orka.agents.agents module
Basic Agents Module
This module implements simple rule-based agents for the OrKa framework that don’t rely on external APIs or complex ML models. These agents serve as building blocks for basic decision-making and classification tasks within orchestrated workflows.
The agents in this module include: - BinaryAgent: Makes true/false decisions based on simple text patterns - ClassificationAgent: Categorizes input into predefined classes using keyword matching
These simple agents can be used for: - Quick prototyping of workflows - Testing the orchestration infrastructure - Implementing basic decision logic without external dependencies - Serving as fallbacks when more complex agents fail or are unavailable
Both agent types inherit from the BaseAgent class and implement the required run() method with simple rule-based logic.
- class orka.agents.agents.BinaryAgent(agent_id, prompt, queue, **kwargs)[source]
Bases:
LegacyBaseAgentA simple agent that performs binary (true/false) decisions.
This agent processes input text and returns either “true” or “false” based on simple text pattern matching. It demonstrates the most basic form of decision-making in the OrKa framework.
The current implementation checks for the presence of ‘yes’, ‘true’, or ‘correct’ in the input to determine if the result should be true. This can be extended to more complex pattern matching or rule-based decision logic.
- run(input_data)[source]
Make a binary decision based on text content.
- Parameters:
input_data (dict) – Input containing text to analyze, expected to have an ‘input’ field with the text content.
- Returns:
‘true’ if input contains positive indicators, ‘false’ otherwise.
- Return type:
str
Note
This is a simplified implementation for demonstration purposes. In production, this would typically use more sophisticated rules or a trained classifier.
- class orka.agents.agents.ClassificationAgent(agent_id, prompt, queue, **kwargs)[source]
Bases:
LegacyBaseAgentA simple agent that performs multi-class classification.
This agent categorizes input text into predefined classes based on keyword matching. It demonstrates how to implement basic classification functionality in the OrKa framework.
The current implementation uses a simple rule-based approach to classify input into ‘cat’ or ‘dog’ categories based on the presence of specific question words, but could be extended to support more sophisticated classification schemes.