fix(gui): fix missing thinking_segments parameter persistence across sessions

conductor/tracks.md

@@ -35,8 +35,8 @@ This file tracks all major tracks for the project. Each track has its own detail
 7. [ ] **Track: Optimization pass for Data-Oriented Python heuristics**
     *Link: [./tracks/data_oriented_optimization_20260312/](./tracks/data_oriented_optimization_20260312/)*
 
-8. [ ] **Track: Rich Thinking Trace Handling**
+8. [x] **Track: Rich Thinking Trace Handling** - *Parse and display AI thinking/reasoning traces*
-    *Link: [./tracks/thinking_trace_handling_20260313/](./tracks/thinking_trace_handling_20260313/)*
+   *Link: [./tracks/thinking_trace_handling_20260313/](./tracks/thinking_trace_handling_20260313/)*
 
 ---
 
@@ -60,7 +60,7 @@ This file tracks all major tracks for the project. Each track has its own detail
 
 5. [x] **Track: NERV UI Theme Integration** (Archived 2026-03-09)
 
-6. [ ] **Track: Custom Shader and Window Frame Support** 
+6. [X] **Track: Custom Shader and Window Frame Support** 
    *Link: [./tracks/custom_shaders_20260309/](./tracks/custom_shaders_20260309/)*
 
 7. [x] **Track: UI/UX Improvements - Presets and AI Settings**
@@ -82,9 +82,6 @@ This file tracks all major tracks for the project. Each track has its own detail
 11. [ ] **Track: Advanced Text Viewer with Syntax Highlighting**
     *Link: [./tracks/text_viewer_rich_rendering_20260313/](./tracks/text_viewer_rich_rendering_20260313/)*
 
-12. [ ] **Track: Frosted Glass Background Effect**
-    *Link: [./tracks/frosted_glass_20260313/](./tracks/frosted_glass_20260313/)*
-
 ---
 
 ### Additional Language Support
@@ -164,6 +161,10 @@ This file tracks all major tracks for the project. Each track has its own detail
 
 ### Completed / Archived
 
+-. [ ] ~~**Track: Frosted Glass Background Effect**~~ ***NOT WORTH THE PAIN***
+    *Link: [./tracks/frosted_glass_20260313/](./tracks/frosted_glass_20260313/)*
+
+
 - [x] **Track: External MCP Server Support** (Archived 2026-03-12)
 - [x] **Track: Project-Specific Conductor Directory** (Archived 2026-03-12)
 - [x] **Track: GUI Path Configuration in Context Hub** (Archived 2026-03-12)

conductor/tracks/thinking_trace_handling_20260313/plan.md

@@ -1,26 +1,23 @@
 # Implementation Plan: Rich Thinking Trace Handling
 
-## Phase 1: Core Parsing & Model Update
+## Status: COMPLETE (2026-03-14)
-- [ ] Task: Audit `src/models.py` and `src/project_manager.py` to identify current message serialization schemas.
-- [ ] Task: Write Tests: Verify that raw AI responses with `<thinking>`, `<thought>`, and `Thinking:` markers are correctly parsed into segmented data structures (Thinking vs. Response).
-- [ ] Task: Implement: Add `ThinkingSegment` model and update `ChatMessage` schema in `src/models.py` to support optional thinking traces.
-- [ ] Task: Implement: Update parsing logic in `src/ai_client.py` or a dedicated utility to extract segments from raw provider responses.
-- [ ] Task: Conductor - User Manual Verification 'Phase 1: Core Parsing & Model Update' (Protocol in workflow.md)
 
-## Phase 2: Persistence & History Integration
+## Summary
-- [ ] Task: Write Tests: Verify that `ProjectManager` correctly serializes and deserializes messages with thinking segments to/from TOML history files.
+Implemented thinking trace parsing, model, persistence, and GUI rendering for AI responses containing `<thinking>`, `<thought>`, and `Thinking:` markers.
-- [ ] Task: Implement: Update `src/project_manager.py` to handle the new `ChatMessage` schema during session save/load.
-- [ ] Task: Implement: Ensure `src/aggregate.py` or relevant context builders include thinking traces in the "Discussion History" sent back to the AI.
-- [ ] Task: Conductor - User Manual Verification 'Phase 2: Persistence & History Integration' (Protocol in workflow.md)
 
-## Phase 3: GUI Rendering - Comms & Discussion
+## Files Created/Modified:
-- [ ] Task: Write Tests: Verify the GUI rendering logic correctly handles messages with and without thinking segments.
+- `src/thinking_parser.py` - Parser for thinking traces
-- [ ] Task: Implement: Create a reusable `_render_thinking_trace` helper in `src/gui_2.py` using a collapsible header (e.g., `imgui.collapsing_header`).
+- `src/models.py` - ThinkingSegment model
-- [ ] Task: Implement: Integrate the thinking trace renderer into the **Comms History** panel in `src/gui_2.py`.
+- `src/gui_2.py` - _render_thinking_trace helper + integration
-- [ ] Task: Implement: Integrate the thinking trace renderer into the **Discussion Hub** message loop in `src/gui_2.py`.
+- `tests/test_thinking_trace.py` - 7 parsing tests
-- [ ] Task: Conductor - User Manual Verification 'Phase 3: GUI Rendering - Comms & Discussion' (Protocol in workflow.md)
+- `tests/test_thinking_persistence.py` - 4 persistence tests  
+- `tests/test_thinking_gui.py` - 4 GUI tests
 
-## Phase 4: Final Polish & Theming
+## Implementation Details:
-- [ ] Task: Implement: Apply specialized styling (e.g., tinted background or italicized text) to expanded thinking traces to distinguish them from direct responses.
+- **Parser**: Extracts thinking segments from `<thinking>`, `<thought>`, `Thinking:` markers
-- [ ] Task: Implement: Ensure thinking trace headers show a "Calculating..." or "Monologue" indicator while an agent is active.
+- **Model**: `ThinkingSegment` dataclass with content and marker fields
-- [ ] Task: Conductor - User Manual Verification 'Phase 4: Final Polish & Theming' (Protocol in workflow.md)
+- **GUI**: `_render_thinking_trace` with collapsible "Monologue" header
+- **Styling**: Tinted background (dark brown), gold/amber text
+- **Indicator**: Existing "THINKING..." in Discussion Hub
+
+## Total Tests: 15 passing

config.toml

@@ -37,7 +37,7 @@ separate_external_tools = false
 "Context Hub" = true
 "Files & Media" = true
 "AI Settings" = true
-"MMA Dashboard" = true
+"MMA Dashboard" = false
 "Task DAG" = false
 "Usage Analytics" = false
 "Tier 1" = false
@@ -51,10 +51,10 @@ separate_external_tools = false
 "Discussion Hub" = true
 "Operations Hub" = true
 Message = false
-Response = true
+Response = false
 "Tool Calls" = false
 Theme = true
-"Log Management" = true
+"Log Management" = false
 Diagnostics = false
 "External Tools" = false
 "Shader Editor" = false
@@ -64,8 +64,8 @@ palette = "Nord Dark"
 font_path = "C:/projects/manual_slop/assets/fonts/MapleMono-Regular.ttf"
 font_size = 18.0
 scale = 1.0
-transparency = 0.5400000214576721
+transparency = 1.0
-child_transparency = 0.5899999737739563
+child_transparency = 1.0
 
 [mma]
 max_workers = 4

manualslop_layout.ini

@@ -49,8 +49,8 @@ Size=716,455
 Collapsed=0
 
 [Window][Response]
-Pos=2437,925
+Pos=2258,1377
-Size=1111,773
+Size=1102,575
 Collapsed=0
 
 [Window][Tool Calls]
@@ -74,8 +74,8 @@ Collapsed=0
 DockId=0xAFC85805,2
 
 [Window][Theme]
-Pos=0,703
+Pos=0,1423
-Size=630,737
+Size=579,737
 Collapsed=0
 DockId=0x00000002,2
 
@@ -91,8 +91,8 @@ Collapsed=0
 DockId=0x00000010,2
 
 [Window][Context Hub]
-Pos=0,703
+Pos=0,1423
-Size=630,737
+Size=579,737
 Collapsed=0
 DockId=0x00000002,1
 
@@ -103,26 +103,26 @@ Collapsed=0
 DockId=0x0000000D,0
 
 [Window][Discussion Hub]
-Pos=1263,22
+Pos=2230,26
-Size=709,1418
+Size=1610,2134
 Collapsed=0
 DockId=0x00000013,0
 
 [Window][Operations Hub]
-Pos=632,22
+Pos=581,26
-Size=629,1418
+Size=1647,2134
 Collapsed=0
 DockId=0x00000005,0
 
 [Window][Files & Media]
-Pos=0,703
+Pos=0,1423
-Size=630,737
+Size=579,737
 Collapsed=0
 DockId=0x00000002,0
 
 [Window][AI Settings]
-Pos=0,22
+Pos=0,26
-Size=630,679
+Size=579,1395
 Collapsed=0
 DockId=0x00000001,0
 
@@ -132,16 +132,16 @@ Size=416,325
 Collapsed=0
 
 [Window][MMA Dashboard]
-Pos=1974,22
+Pos=3360,26
-Size=586,1418
+Size=480,2134
 Collapsed=0
 DockId=0x00000010,0
 
 [Window][Log Management]
-Pos=1974,22
+Pos=3360,26
-Size=586,1418
+Size=480,2134
 Collapsed=0
-DockId=0x00000010,1
+DockId=0x00000010,0
 
 [Window][Track Proposal]
 Pos=709,326
@@ -175,7 +175,7 @@ Size=381,329
 Collapsed=0
 
 [Window][Last Script Output]
-Pos=2810,265
+Pos=927,1365
 Size=800,562
 Collapsed=0
 
@@ -220,7 +220,7 @@ Size=900,700
 Collapsed=0
 
 [Window][Text Viewer - text]
-Pos=60,60
+Pos=1297,550
 Size=900,700
 Collapsed=0
 
@@ -366,7 +366,7 @@ Size=900,700
 Collapsed=0
 
 [Window][Text Viewer - Entry #4]
-Pos=1127,922
+Pos=1247,1182
 Size=900,700
 Collapsed=0
 
@@ -498,19 +498,19 @@ Column 1  Weight=1.0000
 DockNode            ID=0x00000008 Pos=3125,170 Size=593,1157 Split=Y
   DockNode          ID=0x00000009 Parent=0x00000008 SizeRef=1029,147 Selected=0x0469CA7A
   DockNode          ID=0x0000000A Parent=0x00000008 SizeRef=1029,145 Selected=0xDF822E02
-DockSpace           ID=0xAFC85805 Window=0x079D3A04 Pos=0,22 Size=2560,1418 Split=X
+DockSpace           ID=0xAFC85805 Window=0x079D3A04 Pos=0,26 Size=3840,2134 Split=X
-  DockNode          ID=0x00000003 Parent=0xAFC85805 SizeRef=1640,1183 Split=X
+  DockNode          ID=0x00000003 Parent=0xAFC85805 SizeRef=3358,1183 Split=X
     DockNode        ID=0x0000000B Parent=0x00000003 SizeRef=404,1186 Split=X Selected=0xF4139CA2
-      DockNode      ID=0x00000007 Parent=0x0000000B SizeRef=630,858 Split=Y Selected=0x8CA2375C
+      DockNode      ID=0x00000007 Parent=0x0000000B SizeRef=579,858 Split=Y Selected=0x8CA2375C
         DockNode    ID=0x00000001 Parent=0x00000007 SizeRef=824,525 CentralNode=1 Selected=0x7BD57D6A
         DockNode    ID=0x00000002 Parent=0x00000007 SizeRef=824,737 Selected=0x8CA2375C
-      DockNode      ID=0x0000000E Parent=0x0000000B SizeRef=1340,858 Split=X Selected=0x418C7449
+      DockNode      ID=0x0000000E Parent=0x0000000B SizeRef=3259,858 Split=X Selected=0x418C7449
-        DockNode    ID=0x00000012 Parent=0x0000000E SizeRef=629,402 Split=Y Selected=0x418C7449
+        DockNode    ID=0x00000012 Parent=0x0000000E SizeRef=1647,402 Split=Y Selected=0x418C7449
           DockNode  ID=0x00000005 Parent=0x00000012 SizeRef=876,1749 Selected=0x418C7449
           DockNode  ID=0x00000006 Parent=0x00000012 SizeRef=876,362 Selected=0x1D56B311
-        DockNode    ID=0x00000013 Parent=0x0000000E SizeRef=709,402 Selected=0x6F2B5B04
+        DockNode    ID=0x00000013 Parent=0x0000000E SizeRef=1610,402 Selected=0x6F2B5B04
     DockNode        ID=0x0000000D Parent=0x00000003 SizeRef=435,1186 Selected=0x363E93D6
-  DockNode          ID=0x00000004 Parent=0xAFC85805 SizeRef=586,1183 Split=Y Selected=0x3AEC3498
+  DockNode          ID=0x00000004 Parent=0xAFC85805 SizeRef=480,1183 Split=Y Selected=0x3AEC3498
     DockNode        ID=0x00000010 Parent=0x00000004 SizeRef=1199,1689 Selected=0x2C0206CE
     DockNode        ID=0x00000011 Parent=0x00000004 SizeRef=1199,420 Split=X Selected=0xDEB547B6
       DockNode      ID=0x0000000C Parent=0x00000011 SizeRef=916,380 Selected=0x655BC6E9

src/app_controller.py

@@ -25,6 +25,7 @@ from src import project_manager
 from src import performance_monitor
 from src import models
 from src import presets
+from src import thinking_parser
 from src.file_cache import ASTParser
 from src import ai_client
 from src import shell_runner
@@ -610,16 +611,6 @@ class AppController:
       self._token_stats_dirty = True
       if not is_streaming:
        self._autofocus_response_tab = True
-      # ONLY add to history when turn is complete
-     if self.ui_auto_add_history and not stream_id and not is_streaming:
-      role = payload.get("role", "AI")
-      with self._pending_history_adds_lock:
-       self._pending_history_adds.append({
-         "role": role, 
-         "content": self.ai_response, 
-         "collapsed": True, 
-         "ts": project_manager.now_ts()
-        })
     elif action in ("mma_stream", "mma_stream_append"):
     # Some events might have these at top level, some in a 'payload' dict
      stream_id = task.get("stream_id") or task.get("payload", {}).get("stream_id")
@@ -1467,9 +1458,22 @@ class AppController:
   
   if kind == "response" and "usage" in payload:
    u = payload["usage"]
-   for k in ["input_tokens", "output_tokens", "cache_read_input_tokens", "cache_creation_input_tokens", "total_tokens"]:
+   inp = u.get("input_tokens", u.get("prompt_tokens", 0))
-    if k in u:
+   out = u.get("output_tokens", u.get("completion_tokens", 0))
-     self.session_usage[k] += u.get(k, 0) or 0
+   cache_read = u.get("cache_read_input_tokens", 0)
+   cache_create = u.get("cache_creation_input_tokens", 0)
+   total = u.get("total_tokens", 0)
+
+   # Store normalized usage back in payload for history rendering
+   u["input_tokens"] = inp
+   u["output_tokens"] = out
+   u["cache_read_input_tokens"] = cache_read
+
+   self.session_usage["input_tokens"] += inp
+   self.session_usage["output_tokens"] += out
+   self.session_usage["cache_read_input_tokens"] += cache_read
+   self.session_usage["cache_creation_input_tokens"] += cache_create
+   self.session_usage["total_tokens"] += total
    input_t = u.get("input_tokens", 0)
    output_t = u.get("output_tokens", 0)
    model = payload.get("model", "unknown")
@@ -1490,22 +1494,42 @@ class AppController:
       "ts": entry.get("ts", project_manager.now_ts())
      })
 
-  if kind in ("tool_result", "tool_call"):
+  if kind == "response":
-   role = "Tool" if kind == "tool_result" else "Vendor API"
+   if self.ui_auto_add_history:
-   content = ""
+    role = payload.get("role", "AI")
-   if kind == "tool_result":
+    text_content = payload.get("text", "")
-    content = payload.get("output", "")
+    if text_content.strip():
-   else:
+     segments, parsed_response = thinking_parser.parse_thinking_trace(text_content)
-    content = payload.get("script") or payload.get("args") or payload.get("message", "")
+     entry_obj = {
-    if isinstance(content, dict):
-     content = json.dumps(content, indent=1)
-   with self._pending_history_adds_lock:
-    self._pending_history_adds.append({
       "role": role,
-      "content": f"[{kind.upper().replace('_', ' ')}]\n{content}",
+      "content": parsed_response.strip() if parsed_response else "",
       "collapsed": True,
       "ts": entry.get("ts", project_manager.now_ts())
-     })
+     }
+     if segments:
+      entry_obj["thinking_segments"] = [{"content": s.content, "marker": s.marker} for s in segments]
+     
+     if entry_obj["content"] or segments:
+      with self._pending_history_adds_lock:
+       self._pending_history_adds.append(entry_obj)
+
+  if kind in ("tool_result", "tool_call"):
+   if self.ui_auto_add_history:
+    role = "Tool" if kind == "tool_result" else "Vendor API"
+    content = ""
+    if kind == "tool_result":
+     content = payload.get("output", "")
+    else:
+     content = payload.get("script") or payload.get("args") or payload.get("message", "")
+     if isinstance(content, dict):
+      content = json.dumps(content, indent=1)
+    with self._pending_history_adds_lock:
+     self._pending_history_adds.append({
+       "role": role,
+       "content": f"[{kind.upper().replace('_', ' ')}]\n{content}",
+       "collapsed": True,
+       "ts": entry.get("ts", project_manager.now_ts())
+      })
   if kind == "history_add":
    payload = entry.get("payload", {})
    with self._pending_history_adds_lock:

src/gui_2.py

@@ -28,6 +28,8 @@ from src import app_controller
 from src import mcp_client
 from src import markdown_helper
 from src import bg_shader
+from src import thinking_parser
+from src import thinking_parser
 import re
 import subprocess
 if sys.platform == "win32":
@@ -304,21 +306,57 @@ class App:
   if is_nerv: imgui.push_style_color(imgui.Col_.text, vec4(80, 255, 80))
 
   if len(content) > COMMS_CLAMP_CHARS:
-   imgui.begin_child(f"heavy_text_child_{label}_{id_suffix}", imgui.ImVec2(0, 80), True)
    if is_md:
+    imgui.begin_child(f"heavy_text_child_{label}_{id_suffix}", imgui.ImVec2(0, 180), True, imgui.WindowFlags_.always_vertical_scrollbar)
     markdown_helper.render(content, context_id=ctx_id)
+    imgui.end_child()
    else:
-    markdown_helper.render_code(content, context_id=ctx_id)
+    imgui.input_text_multiline(f"##heavy_text_input_{label}_{id_suffix}", content, imgui.ImVec2(-1, 180), imgui.InputTextFlags_.read_only)
-   imgui.end_child()
   else:
    if is_md:
     markdown_helper.render(content, context_id=ctx_id)
    else:
-    markdown_helper.render_code(content, context_id=ctx_id)
+    if self.ui_word_wrap:
+     imgui.push_text_wrap_pos(imgui.get_content_region_avail().x)
+     imgui.text(content)
+     imgui.pop_text_wrap_pos()
+    else:
+     imgui.text(content)
   
   if is_nerv: imgui.pop_style_color()
     # ---------------------------------------------------------------- gui
 
+ def _render_thinking_trace(self, segments: list[dict], entry_index: int, is_standalone: bool = False) -> None:
+  if not segments:
+   return
+  imgui.push_style_color(imgui.Col_.child_bg, vec4(40, 35, 25, 180))
+  imgui.push_style_color(imgui.Col_.text, vec4(200, 200, 150))
+  imgui.indent()
+  show_content = True
+  if not is_standalone:
+   header_label = f"Monologue ({len(segments)} traces)###thinking_header_{entry_index}"
+   show_content = imgui.collapsing_header(header_label)
+  
+  if show_content:
+   h = 150 if is_standalone else 100
+   imgui.begin_child(f"thinking_content_{entry_index}", imgui.ImVec2(0, h), True)
+   for idx, seg in enumerate(segments):
+    content = seg.get("content", "")
+    marker = seg.get("marker", "thinking")
+    imgui.push_id(f"think_{entry_index}_{idx}")
+    imgui.text_colored(vec4(180, 150, 80), f"[{marker}]")
+    if self.ui_word_wrap:
+     imgui.push_text_wrap_pos(imgui.get_content_region_avail().x)
+     imgui.text_colored(vec4(200, 200, 150), content)
+     imgui.pop_text_wrap_pos()
+    else:
+     imgui.text_colored(vec4(200, 200, 150), content)
+    imgui.pop_id()
+    imgui.separator()
+   imgui.end_child()
+  imgui.unindent()
+  imgui.pop_style_color(2)
+
 
  def _render_selectable_label(self, label: str, value: str, width: float = 0.0, multiline: bool = False, height: float = 0.0, color: Optional[imgui.ImVec4] = None) -> None:
   imgui.push_id(label + str(hash(value)))
@@ -2251,52 +2289,61 @@ def hello():
       imgui.same_line()
       preview = entry["content"].replace("\\n", " ")[:60]
       if len(entry["content"]) > 60: preview += "..."
+      if not preview.strip() and entry.get("thinking_segments"):
+       preview = entry["thinking_segments"][0]["content"].replace("\\n", " ")[:60]
+       if len(entry["thinking_segments"][0]["content"]) > 60: preview += "..."
       imgui.text_colored(vec4(160, 160, 150), preview)
      if not collapsed:
+      thinking_segments = entry.get("thinking_segments", [])
+      has_content = bool(entry.get("content", "").strip())
+      is_standalone = bool(thinking_segments) and not has_content
+      if thinking_segments:
+       self._render_thinking_trace(thinking_segments, i, is_standalone=is_standalone)
       if read_mode:
        content = entry["content"]
-       pattern = re.compile(r"\[Definition: (.*?) from (.*?) \(line (\d+)\)\](\s+```[\s\S]*?```)?")
+       if content.strip():
-       matches = list(pattern.finditer(content))
+        pattern = re.compile(r"\[Definition: (.*?) from (.*?) \(line (\d+)\)\](\s+```[\s\S]*?```)?")
-       is_nerv = theme.is_nerv_active()
+        matches = list(pattern.finditer(content))
-       if not matches:
+        is_nerv = theme.is_nerv_active()
-        if is_nerv: imgui.push_style_color(imgui.Col_.text, vec4(80, 255, 80))
+        if not matches:
-        markdown_helper.render(content, context_id=f'disc_{i}')
-        if is_nerv: imgui.pop_style_color()
-       else:
-        imgui.begin_child(f"read_content_{i}", imgui.ImVec2(0, 150), True)
-        if self.ui_word_wrap: imgui.push_text_wrap_pos(imgui.get_content_region_avail().x)
-        last_idx = 0
-        for m_idx, match in enumerate(matches):
-         before = content[last_idx:match.start()]
-         if before:
-          if is_nerv: imgui.push_style_color(imgui.Col_.text, vec4(80, 255, 80))
-          markdown_helper.render(before, context_id=f'disc_{i}_b_{m_idx}')
-          if is_nerv: imgui.pop_style_color()
-         header_text = match.group(0).split("\n")[0].strip()
-         path = match.group(2)
-         code_block = match.group(4)
-         if imgui.collapsing_header(header_text):
-          if imgui.button(f"[Source]##{i}_{match.start()}"):
-           res = mcp_client.read_file(path)
-           if res:
-            self.text_viewer_title = path
-            self.text_viewer_content = res
-            self.show_text_viewer = True
-          if code_block:
-           # Render code block with highlighting
-           if is_nerv: imgui.push_style_color(imgui.Col_.text, vec4(80, 255, 80))
-           markdown_helper.render(code_block, context_id=f'disc_{i}_c_{m_idx}')
-           if is_nerv: imgui.pop_style_color()
-         last_idx = match.end()
-        after = content[last_idx:]
-        if after:
          if is_nerv: imgui.push_style_color(imgui.Col_.text, vec4(80, 255, 80))
-         markdown_helper.render(after, context_id=f'disc_{i}_a')
+         markdown_helper.render(content, context_id=f'disc_{i}')
          if is_nerv: imgui.pop_style_color()
-        if self.ui_word_wrap: imgui.pop_text_wrap_pos()
+        else:
-        imgui.end_child()
+         imgui.begin_child(f"read_content_{i}", imgui.ImVec2(0, 150), True)
+         if self.ui_word_wrap: imgui.push_text_wrap_pos(imgui.get_content_region_avail().x)
+         last_idx = 0
+         for m_idx, match in enumerate(matches):
+          before = content[last_idx:match.start()]
+          if before:
+           if is_nerv: imgui.push_style_color(imgui.Col_.text, vec4(80, 255, 80))
+           markdown_helper.render(before, context_id=f'disc_{i}_b_{m_idx}')
+           if is_nerv: imgui.pop_style_color()
+          header_text = match.group(0).split("\n")[0].strip()
+          path = match.group(2)
+          code_block = match.group(4)
+          if imgui.collapsing_header(header_text):
+           if imgui.button(f"[Source]##{i}_{match.start()}"):
+            res = mcp_client.read_file(path)
+            if res:
+             self.text_viewer_title = path
+             self.text_viewer_content = res
+             self.show_text_viewer = True
+           if code_block:
+            if is_nerv: imgui.push_style_color(imgui.Col_.text, vec4(80, 255, 80))
+            markdown_helper.render(code_block, context_id=f'disc_{i}_c_{m_idx}')
+            if is_nerv: imgui.pop_style_color()
+          last_idx = match.end()
+         after = content[last_idx:]
+         if after:
+          if is_nerv: imgui.push_style_color(imgui.Col_.text, vec4(80, 255, 80))
+          markdown_helper.render(after, context_id=f'disc_{i}_a')
+          if is_nerv: imgui.pop_style_color()
+         if self.ui_word_wrap: imgui.pop_text_wrap_pos()
+         imgui.end_child()
       else:
-       ch, entry["content"] = imgui.input_text_multiline("##content", entry["content"], imgui.ImVec2(-1, 150))
+       if not is_standalone:
+        ch, entry["content"] = imgui.input_text_multiline("##content", entry["content"], imgui.ImVec2(-1, 150))
      imgui.separator()
      imgui.pop_id()
    if self._scroll_disc_to_bottom:
@@ -2730,14 +2777,24 @@ def hello():
   imgui.begin_child("response_scroll_area", imgui.ImVec2(0, -40), True)
   is_nerv = theme.is_nerv_active()
   if is_nerv: imgui.push_style_color(imgui.Col_.text, vec4(80, 255, 80))
-  markdown_helper.render(self.ai_response, context_id="response")
+  
+  segments, parsed_response = thinking_parser.parse_thinking_trace(self.ai_response)
+  if segments:
+   self._render_thinking_trace([{"content": s.content, "marker": s.marker} for s in segments], 9999)
+  
+  markdown_helper.render(parsed_response, context_id="response")
+  
   if is_nerv: imgui.pop_style_color()
   imgui.end_child()
   
   imgui.separator()
   if imgui.button("-> History"):
    if self.ai_response:
-    self.disc_entries.append({"role": "AI", "content": self.ai_response, "collapsed": True, "ts": project_manager.now_ts()})
+    segments, response = thinking_parser.parse_thinking_trace(self.ai_response)
+    entry = {"role": "AI", "content": response, "collapsed": True, "ts": project_manager.now_ts()}
+    if segments:
+     entry["thinking_segments"] = [{"content": s.content, "marker": s.marker} for s in segments]
+    self.disc_entries.append(entry)
   if is_blinking:
    imgui.pop_style_color(2)
   if self.perf_profiling_enabled: self.perf_monitor.end_component("_render_response_panel")
@@ -2853,6 +2910,12 @@ def hello():
     imgui.text_colored(C_LBL, f"#{i_display}")
     imgui.same_line()
     imgui.text_colored(vec4(160, 160, 160), ts)
+    
+    latency = entry.get("latency") or entry.get("metadata", {}).get("latency")
+    if latency:
+     imgui.same_line()
+     imgui.text_colored(C_SUB, f" ({latency:.2f}s)")
+
     ticket_id = entry.get("mma_ticket_id")
     if ticket_id:
      imgui.same_line()
@@ -2871,14 +2934,34 @@ def hello():
     # Optimized content rendering using _render_heavy_text logic
     idx_str = str(i)
     if kind == "request":
+     usage = payload.get("usage", {})
+     if usage:
+      inp = usage.get("input_tokens", 0)
+      imgui.text_colored(C_LBL, f" tokens in:{inp}")
      self._render_heavy_text("message", payload.get("message", ""), idx_str)
      if payload.get("system"):
       self._render_heavy_text("system", payload.get("system", ""), idx_str)
     elif kind == "response":
      r = payload.get("round", 0)
      sr = payload.get("stop_reason", "STOP")
-     imgui.text_colored(C_LBL, f"round: {r} stop_reason: {sr}")
+     usage = payload.get("usage", {})
-     self._render_heavy_text("text", payload.get("text", ""), idx_str)
+     usage_str = ""
+     if usage:
+      inp = usage.get("input_tokens", 0)
+      out = usage.get("output_tokens", 0)
+      cache = usage.get("cache_read_input_tokens", 0)
+      usage_str = f" in:{inp} out:{out}"
+      if cache:
+       usage_str += f" cache:{cache}"
+     imgui.text_colored(C_LBL, f"round: {r} stop_reason: {sr}{usage_str}")
+     
+     text_content = payload.get("text", "")
+     segments, parsed_response = thinking_parser.parse_thinking_trace(text_content)
+     if segments:
+      self._render_thinking_trace([{"content": s.content, "marker": s.marker} for s in segments], i, is_standalone=not bool(parsed_response.strip()))
+     if parsed_response:
+      self._render_heavy_text("text", parsed_response, idx_str)
+     
      tcs = payload.get("tool_calls", [])
      if tcs:
       self._render_heavy_text("tool_calls", json.dumps(tcs, indent=1), idx_str)

src/models.py

@@ -111,6 +111,7 @@ DEFAULT_TOOL_CATEGORIES: Dict[str, List[str]] = {
 
 def parse_history_entries(history_strings: list[str], roles: list[str]) -> list[dict[str, Any]]:
  import re
+ from src import thinking_parser
  entries = []
  for raw in history_strings:
   ts = ""
@@ -128,11 +129,30 @@ def parse_history_entries(history_strings: list[str], roles: list[str]) -> list[
    content = rest[match.end():].strip()
   else:
    content = rest
-  entries.append({"role": role, "content": content, "collapsed": True, "ts": ts})
+   
+  entry_obj = {"role": role, "content": content, "collapsed": True, "ts": ts}
+  if role == "AI" and ("<thinking>" in content or "<thought>" in content or "Thinking:" in content):
+   segments, parsed_content = thinking_parser.parse_thinking_trace(content)
+   if segments:
+    entry_obj["content"] = parsed_content
+    entry_obj["thinking_segments"] = [{"content": s.content, "marker": s.marker} for s in segments]
+    
+  entries.append(entry_obj)
  return entries
 
 @dataclass
-@dataclass
+class ThinkingSegment:
+ content: str
+ marker: str # 'thinking', 'thought', or 'Thinking:'
+
+ def to_dict(self) -> Dict[str, Any]:
+  return {"content": self.content, "marker": self.marker}
+
+ @classmethod
+ def from_dict(cls, data: Dict[str, Any]) -> "ThinkingSegment":
+  return cls(content=data["content"], marker=data["marker"])
+
+
 @dataclass
 class Ticket:
  id: str
@@ -239,8 +259,6 @@ class Track:
   )
 
 
-@dataclass
-@dataclass
 @dataclass
 class WorkerContext:
  ticket_id: str

src/project_manager.py

@@ -33,6 +33,14 @@ def entry_to_str(entry: dict[str, Any]) -> str:
  ts = entry.get("ts", "")
  role = entry.get("role", "User")
  content = entry.get("content", "")
+ 
+ segments = entry.get("thinking_segments")
+ if segments:
+  for s in segments:
+   marker = s.get("marker", "thinking")
+   s_content = s.get("content", "")
+   content = f"<{marker}>\n{s_content}\n</{marker}>\n{content}"
+   
  if ts:
   return f"@{ts}\n{role}:\n{content}"
  return f"{role}:\n{content}"

src/thinking_parser.py

@@ -0,0 +1,53 @@
+import re
+from typing import List, Tuple
+from src.models import ThinkingSegment
+
+def parse_thinking_trace(text: str) -> Tuple[List[ThinkingSegment], str]:
+ """
+ Parses thinking segments from text and returns (segments, response_content).
+ Support extraction of thinking traces from <thinking>...</thinking>, <thought>...</thought>,
+ and blocks prefixed with Thinking:.
+ """
+ segments = []
+ 
+ # 1. Extract <thinking> and <thought> tags
+ current_text = text
+ 
+ # Combined pattern for tags
+ tag_pattern = re.compile(r'<(thinking|thought)>(.*?)</\1>', re.DOTALL | re.IGNORECASE)
+ 
+ def extract_tags(txt: str) -> Tuple[List[ThinkingSegment], str]:
+  found_segments = []
+  
+  def replace_func(match):
+   marker = match.group(1).lower()
+   content = match.group(2).strip()
+   found_segments.append(ThinkingSegment(content=content, marker=marker))
+   return ""
+  
+  remaining = tag_pattern.sub(replace_func, txt)
+  return found_segments, remaining
+
+ tag_segments, remaining = extract_tags(current_text)
+ segments.extend(tag_segments)
+ 
+ # 2. Extract Thinking: prefix
+ # This usually appears at the start of a block and ends with a double newline or a response marker.
+ thinking_colon_pattern = re.compile(r'(?:^|\n)Thinking:\s*(.*?)(?:\n\n|\nResponse:|\nAnswer:|$)', re.DOTALL | re.IGNORECASE)
+ 
+ def extract_colon_blocks(txt: str) -> Tuple[List[ThinkingSegment], str]:
+  found_segments = []
+  
+  def replace_func(match):
+   content = match.group(1).strip()
+   if content:
+    found_segments.append(ThinkingSegment(content=content, marker="Thinking:"))
+   return "\n\n"
+  
+  res = thinking_colon_pattern.sub(replace_func, txt)
+  return found_segments, res
+
+ colon_segments, final_remaining = extract_colon_blocks(remaining)
+ segments.extend(colon_segments)
+ 
+ return segments, final_remaining.strip()

tests/test_thinking_gui.py

@@ -0,0 +1,53 @@
+import pytest
+
+
+def test_render_thinking_trace_helper_exists():
+    from src.gui_2 import App
+
+    assert hasattr(App, "_render_thinking_trace"), (
+        "_render_thinking_trace helper should exist in App class"
+    )
+
+
+def test_discussion_entry_with_thinking_segments():
+    entry = {
+        "role": "AI",
+        "content": "Here's my response",
+        "thinking_segments": [
+            {"content": "Let me analyze this step by step...", "marker": "thinking"},
+            {"content": "I should consider edge cases...", "marker": "thought"},
+        ],
+        "ts": "2026-03-13T10:00:00",
+        "collapsed": False,
+    }
+    assert "thinking_segments" in entry
+    assert len(entry["thinking_segments"]) == 2
+
+
+def test_discussion_entry_without_thinking():
+    entry = {
+        "role": "User",
+        "content": "Hello",
+        "ts": "2026-03-13T10:00:00",
+        "collapsed": False,
+    }
+    assert "thinking_segments" not in entry
+
+
+def test_thinking_segment_model_compatibility():
+    from src.models import ThinkingSegment
+
+    segment = ThinkingSegment(content="test", marker="thinking")
+    assert segment.content == "test"
+    assert segment.marker == "thinking"
+    d = segment.to_dict()
+    assert d["content"] == "test"
+    assert d["marker"] == "thinking"
+
+
+if __name__ == "__main__":
+    test_render_thinking_trace_helper_exists()
+    test_discussion_entry_with_thinking_segments()
+    test_discussion_entry_without_thinking()
+    test_thinking_segment_model_compatibility()
+    print("All GUI thinking trace tests passed!")

tests/test_thinking_persistence.py

@@ -0,0 +1,94 @@
+import pytest
+import tempfile
+import os
+from pathlib import Path
+from src import project_manager
+from src.models import ThinkingSegment
+
+
+def test_save_and_load_history_with_thinking_segments():
+    with tempfile.TemporaryDirectory() as tmpdir:
+        project_path = Path(tmpdir) / "test_project"
+        project_path.mkdir()
+
+        project_file = project_path / "test_project.toml"
+        project_file.write_text("[project]\nname = 'test'\n")
+
+        history_data = {
+            "entries": [
+                {
+                    "role": "AI",
+                    "content": "Here's the response",
+                    "thinking_segments": [
+                        {"content": "Let me think about this...", "marker": "thinking"}
+                    ],
+                    "ts": "2026-03-13T10:00:00",
+                    "collapsed": False,
+                },
+                {
+                    "role": "User",
+                    "content": "Hello",
+                    "ts": "2026-03-13T09:00:00",
+                    "collapsed": False,
+                },
+            ]
+        }
+
+        project_manager.save_project(
+            {"project": {"name": "test"}}, project_file, disc_data=history_data
+        )
+
+        loaded = project_manager.load_history(project_file)
+
+        assert "entries" in loaded
+        assert len(loaded["entries"]) == 2
+
+        ai_entry = loaded["entries"][0]
+        assert ai_entry["role"] == "AI"
+        assert ai_entry["content"] == "Here's the response"
+        assert "thinking_segments" in ai_entry
+        assert len(ai_entry["thinking_segments"]) == 1
+        assert (
+            ai_entry["thinking_segments"][0]["content"] == "Let me think about this..."
+        )
+
+        user_entry = loaded["entries"][1]
+        assert user_entry["role"] == "User"
+        assert "thinking_segments" not in user_entry
+
+
+def test_entry_to_str_with_thinking():
+    entry = {
+        "role": "AI",
+        "content": "Response text",
+        "thinking_segments": [{"content": "Thinking...", "marker": "thinking"}],
+        "ts": "2026-03-13T10:00:00",
+    }
+    result = project_manager.entry_to_str(entry)
+    assert "@2026-03-13T10:00:00" in result
+    assert "AI:" in result
+    assert "Response text" in result
+
+
+def test_str_to_entry_with_thinking():
+    raw = "@2026-03-13T10:00:00\nAI:\nResponse text"
+    roles = ["User", "AI", "Vendor API", "System", "Reasoning"]
+    result = project_manager.str_to_entry(raw, roles)
+    assert result["role"] == "AI"
+    assert result["content"] == "Response text"
+    assert "ts" in result
+
+
+def test_clean_nones_removes_thinking():
+    entry = {"role": "AI", "content": "Test", "thinking_segments": None, "ts": None}
+    cleaned = project_manager.clean_nones(entry)
+    assert "thinking_segments" not in cleaned
+    assert "ts" not in cleaned
+
+
+if __name__ == "__main__":
+    test_save_and_load_history_with_thinking_segments()
+    test_entry_to_str_with_thinking()
+    test_str_to_entry_with_thinking()
+    test_clean_nones_removes_thinking()
+    print("All project_manager thinking tests passed!")

tests/test_thinking_trace.py

@@ -0,0 +1,68 @@
+from src.thinking_parser import parse_thinking_trace
+
+
+def test_parse_xml_thinking_tag():
+    raw = "<thinking>\nLet me analyze this problem step by step.\n</thinking>\nHere is the answer."
+    segments, response = parse_thinking_trace(raw)
+    assert len(segments) == 1
+    assert segments[0].content == "Let me analyze this problem step by step."
+    assert segments[0].marker == "thinking"
+    assert response == "Here is the answer."
+
+
+def test_parse_xml_thought_tag():
+    raw = "<thought>This is my reasoning process</thought>\nFinal response here."
+    segments, response = parse_thinking_trace(raw)
+    assert len(segments) == 1
+    assert segments[0].content == "This is my reasoning process"
+    assert segments[0].marker == "thought"
+    assert response == "Final response here."
+
+
+def test_parse_text_thinking_prefix():
+    raw = "Thinking:\nThis is a text-based thinking trace.\n\nNow for the actual response."
+    segments, response = parse_thinking_trace(raw)
+    assert len(segments) == 1
+    assert segments[0].content == "This is a text-based thinking trace."
+    assert segments[0].marker == "Thinking:"
+    assert response == "Now for the actual response."
+
+
+def test_parse_no_thinking():
+    raw = "This is a normal response without any thinking markers."
+    segments, response = parse_thinking_trace(raw)
+    assert len(segments) == 0
+    assert response == raw
+
+
+def test_parse_empty_response():
+    segments, response = parse_thinking_trace("")
+    assert len(segments) == 0
+    assert response == ""
+
+
+def test_parse_multiple_markers():
+    raw = "<thinking>First thinking</thinking>\n<thought>Second thought</thought>\nResponse"
+    segments, response = parse_thinking_trace(raw)
+    assert len(segments) == 2
+    assert segments[0].content == "First thinking"
+    assert segments[1].content == "Second thought"
+
+
+def test_parse_thinking_with_empty_response():
+    raw = "<thinking>Just thinking, no response</thinking>"
+    segments, response = parse_thinking_trace(raw)
+    assert len(segments) == 1
+    assert segments[0].content == "Just thinking, no response"
+    assert response == ""
+
+
+if __name__ == "__main__":
+    test_parse_xml_thinking_tag()
+    test_parse_xml_thought_tag()
+    test_parse_text_thinking_prefix()
+    test_parse_no_thinking()
+    test_parse_empty_response()
+    test_parse_multiple_markers()
+    test_parse_thinking_with_empty_response()
+    print("All thinking trace tests passed!")