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feat(gui): Implement selectable thinking monologs and fix UI regressions

- Implement [Pure]/[Read] toggle for AI thinking monologues to allow text selection/copying.
- Fix TypeError: render_thinking_trace() missing 'entry_index' argument.
- Fix [+] buttons in Discussion and Comms history by correctly updating window state registry.
- Remove ListClipper from Discussion and Comms panels to fix variable-height clipping issues.
- Increase clipping heights for large entries to improve visibility.
- Fix code block scroll snapping in Markdown helper by robustifying text synchronization.
This commit is contained in:
2026-06-01 19:20:33 -04:00
parent 4dc1eb1283
commit 9ea7d4efcc
4 changed files with 116 additions and 124 deletions
+1 -1
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@@ -278,5 +278,5 @@ This file tracks all major tracks for the project. Each track has its own detail
---
- [ ] **Track: Selectable Thinking Monologs**
- [~] **Track: Selectable Thinking Monologs**
*Link: [./tracks/selectable_thinking_monologs_20260601/](./tracks/selectable_thinking_monologs_20260601/)*
@@ -1,14 +1,14 @@
# Implementation Plan: Selectable Thinking Monologs
## Phase 1: UI Implementation
- [ ] Task: Update `render_thinking_trace` signature
- [ ] Modify `def render_thinking_trace(app: App, segments: list[dict], entry_index: int, is_standalone: bool = False)` to accept the parent `entry: dict`.
- [ ] Update all calls to `render_thinking_trace` in `src/gui_2.py` (e.g., in `render_discussion_entry` and `render_comms_history_panel`) to pass the appropriate `entry` object. For standalone traces where an entry dictionary might not exist, pass a dummy dict to hold the state.
- [ ] Task: Implement the UI Toggle
- [ ] Inside `render_thinking_trace`, below or next to the `imgui.collapsing_header`, add an `imgui.button` that toggles `entry.get("thinking_read_mode", True)`.
- [ ] Task: Implement Conditional Rendering
- [ ] If `thinking_read_mode` is `True` (Read mode), use `markdown_helper.render(content)` or `imgui.text_wrapped` for a clean reading view.
- [ ] If `thinking_read_mode` is `False` (Pure mode), use `render_selectable_label(app, f"think_text_...", content, multiline=True, height=-1)` to make the text selectable and copyable.
- [x] Task: Update `render_thinking_trace` signature
- [x] Modify `def render_thinking_trace(app: App, entry: dict, segments: list[dict], entry_index: int, is_standalone: bool = False)` to accept the parent `entry: dict`.
- [x] Update all calls to `render_thinking_trace` in `src/gui_2.py` (e.g., in `render_discussion_entry` and `render_comms_history_panel`) to pass the appropriate `entry` object. For standalone traces where an entry dictionary might not exist, pass a dummy dict to hold the state.
- [x] Task: Implement the UI Toggle
- [x] Inside `render_thinking_trace`, below or next to the `imgui.collapsing_header`, add an `imgui.button` that toggles `entry.get("thinking_read_mode", True)`.
- [x] Task: Implement Conditional Rendering
- [x] If `thinking_read_mode` is `True` (Read mode), use `markdown_helper.render(content)` or `imgui.text_wrapped` for a clean reading view.
- [x] If `thinking_read_mode` is `False` (Pure mode), use `render_selectable_label(app, f"think_text_...", content, multiline=True, height=-1)` to make the text selectable and copyable.
## Phase 2: Verification
- [ ] Task: Verification
+104 -112
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@@ -3424,7 +3424,7 @@ def render_discussion_entry(app: App, entry: dict, index: int) -> None:
with imscope.id(f"disc_{index}"):
collapsed, read_mode = entry.get("collapsed", False), entry.get("read_mode", False)
if imgui.button("+" if collapsed else "-"): entry["collapsed"] = not collapsed
imgui.same_line(); render_text_viewer(app, f"Entry #{index+1}", entry["content"]); imgui.same_line(); imgui.set_next_item_width(120)
imgui.same_line(); render_text_viewer(app, f"Entry #{index+1}", entry["content"], id_suffix=f"disc_btn_{index}"); imgui.same_line(); imgui.set_next_item_width(120)
if imgui.begin_combo("##role", entry["role"]):
for r in app.disc_roles:
if imgui.selectable(r, r == entry["role"])[0]: entry["role"] = r
@@ -3461,7 +3461,7 @@ def render_discussion_entry(app: App, entry: dict, index: int) -> None:
imgui.text_colored(vec4(160, 160, 150), preview)
if not collapsed:
thinking_segments, has_content = entry.get("thinking_segments", []), bool(entry.get("content", "").strip())
if thinking_segments: render_thinking_trace(app, thinking_segments, index, is_standalone=not has_content)
if thinking_segments: render_thinking_trace(app, entry, thinking_segments, index, is_standalone=not has_content)
if read_mode: render_discussion_entry_read_mode(app, entry, index)
else:
if not (bool(thinking_segments) and not has_content): ch, entry["content"] = imgui.input_text_multiline("##content", entry["content"], imgui.ImVec2(-1, 150))
@@ -3490,7 +3490,7 @@ def render_discussion_entry_read_mode(app: App, entry: dict, index: int) -> None
with theme.ai_text_style():
markdown_helper.render(content, context_id=f'disc_{index}')
else:
with imscope.child(f"read_content_{index}", size_y=150, flags=True):
with imscope.child(f"read_content_{index}", size_y=400, flags=True):
if app.ui_word_wrap: imgui.push_text_wrap_pos(imgui.get_content_region_avail().x)
last_idx = 0
for m_idx, match in enumerate(matches):
@@ -3650,82 +3650,78 @@ def render_comms_history_panel(app: App) -> None:
log_to_render = app._comms_log_cache
clipper = imgui.ListClipper()
clipper.begin(len(log_to_render))
while clipper.step():
for i in range(clipper.display_start, clipper.display_end):
entry = log_to_render[i]
imgui.push_id(f"comms_entry_{i}")
i_display = i + 1
ts = entry.get("ts", "00:00:00")
direction = entry.get("direction", "??")
kind = entry.get("kind", entry.get("type", "??"))
provider = entry.get("provider", "?")
model = entry.get("model", "?")
tier = entry.get("source_tier", "main")
payload = entry.get("payload", {})
if not payload and kind not in ("request", "response", "tool_call", "tool_result"):
payload = entry # legacy
for i, entry in enumerate(log_to_render):
imgui.push_id(f"comms_entry_{i}")
i_display = i + 1
ts = entry.get("ts", "00:00:00")
direction = entry.get("direction", "??")
kind = entry.get("kind", entry.get("type", "??"))
provider = entry.get("provider", "?")
model = entry.get("model", "?")
tier = entry.get("source_tier", "main")
payload = entry.get("payload", {})
if not payload and kind not in ("request", "response", "tool_call", "tool_result"):
payload = entry # legacy
# Row 1: #Idx TS DIR KIND Provider/Model [Tier]
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()
imgui.text_colored(vec4(255, 120, 120), f"[{ticket_id}]")
# Row 1: #Idx TS DIR KIND Provider/Model [Tier]
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()
d_col = DIR_COLORS.get(direction, C_VAL)
imgui.text_colored(d_col, direction); imgui.same_line()
k_col = KIND_COLORS.get(kind, C_VAL)
imgui.text_colored(k_col, kind); imgui.same_line()
imgui.text_colored(C_LBL, f"{provider}/{model}"); imgui.same_line()
imgui.text_colored(C_SUB, f"[{tier}]")
# 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}")
render_heavy_text(app, "message", payload.get("message", ""), idx_str)
if payload.get("system"):
render_heavy_text(app, "system", payload.get("system", ""), idx_str)
elif kind == "response":
r = payload.get("round", 0)
sr = payload.get("stop_reason", "STOP")
usage = payload.get("usage", {})
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: render_thinking_trace(app, [{"content": s.content, "marker": s.marker} for s in segments], i, is_standalone=not bool(parsed_response.strip()))
if parsed_response: render_heavy_text(app, "text", parsed_response, idx_str)
tcs = payload.get("tool_calls", [])
if tcs: render_heavy_text(app, "tool_calls", json.dumps(tcs, indent=1), idx_str)
elif kind == "tool_call": render_heavy_text(app, payload.get("name", "call"), payload.get("script") or json.dumps(payload.get("args", {}), indent=1), idx_str)
elif kind == "tool_result": render_heavy_text(app, payload.get("name", "result"), payload.get("output", ""), idx_str)
else: render_heavy_text(app, "data", str(payload), idx_str)
imgui.text_colored(C_SUB, f" ({latency:.2f}s)")
imgui.separator()
imgui.pop_id()
ticket_id = entry.get("mma_ticket_id")
if ticket_id:
imgui.same_line()
imgui.text_colored(vec4(255, 120, 120), f"[{ticket_id}]")
imgui.same_line()
d_col = DIR_COLORS.get(direction, C_VAL)
imgui.text_colored(d_col, direction); imgui.same_line()
k_col = KIND_COLORS.get(kind, C_VAL)
imgui.text_colored(k_col, kind); imgui.same_line()
imgui.text_colored(C_LBL, f"{provider}/{model}"); imgui.same_line()
imgui.text_colored(C_SUB, f"[{tier}]")
# 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}")
render_heavy_text(app, "message", payload.get("message", ""), idx_str)
if payload.get("system"):
render_heavy_text(app, "system", payload.get("system", ""), idx_str)
elif kind == "response":
r = payload.get("round", 0)
sr = payload.get("stop_reason", "STOP")
usage = payload.get("usage", {})
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: render_thinking_trace(app, payload, [{"content": s.content, "marker": s.marker} for s in segments], i, is_standalone=not bool(parsed_response.strip()))
if parsed_response: render_heavy_text(app, "text", parsed_response, idx_str)
tcs = payload.get("tool_calls", [])
if tcs: render_heavy_text(app, "tool_calls", json.dumps(tcs, indent=1), idx_str)
elif kind == "tool_call": render_heavy_text(app, payload.get("name", "call"), payload.get("script") or json.dumps(payload.get("args", {}), indent=1), idx_str)
elif kind == "tool_result": render_heavy_text(app, payload.get("name", "result"), payload.get("output", ""), idx_str)
else: render_heavy_text(app, "data", str(payload), idx_str)
imgui.separator()
imgui.pop_id()
if app._scroll_comms_to_bottom:
imgui.set_scroll_here_y(1.0)
@@ -3799,11 +3795,8 @@ def render_discussion_entries(app: App) -> None:
if tier_usage:
persona_name = tier_usage.get("persona")
if persona_name: display_entries = [e for e in app.disc_entries if e.get("role") == persona_name or e.get("role") == "User"]
clipper = imgui.ListClipper(); clipper.begin(len(display_entries))
while clipper.step():
for i in range(clipper.display_start, clipper.display_end):
if i < len(display_entries):
render_discussion_entry(app, display_entries[i], i)
for i, entry in enumerate(display_entries):
render_discussion_entry(app, display_entries[i], i)
if app._scroll_disc_to_bottom: imgui.set_scroll_here_y(1.0); app._scroll_disc_to_bottom = False
def render_discussion_entry_controls(app: App) -> None:
@@ -4077,7 +4070,7 @@ def render_response_panel(app: App) -> None:
with theme.ai_text_style():
segments, parsed_response = thinking_parser.parse_thinking_trace(app.ai_response)
if segments:
render_thinking_trace(app, [{"content": s.content, "marker": s.marker} for s in segments], 9999)
render_thinking_trace(app, {}, [{"content": s.content, "marker": s.marker} for s in segments], 9999)
markdown_helper.render(parsed_response, context_id="response")
imgui.separator()
@@ -4620,61 +4613,58 @@ def render_error_tint(app: App) -> None:
imgui.text_colored(imgui.ImVec4(1, 0, 0, 1), "HOT RELOAD ERROR")
imgui.text_wrapped(HotReloader.last_error or "Unknown error")
def render_text_viewer(app: App, label: str, content: str, text_type: str = 'text', force_open: bool = False) -> None:
if imgui.button("[+]##" + str(id(content))) or force_open:
def render_text_viewer(app: App, label: str, content: str, text_type: str = 'text', force_open: bool = False, id_suffix: str = "") -> None:
if imgui.button(f"[+]##{id_suffix or str(id(content))}") or force_open:
app.text_viewer_type = text_type
app.show_text_viewer = True
app.text_viewer_title = label
app.text_viewer_content = content
app.show_windows["Text Viewer"] = True
def render_heavy_text(app: App, label: str, content: str, id_suffix: str = "") -> None:
imgui.text_colored(C_LBL, f"{label}:")
imgui.same_line()
if imgui.button("[+]##" + label + id_suffix):
if imgui.button(f"[+]##{label}{id_suffix}"):
app.show_text_viewer = True
app.show_windows["Text Viewer"] = True
app.text_viewer_type = 'markdown' if label in ('message', 'text', 'content', 'system') else 'json' if label in ('tool_calls', 'data') else 'powershell' if label == 'script' else 'text'
app.text_viewer_title = label
app.text_viewer_content = content
imgui.same_line()
imgui.text_colored(C_LBL, f"{label}:"); imgui.same_line()
render_selectable_label(app, f"heavy_label_{label}_{id_suffix}", content[:60].replace("\n", " ") + ("..." if len(content)>60 else ""), color=C_VAL)
if not content:
imgui.text_disabled("(empty)")
return
is_md = label in ("message", "text", "content")
ctx_id = f"heavy_{label}_{id_suffix}"
with theme.ai_text_style():
if len(content) > COMMS_CLAMP_CHARS:
if content:
ctx_id = f"{label}_{id_suffix}"
is_md = label in ('message', 'text', 'content', 'system')
with imscope.indent():
if is_md:
imgui.begin_child(f"heavy_text_child_{label}_{id_suffix}", imgui.ImVec2(0, 180), True, imgui.WindowFlags_.always_vertical_scrollbar)
imgui.begin_child(f"heavy_text_child_{label}_{id_suffix}", imgui.ImVec2(0, 300), True, imgui.WindowFlags_.always_vertical_scrollbar)
markdown_helper.render(content, context_id=ctx_id)
imgui.end_child()
else:
imgui.input_text_multiline(f"##heavy_text_input_{label}_{id_suffix}", content, imgui.ImVec2(-1, 180), imgui.InputTextFlags_.read_only)
else:
if is_md:
markdown_helper.render(content, context_id=ctx_id)
else:
imgui.begin_child(f"heavy_text_child_{label}_{id_suffix}", imgui.ImVec2(0, 200), True, imgui.WindowFlags_.always_vertical_scrollbar)
if app.ui_word_wrap:
imgui.push_text_wrap_pos(imgui.get_content_region_avail().x)
imgui.text(content)
imgui.pop_text_wrap_pos()
with imscope.text_wrap(imgui.get_content_region_avail().x):
imgui.text(content)
else:
imgui.text(content)
imgui.end_child()
def render_thinking_trace(app: App, segments: list[dict], entry_index: int, is_standalone: bool = False) -> None:
def render_thinking_trace(app: App, entry: dict, segments: list[dict], entry_index: int, is_standalone: bool = False) -> None:
if not segments:
return
with imscope.style_color(imgui.Col_.child_bg, vec4(40, 35, 25, 180)), \
theme.ai_text_style():
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:
thinking_read_mode = entry.get("thinking_read_mode", True)
if imgui.button(f"[Pure]##think_pure_{entry_index}" if thinking_read_mode else f"[Read]##think_read_{entry_index}"):
entry["thinking_read_mode"] = not thinking_read_mode
imgui.same_line()
imgui.text_colored(vec4(180, 150, 80), "Selectable toggle")
h = 150 if is_standalone else 100
with imscope.child(f"thinking_content_{entry_index}", 0, h, True):
for idx, seg in enumerate(segments):
@@ -4682,13 +4672,15 @@ def render_thinking_trace(app: App, segments: list[dict], entry_index: int, is_s
marker = seg.get("marker", "thinking")
with imscope.id(f"think_{entry_index}_{idx}"):
imgui.text_colored(vec4(180, 150, 80), f"[{marker}]")
if app.ui_word_wrap:
with imscope.text_wrap(imgui.get_content_region_avail().x):
if thinking_read_mode:
if app.ui_word_wrap:
with imscope.text_wrap(imgui.get_content_region_avail().x):
imgui.text(content)
else:
imgui.text(content)
else:
imgui.text(content)
render_selectable_label(app, f"think_text_{entry_index}_{idx}", content, multiline=True, height=-1)
imgui.separator()
imgui.unindent()
def render_selectable_label(app: App, label: str, value: str, width: float = 0.0, multiline: bool = False, height: float = 0.0, color: Optional[imgui.ImVec4] = None) -> None:
+3 -3
View File
@@ -126,13 +126,13 @@ class MarkdownRenderer:
# Sync text and language
lang_id = self._lang_map.get(lang_tag, ed.TextEditor.LanguageDefinitionId.none)
target_text = code + "\n"
if editor.get_text() != target_text:
# Robust check to avoid re-setting text every frame (which resets scroll)
curr_text = editor.get_text().replace('\r\n', '\n').strip()
if curr_text != code.replace('\r\n', '\n').strip():
editor.set_text(code)
editor.set_language_definition(lang_id)
elif editor.get_language_definition_name().lower() != lang_tag:
# get_language_definition_name might not match exactly but good enough check
editor.set_language_definition(lang_id)
# Dynamic height calculation