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β•‘ β•‘
β•‘ β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•—β–ˆβ–ˆβ–ˆβ•— β–ˆβ–ˆβ•—β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•—β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•—β–ˆβ–ˆβ–ˆβ•— β–ˆβ–ˆβ–ˆβ•—β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•— β–ˆβ–ˆβ•— β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•— β•‘
β•‘ β–ˆβ–ˆβ•”β•β•β•β•β•β–ˆβ–ˆβ–ˆβ–ˆβ•— β–ˆβ–ˆβ•‘β–ˆβ–ˆβ•”β•β•β•β•β•β–ˆβ–ˆβ•”β•β•β•β•β•β–ˆβ–ˆβ–ˆβ–ˆβ•— β–ˆβ–ˆβ–ˆβ–ˆβ•‘β–ˆβ–ˆβ•”β•β•β–ˆβ–ˆβ•—β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ•”β•β•β•β•β• β•‘
β•‘ β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•— β–ˆβ–ˆβ•”β–ˆβ–ˆβ•— β–ˆβ–ˆβ•‘β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•—β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•— β–ˆβ–ˆβ•”β–ˆβ–ˆβ–ˆβ–ˆβ•”β–ˆβ–ˆβ•‘β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•”β•β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•— β•‘
β•‘ β–ˆβ–ˆβ•”β•β•β• β–ˆβ–ˆβ•‘β•šβ–ˆβ–ˆβ•—β–ˆβ–ˆβ•‘β•šβ•β•β•β•β–ˆβ–ˆβ•‘β–ˆβ–ˆβ•”β•β•β• β–ˆβ–ˆβ•‘β•šβ–ˆβ–ˆβ•”β•β–ˆβ–ˆβ•‘β–ˆβ–ˆβ•”β•β•β–ˆβ–ˆβ•—β–ˆβ–ˆβ•‘ β–ˆβ–ˆβ•”β•β•β• β•‘
β•‘ β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•—β–ˆβ–ˆβ•‘ β•šβ–ˆβ–ˆβ–ˆβ–ˆβ•‘β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•‘β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•—β–ˆβ–ˆβ•‘ β•šβ•β• β–ˆβ–ˆβ•‘β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•”β•β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•—β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•— β•‘
β•‘ β•šβ•β•β•β•β•β•β•β•šβ•β• β•šβ•β•β•β•β•šβ•β•β•β•β•β•β•β•šβ•β•β•β•β•β•β•β•šβ•β• β•šβ•β•β•šβ•β•β•β•β•β• β•šβ•β•β•β•β•β•β•β•šβ•β•β•β•β•β•β• β•‘
β•‘ β•‘
β•‘ Multi-Agent Orchestration Primitives for CASCADE-LATTICE β•‘
β•‘ β•‘
β•‘ "Wrap anything. Orchestrate everything. Deliberate together." β•‘
β•‘ β•‘
β•šβ•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•
ENSEMBLE provides model-agnostic patterns for multi-agent systems:
Scarecrow: Universal model wrapper (the null-port pattern)
Council: N models + deliberation + consensus
EnsembleVoting: Aggregation strategies
Works with ANY model framework:
- PyTorch, JAX, TensorFlow
- Hugging Face Transformers
- OpenAI API, Anthropic API
- Custom models, RL policies, vision systems
USAGE:
>>> from cascade.ensemble import Scarecrow, Council
>>>
>>> # Wrap your models (any framework)
>>> llm1 = Scarecrow().plug_model(my_gpt_model)
>>> llm2 = Scarecrow().plug_model(my_claude_model)
>>> llm3 = Scarecrow().plug_model(my_local_llama)
>>>
>>> # Create a deliberative council
>>> council = Council(consensus='weighted')
>>> council.add_brain(llm1, name="gpt")
>>> council.add_brain(llm2, name="claude")
>>> council.add_brain(llm3, name="llama")
>>>
>>> # All 3 models deliberate together
>>> result = council.forward({'text': 'What is consciousness?'})
>>> print(result['consensus']) # The agreed answer
>>> print(result['deliberation']) # Who said what
>>>
>>> # With HOLD for human oversight
>>> from cascade.hold import Hold
>>> council.enable_hold()
>>> # Now humans can intervene at council decisions
PATTERNS:
Scarecrow: "If I only had a brain!" - Wrapper with no opinion on what's inside
Council: N experts deliberate to consensus
Voting: Aggregation math (majority, weighted, confidence)
INTEGRATES WITH:
cascade.hold - Human-in-the-loop at council level
cascade.core - Causation tracking of multi-agent decisions
"""
from ensemble.scarecrow import (
Scarecrow,
ModelType,
)
from ensemble.council import (
Council,
ConsensusMethod,
)
from ensemble.voting import (
EnsembleVoting,
)
__all__ = [
# Core wrapper
"Scarecrow",
"ModelType",
# Council orchestration
"Council",
"ConsensusMethod",
# Voting strategies
"EnsembleVoting",
]