forked from genewildish/Mainline
feat(integration): Complete feature rewrite with pipeline architecture, effects system, and display improvements
Major changes: - Pipeline architecture with capability-based dependency resolution - Effects plugin system with performance monitoring - Display abstraction with multiple backends (terminal, null, websocket) - Camera system for viewport scrolling - Sensor framework for real-time input - Command-and-control system via ntfy - WebSocket display backend for browser clients - Comprehensive test suite and documentation Issue #48: ADR for preset scripting language included This commit consolidates 110 individual commits into a single feature integration that can be reviewed and tested before further refinement.
This commit is contained in:
97
.opencode/skills/mainline-architecture/SKILL.md
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97
.opencode/skills/mainline-architecture/SKILL.md
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---
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name: mainline-architecture
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description: Pipeline stages, capability resolution, and core architecture patterns
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compatibility: opencode
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metadata:
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audience: developers
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source_type: codebase
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---
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## What This Skill Covers
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This skill covers Mainline's pipeline architecture - the Stage-based system for dependency resolution, data flow, and component composition.
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## Key Concepts
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### Stage Class (engine/pipeline/core.py)
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The `Stage` ABC is the foundation. All pipeline components inherit from it:
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```python
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class Stage(ABC):
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name: str
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category: str # "source", "effect", "overlay", "display", "camera"
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optional: bool = False
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@property
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def capabilities(self) -> set[str]:
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"""What this stage provides (e.g., 'source.headlines')"""
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return set()
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@property
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def dependencies(self) -> set[str]:
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"""What this stage needs (e.g., {'source'})"""
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return set()
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```
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### Capability-Based Dependencies
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The Pipeline resolves dependencies using **prefix matching**:
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- `"source"` matches `"source.headlines"`, `"source.poetry"`, etc.
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- `"camera.state"` matches the camera state capability
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- This allows flexible composition without hardcoding specific stage names
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### Minimum Capabilities
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The pipeline requires these minimum capabilities to function:
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- `"source"` - Data source capability
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- `"render.output"` - Rendered content capability
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- `"display.output"` - Display output capability
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- `"camera.state"` - Camera state for viewport filtering
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These are automatically injected if missing (auto-injection).
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### DataType Enum
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PureData-style data types for inlet/outlet validation:
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- `SOURCE_ITEMS`: List[SourceItem] - raw items from sources
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- `ITEM_TUPLES`: List[tuple] - (title, source, timestamp) tuples
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- `TEXT_BUFFER`: List[str] - rendered ANSI buffer
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- `RAW_TEXT`: str - raw text strings
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- `PIL_IMAGE`: PIL Image object
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### Pipeline Execution
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The Pipeline (engine/pipeline/controller.py):
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1. Collects all stages from StageRegistry
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2. Resolves dependencies using prefix matching
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3. Executes stages in dependency order
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4. Handles errors for non-optional stages
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### Canvas & Camera
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- **Canvas** (`engine/canvas.py`): 2D rendering surface with dirty region tracking
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- **Camera** (`engine/camera.py`): Viewport controller for scrolling content
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Canvas tracks dirty regions automatically when content is written via `put_region`, `put_text`, `fill`, enabling partial buffer updates.
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## Adding New Stages
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1. Create a class inheriting from `Stage`
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2. Define `capabilities` and `dependencies` properties
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3. Implement required abstract methods
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4. Register in StageRegistry or use as adapter
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## Common Patterns
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- Use adapters (engine/pipeline/adapters.py) to wrap existing components as stages
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- Set `optional=True` for stages that can fail gracefully
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- Use `stage_type` and `render_order` for execution ordering
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- Clock stages update state independently of data flow
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## Sources
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- engine/pipeline/core.py - Stage base class
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- engine/pipeline/controller.py - Pipeline implementation
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- engine/pipeline/adapters/ - Stage adapters
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- docs/PIPELINE.md - Pipeline documentation
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163
.opencode/skills/mainline-display/SKILL.md
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163
.opencode/skills/mainline-display/SKILL.md
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---
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name: mainline-display
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description: Display backend implementation and the Display protocol
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compatibility: opencode
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metadata:
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audience: developers
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source_type: codebase
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---
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## What This Skill Covers
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This skill covers Mainline's display backend system - how to implement new display backends and how the Display protocol works.
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## Key Concepts
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### Display Protocol
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All backends implement a common Display protocol (in `engine/display/__init__.py`):
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```python
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class Display(Protocol):
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width: int
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height: int
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def init(self, width: int, height: int, reuse: bool = False) -> None:
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"""Initialize the display"""
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...
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def show(self, buf: list[str], border: bool = False) -> None:
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"""Display the buffer"""
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...
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def clear(self) -> None:
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"""Clear the display"""
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...
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def cleanup(self) -> None:
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"""Clean up resources"""
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...
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def get_dimensions(self) -> tuple[int, int]:
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"""Return (width, height)"""
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...
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```
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### DisplayRegistry
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Discovers and manages backends:
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```python
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from engine.display import DisplayRegistry
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display = DisplayRegistry.create("terminal") # or "websocket", "null", "multi"
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```
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### Available Backends
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| Backend | File | Description |
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|---------|------|-------------|
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| terminal | backends/terminal.py | ANSI terminal output |
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| websocket | backends/websocket.py | Web browser via WebSocket |
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| null | backends/null.py | Headless for testing |
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| multi | backends/multi.py | Forwards to multiple displays |
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| moderngl | backends/moderngl.py | GPU-accelerated OpenGL rendering (optional) |
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### WebSocket Backend
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- WebSocket server: port 8765
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- HTTP server: port 8766 (serves client/index.html)
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- Client has ANSI color parsing and fullscreen support
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### Multi Backend
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Forwards to multiple displays simultaneously - useful for `terminal + websocket`.
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## Adding a New Backend
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1. Create `engine/display/backends/my_backend.py`
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2. Implement the Display protocol methods
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3. Register in `engine/display/__init__.py`'s `DisplayRegistry`
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Required methods:
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- `init(width: int, height: int, reuse: bool = False)` - Initialize display
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- `show(buf: list[str], border: bool = False)` - Display buffer
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- `clear()` - Clear screen
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- `cleanup()` - Clean up resources
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- `get_dimensions() -> tuple[int, int]` - Get terminal dimensions
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Optional methods:
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- `title(text: str)` - Set window title
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- `cursor(show: bool)` - Control cursor
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## Usage
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```bash
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python mainline.py --display terminal # default
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python mainline.py --display websocket
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python mainline.py --display moderngl # GPU-accelerated (requires moderngl)
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```
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## Common Bugs and Patterns
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### BorderMode.OFF Enum Bug
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**Problem**: `BorderMode.OFF` has enum value `1` (not `0`), and Python enums are always truthy.
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**Incorrect Code**:
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```python
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if border:
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buffer = render_border(buffer, width, height, fps, frame_time)
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```
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**Correct Code**:
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```python
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from engine.display import BorderMode
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if border and border != BorderMode.OFF:
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buffer = render_border(buffer, width, height, fps, frame_time)
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```
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**Why**: Checking `if border:` evaluates to `True` even when `border == BorderMode.OFF` because enum members are always truthy in Python.
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### Context Type Mismatch
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**Problem**: `PipelineContext` and `EffectContext` have different APIs for storing data.
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- `PipelineContext`: Uses `set()`/`get()` for services
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- `EffectContext`: Uses `set_state()`/`get_state()` for state
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**Pattern for Passing Data**:
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```python
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# In pipeline setup (uses PipelineContext)
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ctx.set("pipeline_order", pipeline.execution_order)
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# In EffectPluginStage (must copy to EffectContext)
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effect_ctx.set_state("pipeline_order", ctx.get("pipeline_order"))
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```
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### Terminal Display ANSI Patterns
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**Screen Clearing**:
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```python
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output = "\033[H\033[J" + "".join(buffer)
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```
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**Cursor Positioning** (used by HUD effect):
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- `\033[row;colH` - Move cursor to row, column
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- Example: `\033[1;1H` - Move to row 1, column 1
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**Key Insight**: Terminal display joins buffer lines WITHOUT newlines, relying on ANSI cursor positioning codes to move the cursor to the correct location for each line.
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### EffectPluginStage Context Copying
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**Problem**: When effects need access to pipeline services (like `pipeline_order`), they must be copied from `PipelineContext` to `EffectContext`.
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**Pattern**:
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```python
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# In EffectPluginStage.process()
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# Copy pipeline_order from PipelineContext services to EffectContext state
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pipeline_order = ctx.get("pipeline_order")
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if pipeline_order:
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effect_ctx.set_state("pipeline_order", pipeline_order)
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```
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This ensures effects can access `ctx.get_state("pipeline_order")` in their process method.
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113
.opencode/skills/mainline-effects/SKILL.md
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113
.opencode/skills/mainline-effects/SKILL.md
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---
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name: mainline-effects
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description: How to add new effect plugins to Mainline's effect system
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compatibility: opencode
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metadata:
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audience: developers
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source_type: codebase
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---
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## What This Skill Covers
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This skill covers Mainline's effect plugin system - how to create, configure, and integrate visual effects into the pipeline.
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## Key Concepts
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### EffectPlugin ABC (engine/effects/types.py)
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All effects must inherit from `EffectPlugin` and implement:
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```python
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class EffectPlugin(ABC):
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name: str
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config: EffectConfig
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param_bindings: dict[str, dict[str, str | float]] = {}
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supports_partial_updates: bool = False
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@abstractmethod
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def process(self, buf: list[str], ctx: EffectContext) -> list[str]:
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"""Process buffer with effect applied"""
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...
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@abstractmethod
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def configure(self, config: EffectConfig) -> None:
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"""Configure the effect"""
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...
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```
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### EffectContext
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Passed to every effect's process method:
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```python
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@dataclass
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class EffectContext:
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terminal_width: int
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terminal_height: int
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scroll_cam: int
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ticker_height: int
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camera_x: int = 0
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mic_excess: float = 0.0
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grad_offset: float = 0.0
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frame_number: int = 0
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has_message: bool = False
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items: list = field(default_factory=list)
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_state: dict[str, Any] = field(default_factory=dict)
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```
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Access sensor values via `ctx.get_sensor_value("sensor_name")`.
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### EffectConfig
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Configuration dataclass:
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```python
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@dataclass
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class EffectConfig:
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enabled: bool = True
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intensity: float = 1.0
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params: dict[str, Any] = field(default_factory=dict)
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```
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### Partial Updates
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For performance optimization, set `supports_partial_updates = True` and implement `process_partial`:
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```python
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class MyEffect(EffectPlugin):
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supports_partial_updates = True
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def process_partial(self, buf, ctx, partial: PartialUpdate) -> list[str]:
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# Only process changed regions
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...
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```
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## Adding a New Effect
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1. Create file in `effects_plugins/my_effect.py`
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2. Inherit from `EffectPlugin`
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3. Implement `process()` and `configure()`
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4. Add to `effects_plugins/__init__.py` (runtime discovery via issubclass checks)
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## Param Bindings
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Declarative sensor-to-param mappings:
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```python
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param_bindings = {
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"intensity": {"sensor": "mic", "transform": "linear"},
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"rate": {"sensor": "oscillator", "transform": "exponential"},
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}
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```
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Transforms: `linear`, `exponential`, `threshold`
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## Effect Chain
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Effects are chained via `engine/effects/chain.py` - processes each effect in order, passing output to next.
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## Existing Effects
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See `effects_plugins/`:
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- noise.py, fade.py, glitch.py, firehose.py
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- border.py, crop.py, tint.py, hud.py
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103
.opencode/skills/mainline-presets/SKILL.md
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103
.opencode/skills/mainline-presets/SKILL.md
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---
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name: mainline-presets
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description: Creating pipeline presets in TOML format for Mainline
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compatibility: opencode
|
||||
metadata:
|
||||
audience: developers
|
||||
source_type: codebase
|
||||
---
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||||
|
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## What This Skill Covers
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||||
|
||||
This skill covers how to create pipeline presets in TOML format for Mainline's rendering pipeline.
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## Key Concepts
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||||
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### Preset Loading Order
|
||||
|
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Presets are loaded from multiple locations (later overrides earlier):
|
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1. Built-in: `engine/presets.toml`
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2. User config: `~/.config/mainline/presets.toml`
|
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3. Local override: `./presets.toml`
|
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|
||||
### PipelinePreset Dataclass
|
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|
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```python
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@dataclass
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class PipelinePreset:
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name: str
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description: str = ""
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||||
source: str = "headlines" # Data source
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||||
display: str = "terminal" # Display backend
|
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camera: str = "scroll" # Camera mode
|
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effects: list[str] = field(default_factory=list)
|
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border: bool = False
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```
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### TOML Format
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|
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```toml
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[presets.my-preset]
|
||||
description = "My custom pipeline"
|
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source = "headlines"
|
||||
display = "terminal"
|
||||
camera = "scroll"
|
||||
effects = ["noise", "fade"]
|
||||
border = true
|
||||
```
|
||||
|
||||
## Creating a Preset
|
||||
|
||||
### Option 1: User Config
|
||||
|
||||
Create/edit `~/.config/mainline/presets.toml`:
|
||||
|
||||
```toml
|
||||
[presets.my-cool-preset]
|
||||
description = "Noise and glitch effects"
|
||||
source = "headlines"
|
||||
display = "terminal"
|
||||
effects = ["noise", "glitch"]
|
||||
```
|
||||
|
||||
### Option 2: Local Override
|
||||
|
||||
Create `./presets.toml` in project root:
|
||||
|
||||
```toml
|
||||
[presets.dev-inspect]
|
||||
description = "Pipeline introspection for development"
|
||||
source = "headlines"
|
||||
display = "terminal"
|
||||
effects = ["hud"]
|
||||
```
|
||||
|
||||
### Option 3: Built-in
|
||||
|
||||
Edit `engine/presets.toml` (requires PR to repository).
|
||||
|
||||
## Available Sources
|
||||
|
||||
- `headlines` - RSS news feeds
|
||||
- `poetry` - Literature mode
|
||||
- `pipeline-inspect` - Live DAG visualization
|
||||
|
||||
## Available Displays
|
||||
|
||||
- `terminal` - ANSI terminal
|
||||
- `websocket` - Web browser
|
||||
- `null` - Headless
|
||||
- `moderngl` - GPU-accelerated (optional)
|
||||
|
||||
## Available Effects
|
||||
|
||||
See `effects_plugins/`:
|
||||
- noise, fade, glitch, firehose
|
||||
- border, crop, tint, hud
|
||||
|
||||
## Validation Functions
|
||||
|
||||
Use these from `engine/pipeline/presets.py`:
|
||||
- `validate_preset()` - Validate preset structure
|
||||
- `validate_signal_path()` - Detect circular dependencies
|
||||
- `generate_preset_toml()` - Generate skeleton preset
|
||||
136
.opencode/skills/mainline-sensors/SKILL.md
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136
.opencode/skills/mainline-sensors/SKILL.md
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|
||||
---
|
||||
name: mainline-sensors
|
||||
description: Sensor framework for real-time input in Mainline
|
||||
compatibility: opencode
|
||||
metadata:
|
||||
audience: developers
|
||||
source_type: codebase
|
||||
---
|
||||
|
||||
## What This Skill Covers
|
||||
|
||||
This skill covers Mainline's sensor framework - how to use, create, and integrate sensors for real-time input.
|
||||
|
||||
## Key Concepts
|
||||
|
||||
### Sensor Base Class (engine/sensors/__init__.py)
|
||||
|
||||
```python
|
||||
class Sensor(ABC):
|
||||
name: str
|
||||
unit: str = ""
|
||||
|
||||
@property
|
||||
def available(self) -> bool:
|
||||
"""Whether sensor is currently available"""
|
||||
return True
|
||||
|
||||
@abstractmethod
|
||||
def read(self) -> SensorValue | None:
|
||||
"""Read current sensor value"""
|
||||
...
|
||||
|
||||
def start(self) -> None:
|
||||
"""Initialize sensor (optional)"""
|
||||
pass
|
||||
|
||||
def stop(self) -> None:
|
||||
"""Clean up sensor (optional)"""
|
||||
pass
|
||||
```
|
||||
|
||||
### SensorValue Dataclass
|
||||
|
||||
```python
|
||||
@dataclass
|
||||
class SensorValue:
|
||||
sensor_name: str
|
||||
value: float
|
||||
timestamp: float
|
||||
unit: str = ""
|
||||
```
|
||||
|
||||
### SensorRegistry
|
||||
|
||||
Discovers and manages sensors globally:
|
||||
|
||||
```python
|
||||
from engine.sensors import SensorRegistry
|
||||
registry = SensorRegistry()
|
||||
sensor = registry.get("mic")
|
||||
```
|
||||
|
||||
### SensorStage
|
||||
|
||||
Pipeline adapter that provides sensor values to effects:
|
||||
|
||||
```python
|
||||
from engine.pipeline.adapters import SensorStage
|
||||
stage = SensorStage(sensor_name="mic")
|
||||
```
|
||||
|
||||
## Built-in Sensors
|
||||
|
||||
| Sensor | File | Description |
|
||||
|--------|------|-------------|
|
||||
| MicSensor | sensors/mic.py | Microphone input (RMS dB) |
|
||||
| OscillatorSensor | sensors/oscillator.py | Test sine wave generator |
|
||||
| PipelineMetricsSensor | sensors/pipeline_metrics.py | FPS, frame time, etc. |
|
||||
|
||||
## Param Bindings
|
||||
|
||||
Effects declare sensor-to-param mappings:
|
||||
|
||||
```python
|
||||
class GlitchEffect(EffectPlugin):
|
||||
param_bindings = {
|
||||
"intensity": {"sensor": "mic", "transform": "linear"},
|
||||
}
|
||||
```
|
||||
|
||||
### Transform Functions
|
||||
|
||||
- `linear` - Direct mapping to param range
|
||||
- `exponential` - Exponential scaling
|
||||
- `threshold` - Binary on/off
|
||||
|
||||
## Adding a New Sensor
|
||||
|
||||
1. Create `engine/sensors/my_sensor.py`
|
||||
2. Inherit from `Sensor` ABC
|
||||
3. Implement required methods
|
||||
4. Register in `SensorRegistry`
|
||||
|
||||
Example:
|
||||
```python
|
||||
class MySensor(Sensor):
|
||||
name = "my-sensor"
|
||||
unit = "units"
|
||||
|
||||
def read(self) -> SensorValue | None:
|
||||
return SensorValue(
|
||||
sensor_name=self.name,
|
||||
value=self._read_hardware(),
|
||||
timestamp=time.time(),
|
||||
unit=self.unit
|
||||
)
|
||||
```
|
||||
|
||||
## Using Sensors in Effects
|
||||
|
||||
Access sensor values via EffectContext:
|
||||
|
||||
```python
|
||||
def process(self, buf, ctx):
|
||||
mic_level = ctx.get_sensor_value("mic")
|
||||
if mic_level and mic_level > 0.5:
|
||||
# Apply intense effect
|
||||
...
|
||||
```
|
||||
|
||||
Or via param_bindings (automatic):
|
||||
|
||||
```python
|
||||
# If intensity is bound to "mic", it's automatically
|
||||
# available in self.config.intensity
|
||||
```
|
||||
87
.opencode/skills/mainline-sources/SKILL.md
Normal file
87
.opencode/skills/mainline-sources/SKILL.md
Normal file
@@ -0,0 +1,87 @@
|
||||
---
|
||||
name: mainline-sources
|
||||
description: Adding new RSS feeds and data sources to Mainline
|
||||
compatibility: opencode
|
||||
metadata:
|
||||
audience: developers
|
||||
source_type: codebase
|
||||
---
|
||||
|
||||
## What This Skill Covers
|
||||
|
||||
This skill covers how to add new data sources (RSS feeds, poetry) to Mainline.
|
||||
|
||||
## Key Concepts
|
||||
|
||||
### Feeds Dictionary (engine/sources.py)
|
||||
|
||||
All feeds are defined in a simple dictionary:
|
||||
|
||||
```python
|
||||
FEEDS = {
|
||||
"Feed Name": "https://example.com/feed.xml",
|
||||
# Category comments help organize:
|
||||
# Science & Technology
|
||||
# Economics & Business
|
||||
# World & Politics
|
||||
# Culture & Ideas
|
||||
}
|
||||
```
|
||||
|
||||
### Poetry Sources
|
||||
|
||||
Project Gutenberg URLs for public domain literature:
|
||||
|
||||
```python
|
||||
POETRY_SOURCES = {
|
||||
"Author Name": "https://www.gutenberg.org/cache/epub/1234/pg1234.txt",
|
||||
}
|
||||
```
|
||||
|
||||
### Language & Script Mapping
|
||||
|
||||
The sources.py also contains language/script detection mappings used for auto-translation and font selection.
|
||||
|
||||
## Adding a New RSS Feed
|
||||
|
||||
1. Edit `engine/sources.py`
|
||||
2. Add entry to `FEEDS` dict under appropriate category:
|
||||
```python
|
||||
"My Feed": "https://example.com/feed.xml",
|
||||
```
|
||||
3. The feed will be automatically discovered on next run
|
||||
|
||||
### Feed Requirements
|
||||
|
||||
- Must be valid RSS or Atom XML
|
||||
- Should have `<title>` elements for items
|
||||
- Must be HTTP/HTTPS accessible
|
||||
|
||||
## Adding Poetry Sources
|
||||
|
||||
1. Edit `engine/sources.py`
|
||||
2. Add to `POETRY_SOURCES` dict:
|
||||
```python
|
||||
"Author": "https://www.gutenberg.org/cache/epub/XXXX/pgXXXX.txt",
|
||||
```
|
||||
|
||||
### Poetry Requirements
|
||||
|
||||
- Plain text (UTF-8)
|
||||
- Project Gutenberg format preferred
|
||||
- No DRM-protected sources
|
||||
|
||||
## Data Flow
|
||||
|
||||
Feeds are fetched via `engine/fetch.py`:
|
||||
- `fetch_feed(url)` - Fetches and parses RSS/Atom
|
||||
- Results cached for fast restarts
|
||||
- Filtered via `engine/filter.py` for content cleaning
|
||||
|
||||
## Categories
|
||||
|
||||
Organize new feeds by category using comments:
|
||||
- Science & Technology
|
||||
- Economics & Business
|
||||
- World & Politics
|
||||
- Culture & Ideas
|
||||
Reference in New Issue
Block a user