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5 Commits
f9364e173e
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3489b3c4b8
| Author | SHA1 | Date | |
|---|---|---|---|
| 3489b3c4b8 | |||
| 91949575a7 | |||
| b78682dfff | |||
| c3e0cb3243 | |||
| 8e02c1ecec |
@@ -46,6 +46,10 @@ For deep implementation details when planning or implementing tracks, consult `d
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- **Parallel Tool Execution:** Executes independent tool calls (e.g., parallel file reads) concurrently within a single agent turn using an asynchronous execution engine, significantly reducing end-to-end latency.
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- **Automated Tier 4 QA:** Integrates real-time error interception in the shell runner, automatically forwarding technical failures to cheap sub-agents for 20-word diagnostic summaries injected back into the worker history.
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- **Detailed History Management:** Rich discussion history with branching, timestamping, and specific git commit linkage per conversation.
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- **Advanced Log Management:** Optimizes log storage by offloading large data (AI-generated scripts and tool outputs) to unique files within the session directory, using compact `[REF:filename]` pointers in JSON-L logs to minimize token overhead during analysis.
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- **Full Session Restoration:** Allows users to load and reconstruct entire historical sessions from their log directories. Includes a dedicated, tinted **'Historical Replay' mode** that populates discussion history and provides a read-only view of prior agent activities.
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- **Dedicated Diagnostic Logging:** Consolidates transient system warnings and performance alerts into a separate **System Diagnostics** tab within the Log Management panel, ensuring the persistent Discussion History remains focused on high-signal content while providing deep visibility into runtime health.
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- **Improved MMA Observability:** Enhances sub-agent logging by injecting precise ticket IDs and descriptive roles into communication metadata, enabling granular filtering and tracking of parallel worker activities within the Comms History.
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- **In-Depth Toolset Access:** MCP-like file exploration, URL fetching, search, and dynamic context aggregation embedded within a multi-viewport Dear PyGui/ImGui interface.
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- **Integrated Workspace:** A consolidated Hub-based layout (Context, AI Settings, Discussion, Operations) designed for expert multi-monitor workflows.
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- **Session Analysis:** Ability to load and visualize historical session logs with a dedicated tinted "Prior Session" viewing mode.
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+2
-2
@@ -26,13 +26,13 @@ This file tracks all major tracks for the project. Each track has its own detail
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*Goal: Maximize internal state exposure and provide comprehensive control endpoints (worker spawn/kill, pipeline pause/resume, DAG mutation) via the Hook API. Implement WebSocket-based real-time event streaming.*
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5. [ ] **Track: Codebase Audit and Cleanup**
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*Link: [./tracks/codebase_audit_20260308/](./tracks/codebase_audit_20260308/)*
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*Link: [./tracks/codebase_audit_20260308/](./tracks/codebase_audit_20260308/)*
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---
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### GUI Overhauls & Visualizations
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1. [~] **Track: Advanced Log Management and Session Restoration**
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3. [x] **Track: Advanced Log Management and Session Restoration**
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*Link: [./tracks/log_session_overhaul_20260308/](./tracks/log_session_overhaul_20260308/)*
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*Goal: Centralize log management, improve session restoration reliability with full-UI replay mode, and optimize log size via external script/output referencing. Implement transient diagnostic logging for system warnings.*
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@@ -22,7 +22,7 @@
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- [ ] Task: Conductor - User Manual Verification 'Phase 2: Session-Level Restoration' (Protocol in workflow.md)
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## Phase 3: Diagnostic Log & Discussion Cleanup
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- [ ] Task: Clean up discussion history and implement Diagnostic Tab.
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- [x] Task: Clean up discussion history and implement Diagnostic Tab. 8e02c1e
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- [ ] Add `self.diagnostic_log` (a list of transient messages) to `AppController`.
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- [ ] Update `src/app_controller.py:_on_performance_alert` to append to `self.diagnostic_log` instead of `disc_entries`.
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- [ ] Update `src/ai_client.py` (and other areas) to redirect "SYSTEM WARNING" and similar performance-related messages to the diagnostic log via a new event type.
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@@ -30,9 +30,9 @@
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- [ ] Ensure `diagnostic_log` is NOT persisted to `manual_slop.toml` or restored during session loads.
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- [ ] Task: Conductor - User Manual Verification 'Phase 3: Diagnostic Log & Cleanup' (Protocol in workflow.md)
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## Phase 4: MMA Log Integration & Filtering
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- [ ] Task: Improve MMA log visibility and filtering.
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- [ ] Ensure MMA sub-agent `log_comms` calls include sufficient metadata (tier, role) for filtering.
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- [ ] Update `_render_comms_history_panel` in `src/gui_2.py` to ensure MMA logs are clearly distinct and correctly filtered based on existing UI toggles.
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- [ ] Task: Final end-to-end verification of session restoration and log management.
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## Phase 4: MMA Log Integration & Filtering [checkpoint: c3e0cb3]
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- [x] Task: Improve MMA log visibility and filtering. c3e0cb3
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- [x] Ensure MMA sub-agent `log_comms` calls include sufficient metadata (tier, role) for filtering.
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- [x] Update `_render_comms_history_panel` in `src/gui_2.py` to ensure MMA logs are clearly distinct and correctly filtered based on existing UI toggles.
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- [x] Task: Final end-to-end verification of session restoration and log management. c3e0cb3
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- [ ] Task: Conductor - User Manual Verification 'Phase 4: MMA Log Integration' (Protocol in workflow.md)
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@@ -297,6 +297,7 @@ class AppController:
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self._inject_mode: str = "skeleton"
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self._inject_preview: str = ""
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self._show_inject_modal: bool = False
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self.diagnostic_log: List[Dict[str, Any]] = []
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self._settable_fields: Dict[str, str] = {
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'ai_input': 'ui_ai_input',
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'project_git_dir': 'ui_project_git_dir',
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@@ -798,7 +799,6 @@ class AppController:
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"Tool Calls": False,
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"Theme": True,
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"Log Management": False,
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"Diagnostics": False,
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}
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saved = self.config.get("gui", {}).get("show_windows", {})
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self.show_windows = {k: saved.get(k, v) for k, v in _default_windows.items()}
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@@ -1212,12 +1212,10 @@ class AppController:
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self._api_event_queue.append({"type": event_name, "payload": payload})
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def _on_performance_alert(self, message: str) -> None:
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alert_text = f"[PERFORMANCE ALERT] {message}. Please consider optimizing recent changes or reducing load."
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with self._pending_history_adds_lock:
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self._pending_history_adds.append({
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"role": "System",
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"content": alert_text,
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"ts": project_manager.now_ts()
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self.diagnostic_log.append({
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"ts": project_manager.now_ts(),
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"message": message,
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"type": "performance"
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})
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def _confirm_and_run(self, script: str, base_dir: str, qa_callback: Optional[Callable[[str], str]] = None, patch_callback: Optional[Callable[[str, str], Optional[str]]] = None) -> Optional[str]:
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+100
-80
@@ -285,7 +285,7 @@ class App:
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self._flush_to_config()
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models.save_config(self.config)
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except Exception:
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pass # silent — don't disrupt the GUI loop
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pass # silent — don't disrupt the GUI loop
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# Sync pending comms
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with self._pending_comms_lock:
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if self._pending_comms:
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@@ -307,7 +307,7 @@ class App:
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else:
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log_raw = list(self._comms_log)
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if self.ui_focus_agent:
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self._comms_log_cache = [e for e in log_raw if e.get("source_tier") == self.ui_focus_agent]
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self._comms_log_cache = [e for e in log_raw if e.get("source_tier", "").startswith(self.ui_focus_agent)]
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else:
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self._comms_log_cache = log_raw
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self._comms_log_dirty = False
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@@ -315,7 +315,7 @@ class App:
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if self._tool_log_dirty:
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log_raw = list(self._tool_log)
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if self.ui_focus_agent:
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self._tool_log_cache = [e for e in log_raw if e.get("source_tier") == self.ui_focus_agent]
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self._tool_log_cache = [e for e in log_raw if e.get("source_tier", "").startswith(self.ui_focus_agent)]
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else:
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self._tool_log_cache = log_raw
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self._tool_log_dirty = False
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@@ -491,81 +491,7 @@ class App:
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if self.perf_profiling_enabled: self.perf_monitor.start_component("_render_log_management")
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self._render_log_management()
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if self.perf_profiling_enabled: self.perf_monitor.end_component("_render_log_management")
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if self.show_windows["Diagnostics"]:
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exp, opened = imgui.begin("Diagnostics", self.show_windows["Diagnostics"])
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self.show_windows["Diagnostics"] = bool(opened)
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if exp:
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metrics = self.perf_monitor.get_metrics()
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imgui.text("Performance Telemetry")
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imgui.same_line()
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_, self.perf_profiling_enabled = imgui.checkbox("Enable Profiling", self.perf_profiling_enabled)
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imgui.separator()
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if imgui.begin_table("perf_table", 3, imgui.TableFlags_.borders_inner_h):
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imgui.table_setup_column("Metric")
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imgui.table_setup_column("Value")
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imgui.table_setup_column("Graph")
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imgui.table_headers_row()
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# Core Metrics
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for label, key, format_str in [
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("FPS", "fps", "%.1f"),
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("Frame Time (ms)", "frame_time_ms", "%.2f"),
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("CPU %", "cpu_percent", "%.1f"),
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("Input Lag (ms)", "input_lag_ms", "%.1f")
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]:
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imgui.table_next_row()
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imgui.table_next_column()
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imgui.text(label)
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imgui.table_next_column()
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if key == "fps":
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avg_val = imgui.get_io().framerate
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else:
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avg_val = metrics.get(f"{key}_avg", metrics.get(key, 0.0))
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imgui.text(format_str % avg_val)
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imgui.table_next_column()
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self.perf_show_graphs.setdefault(key, False)
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_, self.perf_show_graphs[key] = imgui.checkbox(f"##g_{key}", self.perf_show_graphs[key])
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imgui.end_table()
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if self.perf_profiling_enabled:
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imgui.separator()
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imgui.text("Detailed Component Timings (Moving Average)")
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if imgui.begin_table("comp_timings", 3, imgui.TableFlags_.borders):
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imgui.table_setup_column("Component")
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imgui.table_setup_column("Avg (ms)")
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imgui.table_setup_column("Graph")
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imgui.table_headers_row()
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# Show all components found in metrics
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for key, val in metrics.items():
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if key.startswith("time_") and key.endswith("_ms") and not key.endswith("_avg"):
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comp_name = key[5:-3]
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avg_val = metrics.get(f"{key}_avg", val)
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imgui.table_next_row()
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imgui.table_next_column()
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imgui.text(comp_name)
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imgui.table_next_column()
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if avg_val > 10.0:
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imgui.text_colored(imgui.ImVec4(1.0, 0.2, 0.2, 1.0), f"{avg_val:.2f}")
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else:
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imgui.text(f"{avg_val:.2f}")
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imgui.table_next_column()
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self.perf_show_graphs.setdefault(comp_name, False)
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_, self.perf_show_graphs[comp_name] = imgui.checkbox(f"##g_{comp_name}", self.perf_show_graphs[comp_name])
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imgui.end_table()
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# Render all enabled graphs (core + components)
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imgui.separator()
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imgui.text("Performance Graphs")
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for key, show in self.perf_show_graphs.items():
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if show:
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imgui.text(f"History: {key}")
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hist_data = self.perf_monitor.get_history(key)
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if hist_data:
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imgui.plot_lines(f"##plot_{key}", np.array(hist_data, dtype=np.float32), graph_size=imgui.ImVec2(-1, 60))
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else:
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imgui.text_disabled(f"(no history data for {key})")
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imgui.end()
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self.perf_monitor.end_frame()
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# ---- Modals / Popups
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with self._pending_dialog_lock:
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@@ -1054,12 +980,11 @@ class App:
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imgui.end()
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return
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if imgui.begin_tab_bar("log_mgmt_tabs"):
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if imgui.begin_tab_item("Sessions")[0]:
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if self._log_registry is None:
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self._log_registry = log_registry.LogRegistry(str(paths.get_logs_dir() / "log_registry.toml"))
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else:
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# Refresh data occasionally or on demand? For now let's just use the cached object.
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# The LogRegistry object loads data into self.data upon __init__.
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# We might want a refresh button or to reload every few seconds.
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if imgui.button("Refresh Registry"):
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self._log_registry = log_registry.LogRegistry(str(paths.get_logs_dir() / "log_registry.toml"))
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imgui.same_line()
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@@ -1124,6 +1049,97 @@ class App:
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reason="Manually whitelisted"
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)
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imgui.end_table()
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imgui.end_tab_item()
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if imgui.begin_tab_item("System Diagnostics")[0]:
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metrics = self.perf_monitor.get_metrics()
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imgui.text("Performance Telemetry")
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imgui.same_line()
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_, self.perf_profiling_enabled = imgui.checkbox("Enable Profiling", self.perf_profiling_enabled)
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imgui.separator()
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if imgui.begin_table("perf_table", 3, imgui.TableFlags_.borders_inner_h):
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imgui.table_setup_column("Metric")
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imgui.table_setup_column("Value")
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imgui.table_setup_column("Graph")
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imgui.table_headers_row()
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for label, key, format_str in [
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("FPS", "fps", "%.1f"),
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("Frame Time (ms)", "frame_time_ms", "%.2f"),
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("CPU %", "cpu_percent", "%.1f"),
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("Input Lag (ms)", "input_lag_ms", "%.1f")
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]:
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imgui.table_next_row()
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imgui.table_next_column()
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imgui.text(label)
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imgui.table_next_column()
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if key == "fps":
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avg_val = imgui.get_io().framerate
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else:
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avg_val = metrics.get(f"{key}_avg", metrics.get(key, 0.0))
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imgui.text(format_str % avg_val)
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imgui.table_next_column()
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self.perf_show_graphs.setdefault(key, False)
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_, self.perf_show_graphs[key] = imgui.checkbox(f"##g_{key}", self.perf_show_graphs[key])
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imgui.end_table()
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if self.perf_profiling_enabled:
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imgui.separator()
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imgui.text("Detailed Component Timings (Moving Average)")
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if imgui.begin_table("comp_timings", 3, imgui.TableFlags_.borders):
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imgui.table_setup_column("Component")
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imgui.table_setup_column("Avg (ms)")
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imgui.table_setup_column("Graph")
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imgui.table_headers_row()
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for key, val in metrics.items():
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if key.startswith("time_") and key.endswith("_ms") and not key.endswith("_avg"):
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comp_name = key[5:-3]
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avg_val = metrics.get(f"{key}_avg", val)
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imgui.table_next_row()
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imgui.table_next_column()
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imgui.text(comp_name)
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imgui.table_next_column()
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if avg_val > 10.0:
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imgui.text_colored(imgui.ImVec4(1.0, 0.2, 0.2, 1.0), f"{avg_val:.2f}")
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else:
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imgui.text(f"{avg_val:.2f}")
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imgui.table_next_column()
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self.perf_show_graphs.setdefault(comp_name, False)
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_, self.perf_show_graphs[comp_name] = imgui.checkbox(f"##g_{comp_name}", self.perf_show_graphs[comp_name])
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imgui.end_table()
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imgui.separator()
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imgui.text("Performance Graphs")
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for key, show in self.perf_show_graphs.items():
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if show:
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imgui.text(f"History: {key}")
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hist_data = self.perf_monitor.get_history(key)
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if hist_data:
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import numpy as np
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imgui.plot_lines(f"##plot_{key}", np.array(hist_data, dtype=np.float32), graph_size=imgui.ImVec2(-1, 60))
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else:
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imgui.text_disabled(f"(no history data for {key})")
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imgui.separator()
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imgui.text("Diagnostic Log")
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if imgui.begin_table("diag_log_table", 3, imgui.TableFlags_.borders | imgui.TableFlags_.row_bg | imgui.TableFlags_.resizable):
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imgui.table_setup_column("Timestamp", imgui.TableColumnFlags_.width_fixed, 150)
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imgui.table_setup_column("Type", imgui.TableColumnFlags_.width_fixed, 100)
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imgui.table_setup_column("Message")
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imgui.table_headers_row()
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for entry in reversed(self.controller.diagnostic_log):
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imgui.table_next_row()
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imgui.table_next_column()
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imgui.text(entry.get("ts", ""))
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imgui.table_next_column()
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imgui.text(entry.get("type", ""))
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imgui.table_next_column()
|
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imgui.text_wrapped(entry.get("message", ""))
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||||
imgui.end_table()
|
||||
|
||||
imgui.end_tab_item()
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||||
imgui.end_tab_bar()
|
||||
|
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if self.perf_profiling_enabled: self.perf_monitor.end_component("_render_log_management")
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imgui.end()
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@@ -1852,6 +1868,10 @@ class App:
|
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imgui.text_colored(C_LBL, f"#{i_display}")
|
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imgui.same_line()
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imgui.text_colored(vec4(160, 160, 160), ts)
|
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ticket_id = entry.get("mma_ticket_id")
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if ticket_id:
|
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imgui.same_line()
|
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imgui.text_colored(vec4(255, 120, 120), f"[{ticket_id}]")
|
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imgui.same_line()
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d_col = DIR_COLORS.get(direction, C_VAL)
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imgui.text_colored(d_col, direction)
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||||
@@ -498,6 +498,7 @@ def run_worker_lifecycle(ticket: Ticket, context: WorkerContext, context_files:
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|
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old_comms_cb = ai_client.comms_log_callback
|
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def worker_comms_callback(entry: dict) -> None:
|
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entry["mma_ticket_id"] = ticket.id
|
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if event_queue:
|
||||
kind = entry.get("kind")
|
||||
payload = entry.get("payload", {})
|
||||
@@ -515,7 +516,7 @@ def run_worker_lifecycle(ticket: Ticket, context: WorkerContext, context_files:
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old_comms_cb(entry)
|
||||
|
||||
ai_client.comms_log_callback = worker_comms_callback
|
||||
ai_client.set_current_tier("Tier 3")
|
||||
ai_client.set_current_tier(f"Tier 3 (Worker): {ticket.id}")
|
||||
try:
|
||||
comms_baseline = len(ai_client.get_comms_log())
|
||||
response = ai_client.send(
|
||||
|
||||
Reference in New Issue
Block a user