Rakam System Core

The core package of Rakam Systems providing foundational interfaces, base components, and utilities.

Overview

rakam-systems-core is the foundation of the Rakam Systems framework. It provides:

• Base Component: Abstract base class with lifecycle management
• Interfaces: Standard interfaces for agents, tools, vector stores, embeddings, and loaders
• Configuration System: YAML/JSON configuration loading and validation
• Tracking System (experimental): Input/output tracking for debugging and evaluation
• Logging Utilities (experimental): Structured logging with color support

This package is required by both rakam-systems-agent and rakam-systems-vectorstore.

Installation

pip install rakam-systems-core

Key Components

BaseComponent

All components extend BaseComponent which provides:

• Lifecycle management with setup() and shutdown() methods
• Auto-initialization via __call__
• Context manager support
• Built-in evaluation harness

from rakam_systems_core.ai_core.base import BaseComponent

class MyComponent(BaseComponent):
    def setup(self):
        super().setup()
        # Initialize resources

    def shutdown(self):
        # Clean up resources
        super().shutdown()

    def run(self, *args, **kwargs):
        # Main logic
        pass

Interfaces

Standard interfaces for building AI systems:

• AgentComponent: AI agents with sync/async support
• ToolComponent: Callable tools for agents
• LLMGateway: LLM provider abstraction
• VectorStore: Vector storage interface
• EmbeddingModel: Text embedding interface
• Loader: Document loading interface
• Chunker: Text chunking interface

from rakam_systems_core.ai_core.interfaces.agent import AgentComponent
from rakam_systems_core.ai_core.interfaces.tool import ToolComponent
from rakam_systems_core.ai_core.interfaces.vectorstore import VectorStore

Configuration System

Load and validate configurations from YAML files:

from rakam_systems_core.ai_core.config_loader import ConfigurationLoader

loader = ConfigurationLoader()
config = loader.load_from_yaml("agent_config.yaml")
agent = loader.create_agent("my_agent", config)

Tracking System

Track inputs and outputs for debugging:

from rakam_systems_core.ai_core.tracking import TrackingMixin

class MyAgent(TrackingMixin, BaseAgent):
    pass

agent.enable_tracking(output_dir="./tracking")
# Use agent...
agent.export_tracking_data(format='csv')

Usage in Other Packages

Agent Package

# rakam-systems-agent uses core interfaces
from rakam_systems_core.ai_core.interfaces.agent import AgentComponent
from rakam_systems_agent import BaseAgent

agent = BaseAgent(name="my_agent", model="openai:gpt-4o")

Vectorstore Package

# rakam-systems-vectorstore uses core interfaces
from rakam_systems_core.ai_core.interfaces.vectorstore import VectorStore
from rakam_systems_vectorstore import ConfigurablePgVectorStore

store = ConfigurablePgVectorStore(config=config)

Documentation

For full API reference and architecture details, see the official documentation.

Development

This package contains only interfaces and utilities. To contribute:

1. Install in editable mode: pip install rakam-systems-core
2. Make changes to interfaces or utilities
3. Ensure backward compatibility with agent and vectorstore packages
4. Update version in pyproject.toml

License

Apache 2.0