[codex] Polish Lab TUI agent output

packages/prime/src/prime_cli/lab_setup.py

@@ -15,7 +15,7 @@
 from dataclasses import dataclass
 from importlib import metadata
 from pathlib import Path
-from typing import Any
+from typing import Any, Literal
 from urllib.error import HTTPError, URLError
 from urllib.request import urlopen
 
@@ -67,6 +67,17 @@
 _REPO_TREE_CACHE: dict[tuple[str, str, int], tuple[RepoTreeEntry, ...]] = {}
 
 Emit = Callable[[str], None]
+LabSyncProgressKind = Literal[
+    "started",
+    "lab_assets_prepared",
+    "agent_assets_prepared",
+    "agent_assets_skipped",
+    "templates_refreshed",
+    "guidance_refreshed",
+    "completed",
+    "failed",
+]
+LabSyncProgressEmit = Callable[["LabSyncProgressEvent"], None]
 Runner = Callable[[Sequence[str], Path, Emit], int]
 
 
@@ -113,6 +124,14 @@ class LabSyncResult:
     workspace: Path
 
 
+@dataclass(frozen=True)
+class LabSyncProgressEvent:
+    """One typed Lab sync progress milestone for renderers."""
+
+    kind: LabSyncProgressKind
+    workspace: Path
+
+
 @dataclass(frozen=True)
 class LabDoctorOptions:
     """Options for checking a Lab workspace."""
@@ -316,14 +335,21 @@ def run_lab_sync_service(
     *,
     workspace: Path,
     emit: Emit | None = None,
+    emit_progress: LabSyncProgressEmit | None = None,
 ) -> LabSyncResult:
     """Refresh Lab skills and local agent guidance."""
 
     workspace = workspace.expanduser().resolve()
     emit = emit or (lambda _text: None)
     try:
-        _run_lab_sync_steps(options, workspace=workspace, emit=emit)
+        _run_lab_sync_steps(
+            options,
+            workspace=workspace,
+            emit=emit,
+            emit_progress=emit_progress,
+        )
     except Exception as exc:
+        _emit_sync_progress(emit_progress, "failed", workspace)
         emit(f"Sync failed: {exc}\n")
         return LabSyncResult(exit_code=1, workspace=workspace)
     return LabSyncResult(exit_code=0, workspace=workspace)
@@ -381,37 +407,54 @@ def _run_lab_sync_steps(
     *,
     workspace: Path,
     emit: Emit,
+    emit_progress: LabSyncProgressEmit | None = None,
 ) -> None:
     workspace.mkdir(parents=True, exist_ok=True)
     (workspace / "configs").mkdir(exist_ok=True)
     (workspace / "environments").mkdir(exist_ok=True)
     emit(f"Syncing Lab assets in {workspace}\n")
+    _emit_sync_progress(emit_progress, "started", workspace)
     agents = _resolve_sync_agents(workspace, options.agents, no_agent=options.no_agent)
     guidance_agents = agents
     if not guidance_agents and options.no_agent:
         guidance_agents = _workspace_agents_from_metadata(workspace)
 
     managed_skill_names = _sync_prime_skills(emit)
     _prepare_workspace_skill_dir(workspace, managed_skill_names, emit)
+    _emit_sync_progress(emit_progress, "lab_assets_prepared", workspace)
     if agents:
         _prepare_agent_skill_dirs(workspace, agents, managed_skill_names, emit)
         _report_missing_agent_requirements(agents, emit)
         _prepare_agent_native_surfaces(workspace, agents, emit)
         _sync_lab_metadata(workspace, agents, setup_source="prime lab sync")
+        _emit_sync_progress(emit_progress, "agent_assets_prepared", workspace)
     else:
         reason = (
             "--no-agent"
             if options.no_agent
             else "no configured agent; pass --agent to configure one"
         )
         emit(f"Skipped coding-agent skill roots ({reason})\n")
+        _emit_sync_progress(emit_progress, "agent_assets_skipped", workspace)
     _sync_config_templates(workspace, emit)
+    _emit_sync_progress(emit_progress, "templates_refreshed", workspace)
 
     if not options.skip_docs:
         _sync_workspace_guidance(workspace, guidance_agents, emit, force=True)
         _write_lab_docs_index(workspace, guidance_agents)
+        _emit_sync_progress(emit_progress, "guidance_refreshed", workspace)
 
     emit("Lab sync completed\n")
+    _emit_sync_progress(emit_progress, "completed", workspace)
+
+
+def _emit_sync_progress(
+    emit_progress: LabSyncProgressEmit | None,
+    kind: LabSyncProgressKind,
+    workspace: Path,
+) -> None:
+    if emit_progress is not None:
+        emit_progress(LabSyncProgressEvent(kind=kind, workspace=workspace))
 
 
 def _sync_workspace_guidance(
@@ -854,14 +897,14 @@ def _managed_skill_manifest_check() -> LabDoctorCheck:
     skills = manifest.get("skills")
     if isinstance(skills, dict) and skills:
         return LabDoctorCheck(
-            name="Global Lab skill cache",
+            name="Global Lab asset cache",
             status="PASS",
-            message=f"{len(skills)} managed skill(s) installed.",
+            message=f"{len(skills)} managed asset(s) installed.",
         )
     return LabDoctorCheck(
-        name="Global Lab skill cache",
+        name="Global Lab asset cache",
         status="WARN",
-        message=f"Missing {_global_prime_skills_dir() / PRIME_SKILLS_MANIFEST}",
+        message="Missing local Lab asset cache.",
         remediation="Run prime lab sync.",
     )
 
@@ -886,9 +929,9 @@ def _workspace_managed_skills_check(workspace: Path) -> LabDoctorCheck:
     skill_names = _managed_skill_names_from_manifest()
     if not skill_names:
         return LabDoctorCheck(
-            name="Workspace Lab skills",
+            name="Workspace Lab assets",
             status="WARN",
-            message="No managed Lab skills are installed.",
+            message="No managed Lab assets are installed.",
             remediation="Run prime lab sync.",
         )
     skills_dir = workspace / WORKSPACE_SKILLS_DIR
@@ -899,14 +942,14 @@ def _workspace_managed_skills_check(workspace: Path) -> LabDoctorCheck:
     ]
     if not missing:
         return LabDoctorCheck(
-            name="Workspace Lab skills",
+            name="Workspace Lab assets",
             status="PASS",
-            message=f"{len(skill_names)} managed skill link(s) are present.",
+            message=f"{len(skill_names)} managed asset link(s) are present.",
         )
     return LabDoctorCheck(
-        name="Workspace Lab skills",
+        name="Workspace Lab assets",
         status="WARN",
-        message="Missing " + ", ".join(missing[:5]),
+        message="Missing managed Lab assets: " + ", ".join(missing[:5]),
         remediation="Run prime lab sync.",
     )
 
@@ -915,9 +958,9 @@ def _agent_managed_skills_check(label: str, agent_skill_dir: Path, agent: str) -
     skill_names = _managed_skill_names_from_manifest()
     if not skill_names:
         return LabDoctorCheck(
-            name=f"{label} skills",
+            name=f"{label} assets",
             status="WARN",
-            message="No managed Lab skills are installed.",
+            message="No managed Lab assets are installed.",
             remediation="Run prime lab sync.",
         )
     missing = [
@@ -928,14 +971,14 @@ def _agent_managed_skills_check(label: str, agent_skill_dir: Path, agent: str) -
     ]
     if not missing:
         return LabDoctorCheck(
-            name=f"{label} skills",
+            name=f"{label} assets",
             status="PASS",
-            message=f"{len(skill_names)} managed skill link(s) are present.",
+            message=f"{len(skill_names)} managed asset link(s) are present.",
         )
     return LabDoctorCheck(
-        name=f"{label} skills",
+        name=f"{label} assets",
         status="WARN",
-        message="Missing " + ", ".join(missing[:5]),
+        message="Missing managed Lab assets: " + ", ".join(missing[:5]),
         remediation=f"Run prime lab sync --agent {agent}.",
     )
 
@@ -1692,6 +1735,8 @@ def _print_lab_doctor_result(result: LabDoctorResult, console: Console) -> None:
     "LabSetupOptions",
     "LabSetupResult",
     "LabSyncOptions",
+    "LabSyncProgressEvent",
+    "LabSyncProgressKind",
     "LabSyncResult",
     "SUPPORTED_AGENTS",
     "parse_lab_doctor_args",

packages/prime/src/prime_lab_app/agent_cards.py

@@ -29,6 +29,7 @@
     build_agent_widget_model,
     widget_payload,
 )
+from .agent_widget_titles import config_picker_summary
 from .config_screen import ConfigBuildResult
 from .launch_runner import ConfigLaunchRunner, extract_training_log_follow_command
 from .palette import PRIMARY, STATUS_ERROR, STATUS_WARNING, SUCCESS
@@ -502,10 +503,14 @@ def _widget_card_heading(model: AgentWidgetModel) -> Group:
 def _widget_card_body(model: AgentWidgetModel) -> Group:
     payload = widget_payload(model.action)
     description = str(payload.get("description") or "").strip()
+    kind = str(payload.get("kind") or "").strip()
+    config_kind = str(payload.get("config_kind") or "").strip()
     table = Table.grid(padding=(0, 2))
     table.add_column(style="bold dim", no_wrap=True)
     table.add_column()
-    if config_path := str(payload.get("config_path") or "").strip():
+    if kind in {"config_editor", "run_launcher"} and config_kind:
+        table.add_row("Pickers", config_picker_summary(config_kind))
+    elif config_path := str(payload.get("config_path") or "").strip():
         table.add_row("Path", _short_path(config_path))
     if description:
         table.add_row("Summary", description)

packages/prime/src/prime_lab_app/agent_runtime.py

@@ -726,27 +726,27 @@ def _handle_session_update(self, params: dict[str, Any]) -> None:
             self._append_streaming_assistant_text(event.text)
             return
         if event.kind in {"tool_call", "tool_update"}:
-            self._record_acp_tool_event(event.title, event.status, event.text)
+            self._record_acp_tool_event(event.title, event.tool_kind, event.status, event.text)
             return
 
-    def _record_acp_tool_event(self, title: str, status: str, text: str) -> None:
+    def _record_acp_tool_event(
+        self,
+        title: str,
+        tool_kind: str,
+        status: str,
+        text: str,
+    ) -> None:
         title = title.strip()
+        tool_kind = tool_kind.strip()
         status = status.strip()
-        text = text.strip()
-        if not title and not text:
+        text = _clean_agent_output_text(text.strip())
+        if not text:
             return
         if text and _is_lab_widget_tool_result_text(text):
             return
         label = title or "Tool"
-        content = label if not text else f"{label}\n{text}"
+        content = f"{label}\n{text}"
         with self._lock:
-            if (
-                not text
-                and _is_lab_widget_tool_event_title(label)
-                and self._messages
-                and self._messages[-1].status == "widget"
-            ):
-                return
             if (
                 self._messages
                 and self._messages[-1].role == "system"
@@ -757,15 +757,15 @@ def _record_acp_tool_event(self, title: str, status: str, text: str) -> None:
                     "system",
                     content,
                     "tool",
-                    {"title": label, "tool_status": status},
+                    {"title": label, "tool_kind": tool_kind, "tool_status": status},
                 )
             else:
                 self._messages.append(
                     AgentChatMessage(
                         "system",
                         content,
                         "tool",
-                        {"title": label, "tool_status": status},
+                        {"title": label, "tool_kind": tool_kind, "tool_status": status},
                     )
                 )
             self._emit_messages_locked()
@@ -813,9 +813,12 @@ def _record_dynamic_tool_call(
         content: str,
         action: dict[str, Any] | None = None,
     ) -> None:
+        display_content = _dynamic_tool_chat_content(status, content, action)
+        if display_content is None:
+            return
         with self._lock:
             self._finish_latest_streaming_assistant_locked(fallback="")
-            self._messages.append(AgentChatMessage("system", content, status, action or {}))
+            self._messages.append(AgentChatMessage("system", display_content, status, action or {}))
             self._emit_messages_locked()
 
     def _record_codex_turn(self, result: dict[str, Any]) -> None:
@@ -1191,10 +1194,28 @@ def _is_chunk_message(value: Any) -> bool:
 def _clean_agent_output_text(text: str) -> str:
     if not text:
         return ""
-    cleaned = _ANSI_RE.sub("", text)
-    if cleaned != text and not cleaned.strip():
-        return ""
-    return cleaned
+    return _ANSI_RE.sub("", text)
+
+
+def _dynamic_tool_chat_content(
+    status: str,
+    content: str,
+    action: dict[str, Any] | None,
+) -> str | None:
+    if status == "tool":
+        return None
+    if status == "widget":
+        if isinstance(action, dict):
+            title = str(action.get("title") or "").strip()
+            if title:
+                return title
+            payload = action.get("payload")
+            if isinstance(payload, dict):
+                payload_title = str(payload.get("title") or "").strip()
+                if payload_title:
+                    return payload_title
+        return "Action ready"
+    return content
 
 
 def _is_lab_widget_tool_result_text(text: str) -> bool:
@@ -1233,11 +1254,6 @@ def _contains_lab_widget_tool_result(value: Any) -> bool:
     return False
 
 
-def _is_lab_widget_tool_event_title(value: str) -> bool:
-    normalized = value.strip().lower().replace("-", "_")
-    return normalized.startswith(("prime_lab_", "mcp_prime_lab_"))
-
-
 def _merge_stream_text(existing: str, delta: str) -> str:
     """Append streamed text while ignoring duplicate final snapshots."""
 

packages/prime/src/prime_lab_app/agent_widget_model.py

@@ -327,6 +327,9 @@ def _widget_field_specs(context: dict[str, Any] | None) -> tuple[AgentWidgetFiel
                 value = str(model_options[0][1])
             widget = "select"
             options = model_options
+        if config_kind == "eval" and name == "envs" and value:
+            widget = "select"
+            options = ((value, value),)
         fields.append(
             AgentWidgetFieldSpec(
                 name=name,

packages/prime/src/prime_lab_app/agent_widget_titles.py

@@ -10,3 +10,13 @@ def clean_widget_title(value: str) -> str:
         if lowered.startswith(prefix):
             return title[len(prefix) :].strip() or title
     return title
+
+
+def config_picker_summary(config_kind: str) -> str:
+    if config_kind == "eval":
+        return "Environment, model, examples, rollouts, tokens, concurrency"
+    if config_kind == "rl":
+        return "Environment, model, steps, rollouts, batch, tokens"
+    if config_kind == "gepa":
+        return "Environment, model"
+    return "Environment, model"

packages/prime/src/prime_lab_app/app.py

@@ -2169,7 +2169,7 @@ def _with_workspace_agent_choice(item: LabItem, workspace: Path, agent: str) ->
             key=item.key,
             section=item.section,
             title=item.title,
-            subtitle=f"{agent} · refresh templates, skills, docs, and local guidance",
+            subtitle=f"{agent} · refresh Lab assets and local guidance",
             status=item.status,
             status_style=item.status_style,
             metadata=_replace_metadata(