refactor(aisidebar): restructure project and implement reasoning mode toggle
- Reorganize project structure and file locations - Add ReasoningController to manage model selection and reasoning mode - Update design and requirements for reasoning mode toggle - Implement model switching between Qwen3-4B-Instruct and Qwen3-4B-Thinking models - Remove deprecated files and consolidate project layout - Add new steering and specification documentation - Clean up and remove unnecessary files and directories - Prepare for enhanced AI sidebar functionality with more flexible model handling
This commit is contained in:
Melvin Ragusa
@@ -233,7 +233,11 @@ class ConversationArchive:
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```python
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class ReasoningController:
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"""Manages reasoning mode state and API parameters."""
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"""Manages reasoning mode state and model selection."""
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# Model names for reasoning toggle
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INSTRUCT_MODEL = "hf.co/unsloth/Qwen3-4B-Instruct-2507-GGUF:Q8_K_XL"
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THINKING_MODEL = "hf.co/unsloth/Qwen3-4B-Thinking-2507-GGUF:Q8_K_XL"
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def __init__(self):
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self._enabled = False
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@@ -245,8 +249,9 @@ class ReasoningController:
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def toggle(self) -> bool:
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"""Toggle reasoning mode and persist preference."""
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def get_chat_options(self) -> dict:
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"""Return Ollama API options for reasoning mode."""
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def get_model_name(self) -> str:
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"""Return the appropriate model name based on reasoning mode."""
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return self.THINKING_MODEL if self._enabled else self.INSTRUCT_MODEL
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```
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#### UI Components
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@@ -254,41 +259,35 @@ class ReasoningController:
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Add toggle button to header area:
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```python
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self._reasoning_toggle = Gtk.ToggleButton(label="🧠 Reasoning")
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self._reasoning_toggle.connect("toggled", self._on_reasoning_toggled)
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self._reasoning_toggle = widgets.Button(label="🧠 Reasoning: OFF")
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self._reasoning_toggle.connect("clicked", self._on_reasoning_toggled)
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```
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#### Ollama Integration
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When reasoning mode is enabled, pass additional options to Ollama:
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When reasoning mode is toggled, switch between models:
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```python
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# Standard mode
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ollama.chat(model=model, messages=messages)
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# Get model based on reasoning mode
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model = self._reasoning_controller.get_model_name()
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# Reasoning mode (model-dependent)
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ollama.chat(
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model=model,
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messages=messages,
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options={
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"temperature": 0.7,
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# Model-specific reasoning parameters
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}
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)
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# Use the selected model for chat
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ollama.chat(model=model, messages=messages)
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```
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#### Message Formatting
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When reasoning is enabled and model supports it:
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When using the thinking model:
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- Display thinking process in distinct style (italic, gray text)
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- Separate reasoning from final answer with visual divider
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- Use expandable/collapsible section for reasoning (optional)
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- Parse `<think>` tags from model output to extract reasoning content
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#### Persistence
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- Save reasoning preference to `~/.config/aisidebar/preferences.json`
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- Load preference on startup
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- Apply to all new conversations
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- Automatically switch models when preference changes
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## Data Models
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@@ -62,15 +62,15 @@ This document outlines the requirements for enhancing the AI sidebar module for
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### Requirement 5: Reasoning Mode Toggle
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**User Story:** As a user, I want to enable or disable the model's reasoning output, so that I can choose whether to see the thinking process or just the final answer based on my needs.
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**User Story:** As a user, I want to toggle between a reasoning model and an instruct model, so that I can choose whether to use a model that shows its thinking process or one that provides direct answers.
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#### Acceptance Criteria
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1. THE AI Sidebar SHALL provide a toggle button or control to enable reasoning mode
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2. WHEN reasoning mode is enabled, THE AI Sidebar SHALL request and display the model's thinking process before the final answer
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3. WHEN reasoning mode is disabled, THE AI Sidebar SHALL request and display only the final answer without intermediate reasoning
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1. THE AI Sidebar SHALL provide a toggle button or control to switch between reasoning and instruct models
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2. WHEN reasoning mode is enabled, THE AI Sidebar SHALL switch to the Qwen3-4B-Thinking model and display the model's thinking process
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3. WHEN reasoning mode is disabled, THE AI Sidebar SHALL switch to the Qwen3-4B-Instruct model for direct answers
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4. THE AI Sidebar SHALL persist the reasoning mode preference across conversation sessions
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5. THE AI Sidebar SHALL visually distinguish reasoning content from final answer content when reasoning mode is enabled
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5. THE AI Sidebar SHALL visually distinguish reasoning content from final answer content when using the thinking model
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### Requirement 6: Graceful Ollama Unavailability Handling
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@@ -1,19 +1,19 @@
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# Implementation Plan
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- [ ] 1. Implement streaming response infrastructure
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- [x] 1. Implement streaming response infrastructure
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- Create StreamingHandler class in new file `streaming_handler.py` with token buffering, UI update methods, and stream state management
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- Add `_handle_stream_token()` method to SidebarWindow that uses GLib.idle_add for thread-safe UI updates
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- Implement token buffering logic (accumulate 3-5 tokens before UI update) to reduce overhead
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- _Requirements: 1.1, 1.2, 1.3, 1.4_
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- [ ] 2. Integrate streaming into SidebarWindow
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- [x] 2. Integrate streaming into SidebarWindow
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- Modify `_request_response()` to use `ollama_client.stream_chat()` instead of blocking `chat()`
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- Update worker thread to iterate over stream and call `_handle_stream_token()` for each chunk
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- Add streaming state indicator (visual feedback during generation)
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- Handle stream errors and interruptions gracefully with try-except blocks
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- _Requirements: 1.1, 1.2, 1.3, 1.4_
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- [ ] 3. Replace single-line Entry with multi-line TextView
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- [x] 3. Replace single-line Entry with multi-line TextView
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- Replace `Gtk.Entry` with `Gtk.TextView` wrapped in `Gtk.ScrolledWindow` in `_build_ui()`
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- Configure text view with word wrapping, min height 40px, max height 200px
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- Implement key event controller to handle Enter (submit) vs Shift+Enter (newline)
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@@ -21,37 +21,37 @@
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- Update `_on_submit()` to extract text from TextView buffer instead of Entry
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- _Requirements: 2.1, 2.2, 2.3, 2.4_
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- [ ] 4. Create command processing system
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- [x] 4. Create command processing system
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- Create `command_processor.py` with CommandProcessor class
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- Implement command parsing logic with `is_command()` and `execute()` methods
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- Define CommandResult dataclass for structured command responses
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- Add command registry dictionary mapping command strings to handler methods
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- _Requirements: 3.1, 3.2, 3.3, 3.4, 3.5_
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- [ ] 5. Implement conversation management commands
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- [ ] 5.1 Implement `/new` and `/clear` commands
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- [x] 5. Implement conversation management commands
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- [x] 5.1 Implement `/new` and `/clear` commands
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- Add `_cmd_new_conversation()` method to save current conversation and reset to fresh state
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- Clear message list UI and show confirmation message
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- _Requirements: 3.1, 3.2_
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- [ ] 5.2 Implement `/models` command
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- [x] 5.2 Implement `/models` command
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- Add `_cmd_list_models()` method to query and display available models
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- Format model list with current model highlighted
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- _Requirements: 3.3_
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- [ ] 5.3 Implement `/model` command
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- [x] 5.3 Implement `/model` command
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- Add `_cmd_switch_model()` method to validate and switch active model
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- Update model label in header UI
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- _Requirements: 3.4_
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- [ ] 5.4 Integrate CommandProcessor into SidebarWindow
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- [x] 5.4 Integrate CommandProcessor into SidebarWindow
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- Add CommandProcessor instance to SidebarWindow initialization
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- Modify `_on_submit()` to check for commands before processing as user message
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- Display command results as system messages with distinct styling
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- _Requirements: 3.5_
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- [ ] 6. Implement conversation archive system
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- [ ] 6.1 Create ConversationArchive class
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- [x] 6. Implement conversation archive system
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- [x] 6.1 Create ConversationArchive class
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- Create `conversation_archive.py` with ConversationArchive class
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- Implement `list_conversations()` to scan storage directory and return metadata
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- Implement `archive_conversation()` to save with timestamp-based ID format
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@@ -59,60 +59,60 @@
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- Define ConversationMetadata dataclass
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- _Requirements: 4.1, 4.2_
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- [ ] 6.2 Implement conversation loading
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- [x] 6.2 Implement conversation loading
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- Add `load_conversation()` method to ConversationArchive
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- Handle JSON parsing errors and missing files gracefully
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- Return ConversationState compatible with existing ConversationManager
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- _Requirements: 4.4_
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- [ ] 6.3 Implement `/list` and `/resume` commands
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- [x] 6.3 Implement `/list` and `/resume` commands
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- Add `_cmd_list_conversations()` to display archived conversations with metadata
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- Add `_cmd_resume_conversation()` to load and display selected conversation
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- Update SidebarWindow to repopulate message list from loaded conversation
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- _Requirements: 4.3, 4.4, 4.5_
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- [ ] 7. Implement reasoning mode toggle
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- [ ] 7.1 Create ReasoningController class
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- [x] 7. Implement reasoning mode toggle
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- [x] 7.1 Create ReasoningController class
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- Create `reasoning_controller.py` with ReasoningController class
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- Implement preference persistence to `~/.config/aisidebar/preferences.json`
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- Add `toggle()`, `is_enabled()`, and `get_chat_options()` methods
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- Define PreferencesState dataclass
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- _Requirements: 5.4_
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- [ ] 7.2 Add reasoning toggle UI
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- [x] 7.2 Add reasoning toggle UI
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- Add ToggleButton to header area in `_build_ui()`
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- Connect toggle signal to `_on_reasoning_toggled()` callback
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- Update button state from persisted preference on startup
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- _Requirements: 5.1_
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- [ ] 7.3 Integrate reasoning mode with Ollama calls
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- [x] 7.3 Integrate reasoning mode with Ollama calls
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- Modify `_request_response()` to include reasoning options when enabled
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- Pass model-specific parameters via `get_chat_options()`
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- Handle both streaming and non-streaming modes with reasoning
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- _Requirements: 5.2, 5.3_
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- [ ] 7.4 Implement reasoning content formatting
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- [x] 7.4 Implement reasoning content formatting
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- Add visual distinction for reasoning content (italic, gray text, or expandable section)
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- Separate reasoning from final answer with visual divider
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- Update message rendering to handle reasoning metadata
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- _Requirements: 5.5_
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- [-] 8. Implement graceful Ollama unavailability handling
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- [ ] 8.1 Update OllamaClient initialization
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- [x] 8. Implement graceful Ollama unavailability handling
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- [x] 8.1 Update OllamaClient initialization
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- Modify `__init__()` to never raise exceptions during initialization
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- Add connection check that sets internal availability flag
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- Update `list_models()` to return empty list instead of raising on connection failure
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- Update `chat()` and `stream_chat()` to return error messages instead of raising
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- _Requirements: 6.1, 6.3, 6.5_
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- [ ] 8.2 Create OllamaAvailabilityMonitor
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- [x] 8.2 Create OllamaAvailabilityMonitor
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- Create `ollama_monitor.py` with OllamaAvailabilityMonitor class
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- Implement periodic availability checking using GLib.timeout_add (30s interval)
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- Add callback mechanism to notify UI of state changes
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- Ensure checks are non-blocking and don't impact UI responsiveness
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- _Requirements: 6.4_
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- [ ] 8.3 Update SidebarWindow for Ollama unavailability
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- [x] 8.3 Update SidebarWindow for Ollama unavailability
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- Initialize OllamaAvailabilityMonitor in SidebarWindow
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- Display "Ollama not running" status message when unavailable at startup
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- Update model label to show connection status
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@@ -120,7 +120,7 @@
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- Add callback to re-enable features when Ollama becomes available
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- _Requirements: 6.1, 6.2, 6.4_
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- [ ] 8.4 Add user-friendly error messages
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- [x] 8.4 Add user-friendly error messages
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- Display clear instructions when user tries to chat without Ollama
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- Show notification when Ollama connection is restored
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- Update all command handlers to check Ollama availability
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