Ollama Function Library - Detailed Specification
I'll develop a comprehensive specification for the Ollama Function Library that will enable semantic function invocation for Linux commands, web requests, and documentation tools. Let's build this step by step.
1. Project Overview
1.1 Project Name
OllamaTools
1.2 Description
A Python library that extends Ollama's capabilities by providing a collection of useful functions that can be automatically invoked based on semantic context during conversations. The library focuses on enabling local command execution, web requests, and documentation utilities with appropriate security controls.
1.3 Goals
Enable Ollama to detect when function execution is appropriate based on user queries
Provide a secure interface for executing Linux commands with permission controls
Create utilities for making web requests and processing responses
Build tools for generating and processing documentation
Maintain a simple, extensible architecture that can grow over time
2. System Architecture
2.1 High-Level Components
OllamaTools/
├── ollamatools/
│ ├── __init__.py
│ ├── agent.py # Main agent class that interfaces with Ollama
│ ├── config.py # Configuration management
│ ├── security.py # Permission system implementation
│ ├── utils/ # Utility functions
│ │ ├── __init__.py
│ │ └── logging.py
│ ├── tools/ # Core function modules
│ │ ├── __init__.py
│ │ ├── system_tools.py # Linux command execution functions
│ │ ├── web_tools.py # Web request functions
│ │ └── doc_tools.py # Documentation utilities
│ └── exceptions.py # Custom exceptions
├── tests/ # Unit and integration tests
├── examples/ # Example usage scripts
├── README.md
├── LICENSE
├── setup.py
└── requirements.txt
2.2 Dependencies
Python 3.8+
ollama-python >= 0.4.0 (for function calling support)
requests (for web requests)
beautifulsoup4 (for HTML parsing)
pydantic (for data validation and schema generation)
markdown (for documentation processing)
pytest (for testing)
3. Core Modules
3.1 System Tools Module
3.1.1 Purpose
Provide a secure interface for executing Linux commands and interacting with the system.
3.1.2 Key Functions
python
def execute_command(command: str, args: Optional[List[str]] = None) -> dict:
"""
Execute a shell command with optional arguments.
This function runs the specified command with its arguments
and returns the output. Commands requiring elevated privileges
will always prompt for permission.
Args:
command: The command to execute (e.g., 'ls', 'cat', 'find')
args: List of arguments to pass to the command
Returns:
dict: A dictionary containing:
- stdout: Standard output as string
- stderr: Standard error as string
- exit_code: Command exit code
- execution_time: Time taken to execute in seconds
"""
python
def read_file(path: str, max_size: Optional[int] = None) -> str:
"""
Read the contents of a file.
Args:
path: Path to the file
max_size: Maximum file size to read in bytes (None for no limit)
Returns:
str: Contents of the file
"""
python
def write_file(path: str, content: str, mode: str = 'w') -> bool:
"""
Write content to a file.
Args:
path: Path to the file
content: Content to write
mode: Write mode ('w' for overwrite, 'a' for append)
Returns:
bool: True if successful
"""
python
def find_files(pattern: str, directory: str = '.', recursive: bool = True) -> List[str]:
"""
Find files matching a pattern in the specified directory.
Args:
pattern: Glob pattern to match
directory: Directory to search in
recursive: Whether to search recursively
Returns:
List[str]: List of matching file paths
"""
3.1.3 Security Considerations
All system commands will be checked against a configurable whitelist/blacklist
Commands that could potentially modify the system will require explicit permission
Sudo commands will always require permission regardless of configuration
Execution timeout to prevent long-running commands
3.2 Web Tools Module
3.2.1 Purpose
Provide functions for making web requests and processing web content.
3.2.2 Key Functions
python
def get_webpage(url: str, params: Optional[Dict[str, str]] = None) -> dict:
"""
Fetch a webpage using HTTP GET.
Args:
url: The URL to fetch
params: Optional query parameters
Returns:
dict: A dictionary containing:
- status_code: HTTP status code
- content: Page content as string
- headers: Response headers
- text: Text content with HTML tags removed
"""
python
def search_web(query: str, search_engine: str = 'duckduckgo') -> List[dict]:
"""
Search the web for a query.
Args:
query: Search query
search_engine: Search engine to use ('duckduckgo', 'brave', etc.)
Returns:
List[dict]: List of search results, each containing:
- title: Result title
- url: Result URL
- snippet: Text snippet from the result
"""
python
def get_weather(location: str, units: str = 'metric') -> dict:
"""
Get weather information for a location from weather.gov.
Args:
location: City or location name
units: Units for temperature ('metric' or 'imperial')
Returns:
dict: Weather information containing:
- temperature: Current temperature
- conditions: Weather conditions
- forecast: List of forecast days
- humidity: Current humidity
- wind: Wind information
"""
python
def download_file(url: str, output_path: str) -> bool:
"""
Download a file from a URL.
Args:
url: URL of the file to download
output_path: Path to save the file
Returns:
bool: True if successful
"""
3.2.3 Security Considerations
Rate limiting to prevent abuse
URL validation to prevent malicious requests
Timeout configuration for requests
Option to restrict to specific domains
3.3 Documentation Tools Module
3.3.1 Purpose
Provide utilities for generating, processing, and extracting information from documentation.
3.3.2 Key Functions
python
def generate_markdown_doc(content: str, title: str,
format: str = 'markdown') -> str:
"""
Generate formatted documentation from text content.
Args:
content: The content to format
title: Document title
format: Output format ('markdown', 'html', etc.)
Returns:
str: Formatted documentation
"""
python
def extract_code_from_file(file_path: str, language: Optional[str] = None) -> List[dict]:
"""
Extract code blocks from a file.
Args:
file_path: Path to the file
language: Optional language filter
Returns:
List[dict]: List of code blocks, each containing:
- code: Code content
- language: Detected language
- line_numbers: Start and end line numbers
"""
python
def summarize_document(content: str, max_length: int = 500) -> str:
"""
Generate a summary of a document.
Args:
content: Document content
max_length: Maximum summary length in characters
Returns:
str: Document summary
"""
python
def extract_context_from_docs(query: str, docs: List[str]) -> str:
"""
Extract relevant context from a collection of documents based on a query.
Args:
query: Search query
docs: List of document contents
Returns:
str: Relevant context extracted from documents
"""
4. Security Module
4.1 Purpose
Manage permissions and security for function execution.
4.2 Key Components
4.2.1 PermissionManager Class
python
class PermissionManager:
"""
Manages permissions for executing functions.
This class handles permission prompts, configuration, and security policies
for all tools in the library.
"""
def __init__(self, prompt_enabled: bool = True,
sudo_always_prompt: bool = True,
command_whitelist: Optional[List[str]] = None,
command_blacklist: Optional[List[str]] = None):
"""
Initialize the permission manager.
Args:
prompt_enabled: Whether to prompt for permissions
sudo_always_prompt: Whether to always prompt for sudo commands
command_whitelist: List of allowed commands (None for all)
command_blacklist: List of forbidden commands
"""
def request_permission(self, function_name: str,
args: Dict[str, Any]) -> bool:
"""
Request permission to execute a function.
Args:
function_name: Name of the function
args: Function arguments
Returns:
bool: True if permission granted
"""
def validate_command(self, command: str, args: List[str]) -> bool:
"""
Validate a command against security policies.
Args:
command: Command to validate
args: Command arguments
Returns:
bool: True if command is allowed
"""
5. Agent Module
5.1 Purpose
Provide the main integration with Ollama and handle function invocation.
5.2 Key Components
5.2.1 OllamaAgent Class
python
class OllamaAgent:
"""
Main agent class that interfaces with Ollama.
This class manages the connection to Ollama, handles function registration,
and processes responses from the model.
"""
def __init__(self, model: str = "llama3.1",
permission_prompts: bool = True,
host: str = "http://localhost:11434",
sudo_always_prompt: bool = True):
"""
Initialize the Ollama agent.
Args:
model: Ollama model to use
permission_prompts: Whether to prompt for permissions
host: Ollama host address
sudo_always_prompt: Whether to always prompt for sudo commands
"""
def register_tools(self):
"""
Register all available tools with the Ollama client.
This method scans the tools modules and registers all functions
with appropriate documentation and type hints.
"""
def chat(self, message: str,
system_prompt: Optional[str] = None) -> str:
"""
Send a message to Ollama and handle any function calls.
Args:
message: User message
system_prompt: Optional system prompt
Returns:
str: Response from Ollama
"""
def process_function_calls(self,
function_calls: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
"""
Process function calls from Ollama.
Args:
function_calls: List of function calls from Ollama
Returns:
List[Dict[str, Any]]: Results of function calls
"""
6. Configuration Module
6.1 Purpose
Manage library configuration and settings.
6.2 Key Components
6.2.1 Configuration Class
python
class Configuration:
"""
Configuration management for OllamaTools.
This class handles loading, saving, and accessing configuration settings
for the library.
"""
def __init__(self, config_file: Optional[str] = None):
"""
Initialize configuration.
Args:
config_file: Path to configuration file
"""
def load(self):
"""
Load configuration from file.
"""
def save(self):
"""
Save configuration to file.
"""
def get(self, key: str, default: Any = None) -> Any:
"""
Get a configuration value.
Args:
key: Configuration key
default: Default value if key not found
Returns:
Any: Configuration value
"""
def set(self, key: str, value: Any):
"""
Set a configuration value.
Args:
key: Configuration key
value: Configuration value
"""
7. Usage Examples
7.1 Basic Usage
python
from ollamatools import OllamaAgent
# Create agent with default settings
agent = OllamaAgent(model="llama3.1")
# Chat with automatic function invocation
response = agent.chat("What's the weather like in New York?")
print(response)
# Execute Linux command with permission prompt
response = agent.chat("List all files in the current directory sorted by size")
print(response)
# Generate documentation
response = agent.chat("Create documentation for a Python function that calculates the Fibonacci sequence")
print(response)
7.2 Custom Configuration
python
from ollamatools import OllamaAgent, Configuration
# Create custom configuration
config = Configuration()
config.set("permission_prompts", False) # Disable permission prompts
config.set("command_whitelist", ["ls", "cat", "grep"]) # Only allow specific commands
# Create agent with custom configuration
agent = OllamaAgent(model="llama3.1", config=config)
# Chat with automatic function invocation
response = agent.chat("What are the largest files in this directory?")
print(response)
8. Implementation Plan
8.1 Phase 1: Core Framework
Set up project structure
Implement security module
Implement basic agent functionality
Add configuration management
Write unit tests
8.2 Phase 2: System Tools
Implement command execution functions
Add file operations
Set up security policies
Test system tool integration
8.3 Phase 3: Web Tools
Implement web request functions
Add weather API integration
Implement search functionality
Test web tool integration
8.4 Phase 4: Documentation Tools
Implement documentation generation
Add context extraction
Implement code extraction utilities
Test documentation tool integration
8.5 Phase 5: Integration and Testing
Integration testing with Ollama
Performance optimization
Security auditing
Documentation and examples
9. Extensibility
The library is designed to be easily extended with new tools:
Create a new module in the tools directory
Implement functions with proper type hints and docstrings
Import and register the module in __init__.py
The agent will automatically discover and register the new functions.
10. Testing Strategy
10.1 Unit Tests
Test each function in isolation
Mock external dependencies
Test permission system
10.2 Integration Tests
Test interaction with Ollama
Test function calling flow
Test error handling
10.3 Security Tests
Test permission prompts
Test command validation
Test input sanitization
Is there any specific aspect of this specification you'd like me to expand on or modify?
can you elaborate on what you meant with a whitelist / blacklist of commands? i think we decided to omit that and just stick with prompt based with the option to turn off?
You're absolutely right - I included the whitelist/blacklist approach in the specification despite our earlier decision to go with a purely prompt-based system with the option to disable it.
Let me revise the Security Module section to properly reflect our design decision:
4. Security Module (Revised)
4.1 Purpose
Manage permissions and security for function execution using a prompt-based approach.
4.2 Key Components
4.2.1 PermissionManager Class
python
class PermissionManager:
"""
Manages permissions for executing functions.
This class handles permission prompts with configurable options to disable prompting.
By default, it will prompt the user for permission before executing potentially
sensitive operations, with special handling for sudo commands.
"""
def __init__(self, prompt_enabled: bool = True,
sudo_always_prompt: bool = True):
"""
Initialize the permission manager.
Args:
prompt_enabled: Whether to prompt for permissions (can be disabled)
sudo_always_prompt: Whether to always prompt for sudo commands
(overrides prompt_enabled for sudo)
"""
def request_permission(self, function_name: str,
args: Dict[str, Any],
is_sudo: bool = False) -> bool:
"""
Request permission to execute a function.
Prompts the user for permission if prompt_enabled is True,
or if is_sudo is True and sudo_always_prompt is True.
Otherwise automatically grants permission.
Args:
function_name: Name of the function
args: Function arguments
is_sudo: Whether the command uses sudo
Returns:
bool: True if permission granted
"""
def format_permission_prompt(self, function_name: str,
args: Dict[str, Any]) -> str:
"""
Format a human-readable permission prompt.
Args:
function_name: Name of the function
args: Function arguments
Returns:
str: Formatted permission prompt
"""
4.3 Implementation Details
Simple On/Off Toggle:
Users can completely disable permission prompts through a configuration setting
When disabled, all commands except sudo will execute without prompting
Special Handling for Sudo:
Sudo commands always require permission by default
This behavior can be configured but is separate from the general prompt toggle
Informative Prompts:
Permission prompts clearly explain what command will be executed and with what parameters
Includes potential security implications for sensitive operations
Permission Response Options:
Allow: Grant permission for this single operation
Allow for session: Grant permission for similar operations for the rest of the session
Deny: Reject this operation
Modify: Allow the user to modify command parameters before execution
This revised approach focuses on the prompt-based permission system we agreed upon, removing the whitelist/blacklist concept entirely. The system is designed to be secure by default but allows for flexibility by providing an option to disable prompts (except for sudo commands which can have their own setting).
Now that we’ve wrapped up the brainstorming process, can you compile our findings into a comprehensive, developer-ready specification? Include all relevant requirements, architecture choices, data handling details, error handling strategies, and a testing plan so a developer can immediately begin implementation.
OllamaTools: Function Library for Ollama LLMs
Technical Specification Document
1. Project Overview
Project Name: OllamaTools
Description: A Python library that extends Ollama with semantic function calling capabilities, enabling automatic invocation of system commands, web requests, and documentation utilities based on conversational context.
Primary Goal: Allow Ollama LLMs to execute external functions based on semantic understanding of user queries without requiring explicit enabling/disabling of tools.
2. System Requirements
2.1 Software Requirements
Python 3.8+
Ollama 0.4.0+ with function calling support
Linux-based operating system (primary target)
Optional: Windows/macOS support may be added in future releases
2.2 Dependencies
ollama-python >= 0.4.0
requests >= 2.28.0
beautifulsoup4 >= 4.11.0
pydantic >= 1.10.0
markdown >= 3.4.0
typing-extensions >= 4.4.0
pytest >= 7.0.0 (for testing)
3. Architecture
3.1 System Architecture
OllamaTools is designed as a Python package that extends the functionality of the official Ollama Python client, adding semantic function detection and execution capabilities.
OllamaTools/
├── ollamatools/
│ ├── __init__.py
│ ├── agent.py # Main agent interface
│ ├── security.py # Permission management
│ ├── config.py # Configuration management
│ ├── tools/ # Function groups
│ │ ├── __init__.py
│ │ ├── system_tools.py # Linux command execution
│ │ ├── web_tools.py # Web requests
│ │ └── doc_tools.py # Documentation utilities
│ └── utils/
│ ├── __init__.py
│ └── logger.py # Logging utilities
├── tests/ # Unit and integration tests
├── examples/ # Example scripts
├── README.md
├── LICENSE
├── setup.py
└── requirements.txt
3.2 Core Components
OllamaAgent: Primary interface that manages communication with Ollama and handles function detection and execution.
PermissionManager: Handles security and permissions for executing functions, especially system commands.
Function Libraries:
System Tools: Execute Linux commands and file operations
Web Tools: Make web requests and process responses
Documentation Tools: Generate and process documentation
4. Detailed Component Specifications
4.1 OllamaAgent
The OllamaAgent class serves as the main entry point for the library. It extends the standard Ollama client with function execution capabilities.
python
class OllamaAgent:
def __init__(
self,
model: str = "llama3.1",
host: str = "http://localhost:11434",
permission_prompts: bool = True,
sudo_always_prompt: bool = True
):
"""
Initialize the OllamaAgent with specified configuration.
Args:
model: Name of the Ollama model to use
host: Ollama server address
permission_prompts: Whether to prompt for function execution permission
sudo_always_prompt: Whether to always prompt for sudo commands
"""
def chat(
self,
message: str,
system_prompt: Optional[str] = None,
context: Optional[List[Dict[str, str]]] = None
) -> str:
"""
Send a message to Ollama, automatically detecting and executing functions.
Args:
message: User message
system_prompt: Optional system prompt
context: Optional conversation context
Returns:
str: Response from Ollama, potentially after executing functions
"""
def register_tools(self):
"""
Register all available tools with the Ollama client.
"""
def process_function_calls(
self,
function_calls: List[Dict[str, Any]]
) -> List[Dict[str, Any]]:
"""
Process function calls detected by Ollama.
Args:
function_calls: List of function calls from Ollama
Returns:
List of function call results
"""
4.2 PermissionManager
The PermissionManager handles security for function execution, with a focus on a prompt-based approach.
python
class PermissionManager:
def __init__(
self,
prompt_enabled: bool = True,
sudo_always_prompt: bool = True
):
"""
Initialize the permission manager.
Args:
prompt_enabled: Whether to prompt for permissions
sudo_always_prompt: Whether to always prompt for sudo commands
"""
def request_permission(
self,
function_name: str,
args: Dict[str, Any],
is_sudo: bool = False
) -> bool:
"""
Request permission to execute a function.
Args:
function_name: Name of the function
args: Function arguments
is_sudo: Whether the command uses sudo
Returns:
bool: True if permission granted
"""
def detect_sudo(self, command: str) -> bool:
"""
Detect if a command uses sudo.
Args:
command: Command string
Returns:
bool: True if command uses sudo
"""
4.3 System Tools
System tools provide functions to execute Linux commands and perform file operations.
python
def execute_command(
command: str,
args: Optional[List[str]] = None,
timeout: int = 60
) -> Dict[str, Any]:
"""
Execute a shell command with arguments.
Args:
command: Command to execute
args: Command arguments
timeout: Command timeout in seconds
Returns:
dict: Result with stdout, stderr, and exit code
"""
def read_file(
path: str,
max_size: Optional[int] = None
) -> str:
"""
Read file contents.
Args:
path: File path
max_size: Maximum file size to read in bytes
Returns:
str: File contents
"""
def write_file(
path: str,
content: str,
mode: str = 'w'
) -> bool:
"""
Write content to a file.
Args:
path: File path
content: Content to write
mode: Write mode ('w' for write, 'a' for append)
Returns:
bool: True if successful
"""
def find_files(
pattern: str,
directory: str = '.',
recursive: bool = True
) -> List[str]:
"""
Find files matching a pattern.
Args:
pattern: File pattern
directory: Search directory
recursive: Whether to search recursively
Returns:
List[str]: Matching file paths
"""
4.4 Web Tools
Web tools provide functions for making web requests and processing responses.
python
def fetch_url(
url: str,
method: str = 'GET',
params: Optional[Dict[str, str]] = None,
headers: Optional[Dict[str, str]] = None,
data: Optional[Dict[str, Any]] = None,
timeout: int = 30
) -> Dict[str, Any]:
"""
Fetch a URL with specified parameters.
Args:
url: URL to fetch
method: HTTP method
params: URL parameters
headers: HTTP headers
data: Request data
timeout: Request timeout in seconds
Returns:
dict: Response with status, headers, and content
"""
def get_weather(
location: str,
days: int = 3,
units: str = 'metric'
) -> Dict[str, Any]:
"""
Get weather information for a location.
Args:
location: Location name or coordinates
days: Number of forecast days
units: Temperature units ('metric' or 'imperial')
Returns:
dict: Weather information
"""
def search_web(
query: str,
num_results: int = 5
) -> List[Dict[str, str]]:
"""
Search the web for a query.
Args:
query: Search query
num_results: Number of results to return
Returns:
List[dict]: Search results with title, URL, and snippet
"""
4.5 Documentation Tools
Documentation tools provide functions for creating and processing documentation.
python
def generate_markdown(
content: str,
title: str,
format_type: str = 'markdown'
) -> str:
"""
Generate formatted documentation.
Args:
content: Document content
title: Document title
format_type: Output format ('markdown' or 'html')
Returns:
str: Formatted documentation
"""
def extract_context(
query: str,
documents: List[str],
max_length: int = 1000
) -> str:
"""
Extract relevant context from documents based on a query.
Args:
query: Search query
documents: List of document contents
max_length: Maximum context length
Returns:
str: Extracted context
"""
def summarize_text(
text: str,
max_length: int = 500
) -> str:
"""
Generate a summary of text.
Args:
text: Text to summarize
max_length: Maximum summary length
Returns:
str: Text summary
"""
5. Security Considerations
5.1 Permission System
The permission system is designed to be secure by default while allowing flexibility.
Prompt-Based Permissions:
By default, prompts user for permission before executing potentially sensitive operations
Clear, informative prompts explaining the operation and potential risks
Option to disable prompts for non-sudo commands through configuration
Special Handling for Sudo:
Sudo commands always require permission by default
This behavior can be configured but is separate from the general permission setting
Permission Response Options:
Allow: Grant permission for this operation
Allow for session: Grant permission for similar operations in this session
Deny: Reject the operation
Modify: Allow modifying the operation before execution
5.2 Command Execution Security
Sanitization:
All command inputs are sanitized to prevent injection attacks
Arguments are properly escaped and validated
Timeouts:
Commands have configurable timeouts to prevent hanging processes
Resource Limits:
Options to limit resource usage (CPU, memory) for commands
6. Error Handling
6.1 Error Types
PermissionError: Raised when permission is denied for an operation
CommandExecutionError: Raised when a command fails to execute
WebRequestError: Raised when a web request fails
TimeoutError: Raised when an operation times out
ValidationError: Raised when input validation fails
6.2 Error Handling Strategy
Graceful Degradation:
When a function fails, the system attempts to continue with alternative approaches
Clear error messages are provided to the user
Detailed Logging:
All errors are logged with detailed information
Optional debug mode for extensive logging
User Feedback:
Informative error messages returned to the user
Suggestions for resolving common errors
7. Testing Strategy
7.1 Unit Testing
Component Tests:
Tests for each individual function
Tests for error handling and edge cases
Mocked dependencies for isolated testing
Security Tests:
Tests for permission system
Tests for command sanitization
Tests for input validation
7.2 Integration Testing
Function Integration:
Tests for function detection and execution
Tests for proper function argument passing
Tests for result handling
Ollama Integration:
Tests for integration with the Ollama API
Tests with different models and configurations
7.3 System Testing
End-to-End Tests:
Complete workflow tests with realistic scenarios
Performance testing under various conditions
Security Auditing:
Systematic security review of command execution
Testing of permission system effectiveness
8. Implementation Guidelines
8.1 Coding Standards
Code Style:
Follow PEP 8 for Python code style
Use type hints for all functions
Document all functions with detailed docstrings
Error Handling:
Use appropriate exception classes
Provide informative error messages
Log all errors with context
Testing:
Write tests for all functions
Aim for high test coverage
Include edge cases and error conditions
8.2 Documentation
Code Documentation:
Detailed docstrings for all public functions
Module-level documentation explaining purpose and usage
Inline comments for complex code sections
User Documentation:
Installation and setup guide
API reference
Usage examples
Security best practices
9. Usage Examples
9.1 Basic Usage
python
from ollamatools import OllamaAgent
# Create agent with default settings
agent = OllamaAgent(model="llama3.1")
# Chat with automatic function detection
response = agent.chat("What's the weather like in San Francisco?")
print(response)
# Execute a system command
response = agent.chat("Show me the largest files in the current directory")
print(response)
# Generate documentation
response = agent.chat("Create documentation for a function that calculates prime numbers")
print(response)
9.2 Configuration
python
from ollamatools import OllamaAgent, Config
# Configure the agent
config = Config()
config.permission_prompts = False # Disable permission prompts
config.sudo_always_prompt = True # Still prompt for sudo commands
# Create agent with configuration
agent = OllamaAgent(model="llama3.1", config=config)
# Use configured agent
response = agent.chat("Count the number of files in /etc")
print(response)
10. Implementation Plan
10.1 Phase 1: Core Infrastructure
Set up project structure
Implement basic OllamaAgent
Implement permission system
Implement configuration management
10.2 Phase 2: System Tools
Implement command execution
Implement file operations
Add security features
Test system integration
10.3 Phase 3: Web Tools
Implement web request functions
Implement weather API
Implement web search
Test web integration
10.4 Phase 4: Documentation Tools
Implement markdown generation
Implement context extraction
Implement summarization
Test documentation integration
10.5 Phase 5: Testing and Refinement
Comprehensive testing
Performance optimization
Security auditing
Documentation completion
11. Extension Points
The library is designed to be extensible in the following ways:
Custom Tool Addition:
Create new tool modules by adding Python files to the tools directory
Use docstrings and type hints for automatic registration
Follow the existing tool pattern for consistency
Custom Permission Handlers:
Extend or replace the permission system with custom implementations
Implement the PermissionManager interface
Integration with Other Systems:
Add adapters for other AI systems
Extend to support additional platforms
12. Conclusion
This specification outlines the design and implementation of the OllamaTools library, a Python package that extends Ollama with semantic function calling capabilities. By following this specification, developers can create a robust, secure, and flexible library that enhances Ollama's capabilities with system command execution, web requests, and documentation utilities.
The implementation should prioritize security, ease of use, and extensibility, while maintaining compatibility with the existing Ollama ecosystem. The prompt-based permission system ensures security while allowing users to disable prompts for convenience when appropriate.
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