Metadata-Version: 2.1
Name: onedrive-skill
Version: 0.1.0
Summary: A Python skill for connecting to Microsoft OneDrive via Graph API
Home-page: https://github.com/lucapaone76/onedrive-connect
Author: lucapaone76
Author-email: lucapaone@gmail.com
License: MIT
Project-URL: Homepage, https://github.com/lucapaone76/onedrive-connect
Project-URL: Repository, https://github.com/lucapaone76/onedrive-connect
Project-URL: Issues, https://github.com/lucapaone76/onedrive-connect/issues
Keywords: onedrive,microsoft,graph-api,llm,skill
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Provides-Extra: dev

# OneDrive Connect - LLM Skill

A Python project to provide a skill (in the sense of the standard skills now available for LLMs) to connect to personal Microsoft OneDrive. Authentication tokens are injected via environment variables or secrets for security.

**✨ Compliant with LLM Agent Skills Best Practices ✨**

## Quick Links

- 📋 [Installation Guide](#installation) - Detailed setup instructions
- 📦 [Requirements](REQUIREMENTS.md) - Dependencies and system requirements
- 🔐 [Authentication Setup](#authentication-setup) - Azure AD configuration
- 📖 [API Reference](#api-reference) - Complete method documentation
- 💡 [Usage Examples](#usage) - Code samples and demos
- 🛡️ [Safety Features](#safety-features) - Security and confirmations
- 📄 [Skill Specification](SKILL.md) - Complete skill documentation
- 📝 [Changelog](CHANGELOG.md) - Version history and release notes

## LLM Skills Compliance

This skill follows best practices for LLM agent skills:

- **Structured Metadata**: Provides `skill_manifest.json` with detailed capability descriptions
- **Safety Levels**: Clear categorization (read-only, write, destructive)
- **User Consent**: Required confirmations for destructive operations
- **Discoverable**: Implements `get_skill_metadata()` for runtime introspection
- **Type-Safe**: Full type hints for all public APIs
- **Well-Documented**: Comprehensive docstrings and usage examples

For more on LLM agent skills standards, see the [skill manifest](skill_manifest.json).

## Features

- 🔐 Secure authentication via environment variables
- 📁 List files and folders in OneDrive
- ⬆️ Upload files to OneDrive
- ⬇️ Download files from OneDrive
- 🔍 Search for files across OneDrive
- 📂 Create and manage folders
- 🗑️ Delete items
- 🤖 LLM-friendly skill interface
- ⚠️ **User confirmation for destructive operations**
- 📋 **Skill metadata for LLM discovery**
- 🛡️ **Safety mechanisms and cancellation support**

## Safety Features

This skill implements industry-standard safety features for LLM agent skills:

- **User Confirmation Required**: Destructive operations (delete, overwrite) require explicit user confirmation
- **Clear Warnings**: Operations that modify or delete data display clear warnings
- **Cancellation Support**: Users can cancel any operation before execution
- **Skill Metadata**: Provides structured metadata for LLM discovery and capability assessment
- **Safe Defaults**: Operations default to safe behaviors (e.g., rename on conflict)

## Installation

### Prerequisites

- Python 3.8 or higher
- pip (Python package installer)
- An Azure AD application with Microsoft Graph API permissions (see [Authentication Setup](#authentication-setup))

### Method 1: Install from source (Recommended for development)

1. **Clone the repository:**
   ```bash
   git clone https://github.com/lucapaone76/onedrive-connect.git
   cd onedrive-connect
   ```

2. **Install dependencies:**
   ```bash
   pip install -r requirements.txt
   ```

3. **Install the package in development mode (optional):**
   ```bash
   pip install -e .
   ```

4. **Verify installation:**
   ```bash
   python -c "from onedrive_skill import OneDriveSkill; print('Installation successful!')"
   ```

### Method 2: Install from PyPI (after publishing)

```bash
pip install onedrive-skill
```

### Method 3: Install with development dependencies

For contributing or running tests:

```bash
git clone https://github.com/lucapaone76/onedrive-connect.git
cd onedrive-connect
pip install -e ".[dev]"
```

This installs the package along with development tools (pytest, black, ruff).

### Virtual Environment (Recommended)

It's recommended to use a virtual environment to avoid dependency conflicts:

```bash
# Create virtual environment
python -m venv venv

# Activate virtual environment
# On Linux/Mac:
source venv/bin/activate
# On Windows:
venv\Scripts\activate

# Install the package
pip install -r requirements.txt
```

### Docker Installation (Alternative)

If you prefer using Docker:

```dockerfile
FROM python:3.11-slim

WORKDIR /app
COPY requirements.txt .
RUN pip install -r requirements.txt

COPY . .
ENV ONEDRIVE_ACCESS_TOKEN=""

CMD ["python", "example_usage.py"]
```

Build and run:
```bash
docker build -t onedrive-skill .
docker run -e ONEDRIVE_ACCESS_TOKEN="your_token" onedrive-skill
```

For detailed requirements and dependencies, see [REQUIREMENTS.md](REQUIREMENTS.md).

## Authentication Setup

This skill uses the Microsoft Graph API to connect to OneDrive. You need to obtain an access token:

### Step 1: Register an Application in Azure AD

1. Go to [Azure Portal](https://portal.azure.com/)
2. Navigate to **Azure Active Directory** > **App registrations**
3. Click **New registration**
4. Name your application (e.g., "OneDrive Skill")
5. Select appropriate account type (Personal Microsoft accounts for personal OneDrive)
6. Click **Register**

### Step 2: Configure API Permissions

1. In your app registration, go to **API permissions**
2. Click **Add a permission** > **Microsoft Graph** > **Delegated permissions**
3. Add the following permissions:
   - `Files.ReadWrite` (or `Files.ReadWrite.All` for broader access)
   - `User.Read`
4. Click **Add permissions**
5. Click **Grant admin consent** if applicable

### Step 3: Generate Access Token

You can generate an access token using various OAuth2 flows. For testing purposes, you can use:

- **Azure AD OAuth2 authorization code flow**
- **Device code flow**
- **MSAL (Microsoft Authentication Library)**

Example using MSAL (Python):

```python
from msal import PublicClientApplication

app = PublicClientApplication(
    client_id="YOUR_CLIENT_ID",
    authority="https://login.microsoftonline.com/common"
)

# Interactive authentication
result = app.acquire_token_interactive(
    scopes=["Files.ReadWrite", "User.Read"]
)

if "access_token" in result:
    access_token = result["access_token"]
    print(f"Access token: {access_token}")
```

### Step 4: Set Environment Variable

```bash
export ONEDRIVE_ACCESS_TOKEN="your_access_token_here"
```

Or create a `.env` file (see `.env.example`):

```bash
cp .env.example .env
# Edit .env and add your access token
```

**⚠️ Security Note:** Never commit your `.env` file or access tokens to version control!

## Usage

### Basic Usage with OneDriveClient

```python
from onedrive_skill import OneDriveClient

# Initialize client (uses ONEDRIVE_ACCESS_TOKEN from environment)
client = OneDriveClient()

# Or provide token explicitly
client = OneDriveClient(access_token="your_token")

# Get user information
user = client.get_user_info()
print(f"Logged in as: {user['displayName']}")

# List files in root
items = client.list_root_items()
for item in items:
    print(f"- {item['name']}")

# Upload a file
with open("example.txt", "rb") as f:
    result = client.upload_file("Documents/example.txt", f.read())
    print(f"Uploaded: {result['name']}")

# Download a file
content = client.download_file(item_id="FILE_ID")
with open("downloaded.txt", "wb") as f:
    f.write(content)

# Search for files
results = client.search_items("quarterly report")
for item in results:
    print(f"Found: {item['name']}")
```

### Using the OneDriveSkill (LLM-Friendly Interface)

```python
from onedrive_skill import OneDriveSkill

# Initialize skill
skill = OneDriveSkill()

# Get skill metadata (useful for LLM discovery)
metadata = skill.get_skill_metadata()
print(f"Skill: {metadata['name']} v{metadata['version']}")

# List files (returns formatted string)
print(skill.list_files())
# Output:
# - [File] document.docx (12345 bytes)
# - [Folder] Photos (0 bytes)
# - [File] report.pdf (98765 bytes)

# Search for items
print(skill.search("budget"))
# Output:
# Found 3 item(s):
# - [File] budget_2024.xlsx (ID: ABC123)
# - [File] budget_proposal.docx (ID: DEF456)
# - [Folder] Budget Archive (ID: GHI789)

# Upload content (with confirmation)
content = b"Hello, OneDrive!"
result = skill.upload_content("test.txt", content)
# User will be prompted:
# ⚠️  CONFIRMATION REQUIRED ⚠️
# You are about to upload a file to: test.txt
# File size: 17 bytes
# WARNING: This will OVERWRITE any existing file at this path!
# Do you want to proceed? (yes/no):
print(result)
# Output: ✅ File uploaded successfully: test.txt (ID: XYZ999)

# Delete item (with confirmation - DESTRUCTIVE)
result = skill.delete_item("ABC123", "budget_2024.xlsx")
# User will be prompted:
# ⚠️  DESTRUCTIVE OPERATION ⚠️
# You are about to PERMANENTLY DELETE: budget_2024.xlsx
# Item ID: ABC123
# This action CANNOT be undone!
# Do you want to proceed? (yes/no):
print(result)
# If cancelled: ❌ Deletion cancelled by user for: budget_2024.xlsx
# If confirmed: ✅ Item deleted successfully: budget_2024.xlsx
```

### Using Custom Confirmation Handler

For integration with LLM systems or custom UI, provide your own confirmation handler:

```python
def custom_confirmation(message: str) -> bool:
    """Custom handler that integrates with your UI/LLM system."""
    # Display message in your UI
    # Get user's response through your preferred method
    # Return True to proceed, False to cancel
    return get_user_response(message)

skill = OneDriveSkill(confirmation_callback=custom_confirmation)
```

### Running the Example

```bash
# Set your access token
export ONEDRIVE_ACCESS_TOKEN="your_token"

# Run the example
python example_usage.py
```

## API Reference

### OneDriveClient

Main client for interacting with OneDrive via Microsoft Graph API.

**Methods:**
- `get_user_info()` - Get authenticated user information
- `list_root_items()` - List items in root directory
- `list_items(folder_path)` - List items in a specific folder
- `get_item_info(item_id)` - Get information about an item
- `download_file(item_id)` - Download a file
- `upload_file(file_path, content, overwrite)` - Upload a file
- `create_folder(folder_name, parent_path)` - Create a new folder
- `delete_item(item_id)` - Delete an item
- `search_items(query)` - Search for items

### OneDriveSkill

Simplified skill interface for LLM integration with safety features.

**Constructor:**
- `OneDriveSkill(access_token, confirmation_callback)` - Initialize with optional custom confirmation handler

**Methods:**
- `get_skill_metadata()` - Get skill metadata for LLM discovery
- `list_files(folder_path)` - List files with formatted output (read-only)
- `get_file_content(item_id)` - Download file content (read-only)
- `upload_content(file_path, content, require_confirmation)` - Upload file with status message (requires confirmation by default)
- `create_folder(folder_name, parent_path, conflict_behavior)` - Create folder with configurable conflict resolution
- `delete_item(item_id, item_name, require_confirmation)` - Delete item (requires confirmation by default, DESTRUCTIVE)
- `search(query)` - Search with formatted results (read-only)

**Safety Levels:**
- 🟢 **Read-only**: `list_files`, `get_file_content`, `search`
- 🟡 **Write**: `create_folder`
- 🔴 **Destructive** (requires confirmation): `upload_content` (overwrites), `delete_item`

## Security Considerations

1. **Never hardcode access tokens** in your code
2. **Use environment variables** or secure secret management systems
3. **Rotate tokens regularly** - access tokens expire and should be refreshed
4. **Limit API permissions** to only what's necessary
5. **Use `.gitignore`** to prevent committing sensitive files
6. **Consider using refresh tokens** for long-lived applications

## Development

### Installing Development Dependencies

```bash
pip install -e ".[dev]"
```

### Running Tests

```bash
pytest
```

### Code Formatting

```bash
black onedrive_skill/
ruff check onedrive_skill/
```

## License

MIT License - see [LICENSE](LICENSE) file for details.

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

## Troubleshooting

### "No access token provided" Error

Make sure you've set the `ONEDRIVE_ACCESS_TOKEN` environment variable:

```bash
export ONEDRIVE_ACCESS_TOKEN="your_token"
```

### "401 Unauthorized" Error

Your access token may have expired. Generate a new token and update the environment variable.

### "403 Forbidden" Error

Check that your application has the necessary API permissions in Azure AD and that admin consent has been granted if required.

## Related Links

- [Microsoft Graph API Documentation](https://docs.microsoft.com/en-us/graph/)
- [OneDrive API Reference](https://docs.microsoft.com/en-us/graph/api/resources/onedrive)
- [Azure AD App Registration](https://docs.microsoft.com/en-us/azure/active-directory/develop/quickstart-register-app)

## Documentation

This project includes comprehensive documentation:

- **[README.md](README.md)** - Main documentation with quick start and usage
- **[SKILL.md](SKILL.md)** - Complete skill specification and API reference
- **[REQUIREMENTS.md](REQUIREMENTS.md)** - Dependencies and system requirements
- **[CHANGELOG.md](CHANGELOG.md)** - Version history and release notes
- **[skill_manifest.json](skill_manifest.json)** - Machine-readable skill metadata


