test_work_graph_fork.py
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"""D (2026-08-06) tests: work_graph_fork.py, mocked at the claude
subprocess boundary (CLAUDE.md Testing constraint) -- same pattern as
test_work_graph_orchestrate.py. Covers the requirements doc's acceptance
standards 1-3 (docs/done/work-graph-time-travel-debugging-requirements.md).
Run: python3 -m unittest src.test_work_graph_fork -v
"""
import json
import os
import tempfile
import unittest
from unittest.mock import patch
from src import org_node_trigger, schema, work_graph_fork
_BRD_PRD_SDD_BENCHMARK_MANIFEST = {
"nodes": [
{"node_id": "brd", "artifact_type": "brd", "depends_on": []},
{"node_id": "prd", "artifact_type": "prd", "depends_on": ["brd"]},
{"node_id": "sdd", "artifact_type": "sdd", "depends_on": ["prd"]},
{"node_id": "benchmark", "artifact_type": "benchmark", "depends_on": ["sdd"]},
],
"edges": [],
}
class ForkTestBase(unittest.TestCase):
def setUp(self):
self.home_tmp = tempfile.TemporaryDirectory()
self.addCleanup(self.home_tmp.cleanup)
self.old_graphlemon_home = os.environ.get("GRAPHLEMON_HOME")
os.environ["GRAPHLEMON_HOME"] = self.home_tmp.name
self.addCleanup(self._restore_graphlemon_home)
self.conn = schema.connect(":memory:", check_same_thread=False)
schema.create_schema(self.conn)
self.conn.execute(
"INSERT INTO project (project_id, name, target_folder_path, has_git_repo, status) "
"VALUES ('proj-1', 'P', '/tmp/proj-1', 1, 'active')"
)
self.conn.execute(
"INSERT INTO task (task_id, project_id, goal_text, task_type, status, assigned_org_node) "
"VALUES ('task-1', 'proj-1', '实现贪吃蛇游戏', 'goal', 'validating', 'planner')"
)
self.conn.execute(
"INSERT INTO skill (skill_id, owner_org_node, file_path, current_git_commit_sha, source, status) "
"VALUES ('planner-doc-writing', 'planner', 'skills/planner-doc-writing/', 'unknown', 'new', 'active')"
)
self.conn.commit()
def _restore_graphlemon_home(self):
if self.old_graphlemon_home is None:
os.environ.pop("GRAPHLEMON_HOME", None)
else:
os.environ["GRAPHLEMON_HOME"] = self.old_graphlemon_home
def tearDown(self):
self.conn.close()
def _seed_completed_run(self, run_id, org_node, graph_manifest, contents, status="done"):
"""Simulates an already-finished original run: a work_graph_run
row plus one 'done' work_node_execution row per node, each holding
contents[node_id] as its output_payload."""
self.conn.execute(
"INSERT INTO work_graph_run (run_id, task_id, graph_manifest, status) VALUES (?, 'task-1', ?, ?)",
(run_id, json.dumps(graph_manifest), status),
)
node_exec_ids = {}
for node in graph_manifest["nodes"]:
node_id = node["node_id"]
node_exec_id = run_id + "-" + node_id
node_exec_ids[node_id] = node_exec_id
self.conn.execute(
"INSERT INTO work_node_execution (node_exec_id, run_id, node_id, subagent_type, skill_ref, "
"input_schema_ref, output_schema_ref, input_payload, output_payload, status) "
"VALUES (?, ?, ?, ?, 'planner-doc-writing', 'in.json', 'out.json', ?, ?, 'done')",
(
node_exec_id, run_id, node_id, org_node,
json.dumps({"node_id": node_id}), json.dumps(contents[node_id]),
),
)
self.conn.commit()
return node_exec_ids
class ForkFromPrdAcceptanceCriterion1Test(ForkTestBase):
"""Acceptance standard 1: fork from PRD with different content, SDD and
Benchmark re-execute with the new PRD content, BRD is not re-executed."""
def test_downstream_nodes_reexecute_upstream_node_reused(self):
contents = {
"brd": {"content": "original brd"}, "prd": {"content": "original prd"},
"sdd": {"content": "original sdd"}, "benchmark": {"content": "original benchmark"},
}
node_exec_ids = self._seed_completed_run(
"run-orig", "planner", _BRD_PRD_SDD_BENCHMARK_MANIFEST, contents
)
execute_calls = []
def fake_trigger(org_node, prompt, cwd, output_schema, model=None, timeout=300):
execute_calls.append(prompt)
return {"content": "regenerated for " + prompt}
with patch.object(org_node_trigger, "trigger_org_node_structured", side_effect=fake_trigger):
result = work_graph_fork.fork_work_graph_run(
self.conn, node_exec_ids["prd"], {"content": "a completely different prd"}, "/tmp/proj-1",
)
# only SDD and Benchmark actually ran claude -p calls -- BRD and PRD did not.
self.assertEqual(len(execute_calls), 2)
outputs = result["outputs"]
self.assertEqual(outputs["brd"], {"content": "original brd"})
self.assertEqual(outputs["prd"], {"content": "a completely different prd"})
self.assertNotEqual(outputs["sdd"], {"content": "original sdd"})
self.assertNotEqual(outputs["benchmark"], {"content": "original benchmark"})
new_run_id = result["run_id"]
rows = {
r[0]: (r[1], json.loads(r[2]))
for r in self.conn.execute(
"SELECT node_id, status, output_payload FROM work_node_execution WHERE run_id = ?", (new_run_id,)
).fetchall()
}
self.assertEqual(rows["brd"], ("done", {"content": "original brd"}))
self.assertEqual(rows["prd"], ("done", {"content": "a completely different prd"}))
self.assertEqual(rows["sdd"][0], "done")
self.assertEqual(rows["benchmark"][0], "done")
run_row = self.conn.execute(
"SELECT status, parent_run_id, fork_of_node_exec_id FROM work_graph_run WHERE run_id = ?",
(new_run_id,),
).fetchone()
self.assertEqual(run_row, ("done", "run-orig", node_exec_ids["prd"]))
class ForkFromMixedShapeGraphTest(ForkTestBase):
"""Phase 2 §2.1.2 (2026-08-12) regression: a graph_manifest can now
genuinely mix Planner-shaped nodes ('artifact_type') and Coder-shaped
nodes ('task_prompt') side by side, once plan_work_graph(...,
append_to_run_id=...) appends Coder's self-planned nodes onto
Planner's original run. Forking from the artifact_type node must
still correctly reconstruct a build_prompt for the DOWNSTREAM
task_prompt node -- before this fix, _reconstruct_build_prompt
required the WHOLE graph to be one uniform shape and would have
raised ForkGraphShapeUnsupportedError here."""
def test_downstream_generic_node_reexecutes_after_forking_upstream_planner_node(self):
manifest = {
"nodes": [
{"node_id": "sdd", "artifact_type": "sdd", "depends_on": []},
{
"node_id": "impl", "depends_on": ["sdd"], "task_prompt": "implement per the sdd",
"promotes_to_artifact": {"artifact_type": "test_report"},
},
],
"edges": [],
}
contents = {"sdd": {"content": "original sdd"}, "impl": {"content": "original impl"}}
node_exec_ids = self._seed_completed_run("run-orig", "planner", manifest, contents)
execute_calls = []
def fake_trigger(org_node, prompt, cwd, output_schema, model=None, timeout=300):
execute_calls.append(prompt)
return {"content": "regenerated for " + prompt}
with patch.object(org_node_trigger, "trigger_org_node_structured", side_effect=fake_trigger):
result = work_graph_fork.fork_work_graph_run(
self.conn, node_exec_ids["sdd"], {"content": "a completely different sdd"}, "/tmp/proj-1",
)
# only "impl" (downstream of the fork point) genuinely re-ran.
self.assertEqual(len(execute_calls), 1)
outputs = result["outputs"]
self.assertEqual(outputs["sdd"], {"content": "a completely different sdd"})
self.assertNotEqual(outputs["impl"], {"content": "original impl"})
class OriginalRunUnaffectedTest(ForkTestBase):
"""Acceptance standard 2: the original run's records are completely
untouched by a fork."""
def test_original_run_and_nodes_unchanged_after_fork(self):
contents = {
"brd": {"content": "original brd"}, "prd": {"content": "original prd"},
"sdd": {"content": "original sdd"}, "benchmark": {"content": "original benchmark"},
}
node_exec_ids = self._seed_completed_run(
"run-orig", "planner", _BRD_PRD_SDD_BENCHMARK_MANIFEST, contents
)
before_run = self.conn.execute("SELECT * FROM work_graph_run WHERE run_id = 'run-orig'").fetchone()
before_nodes = self.conn.execute(
"SELECT * FROM work_node_execution WHERE run_id = 'run-orig' ORDER BY node_id"
).fetchall()
with patch.object(org_node_trigger, "trigger_org_node_structured", return_value={"content": "x"}):
work_graph_fork.fork_work_graph_run(
self.conn, node_exec_ids["prd"], {"content": "different"}, "/tmp/proj-1",
)
after_run = self.conn.execute("SELECT * FROM work_graph_run WHERE run_id = 'run-orig'").fetchone()
after_nodes = self.conn.execute(
"SELECT * FROM work_node_execution WHERE run_id = 'run-orig' ORDER BY node_id"
).fetchall()
self.assertEqual(before_run, after_run)
self.assertEqual(before_nodes, after_nodes)
class MultipleForksFromSameNodeTest(ForkTestBase):
"""Acceptance standard 3: the same historical node can be forked
multiple times, producing independent, separately-traceable branches."""
def test_two_forks_from_same_node_are_independent(self):
contents = {
"brd": {"content": "original brd"}, "prd": {"content": "original prd"},
"sdd": {"content": "original sdd"}, "benchmark": {"content": "original benchmark"},
}
node_exec_ids = self._seed_completed_run(
"run-orig", "planner", _BRD_PRD_SDD_BENCHMARK_MANIFEST, contents
)
with patch.object(org_node_trigger, "trigger_org_node_structured", return_value={"content": "branch-a"}):
result_a = work_graph_fork.fork_work_graph_run(
self.conn, node_exec_ids["prd"], {"content": "prd variant A"}, "/tmp/proj-1",
)
with patch.object(org_node_trigger, "trigger_org_node_structured", return_value={"content": "branch-b"}):
result_b = work_graph_fork.fork_work_graph_run(
self.conn, node_exec_ids["prd"], {"content": "prd variant B"}, "/tmp/proj-1",
)
self.assertNotEqual(result_a["run_id"], result_b["run_id"])
self.assertEqual(result_a["outputs"]["prd"], {"content": "prd variant A"})
self.assertEqual(result_b["outputs"]["prd"], {"content": "prd variant B"})
self.assertEqual(result_a["outputs"]["sdd"], {"content": "branch-a"})
self.assertEqual(result_b["outputs"]["sdd"], {"content": "branch-b"})
for run_id in (result_a["run_id"], result_b["run_id"]):
row = self.conn.execute(
"SELECT parent_run_id, fork_of_node_exec_id FROM work_graph_run WHERE run_id = ?", (run_id,)
).fetchone()
self.assertEqual(row, ("run-orig", node_exec_ids["prd"]))
class ForkValidationErrorsTest(ForkTestBase):
def test_forking_a_non_done_node_raises(self):
self.conn.execute(
"INSERT INTO work_graph_run (run_id, task_id, graph_manifest, status) "
"VALUES ('run-1', 'task-1', ?, 'running')",
(json.dumps(_BRD_PRD_SDD_BENCHMARK_MANIFEST),),
)
self.conn.execute(
"INSERT INTO work_node_execution (node_exec_id, run_id, node_id, subagent_type, skill_ref, "
"input_schema_ref, output_schema_ref, input_payload, status) "
"VALUES ('node-1', 'run-1', 'prd', 'planner', 'planner-doc-writing', 'in.json', 'out.json', '{}', 'running')"
)
self.conn.commit()
with self.assertRaises(work_graph_fork.ForkSourceNotDoneError):
work_graph_fork.fork_work_graph_run(self.conn, "node-1", {"content": "x"}, "/tmp/proj-1")
def test_forking_from_a_non_terminal_parent_run_raises(self):
contents = {"brd": {"content": "b"}, "prd": {"content": "p"}, "sdd": {"content": "s"}, "benchmark": {"content": "bm"}}
node_exec_ids = self._seed_completed_run(
"run-orig", "planner", _BRD_PRD_SDD_BENCHMARK_MANIFEST, contents, status="running",
)
with self.assertRaises(work_graph_fork.ForkParentRunNotTerminalError):
work_graph_fork.fork_work_graph_run(
self.conn, node_exec_ids["prd"], {"content": "x"}, "/tmp/proj-1",
)
def test_unsupported_graph_shape_raises(self):
manifest = {"nodes": [{"node_id": "a", "depends_on": []}, {"node_id": "b", "depends_on": ["a"]}], "edges": []}
node_exec_ids = self._seed_completed_run(
"run-orig", "coder", manifest, {"a": {"content": "x"}, "b": {"content": "y"}},
)
with self.assertRaises(work_graph_fork.ForkGraphShapeUnsupportedError):
work_graph_fork.fork_work_graph_run(
self.conn, node_exec_ids["a"], {"content": "z"}, "/tmp/proj-1",
)
class StartForkInBackgroundTest(unittest.TestCase):
"""Real threading (own connection per thread) -- needs a real file
db_path, not ':memory:' (a fresh ':memory:' connection per thread
would be a completely separate, empty database), same reasoning as
test_task_execution.py's own StartTaskExecutionInBackgroundTest."""
def setUp(self):
self.home_tmp = tempfile.TemporaryDirectory()
self.addCleanup(self.home_tmp.cleanup)
self.old_graphlemon_home = os.environ.get("GRAPHLEMON_HOME")
os.environ["GRAPHLEMON_HOME"] = self.home_tmp.name
self.addCleanup(self._restore_graphlemon_home)
self.tmp_db = tempfile.NamedTemporaryFile(suffix=".db", delete=False)
self.tmp_db.close()
self.db_path = self.tmp_db.name
self.addCleanup(lambda: os.path.exists(self.db_path) and os.remove(self.db_path))
conn = schema.connect(self.db_path)
schema.create_schema(conn)
conn.execute(
"INSERT INTO project (project_id, name, target_folder_path, has_git_repo, status) "
"VALUES ('proj-1', 'P', '/tmp/proj-1', 1, 'active')"
)
conn.execute(
"INSERT INTO task (task_id, project_id, goal_text, task_type, status, assigned_org_node) "
"VALUES ('task-1', 'proj-1', 'g', 'goal', 'validating', 'planner')"
)
conn.execute(
"INSERT INTO skill (skill_id, owner_org_node, file_path, current_git_commit_sha, source, status) "
"VALUES ('planner-doc-writing', 'planner', 'skills/planner-doc-writing/', 'unknown', 'new', 'active')"
)
conn.execute(
"INSERT INTO work_graph_run (run_id, task_id, graph_manifest, status) "
"VALUES ('run-orig', 'task-1', ?, 'done')",
(json.dumps(_BRD_PRD_SDD_BENCHMARK_MANIFEST),),
)
contents = {
"brd": {"content": "b"}, "prd": {"content": "p"}, "sdd": {"content": "s"}, "benchmark": {"content": "bm"},
}
for node in _BRD_PRD_SDD_BENCHMARK_MANIFEST["nodes"]:
node_id = node["node_id"]
conn.execute(
"INSERT INTO work_node_execution (node_exec_id, run_id, node_id, subagent_type, skill_ref, "
"input_schema_ref, output_schema_ref, input_payload, output_payload, status) "
"VALUES (?, 'run-orig', ?, 'planner', 'planner-doc-writing', 'in.json', 'out.json', ?, ?, 'done')",
("run-orig-" + node_id, node_id, json.dumps({"node_id": node_id}), json.dumps(contents[node_id])),
)
conn.commit()
conn.close()
def _restore_graphlemon_home(self):
if self.old_graphlemon_home is None:
os.environ.pop("GRAPHLEMON_HOME", None)
else:
os.environ["GRAPHLEMON_HOME"] = self.old_graphlemon_home
def test_returns_run_id_immediately_and_completes_in_background(self):
with patch.object(org_node_trigger, "trigger_org_node_structured", return_value={"content": "regenerated"}):
run_id, thread = work_graph_fork.start_fork_in_background(
self.db_path, "run-orig-prd", {"content": "new prd"}, "/tmp/proj-1",
)
self.assertTrue(run_id)
thread.join(timeout=10)
conn = schema.connect(self.db_path)
status = conn.execute("SELECT status FROM work_graph_run WHERE run_id = ?", (run_id,)).fetchone()[0]
sdd_output = conn.execute(
"SELECT output_payload FROM work_node_execution WHERE run_id = ? AND node_id = 'sdd'", (run_id,)
).fetchone()[0]
conn.close()
self.assertEqual(status, "done")
self.assertEqual(json.loads(sdd_output), {"content": "regenerated"})
class ForkOfLeafNodeTest(ForkTestBase):
"""Forking the last node in a chain has nothing downstream -- no real
execution needed, just the substituted output in a new run."""
def test_forking_leaf_node_needs_no_execution(self):
contents = {
"brd": {"content": "original brd"}, "prd": {"content": "original prd"},
"sdd": {"content": "original sdd"}, "benchmark": {"content": "original benchmark"},
}
node_exec_ids = self._seed_completed_run(
"run-orig", "planner", _BRD_PRD_SDD_BENCHMARK_MANIFEST, contents
)
with patch.object(org_node_trigger, "trigger_org_node_structured") as mock_trigger:
mock_trigger.side_effect = AssertionError("should not be called -- nothing downstream of benchmark")
result = work_graph_fork.fork_work_graph_run(
self.conn, node_exec_ids["benchmark"], {"content": "different benchmark"}, "/tmp/proj-1",
)
self.assertEqual(result["outputs"]["benchmark"], {"content": "different benchmark"})
if __name__ == "__main__":
unittest.main()