Architecture Overview¶

This document provides a high-level overview of the Gemini Agent Framework's architecture and design principles.

Core Components¶

1. Agent Class¶

The central component of the framework, responsible for: - Managing tool registration and execution - Handling API communication with Gemini - Managing agent state and variables - Processing prompts and responses

class Agent:
    def __init__(self, api_key: str, tools: List[Callable] = None, model_name: str = "gemini-1.5-flash"):
        # Initialize agent with API key and tools
        pass

    def prompt(self, user_prompt: str, ...) -> Any:
        # Process user prompt and return response
        pass

2. Tool System¶

The tool system allows users to define custom functions that the agent can use:

@Agent.description("Tool description")
@Agent.parameters({
    'param': {'type': type, 'description': 'Parameter description'}
})
def tool_function(param: type) -> return_type:
    # Tool implementation
    pass

Tool Registration¶

Tools are registered using decorators that: 1. Store tool metadata 2. Validate tool parameters 3. Map Python types to Gemini types 4. Handle tool execution

3. Variable Management¶

The framework includes a robust variable management system:

def set_variable(self, name: str, value: Any, description: str = "", type_hint: type = None) -> str:
    # Store variable with metadata
    pass

def get_variable(self, name: str) -> Any:
    # Retrieve stored variable
    pass

Variable Storage¶

Variables are stored with: - Value - Description - Type information - Creation timestamp - Metadata

Data Flow¶

1. Prompt Processing¶

graph LR
    A[User Prompt] --> B[Agent]
    B --> C[Tool Selection]
    C --> D[Tool Execution]
    D --> E[Response Generation]
    E --> F[User Response]

2. Tool Execution¶

graph LR
    A[Tool Call] --> B[Parameter Validation]
    B --> C[Type Conversion]
    C --> D[Function Execution]
    D --> E[Result Processing]
    E --> F[Response]

Type System¶

1. Python to Gemini Type Mapping¶

Python Type	Gemini Type	Description
str	STRING	Text data
int	INTEGER	Whole numbers
float	NUMBER	Decimal numbers
bool	BOOLEAN	True/False values
list	ARRAY	Ordered collections
dict	OBJECT	Key-value pairs

2. Type Validation¶

The framework includes: - Runtime type checking - Automatic type conversion - Error handling for type mismatches

Error Handling¶

1. Error Types¶

The framework handles: - API errors - Tool execution errors - Type conversion errors - Variable management errors

2. Error Recovery¶

Features include: - Graceful error handling - Error reporting - Recovery mechanisms - User feedback

Security¶

1. API Key Management¶

Secure storage
Environment variable support
No hardcoding

2. Input Validation¶

Parameter validation
Type checking
Sanitization

Performance¶

1. Caching¶

Tool result caching
Variable caching
Response caching

2. Optimization¶

Batch processing
Parallel execution
Resource management

Extensibility¶

1. Custom Tools¶

Users can create custom tools by: 1. Defining functions 2. Adding decorators 3. Specifying parameters 4. Implementing logic

2. Custom Types¶

Support for: - Custom type definitions - Type conversion - Validation rules

Future Considerations¶

1. Planned Features¶

Async support
Streaming responses
Custom model support
Enhanced caching

2. Architecture Improvements¶

Modular design
Plugin system
Enhanced error handling
Better type system

Contributing¶

1. Code Structure¶

gemini_agent_framework/
├── src/
│   └── gemini_agent/
│       ├── __init__.py
│       └── agent.py
├── tests/
├── docs/
└── examples/

2. Development Guidelines¶

Follow PEP 8
Write tests
Update documentation
Use type hints