LadyOl
Object-based prompt injection system for AI agents.
## Features
- **Context Injection** - Inject past experiences and project context into messages
- **Context Closure** - Store task outcomes for continuous learning
- **Identity Management** - Persistent agent identity documents in Glain
- **Memory System** - Two-layer memory (MEMORY.md + Glain)
- **Skills Loading** - Load and manage agent skills
- **Prompt Scaling** - Automatically adjust prompt complexity based on model capability
## Installation
```bash
pip install ladyol
```
## Usage
```bash
# Run LadyOL
ladyol run
# Check status
ladyol status
```
### Options
| Argument | Type | Required | Default | Description |
|----------|------|----------|---------|-------------|
| `--verbose` / `-v` | flag | No | false | Enable verbose output |
| `--config` / `-c` | path | No | None | Path to configuration file |
### Commands
#### `run`
Run the main operation.
```bash
ladyol run
```
#### `status`
Check project status.
```bash
ladyol status
```
## Quick Start
```python
from pathlib import Path
from ladyol import LadyOlPromptEngine, LadyOlConfig
# Initialize the engine
config = LadyOlConfig()
engine = LadyOlPromptEngine(
workspace=Path("./workspace"),
config=config,
)
# Inject context into messages
messages = [{"role": "user", "content": "What was I working on?"}]
updated_messages = await engine.inject_context(messages)
# Get memory context
memory_context = engine.get_memory_context()
# Get skills summary
skills = engine.get_skills_summary()
```
## Architecture
```
ladyol/
├── agent/ # Core agent components
│ ├── context_closure.py
│ ├── context_injector.py
│ ├── identity.py
│ ├── memory.py
│ ├── prompt_scaler.py
│ └── skills.py
├── config/ # Configuration schemas
├── prompt/ # Prompt engine
└── utils/ # Utilities
```
## License
MIT
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