graphlemon: auto-commit uncommitted changes for judgment-92eccdb1933c-main-checkout-drift

graphlemon
1 parent 98d86e47
Showing 2 changed files with 75 additions and 1 deletions
src/task_query.py
src/work_graph_plan.py
@@ -206,9 +206,10 @@ def get_task(conn, task_id):
     task["work_graph_runs"] = []
     for w in runs:
         nodes = _work_nodes_for_run(conn, w[0])
+        graph_manifest = json.loads(w[1]) if w[1] else None
         task["work_graph_runs"].append({
             "run_id": w[0],
-            "graph_manifest": json.loads(w[1]) if w[1] else None,
+            "graph_manifest": _display_graph_manifest(graph_manifest, nodes),
             "status": w[2], "started_at": w[3], "completed_at": w[4],
             # D (2026-08-06): both None for a normal run; both set when this
             # run was forked from a historical node (src/work_graph_fork.py).
@@ -29,6 +29,13 @@ import json
 import subprocess
 import uuid
  
+from src import execution_log, paths
+
+# node_id reserved for the synthetic work_node_execution _record_planning_node
+# creates below -- task_query.py matches on this exact string to recognize
+# "this run has a real planning node to display", so keep the two in sync.
+PLANNING_NODE_ID = "__planning__"
+
 GRAPH_MANIFEST_SCHEMA = {
     "type": "object",
     "required": ["nodes", "edges"],
@@ -571,6 +578,71 @@ def _normalize_graph_manifest(manifest, additional_valid_loop_back_target_ids=()
     return manifest
  
  
+def _record_planning_node(conn, run_id, task_id, org_node, prompt, raw_response, graph_manifest):
+    """Persists the planning call itself (the `claude --agent <org_node> -p
+    <prompt>` subprocess call in plan_work_graph() below, NOT any node it
+    planned) as a real, clickable work_node_execution -- previously this
+    call's own raw output was discarded the moment _extract_graph_manifest
+    pulled the JSON back out of it, and the call itself left no trace
+    anywhere the console renders (v_task_detail's to-do tree/DAG only ever
+    show the nodes a planning call PRODUCED, never the act of planning
+    itself). Deliberately does NOT touch work_graph_run.graph_manifest --
+    that column stays the pure, LLM-authored manifest run_graph()/fork/
+    append-mode all still execute and merge against unchanged; task_query.py
+    synthesizes a display-only node from THIS row (matched by node_id ==
+    PLANNING_NODE_ID) when building the console's API response instead, so
+    execution/fork/append logic never has to know this row exists.
+
+    Only called from the fresh (non-append) branch of plan_work_graph() --
+    one real "how was this run planned" entry per run is enough to answer
+    the question; Coder/Validator's own append_to_run_id planning calls
+    aren't given one (YAGNI until someone actually needs to inspect those
+    too)."""
+    project_id = conn.execute("SELECT project_id FROM task WHERE task_id = ?", (task_id,)).fetchone()[0]
+
+    # work_node_execution.skill_ref is a required FK to a real skill row.
+    # design-dynamic-work-graph is the actual Skill documenting this
+    # self-planning mechanism (skills/design-dynamic-work-graph/SKILL.md) --
+    # reused here rather than inventing a placeholder skill_id nothing else
+    # would ever reference.
+    skill_id = "design-dynamic-work-graph"
+    if conn.execute("SELECT 1 FROM skill WHERE skill_id = ?", (skill_id,)).fetchone() is None:
+        conn.execute(
+            "INSERT INTO skill (skill_id, owner_org_node, file_path, current_git_commit_sha, source, status) "
+            "VALUES (?, ?, ?, 'unknown', 'new', 'active')",
+            (skill_id, org_node, "skills/" + skill_id + "/"),
+        )
+
+    node_exec_id = str(uuid.uuid4())
+    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 (?, ?, ?, ?, ?, 'work_graph_plan.goal_text', 'work_graph_plan.graph_manifest', ?, ?, 'done')",
+        (
+            node_exec_id, run_id, PLANNING_NODE_ID, org_node, skill_id,
+            json.dumps({"prompt": prompt}), json.dumps({"graph_manifest": graph_manifest}),
+        ),
+    )
+
+    log_file_id = str(uuid.uuid4())
+    log_path = paths.log_file_path(project_id, task_id, run_id, node_exec_id)
+    conn.execute(
+        "INSERT INTO execution_log_file (log_file_id, node_exec_id, project_id, file_path, format, status) "
+        "VALUES (?, ?, ?, ?, 'jsonl', 'closed')",
+        (log_file_id, node_exec_id, project_id, log_path),
+    )
+    # execution_log.append_log does its own conn.commit() -- covers the two
+    # INSERTs above too, same connection/transaction.
+    execution_log.append_log(
+        conn, node_exec_id,
+        json.dumps({"event": "node_start", "org_node": org_node, "prompt": prompt}, ensure_ascii=False) + "\n"
+        + json.dumps(
+            {"event": "node_completed", "raw_response": raw_response, "graph_manifest": graph_manifest},
+            ensure_ascii=False,
+        ) + "\n",
+    )
+
+
 def plan_work_graph(conn, org_node, task_id, goal_text, target_folder_path, timeout=300, append_to_run_id=None):
     """Returns {"run_id", "graph_manifest", "new_node_ids"}. Creates one
     `work_graph_run` row (status='planning') -- moving it to 'running'/
@@ -672,6 +744,7 @@ def plan_work_graph(conn, org_node, task_id, goal_text, target_folder_path, time
             (run_id, task_id, json.dumps(new_manifest)),
         )
         conn.commit()
+        _record_planning_node(conn, run_id, task_id, org_node, prompt, payload.get("result", ""), new_manifest)
         return {"run_id": run_id, "graph_manifest": new_manifest, "new_node_ids": []}
  
     new_node_ids = [n["node_id"] for n in new_manifest["nodes"]]