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# Edison Documentation
Welcome to the Edison documentation! This documentation is designed to help users and developers understand how to use and extend Edison.
## Documentation Overview
The documentation is organized into two main sections:
- **[User Documentation](user/README.md)**: For end users who want to learn how to use Edison effectively.
- **[Developer Documentation](developer/README.md)**: For developers who want to understand Edison's architecture and how to extend it.
## What is Edison?
Edison is an AI-powered command line assistant that translates natural language into shell commands. It helps users interact with their terminal more effectively by allowing them to describe what they want to do in plain English.
```
$ edison how to find large files in the current directory
Command: find . -type f -size +10M -exec ls -lh {} \; | sort -k5,5hr
Execute command? [Y]es [n]o [m]odify [c]opy to clipboard ==>
```
## Quick Links
- [Installation Guide](user/installation.md)
- [Basic Usage](user/basic-usage.md)
- [Advanced Features](user/advanced-features.md)
- [Architecture Overview](developer/architecture.md)
- [Contribution Guide](developer/contributing.md)
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# Edison Developer Documentation
Welcome to the Edison developer documentation! This guide will help you understand Edison's architecture, code organization, and how to extend its functionality.
## Table of Contents
1. [Architecture Overview](architecture.md)
2. [Code Structure](code-structure.md)
3. [API Integration](api-integration.md)
4. [Contributing Guidelines](contributing.md)
5. [Development Environment Setup](development-setup.md)
## Getting Started with Development
Edison is a Python application that translates natural language into shell commands using OpenAI's APIs. It's designed to be modular and extensible, making it easy to add new features.
```mermaid
flowchart TD
User([User]) -->|Query| CLI[CLI Module]
CLI -->|Process| Core[Core Module]
Core -->|API Request| OpenAI[OpenAI API]
OpenAI -->|Response| Core
Core -->|Command| Shell[Shell]
Core -->|Feedback| CLI
CLI -->|Display| User
subgraph Edison Application
CLI
Core
end
style User fill:#f9d5e5,stroke:#333,stroke-width:2px
style Edison Application fill:#d3f6db,stroke:#333,stroke-width:4px
style OpenAI fill:#d3f6f5,stroke:#333,stroke-width:2px
style Shell fill:#eeeeee,stroke:#333,stroke-width:2px
```
## Quick Start for Developers
1. **Clone the repository**:
```bash
git clone https://github.com/user/command-assistant
cd command-assistant
```
2. **Create a development environment**:
```bash
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
pip install -e .
```
3. **Run Edison in development mode**:
```bash
python -m edison your query here
```
## Key Developer Resources
| Resource | Description |
|----------|-------------|
| [Architecture Overview](architecture.md) | High-level design and component interaction |
| [Code Structure](code-structure.md) | Detailed breakdown of the codebase |
| [API Integration](api-integration.md) | How Edison interacts with the OpenAI API |
| [Contributing Guidelines](contributing.md) | How to contribute to the project |
## Development Philosophy
Edison follows these design principles:
1. **Modularity**: Components should be loosely coupled and focused on a single responsibility
2. **Simplicity**: Keep the codebase simple and maintainable
3. **User-centric**: Features should address real user needs
4. **Safety**: Prioritize user safety when generating and executing commands
## Component Overview
Edison is organized into several main components:
- **CLI**: Command-line interface and user interaction
- **Core**: Business logic, API integration, and command processing
- **Config**: Configuration management
- **UI**: User interface components
- **Utils**: Utility functions and helpers
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# API Integration
This document explains how Edison integrates with the OpenAI API to translate natural language into shell commands.
## Overview
```mermaid
flowchart LR
A[User Query] --> B[Prompt Construction]
B --> C[API Request]
C --> D[Response Processing]
D --> E[Command Extraction]
E --> F[Command Validation]
F --> G[Command Execution]
style A fill:#f9d5e5,stroke:#333,stroke-width:2px
style B fill:#eeeeee,stroke:#333,stroke-width:2px
style C fill:#d3f6db,stroke:#333,stroke-width:2px
style D fill:#d3f6f5,stroke:#333,stroke-width:2px
style E fill:#d5f6d5,stroke:#333,stroke-width:2px
style F fill:#f6f6d5,stroke:#333,stroke-width:2px
style G fill:#f5d5f5,stroke:#333,stroke-width:2px
```
## API Client Module
The `api_client.py` module is responsible for all OpenAI API interactions:
```python
def get_api_key(config):
"""Get the OpenAI API key from various sources."""
# Find API key from environment, file, or config
def create_client(config):
"""Create and initialize an OpenAI client."""
# Initialize client with API key
def call_api(client, config, query):
"""Call the OpenAI API with the given query."""
# Send request to API and extract response
def generate_command(client, config, query, max_retries=3):
"""Generate a command using the OpenAI API with retry logic."""
# Call API with retries for rate limits
```
## API Key Management
Edison supports multiple methods for supplying the OpenAI API key, processed in this order:
1. **Environment Variable**: `OPENAI_API_KEY`
2. **API Key File**: `~/.openai.apikey`
3. **Configuration File**: `openai_api_key` in `edison.yaml`
This implementation is in `get_api_key()`:
```python
def get_api_key(config):
"""Get the OpenAI API key from various sources."""
dotenv.load_dotenv()
# Method 1: Environment variable
api_key = os.getenv("OPENAI_API_KEY")
# Method 2: File in home directory
if not api_key:
home_path = os.path.expanduser("~")
api_key_path = os.path.join(home_path, ".openai.apikey")
if os.path.exists(api_key_path):
with open(api_key_path, 'r') as f:
api_key = f.read().strip()
# Method 3: Configuration file
if not api_key:
api_key = config.get("openai_api_key")
if not api_key:
raise ValueError("No OpenAI API key found")
return api_key
```
## Prompt Construction
Edison uses a template-based approach to construct effective prompts:
```mermaid
sequenceDiagram
participant User
participant PromptManager
participant Template
participant APIClient
participant OpenAI
User->>APIClient: Query: "list all files"
APIClient->>PromptManager: get_full_prompt(query, shell)
PromptManager->>Template: Load template
Template-->>PromptManager: Template content
PromptManager->>PromptManager: Format template with query
PromptManager-->>APIClient: Formatted prompt
APIClient->>OpenAI: Send API request
OpenAI-->>APIClient: Command response
```
The `prompt_manager.py` module handles this:
```python
def load_prompt_template(shell="bash"):
"""Load the prompt template with shell-specific considerations."""
# Load and return the appropriate template
def get_full_prompt(query, shell="bash"):
"""Get the full prompt for the given query and shell."""
# Format prompt with query and shell
```
### Prompt Template
Edison uses a prompt template (`edison.prompt`) to structure requests to the AI model. The template:
1. Provides context about the desired output format
2. Includes examples of good responses
3. Specifies the shell environment
4. Encourages safe commands
5. Includes the user's query
## API Request
Edison uses the OpenAI Python client library for API requests:
```python
def call_api(client, config, query):
"""Call the OpenAI API with the given query."""
prompt = prompt_manager.get_full_prompt(query, config.get("shell", "bash"))
system_prompt = prompt.split('\n')[0] if '\n' in prompt else prompt
response = client.chat.completions.create(
model=config.get("model", "gpt-3.5-turbo"),
messages=[
{"role": "system", "content": system_prompt},
{"role": "user", "content": prompt}
],
temperature=config.get("temperature", 0),
max_tokens=config.get("max_tokens", 500),
)
return response.choices[0].message.content.strip()
```
### Streaming API Integration
Edison also supports streaming command generation, which provides a more responsive user experience:
```python
def call_api_streaming(client, config, query, callback):
"""Call the OpenAI API with streaming enabled.
Args:
client: The OpenAI client
config: The configuration dictionary
query: The user query
callback: Function to call with each token
"""
prompt = prompt_manager.get_full_prompt(query, config.get("shell", "bash"))
system_prompt = prompt.split('\n')[0] if '\n' in prompt else prompt
response = client.chat.completions.create(
model=config.get("model", "gpt-3.5-turbo"),
messages=[
{"role": "system", "content": system_prompt},
{"role": "user", "content": prompt}
],
temperature=config.get("temperature", 0),
max_tokens=config.get("max_tokens", 500),
stream=True # Enable streaming
)
# Collect the full response while calling the callback for each chunk
full_response = ""
for chunk in response:
if chunk.choices and chunk.choices[0].delta.content:
content = chunk.choices[0].delta.content
full_response += content
callback(content) # Call the callback with each chunk
return full_response.strip()
```
This streaming functionality is integrated with the UI through a callback function that updates the display in real-time as tokens are received.
### Request Parameters
The API request includes these key parameters:
| Parameter | Description | Default |
|-----------|-------------|---------|
| model | The OpenAI model to use | gpt-3.5-turbo |
| temperature | Randomness of completions (0-1) | 0 |
| max_tokens | Maximum tokens in response | 500 |
## Error Handling and Retries
The `generate_command()` function implements retry logic to handle rate limiting:
```python
def generate_command(client, config, query, max_retries=3):
"""Generate a command using the OpenAI API with retry logic."""
for attempt in range(max_retries):
try:
return call_api(client, config, query)
except Exception as e:
if "rate limit" in str(e).lower() and attempt < max_retries - 1:
wait_time = 2 ** attempt # Exponential backoff
logger.warning(f"Rate limited. Retrying in {wait_time} seconds...")
time.sleep(wait_time)
else:
logger.error(f"Error after {attempt+1} attempts: {str(e)}")
raise
```
Key features:
- Exponential backoff for rate limits
- Maximum retry attempts
- Detailed error logging
## Command Processing and Validation
After receiving the API response, Edison:
1. Extracts the command from the response
2. Validates the command for safety
3. Checks for markdown or other formatting issues
4. Prepares the command for execution
## Extending the API Integration
To support additional AI providers or models:
1. **Create a new client factory function**:
```python
def create_anthropic_client(config):
# Initialize Anthropic client
```
2. **Add a model selection mechanism**:
```python
def get_client_for_model(config):
model = config.get("model", "gpt-3.5-turbo")
if model.startswith("claude"):
return create_anthropic_client(config)
else:
return create_client(config)
```
3. **Implement provider-specific API call function**:
```python
def call_anthropic_api(client, config, query):
# Format request for Anthropic API
```
4. **Update the command generation logic**:
```python
def generate_command(client, config, query, max_retries=3):
model = config.get("model", "gpt-3.5-turbo")
if model.startswith("claude"):
return call_anthropic_api(client, config, query)
else:
return call_api(client, config, query)
```
## API Response Examples
### Successful Response
```json
{
"choices": [
{
"message": {
"content": "ls -la",
"role": "assistant"
},
"index": 0,
"finish_reason": "stop"
}
]
}
```
### Error Response
```json
{
"error": {
"message": "Rate limit exceeded",
"type": "rate_limit_error",
"param": null,
"code": null
}
}
```
## Performance Considerations
To optimize API usage and performance:
1. **Use Efficient Models**: Default to `gpt-3.5-turbo` for lower latency
2. **Limit Token Usage**: Keep max_tokens reasonable (default 500)
3. **Request Caching**: Consider implementing caching for common queries
4. **Concurrent Requests**: For batch processing, consider async requests
5. **Prompt Optimization**: Keep prompt templates concise but effective
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# Architecture Overview
This document provides a comprehensive overview of Edison's architecture, components, and their interactions.
## System Architecture
```mermaid
graph TD
subgraph User Interaction
CLI[CLI Module]
Interactive[Interactive Mode]
Console[Console UI]
end
subgraph Core Components
APIClient[API Client]
PromptManager[Prompt Manager]
CommandExecutor[Command Executor]
end
subgraph Configuration
ConfigManager[Config Manager]
Validation[Validation]
end
subgraph Utilities
Logging[Logging Utils]
OSUtils[OS Utils]
end
CLI --> APIClient
CLI --> CommandExecutor
CLI --> Console
CLI --> Interactive
Interactive --> APIClient
Interactive --> CommandExecutor
APIClient --> PromptManager
APIClient --> ConfigManager
CommandExecutor --> Validation
CommandExecutor --> OSUtils
ConfigManager --> Logging
style User Interaction fill:#f9d5e5,stroke:#333,stroke-width:2px
style Core Components fill:#d3f6db,stroke:#333,stroke-width:2px
style Configuration fill:#d3f6f5,stroke:#333,stroke-width:2px
style Utilities fill:#eeeeee,stroke:#333,stroke-width:2px
```
## Component Breakdown
### User Interaction Layer
The user interaction layer handles all user-facing functionality:
1. **CLI Module** (`edison/cli.py`):
- Entry point for the application
- Parses command-line arguments
- Initializes logging and configuration
- Coordinates between components
2. **Interactive Mode** (`edison/ui/interactive.py`):
- Provides a dedicated shell for continuous interaction
- Manages command history and user input
- Handles special commands and actions
3. **Console UI** (`edison/ui/console.py`):
- Formats and displays text output
- Presents commands and prompt options
- Manages colored output with termcolor
### Core Components
The core components handle the main business logic:
1. **API Client** (`edison/core/api_client.py`):
- Manages communication with the OpenAI API
- Handles API key management and retry logic
- Processes responses from the API
2. **Prompt Manager** (`edison/core/prompt_manager.py`):
- Constructs effective prompts for the AI model
- Formats user queries for optimal command generation
- Adapts prompts based on shell and OS
3. **Command Executor** (`edison/core/command_executor.py`):
- Safely executes generated commands
- Handles command output and errors
- Adapts execution for different shells and platforms
### Configuration Layer
The configuration layer manages settings and validation:
1. **Config Manager** (`edison/config/config_manager.py`):
- Loads and validates configuration from edison.yaml
- Provides default settings
- Handles environment variables for API keys
2. **Validation** (`edison/utils/validation.py`):
- Validates commands for safety
- Detects potentially dangerous operations
- Checks for invalid syntax or formatting
### Utilities
Utility modules provide support functions:
1. **Logging Utils** (`edison/utils/logging_utils.py`):
- Configures logging for the application
- Manages log files and levels
- Provides logger access
2. **OS Utils** (`edison/utils/os_utils.py`):
- Provides OS-specific functionality
- Detects platform and shell information
- Manages environment variables
## Data Flow
```mermaid
sequenceDiagram
participant User
participant CLI
participant Config
participant APIClient
participant CommandExecutor
participant Shell
User->>CLI: Input query
CLI->>Config: Load configuration
CLI->>APIClient: Send query
APIClient->>APIClient: Format prompt
APIClient->>OpenAI: API request
OpenAI-->>APIClient: Command response
APIClient-->>CLI: Return command
CLI->>User: Display command
User->>CLI: Confirm execution
CLI->>CommandExecutor: Execute command
CommandExecutor->>Shell: Run in shell
Shell-->>CommandExecutor: Command output
CommandExecutor-->>CLI: Execution result
CLI->>User: Display output
```
1. User inputs a natural language query
2. CLI loads configuration and processes arguments
3. Query is sent to the API client
4. API client formats the prompt and sends it to OpenAI
5. Response is received and processed
6. Command is displayed to the user
7. User confirms, modifies, or cancels execution
8. If confirmed, command is sent to the command executor
9. Command executor runs the command in the appropriate shell
10. Output is returned to the CLI and displayed to the user
## Extension Points
Edison is designed to be extensible in several ways:
1. **New UI Components**: Add new UI modes by extending the UI components
2. **Alternative AI Providers**: The API client can be extended to support other AI providers
3. **Custom Prompt Templates**: The prompt manager can be enhanced with specialized prompts
4. **Additional Command Validation**: Add custom validation rules in the validation module
5. **Platform-Specific Features**: Extend OS utils for additional platform support
## Technologies Used
Edison is built using:
- **Python**: Core programming language
- **OpenAI API**: For natural language processing and command generation
- **prompt_toolkit**: For interactive shell functionality
- **termcolor**: For colored terminal output
- **pyyaml**: For configuration file parsing
- **pyperclip**: For clipboard integration
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# Code Structure
This document provides a detailed overview of Edison's code organization and file structure.
## Directory Structure
```
edison/
├── __init__.py # Package initialization
├── __main__.py # Entry point for module execution
├── cli.py # Command-line interface
├── edison.prompt # Prompt template for command generation
├── edison.yaml # Default configuration file
├── config/ # Configuration management
│ ├── __init__.py
│ └── config_manager.py
├── core/ # Core business logic
│ ├── __init__.py
│ ├── api_client.py # OpenAI API integration
│ ├── command_executor.py # Command execution
│ └── prompt_manager.py # Prompt handling
├── logs/ # Log files directory
├── ui/ # User interface components
│ ├── __init__.py
│ ├── console.py # Console output formatting
│ └── interactive.py # Interactive shell mode
└── utils/ # Utility functions
├── __init__.py
├── logging_utils.py # Logging configuration
├── os_utils.py # OS-specific utilities
└── validation.py # Command validation
```
## Key Files and Their Functions
```mermaid
classDiagram
cli <|-- config_manager
cli <|-- api_client
cli <|-- console
cli <|-- interactive
api_client <|-- prompt_manager
interactive <|-- api_client
interactive <|-- command_executor
class cli {
+main()
+parse_arguments()
}
class config_manager {
+load_config()
+print_config()
}
class api_client {
+create_client()
+generate_command()
+call_api()
+get_api_key()
}
class prompt_manager {
+get_full_prompt()
+load_prompt_template()
}
class command_executor {
+execute_command()
}
class console {
+print_command()
+prompt_user_input()
+handle_command_execution()
+handle_user_input()
}
class interactive {
+interactive_mode()
+get_command_explanation()
+show_help()
}
class logging_utils {
+setup_logging()
+get_logger()
}
class os_utils {
+get_default_shell()
+missing_posix_display()
}
class validation {
+check_for_issue()
+check_for_markdown()
+is_dangerous_command()
}
```
### Core Modules
#### cli.py
The main entry point and command-line interface for Edison:
- Parses command-line arguments
- Initializes logging
- Loads configuration
- Handles user interaction flow
- Manages error handling
```python
def main():
"""Main entry point for the application."""
# Parse arguments, set up logging, load config, etc.
def parse_arguments():
"""Parse command line arguments."""
# Define and parse command-line arguments
```
#### config/config_manager.py
Handles configuration loading and management:
- Loads settings from edison.yaml
- Provides default values
- Validates configuration
```python
def load_config():
"""Load configuration from the YAML file."""
# Find and load the configuration file
def print_config(config):
"""Print the current configuration."""
# Display configuration settings
```
#### core/api_client.py
Manages interaction with the OpenAI API:
- Creates and initializes the API client
- Handles API key management
- Formats queries and processes responses
- Implements retry logic
- Supports both streaming and non-streaming command generation
```python
def create_client(config):
"""Create and initialize an OpenAI client."""
# Initialize API client with key
def generate_command(client, config, query, max_retries=3):
"""Generate a command using the OpenAI API with retry logic."""
# Send query to API and handle response
def generate_command_streaming(client, config, query, callback):
"""Generate a command using the OpenAI API with streaming output.
Args:
client: The OpenAI client
config: The configuration dictionary
query: The user query
callback: Function to call with each token
"""
# Stream response tokens and call the callback for each one
```
#### core/command_executor.py
Executes shell commands:
- Runs commands in the appropriate shell
- Handles command output and errors
- Implements safety checks
```python
def execute_command(shell, command):
"""Execute a shell command."""
# Run command and handle result
```
#### core/prompt_manager.py
Manages prompt templates and formatting:
- Loads prompt templates
- Formats user queries for optimal results
- Adapts prompts based on shell and OS
```python
def get_full_prompt(query, shell="bash"):
"""Get the full prompt for the given query and shell."""
# Format prompt with query and shell info
```
### UI Modules
#### ui/console.py
Handles console output and user interaction:
- Formats and displays text
- Presents command options
- Handles user input
- Supports direct command modification
- Controls display of generating prefix
```python
def print_command(command, show_generating_prefix=True):
"""Print a command to the console."""
# Display command with formatting, optionally showing the generating prefix
def handle_command_execution(client, config, command, explain=False):
"""Handle the execution of a command."""
# Manage command execution flow
def handle_direct_modification(command):
"""Handle direct modification of a command.
Args:
command: The command to modify
Returns:
The modified command
"""
# Present interactive editor for direct command modification
```
#### ui/interactive.py
Provides an interactive shell mode:
- Manages continuous interaction
- Handles command history
- Processes special commands
```python
def interactive_mode(client, config):
"""Start an interactive shell."""
# Run interactive loop
def get_command_explanation(client, command):
"""Get an explanation for a command."""
# Generate explanation
```
### Utility Modules
#### utils/logging_utils.py
Configures and manages logging:
- Sets up log files and formats
- Controls log levels
- Provides access to loggers
```python
def setup_logging(verbose=False):
"""Configure logging for the application."""
# Set up logging with appropriate levels
```
#### utils/os_utils.py
Provides OS-specific functionality:
- Detects platform information
- Manages environment-specific behavior
- Determines default shell
```python
def get_default_shell():
"""Get the default shell for the current OS."""
# Determine system shell
```
#### utils/validation.py
Validates and checks commands:
- Detects potentially dangerous commands
- Checks for markdown formatting
- Identifies command issues
```python
def is_dangerous_command(command):
"""Check if a command is potentially dangerous."""
# Analyze command for dangerous patterns
```
## Static Files
- **edison.prompt**: Template for generating prompts sent to the OpenAI API
- **edison.yaml**: Default configuration file with settings
## Dependencies and Imports
The project uses these key dependencies:
1. **Core Python Libraries**:
- `argparse`: For command-line argument parsing
- `logging`: For log management
- `subprocess`: For command execution
- `os`, `sys`: For system interaction
2. **External Libraries**:
- `openai`: For API interaction
- `termcolor`: For colored terminal output
- `python-dotenv`: For environment variable loading
- `pyyaml`: For configuration parsing
- `pyperclip`: For clipboard operations
- `prompt_toolkit`: For interactive shell functionality
- `colorama`: For cross-platform color support
## Code Style and Conventions
Edison follows these coding conventions:
1. **PEP 8**: Standard Python style guide
2. **Docstrings**: All functions and classes have docstrings in the Google style
3. **Error Handling**: Comprehensive try/except blocks with detailed logging
4. **Modularity**: Functions and classes have single responsibilities
5. **Type Hints**: Not currently used but planned for future versions
## Special Considerations
1. **Cross-Platform Support**: Code includes handling for different operating systems
2. **API Key Security**: Multiple secure methods for handling API keys
3. **Command Safety**: Validation to prevent dangerous command execution
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# Contributing Guidelines
Thank you for your interest in contributing to Edison! This guide will help you get started with contributing to the project.
## Development Workflow
```mermaid
gitGraph
commit id: "Initial setup"
branch feature/my-feature
checkout feature/my-feature
commit id: "Implement feature"
commit id: "Add tests"
commit id: "Fix bugs"
checkout main
merge feature/my-feature
commit id: "Release v1.0.1"
```
## Getting Started
### Setting Up Your Development Environment
1. **Fork the repository**:
- Visit the GitHub repository and click the "Fork" button
2. **Clone your fork**:
```bash
git clone https://github.com/YOUR_USERNAME/command-assistant.git
cd command-assistant
```
3. **Set up a virtual environment**:
```bash
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
```
4. **Install in development mode**:
```bash
pip install -e .
```
5. **Install development dependencies**:
```bash
pip install pylint pytest
```
### Development Process
1. **Create a branch**:
```bash
git checkout -b feature/my-feature-name
```
2. **Make your changes**:
- Write code
- Add tests
- Update documentation
3. **Run tests and linting**:
```bash
# Run tests (future addition)
pytest
# Run linting
pylint edison
```
4. **Commit your changes**:
```bash
git add .
git commit -m "Descriptive commit message"
```
5. **Push to your fork**:
```bash
git push origin feature/my-feature-name
```
6. **Submit a pull request**:
- Go to your fork on GitHub
- Click "New Pull Request"
- Select your branch and submit
## Code Style and Guidelines
### Python Style Guide
Edison follows [PEP 8](https://www.python.org/dev/peps/pep-0008/) with some additional guidelines:
- Use 4 spaces for indentation
- Maximum line length of 100 characters
- Use meaningful variable and function names
- Write docstrings for all classes and functions
### Docstring Format
We use Google-style docstrings:
```python
def example_function(param1, param2):
"""
Brief description of the function.
Args:
param1: Description of param1
param2: Description of param2
Returns:
Description of return value
Raises:
ExceptionType: When and why this exception is raised
"""
pass
```
### Code Organization
- Keep functions focused on a single responsibility
- Group related functionality in modules
- Use appropriate error handling
- Add useful log messages
## Adding New Features
When adding new features:
1. **Start by discussing**: Open an issue to discuss your proposed feature
2. **Design the interface**: How will users interact with your feature?
3. **Plan the implementation**: Sketch out the implementation before coding
4. **Write tests**: Add tests to verify your feature works correctly
5. **Document the feature**: Update or add documentation explaining the feature
6. **Submit for review**: Submit a pull request for review
## Release Process
```mermaid
flowchart TD
A[Feature Development] --> B[Testing]
B --> C[Code Review]
C --> D{Approved?}
D -->|No| B
D -->|Yes| E[Merge to Main]
E --> F[Version Bump]
F --> G[Release]
style A fill:#f9d5e5,stroke:#333,stroke-width:2px
style B fill:#eeeeee,stroke:#333,stroke-width:2px
style C fill:#d3f6db,stroke:#333,stroke-width:2px
style D fill:#d3f6f5,stroke:#333,stroke-width:2px
style E fill:#f5d5f5,stroke:#333,stroke-width:2px
style F fill:#f5d5d5,stroke:#333,stroke-width:2px
style G fill:#d5d5f5,stroke:#333,stroke-width:2px
```
Edison follows semantic versioning (MAJOR.MINOR.PATCH):
- **MAJOR**: Incompatible API changes
- **MINOR**: Backwards-compatible new features
- **PATCH**: Backwards-compatible bug fixes
## Future Development Areas
We're looking for contributions in these areas:
1. **Testing Framework**: Adding a comprehensive test suite
2. **Documentation**: Expanding and improving documentation
3. **Supported Shells**: Adding support for additional shells
4. **Platform Support**: Enhancing cross-platform compatibility
5. **Model Support**: Adding support for alternative AI models
6. **Command Validation**: Improving safety checks
7. **Interactive Features**: Enhancing the interactive shell
8. **Performance Optimization**: Improving response times
## Best Practices
### Security Considerations
- Never commit API keys or sensitive information
- Validate user input thoroughly
- Use safe subprocess execution methods
- Be careful with permissions and file operations
### Performance
- Minimize API calls where possible
- Use efficient algorithms and data structures
- Avoid unnecessary file I/O
- Profile code to identify bottlenecks
### User Experience
- Provide clear feedback to users
- Use consistent command-line interfaces
- Add helpful error messages
- Consider accessibility in your design
## Getting Help
If you need help with contributing:
- Open an issue on GitHub
- Check existing documentation
- Reach out to maintainers
Thank you for contributing to Edison!
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# Development Environment Setup
This guide explains how to set up your development environment for Edison.
## Prerequisites
Before beginning development on Edison, ensure you have:
- **Python 3.6+**: Required for core development
- **Git**: For version control
- **OpenAI API Key**: For testing API integration
- **pip**: For package management
## Setting Up Your Development Environment
```mermaid
flowchart TD
A[Clone Repository] --> B[Set Up Virtual Environment]
B --> C[Install Dependencies]
C --> D[Configure API Key]
D --> E[Run Tests]
E --> F[Start Development]
style A fill:#f9d5e5,stroke:#333,stroke-width:2px
style B fill:#eeeeee,stroke:#333,stroke-width:2px
style C fill:#d3f6db,stroke:#333,stroke-width:2px
style D fill:#d3f6f5,stroke:#333,stroke-width:2px
style E fill:#f5d5f5,stroke:#333,stroke-width:2px
style F fill:#f5f5d5,stroke:#333,stroke-width:2px
```
### Step 1: Clone the Repository
```bash
# If you're a contributor, fork the repository first, then:
git clone https://github.com/YOUR_USERNAME/command-assistant.git
# If you're a maintainer:
git clone https://github.com/user/command-assistant.git
# Navigate to the directory
cd command-assistant
```
### Step 2: Create a Virtual Environment
```bash
# Create virtual environment
python -m venv venv
# Activate virtual environment
# On macOS/Linux:
source venv/bin/activate
# On Windows:
venv\Scripts\activate
```
### Step 3: Install in Development Mode
```bash
# Install Edison in development mode
pip install -e .
# Install development dependencies
pip install pylint pytest
```
### Step 4: Configure OpenAI API Key
For development, it's best to use environment variables:
```bash
# On macOS/Linux:
export OPENAI_API_KEY="your-api-key-here"
# On Windows:
set OPENAI_API_KEY=your-api-key-here
```
Or create a `.env` file in the project root:
```
OPENAI_API_KEY="your-api-key-here"
```
## Directory Structure Setup
The development environment should match this structure:
```
command-assistant/ # Root directory
├── docs/ # Documentation
├── edison/ # Main package
├── tests/ # Test directory (future addition)
├── venv/ # Virtual environment (generated)
├── .gitignore # Git ignore file
├── LICENSE # License file
├── README.md # Project readme
├── install_edison.sh # Installation script for Linux/macOS
├── install_edison.bat # Installation script for Windows
├── requirements.txt # Package dependencies
└── setup.py # Package setup file
```
## Running Edison in Development Mode
```bash
# Run Edison from the command line
edison your query here
# Run Edison as a module
python -m edison your query here
# Run with verbose logging
edison -v your query here
```
## Development Tools
### Code Linting
Edison uses `pylint` for code linting:
```bash
# Lint the entire package
pylint edison
# Lint a specific file
pylint edison/cli.py
```
### Testing
In the future, Edison will use `pytest` for testing:
```bash
# Run all tests
pytest
# Run specific tests
pytest tests/test_api_client.py
# Run with coverage
pytest --cov=edison
```
## Debugging
### Logging
Enable verbose logging for debugging:
```bash
edison -v your query here
```
Logs are stored in `edison/logs/edison.log`.
### Using a Debugger
For detailed debugging, you can use Python's built-in debugger or an IDE:
```python
import pdb; pdb.set_trace() # Add this line where you want to break
# Or with Python 3.7+
breakpoint()
```
## Development Workflow
```mermaid
stateDiagram-v2
[*] --> Feature
Feature --> Development
Development --> Testing
Testing --> Refinement
Refinement --> Testing: Issues found
Testing --> PullRequest: Tests pass
PullRequest --> Review
Review --> Refinement: Changes requested
Review --> Merge: Approved
Merge --> [*]
```
1. **Pick a Feature/Issue**: Select something to work on
2. **Create a Branch**: Make a new branch for your work
3. **Development**: Write code, docstrings, and comments
4. **Testing**: Test your changes thoroughly
5. **Pull Request**: Submit your changes for review
6. **Review**: Address any feedback
7. **Merge**: Changes are merged into main branch
## IDE Setup
### VS Code
Recommended settings for `settings.json`:
```json
{
"python.linting.pylintEnabled": true,
"python.linting.enabled": true,
"python.formatting.provider": "black",
"python.formatting.blackArgs": ["--line-length", "100"],
"editor.formatOnSave": true,
"python.testing.pytestEnabled": true,
"python.testing.unittestEnabled": false,
"python.testing.nosetestsEnabled": false,
"python.testing.pytestArgs": ["tests"]
}
```
### PyCharm
Recommended settings:
- Enable pylint integration
- Set code style to PEP 8
- Configure pytest as the test runner
## Pre-Commit Hooks (Future Addition)
In the future, we'll add pre-commit hooks for:
- Code formatting with `black`
- Import sorting with `isort`
- Linting with `pylint`
- Type checking with `mypy`
## Troubleshooting Development Issues
### Common Issues and Solutions
| Issue | Solution |
|-------|----------|
| `ModuleNotFoundError` | Ensure your virtual environment is activated and package is installed with `pip install -e .` |
| Import errors | Check your PYTHONPATH and package structure |
| API errors | Verify your API key is set correctly |
| Permission denied | Check file permissions, especially for executable scripts |
### Getting Help
If you encounter issues during development:
- Check the documentation
- Search for similar issues on GitHub
- Ask for help in your pull request
- Open a new issue describing your problem
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# Edison User Documentation
Welcome to the Edison user documentation! This guide will help you understand how to use Edison effectively in your day-to-day terminal usage.
## Table of Contents
1. [Installation](installation.md)
2. [Basic Usage](basic-usage.md)
3. [Advanced Features](advanced-features.md)
4. [Configuration](configuration.md)
5. [Troubleshooting](troubleshooting.md)
## Quick Start
Edison is a command-line tool that translates natural language into shell commands. To use Edison, simply type `edison` followed by your query:
```bash
edison how to compress all jpg files in the current directory
```
Edison will generate the appropriate command and ask for your confirmation before executing it.
## Feature Overview
```mermaid
flowchart TD
A[Edison CLI] --> B[Natural Language Processing]
B --> C{Command Generation}
C --> D[Command Execution]
C --> E[Command Explanation]
C --> F[Interactive Mode]
style A fill:#f9d5e5,stroke:#333,stroke-width:2px
style B fill:#eeeeee,stroke:#333,stroke-width:2px
style C fill:#d3f6db,stroke:#333,stroke-width:2px
style D fill:#d3f6f5,stroke:#333,stroke-width:2px
style E fill:#d3f6f5,stroke:#333,stroke-width:2px
style F fill:#d3f6f5,stroke:#333,stroke-width:2px
```
Edison offers several key features:
- **Natural Language Command Generation**: Describe what you want to do in plain English
- **Command Explanation**: Get explanations for complex commands
- **Interactive Mode**: Use Edison in an interactive shell
- **Shell Integration**: Works with your default shell
- **Configurable**: Adjust settings via `edison.yaml`
Check the individual documentation pages for more detailed information on each feature.
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# Advanced Features
Edison offers several advanced features to enhance your productivity. This guide explores these capabilities in detail.
## Interactive Mode
Interactive mode provides a dedicated shell for continuous Edison interactions.
```mermaid
stateDiagram-v2
[*] --> Interactive: edison -i
Interactive --> Query: Enter query
Query --> CommandGeneration: Process query
CommandGeneration --> CommandDisplay: Display command
CommandDisplay --> ActionChoice: Prompt for action
ActionChoice --> Execution: y/Enter
ActionChoice --> Modification: m
ActionChoice --> Explanation: x
ActionChoice --> Clipboard: c
ActionChoice --> Query: n/skip
Execution --> Query: Command executed
Modification --> Execution: Execute modified command
Explanation --> ActionChoice: Show explanation
Clipboard --> ActionChoice: Copy to clipboard
Interactive --> [*]: exit/quit/!exit/Ctrl+D
```
To start interactive mode:
```bash
edison -i
```
In interactive mode, you can:
- Enter queries one after another without restarting Edison
- Access command history with up/down arrows
- Use tab completion for Edison commands
- Type `!help` to see available commands
- Type `!exit`, `exit`, `!quit`, `quit` or press `Ctrl+D` to exit
## Command Explanations
Get explanations for complex commands:
```bash
edison -e how to find duplicate files in a directory
```
The `-e` (or `--explain`) flag makes Edison provide an explanation of the generated command, breaking it down part by part. Edison uses terminal-friendly formatting to make explanations more readable:
- **Bold text** for emphasis and headers
- **Green text** for commands and file paths
- **Yellow text** for command parameters and options
- **Cyan text** for section beginnings and important concepts
- **Code formatting** for command snippets and examples
In interactive mode, use the `x` option when prompted for an action to get an explanation.
## Configuration
Edison can be configured through the `edison.yaml` file. This configuration file is located in the Edison installation directory.
Here's an example configuration:
```yaml
# OpenAI API settings
model: gpt-3.5-turbo
temperature: 0
max_tokens: 500
# Safety settings
safety: true
# Shell settings
shell: bash
```
Configuration options:
| Option | Description | Default |
|--------|-------------|---------|
| model | OpenAI model to use | gpt-3.5-turbo |
| temperature | Randomness of completions (0-1) | 0 |
| max_tokens | Maximum response tokens | 500 |
| safety | Require confirmation before execution | true |
| shell | Shell to use for command execution | system default |
| openai_api_key | OpenAI API key (optional) | - |
You can view your current configuration with:
```bash
edison -c
```
## Logging and Debugging
Edison provides verbose logging for troubleshooting:
```bash
edison -v list all processes
```
With the `-v` (or `--verbose`) flag, Edison will output detailed DEBUG level logs.
Log files are stored in the `edison/logs` directory and can be useful for debugging issues.
## Streaming Command Generation
Edison supports streaming command generation, which shows the command being generated in real-time:
```mermaid
sequenceDiagram
participant User
participant Edison
participant API as OpenAI API
User->>Edison: Natural language query
Edison->>API: Request with streaming enabled
Note over Edison,API: Streaming connection established
API-->>Edison: Token: "f"
Edison->>User: Display: "f"
API-->>Edison: Token: "ind"
Edison->>User: Update: "find"
API-->>Edison: Token: " -name"
Edison->>User: Update: "find -name"
API-->>Edison: Token: " \"*.txt\""
Edison->>User: Update: "find -name \"*.txt\""
API-->>Edison: Token: " -type f"
Edison->>User: Final: "find -name \"*.txt\" -type f"
```
This feature:
- Provides immediate feedback during command generation
- Makes Edison feel more responsive, especially for complex commands
- Allows you to see the thought process in real-time
### Hiding the "Generating command:" Prefix
By default, Edison displays "Generating command:" while it's working. You can hide this prefix with the following configuration:
```yaml
# In edison.yaml
show_generating_prefix: false
```
## Direct Command Modification
Edison provides a direct command modification option that allows you to edit the generated command in-place:
1. When prompted for action, press `d` to directly modify the command
2. Edison will present an interactive editor with the current command
3. Edit the command as needed
4. Press Enter to execute the modified command
This feature is especially useful for:
- Making minor adjustments to generated commands
- Adding flags or options that weren't included
- Correcting parts of the command that may not be exactly what you want
## Performance Optimization
For faster response times:
1. Use a faster model like `gpt-3.5-turbo` (default) instead of larger models
2. Keep queries concise and specific
3. Use interactive mode to avoid startup overhead for multiple commands
4. Enable streaming mode for perceived performance improvements
## Safety Features
Edison includes built-in safety measures:
1. **Command confirmation**: By default, Edison asks for confirmation before executing commands
2. **Dangerous command detection**: Edison will warn about potentially dangerous operations
3. **Markdown filtering**: Commands containing markdown formatting are not executed directly
To disable the safety confirmation (not recommended):
```yaml
# In edison.yaml
safety: false
```
## Cross-Platform Considerations
Edison works on Linux, macOS, and Windows, but some commands might be platform-specific. For best results:
1. Mention your operating system in queries for system-specific commands
2. Use the `-e` flag to understand what a command does before executing it
3. Be aware that file paths use different separators (/ vs \\) on different platforms
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# Basic Usage
Edison is designed to be intuitive and easy to use. This guide covers the fundamental operations and commands.
## Command Structure
```
edison [OPTIONS] <your natural language query>
```
For example:
```bash
edison how to find all png files in the current directory
```
## Basic Workflow
```mermaid
sequenceDiagram
participant User
participant Edison
participant API as OpenAI API
participant Shell
User->>Edison: Natural language query
Edison->>API: Send prompt with query
API-->>Edison: Return command
Edison->>User: Display command & ask for confirmation
User->>Edison: Confirm (Y/n/m)
alt User confirms
Edison->>Shell: Execute command
Shell-->>User: Show command output
else User modifies
User->>Edison: Modified command
Edison->>Shell: Execute modified command
Shell-->>User: Show command output
else User declines
Edison->>User: Command skipped
end
```
1. **Enter your query**: Describe in natural language what you want to do
2. **Review the command**: Edison will display the generated shell command
3. **Choose an action**:
- Press `Enter` or type `y` to execute the command
- Type `n` to skip execution
- Type `m` to modify the command before execution
- Type `d` to directly modify the command (new feature!)
- Type `c` to copy the command to clipboard
## Command Line Options
Edison supports several command-line options:
| Option | Description |
|--------|-------------|
| `-v, --verbose` | Enable verbose logging (DEBUG level) |
| `-i, --interactive` | Start interactive shell mode |
| `-e, --explain` | Explain the generated command |
| `-c, --config` | Print current configuration |
| `-s, --safety` | Enable safety mode (only useful when safety is off) |
## Examples
Here are some example queries you can try:
```bash
# File operations
edison list all files larger than 10MB
edison create a new directory called "project"
edison find files modified in the last 24 hours
# System information
edison check CPU usage
edison show network connections
edison how much disk space do I have left
# Text processing
edison count lines in all python files
edison find lines containing "error" in log files
edison replace "old" with "new" in all text files
```
## Tips for Effective Queries
1. **Be specific**: The more specific your query, the better the generated command
2. **Include parameters**: Mention specific filenames, sizes, or other parameters
3. **Start with verbs**: Commands usually work best when starting with actions like "find", "list", "create"
4. **Use common terminology**: Avoid obscure technical terms when possible
## Next Steps
Once you're comfortable with basic usage, explore [Advanced Features](advanced-features.md) to learn about interactive mode, command explanations, and more.
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# Configuration
Edison provides several ways to configure its behavior to suit your needs. This guide explains the available configuration options and how to set them.
## Configuration File
The primary way to configure Edison is through the `edison.yaml` file. This file is located in the Edison installation directory.
```mermaid
flowchart LR
A[edison.yaml] --> B[OpenAI Settings]
A --> C[Safety Settings]
A --> D[Shell Settings]
B --> B1[Model]
B --> B2[Temperature]
B --> B3[Max Tokens]
B --> B4[API Key]
C --> C1[Safety Mode]
D --> D1[Shell Type]
style A fill:#f9d5e5,stroke:#333,stroke-width:2px
style B fill:#eeeeee,stroke:#333,stroke-width:2px
style C fill:#d3f6db,stroke:#333,stroke-width:2px
style D fill:#d3f6f5,stroke:#333,stroke-width:2px
```
### Sample Configuration File
Here's an example `edison.yaml` file with all available options:
```yaml
# OpenAI API settings
model: gpt-4o-mini
temperature: 0
max_tokens: 500
openai_api_key: your_api_key_here # Optional, can be set via environment variable
streaming: true # Enable streaming command generation
# Safety settings
safety: true
# UI settings
show_generating_prefix: true # Show "Generating command:" prefix during generation
# Shell settings
shell: bash # Options: bash, zsh, powershell.exe, cmd.exe, etc.
```
## Configuration Options
### OpenAI API Settings
| Option | Description | Default | Possible Values |
|--------|-------------|---------|----------------|
| model | OpenAI model to use | gpt-4o-mini | gpt-4o-mini, gpt-3.5-turbo, gpt-4, etc. |
| temperature | Randomness of completions | 0 | 0.0 - 1.0 |
| max_tokens | Maximum tokens in response | 500 | 1 - 4096 |
| openai_api_key | Your OpenAI API key | - | Valid API key |
| streaming | Enable streaming command generation | true | true, false |
### Safety Settings
| Option | Description | Default | Possible Values |
|--------|-------------|---------|----------------|
| safety | Require confirmation before execution | true | true, false |
### UI Settings
| Option | Description | Default | Possible Values |
|--------|-------------|---------|----------------|
| show_generating_prefix | Show "Generating command:" prefix during generation | true | true, false |
### Shell Settings
| Option | Description | Default | Possible Values |
|--------|-------------|---------|----------------|
| shell | Shell to use for command execution | (system default) | bash, zsh, powershell.exe, cmd.exe, etc. |
## Setting Your OpenAI API Key
There are several ways to set your OpenAI API key, listed in order of precedence:
1. **Environment variable**:
- Linux/macOS: `export OPENAI_API_KEY=<yourkey>`
- Windows: `$env:OPENAI_API_KEY="<yourkey>"`
2. **API key file**:
Create a file at `~/.openai.apikey` containing only your API key.
3. **Configuration file**:
Add your key to the `edison.yaml` file:
```yaml
openai_api_key: your_api_key_here
```
## Viewing Current Configuration
To view your current configuration:
```bash
edison -c
```
This will display all current settings, including where your OpenAI API key is being loaded from (but will not display the key itself for security reasons).
## Configuration Load Order
Edison loads configuration in this order:
1. Default values
2. Values from `edison.yaml`
3. Environment variables (for API key)
4. Command-line arguments
Later sources override earlier ones.
## Recommended Configurations
### For Beginners
```yaml
model: gpt-4o-mini
temperature: 0
max_tokens: 500
safety: true
```
### For Advanced Users
```yaml
model: gpt-4 # If you have access
temperature: 0.2 # Slightly more creative
max_tokens: 1000 # For more detailed responses
safety: true # Keep safety on unless you really know what you're doing
```
### For Performance
```yaml
model: gpt-3.5-turbo # Fastest option if you need maximum speed
temperature: 0
max_tokens: 300 # Lower limits can be faster
```
## Troubleshooting Configuration Issues
- **Configuration not applying**: Ensure your `edison.yaml` file is in the correct location
- **API key not recognized**: Check for extra whitespace or quotes in your key
- **Model not available**: Verify you have access to the specified model in your OpenAI account
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# Edison Installation Guide
This guide covers how to install Edison on different operating systems.
## Prerequisites
Before installing Edison, ensure you have:
- Python 3.6 or higher
- pip (Python package manager)
- An OpenAI API key
## Installation Process
```mermaid
flowchart LR
A[Get Repository] --> B[Install Dependencies]
B --> C[Configure API Key]
C --> D[Test Installation]
style A fill:#f9d5e5,stroke:#333,stroke-width:2px
style B fill:#eeeeee,stroke:#333,stroke-width:2px
style C fill:#d3f6db,stroke:#333,stroke-width:2px
style D fill:#d3f6f5,stroke:#333,stroke-width:2px
```
### Linux and macOS
1. Clone the repository:
```bash
git clone https://github.com/user/command-assistant
cd command-assistant
```
2. Run the installation script:
```bash
source install_edison.sh
```
This script will:
- Create a virtual environment
- Install required dependencies
- Set up the Edison command
3. Configure your OpenAI API key using one of these methods:
- Environment variable: `export OPENAI_API_KEY=<yourkey>`
- Create a file at `~/.openai.apikey` with just the key
- Add the key to the `edison.yaml` configuration file
### Windows
1. Clone the repository:
```powershell
git clone https://github.com/user/command-assistant
cd command-assistant
```
2. Run the installation script:
```powershell
.\install_edison.bat
```
3. Configure your OpenAI API key using one of these methods:
- Environment variable: `$env:OPENAI_API_KEY="<yourkey>"`
- Create a file at `~/.openai.apikey` with just the key
- Add the key to the `edison.yaml` configuration file
## Manual Installation
If you prefer to install manually:
1. Clone the repository:
```bash
git clone https://github.com/user/command-assistant
cd command-assistant
```
2. Create and activate a virtual environment:
```bash
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
```
3. Install the package:
```bash
pip install -e .
```
4. Configure your OpenAI API key as described above
## Verifying Installation
To test your installation, run:
```bash
edison what is the current time
```
You should see a command generated that displays the current time.
## Troubleshooting
If you encounter issues during installation:
- Ensure Python 3.6+ is installed and in your PATH
- Check that your OpenAI API key is correctly set
- Verify that all dependencies were installed correctly
See the [Troubleshooting](troubleshooting.md) page for more detailed help.
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# Edison Themes Guide
Edison supports rich syntax highlighting for commands through its theme system. This guide explains how to use and customize themes in Edison.
## Available Themes
Edison uses the Rich library's syntax highlighting capabilities, which are powered by Pygments. The following themes are available out of the box:
| Theme Name | Description | Style |
|------------|-------------|-------|
| monokai | Default theme with vibrant colors | Dark |
| github-dark | Based on GitHub's dark theme | Dark |
| solarized-dark | Popular dark theme with softer colors | Dark |
| dracula | High contrast dark theme | Dark |
| nord | Bluish dark theme | Dark |
| gruvbox-dark | Retro dark theme with warm colors | Dark |
| one-dark | Based on Atom's One Dark theme | Dark |
| vs | Based on Visual Studio's default theme | Light |
| solarized-light | Light version of the Solarized theme | Light |
| gruvbox-light | Light version of the Gruvbox theme | Light |
## Using Themes
You can specify a theme in three ways:
### 1. In the Configuration File
Edit your `edison.yaml` file to set the default theme:
```yaml
ui:
theme: "github-dark" # Change from the default "monokai"
```
### 2. Via Command-Line Argument
Specify a theme for a single command:
```bash
edison --theme dracula "list all files"
```
### 3. In Interactive Mode
The theme specified in the configuration or command-line will be used in interactive mode as well.
## Theme Elements
Themes apply different colors to various syntax elements:
- **Keywords**: Shell keywords like `if`, `for`, `while`, etc.
- **Strings**: Text enclosed in quotes
- **Comments**: Lines starting with `#` in bash
- **Variables**: Names prefixed with `$` in bash
- **Operators**: Symbols like `=`, `-gt`, `|`, etc.
- **Functions**: Function names and calls
- **Numbers**: Numeric literals
- **Punctuation**: Brackets, parentheses, etc.
## Creating Custom Themes
While Edison doesn't directly support custom themes, you can create your own by extending the Rich library:
1. Create a custom theme file (e.g., `custom_themes.py`):
```python
from pygments.style import Style
from pygments.token import (
Comment, Error, Keyword, Literal, Name, Number, Operator, String, Text
)
class CustomTheme(Style):
"""A custom syntax highlighting theme."""
# Define colors
background_color = "#282c34"
highlight_color = "#3e4451"
# Define token colors
styles = {
Text: "#abb2bf",
Error: "#e06c75",
Comment: "#5c6370",
Keyword: "#c678dd",
Keyword.Reserved: "#c678dd",
Keyword.Namespace: "#c678dd",
Name: "#abb2bf",
Name.Builtin: "#e5c07b",
Name.Function: "#61afef",
Name.Class: "#e5c07b",
Name.Decorator: "#61afef",
Name.Variable: "#e06c75",
Number: "#d19a66",
Operator: "#56b6c2",
String: "#98c379",
}
```
2. Register your theme with Pygments:
```python
from pygments.styles import STYLE_MAP
STYLE_MAP["custom"] = "custom_themes.CustomTheme"
```
3. Use your custom theme:
```python
from edison.utils.markdown_utils import print_command_rich
print_command_rich("ls -la", theme="custom")
```
## Theme Compatibility
Theme appearance may vary depending on:
1. **Terminal Capabilities**: Some terminals have limited color support or override colors with their own theme settings.
2. **Color Schemes**: Your terminal's color scheme may affect how themes appear.
3. **Font Settings**: Certain font features like ligatures can affect the display of syntax-highlighted code.
## Troubleshooting
If you're not seeing theme differences:
1. **Check Terminal Support**: Ensure your terminal supports 256 colors or true color:
```bash
echo $TERM
echo $COLORTERM
```
For best results, use a terminal that supports true color (24-bit color).
2. **Try High-Contrast Themes**: If differences are subtle, try themes with higher contrast like `dracula` vs `solarized-light`.
3. **Use Complex Commands**: Simple commands might not have enough syntax elements to show significant differences between themes.
## Demo Scripts
Edison includes two demonstration scripts to help you visualize theme differences:
1. `theme_demo.py`: Shows the same bash script rendered with different themes
2. `edison_theme_demo.py`: Demonstrates how Edison's theme functionality works with its markdown_utils module
Run these scripts to see the themes in action:
```bash
python theme_demo.py
python edison_theme_demo.py
+128
View File
@@ -0,0 +1,128 @@
# Troubleshooting
This guide helps you diagnose and resolve common issues with Edison.
## Common Issues and Solutions
```mermaid
flowchart TB
Start[Issue Detected] --> A{API Related?}
A -->|Yes| B[API Issues]
A -->|No| C{Installation Related?}
C -->|Yes| D[Installation Issues]
C -->|No| E{Command Related?}
E -->|Yes| F[Command Issues]
E -->|No| G[Other Issues]
B --> B1[Check API Key]
B --> B2[Check Network]
B --> B3[Check Model Access]
D --> D1[Check Python Version]
D --> D2[Check Dependencies]
D --> D3[Check PATH]
F --> F1[Check Command Syntax]
F --> F2[Check Shell Compatibility]
style Start fill:#f9d5e5,stroke:#333,stroke-width:2px
style B fill:#eeeeee,stroke:#333,stroke-width:2px
style D fill:#d3f6db,stroke:#333,stroke-width:2px
style F fill:#d3f6f5,stroke:#333,stroke-width:2px
style G fill:#f5d3d3,stroke:#333,stroke-width:2px
```
### API Issues
| Issue | Solution |
|-------|----------|
| `No OpenAI API key found` | Set your API key using one of the [configuration methods](configuration.md#setting-your-openai-api-key) |
| `Rate limit exceeded` | Wait a minute before trying again, or check your OpenAI rate limits |
| `Invalid API key` | Verify your API key is correct and has not expired |
| `Model not available` | Ensure you have access to the requested model, or change to `gpt-3.5-turbo` |
### Installation Issues
| Issue | Solution |
|-------|----------|
| `Command not found: edison` | Ensure Edison is installed and in your PATH |
| `No module named 'openai'` | Reinstall Edison or run `pip install -r requirements.txt` |
| `ModuleNotFoundError` | Ensure all dependencies are installed correctly |
| `Python version error` | Ensure you're using Python 3.6+ |
### Command Execution Issues
| Issue | Solution |
|-------|----------|
| `Command contains markdown` | Edison detected markdown in the response; rerun the query |
| `Command execution failed` | The generated command has syntax errors; try modifying it |
| `Permission denied` | The command requires higher permissions; prefix with sudo if appropriate |
| `Command not found` | The generated command uses a program not installed on your system |
### Other Issues
| Issue | Solution |
|-------|----------|
| `Slow response times` | Try a faster model or check your internet connection |
| `Inaccurate commands` | Be more specific in your query or add more context |
| `Unexpected behavior` | Check the logs for detailed error information |
## Enabling Verbose Mode
For more detailed troubleshooting, use verbose mode:
```bash
edison -v your query here
```
This will print detailed logs that can help identify issues.
## Checking Logs
Log files are stored in the `edison/logs` directory. The main log file is `edison.log`. Check this file for detailed error messages and API interactions.
```bash
cat edison/logs/edison.log | tail -n 50
```
## Resetting Configuration
If you suspect a configuration issue, you can reset to defaults by removing or renaming your `edison.yaml` file:
```bash
mv edison.yaml edison.yaml.bak
```
Edison will create a new configuration file with default settings on the next run.
## Common Error Messages and Meanings
### "No OpenAI API key found"
You need to set your OpenAI API key. See [configuration options](configuration.md).
### "Error calling OpenAI API"
There was an issue communicating with the OpenAI API. Check:
1. Your internet connection
2. API key validity
3. OpenAI service status
### "Response does not contain a valid command"
The AI generated a response that Edison couldn't interpret as a command. Try:
1. Rephrasing your query to be more specific
2. Checking logs for the full response
3. Using a different model
## Getting Help
If you continue to experience issues:
1. Check the full documentation
2. Look for similar issues in the GitHub repository
3. Open a new issue with:
- A clear description of the problem
- Steps to reproduce
- Any error messages (with sensitive information redacted)
- Your OS and Python version