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🤖 Agentic AutoML - Complete Agent Package
This package contains all components for the autonomous multi-agent AutoML system.
Agents:
1. Data Quality Agent - Detects and fixes dataset issues
2. Preprocessing Agent - Smart encoding and scaling
3. Feature Engineer Agent - Feature creation and selection
4. Model Strategy Agent - Algorithm selection
5. Hyperparameter Agent - Optuna optimization
6. Training Validator Agent - Bias-variance analysis
7. Evaluation Agent - Final approval gate
8. Visualization Agent - Explainability charts
9. Deployment Agent - Production inference
"""
# Base components
from .base import (
BaseAgent,
AgentResult,
AgentStatus,
AgentMessage,
MessageType,
Phase,
AgentRegistry
)
# Memory and orchestration
from .memory import AgentMemory, StateEntry, Artifact
from .orchestrator import AgentOrchestrator, PipelineStatus
# Data agents
from .data_quality import DataQualityAgent
from .preprocessing import PreprocessingAgent
from .feature_engineer import FeatureEngineerAgent
# Model agents
from .model_strategy import ModelStrategyAgent
from .hyperparam import HyperparamAgent
from .training_validator import TrainingValidatorAgent
# Validation agents
from .evaluation import EvaluationAgent
from .visualization import VisualizationAgent
from .deployment import DeploymentAgent
def create_agentic_pipeline() -> AgentOrchestrator:
"""
Factory function to create a fully configured agentic AutoML pipeline.
Returns:
AgentOrchestrator with all agents registered
"""
orchestrator = AgentOrchestrator()
# Register all agents
orchestrator.register_agent("data_quality", DataQualityAgent())
orchestrator.register_agent("preprocessing", PreprocessingAgent())
orchestrator.register_agent("feature_engineer", FeatureEngineerAgent())
orchestrator.register_agent("model_strategy", ModelStrategyAgent())
orchestrator.register_agent("hyperparam", HyperparamAgent())
orchestrator.register_agent("training_validator", TrainingValidatorAgent())
orchestrator.register_agent("evaluation", EvaluationAgent())
orchestrator.register_agent("visualization", VisualizationAgent())
orchestrator.register_agent("deployment", DeploymentAgent())
return orchestrator
__all__ = [
# Base
'BaseAgent',
'AgentResult',
'AgentStatus',
'AgentMessage',
'MessageType',
'Phase',
'AgentRegistry',
# Memory
'AgentMemory',
'StateEntry',
'Artifact',
# Orchestrator
'AgentOrchestrator',
'PipelineStatus',
# Agents
'DataQualityAgent',
'PreprocessingAgent',
'FeatureEngineerAgent',
'ModelStrategyAgent',
'HyperparamAgent',
'TrainingValidatorAgent',
'EvaluationAgent',
'VisualizationAgent',
'DeploymentAgent',
# Factory
'create_agentic_pipeline'
]
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