langgraph.constants import (
     CONFIG_KEY_DEDUPE_TASKS,
     CONFIG_KEY_DELEGATE,
     CONFIG_KEY_ENSURE_LATEST,
+    CONFIG_KEY_RESUME_MAP,
     CONFIG_KEY_RESUMING,
     CONFIG_KEY_SCRATCHPAD,
     CONFIG_KEY_STREAM,
@@ -649,6 +650,8 @@ class PregelLoop(LoopProtocol):
 
         # map command to writes
         if isinstance(self.input, Command):
+            if self.input.resume_map:
+                self.config[CONF][CONFIG_KEY_RESUME_MAP] = self.input.resume_map
             if self.input.resume is not None and not self.checkpointer:
                 raise RuntimeError(
                     "Cannot use Command(resume=...) without checkpointer"
@@ -657,7 +660,7 @@ class PregelLoop(LoopProtocol):
             # group writes by task ID
             for tid, c, v in map_command(self.input, self.checkpoint_pending_writes):
                 writes[tid].append((c, v))
-            if not writes:
+            if not writes and not self.input.resume_map:
                 raise EmptyInputError("Received empty Command input")
             # save writes
             for tid, ws in writes.items():

libs/langgraph/langgraph/types.py

@@ -147,7 +147,7 @@ class Interrupt:
         """Generate a unique ID for the interrupt based on its namespace."""
         if self.ns is None:
             return "placeholder-id"
-        return xxh3_128_hexdigest("".join(self.ns).encode())
+        return xxh3_128_hexdigest("|".join(self.ns).encode())
 
 
 class StateUpdate(NamedTuple):
@@ -300,12 +300,14 @@ class Command(Generic[N], ToolOutputMixin):
             - sequence of node names to navigate to next
             - `Send` object (to execute a node with the input provided)
             - sequence of `Send` objects
+        resume_map: mapping of interrupt ids to resume values. To be used together with [`interrupt()`][langgraph.types.interrupt].
     """
 
     graph: Optional[str] = None
     update: Optional[Any] = None
     resume: Optional[Union[Any, dict[str, Any]]] = None
     goto: Union[Send, Sequence[Union[Send, str]], str] = ()
+    resume_map: Optional[dict[str, Any]] = None
 
     def __repr__(self) -> str:
         # get all non-None values