SelfMoASeq

pip install -U swarms

def run(self, task: str) -> Dict[str, Any]

def get_metrics(self) -> Dict[str, Any]

def to_dict(self) -> Dict[str, Any]

def _generate_samples(self, task: str, num_samples: int) -> List[str]

def _format_aggregation_prompt(self, task: str, samples: List[str], best_so_far: Optional[str] = None) -> str

def _aggregate_window(self, task: str, window_samples: List[str], best_so_far: Optional[str] = None) -> str

from swarms import SelfMoASeq

# Initialize
moa_seq = SelfMoASeq(
    model_name="gpt-5.4",
    temperature=0.7,
    window_size=6,
    verbose=True,
    num_samples=4,
)

# Run
task = (
    "Describe an effective treatment plan for a patient with a broken rib. "
    "Include immediate care, pain management, expected recovery timeline, and potential complications to watch for."
)

result = moa_seq.run(task)
print(result)

from swarms import SelfMoASeq

# Initialize with medical-focused configuration
medical_moa = SelfMoASeq(
    model_name="claude-sonnet-4-6",
    temperature=0.8,  # Higher creativity for diverse medical perspectives
    window_size=8,    # Larger window for complex medical reasoning
    num_samples=12,   # More samples for comprehensive analysis
    max_loops=15,
    verbose=True,
    proposer_model_name="claude-sonnet-4-6",  # Use same model for consistency
    aggregator_model_name="claude-sonnet-4-6"
)

# Complex medical case
medical_case = """
Patient: 45-year-old female
Symptoms:
- Chest pain for 3 days, worse with deep breathing
- Shortness of breath
- Low-grade fever (100.2°F)
- Recent travel to Southeast Asia
- History of smoking (quit 5 years ago)

Vital signs: BP 140/90, HR 95, RR 22, O2 sat 94% on room air
Physical exam: Decreased breath sounds in right lower lobe, no JVD, no peripheral edema

Lab results pending: CBC, CMP, D-dimer, troponin
Chest X-ray: Small pleural effusion on right side

Provide a comprehensive differential diagnosis, immediate management plan,
and follow-up recommendations.
"""

result = medical_moa.run(medical_case)
print("Medical Diagnosis Analysis:")
print("=" * 50)
print(result["final_output"])
print(f"\nGenerated {len(result['all_samples'])} samples in {result['aggregation_steps']} iterations")
print(f"Execution time: {result['metrics']['execution_time_seconds']:.2f} seconds")

from swarms import SelfMoASeq

# Initialize with different models for proposer and aggregator
creative_moa = SelfMoASeq(
    model_name="gpt-5.4",  # Base model (fallback)
    temperature=1.2,  # High creativity for writing
    window_size=4,    # Smaller window for focused synthesis
    num_samples=6,    # Moderate number of samples
    max_loops=8,
    verbose=True,
    proposer_model_name="claude-sonnet-4-6",      # Creative model for generation
    aggregator_model_name="gpt-5.4", # Efficient model for synthesis
    max_retries=2,
    retry_delay=0.5
)

# Creative writing prompt
writing_prompt = """
Write a compelling opening chapter for a science fiction novel set in 2150.
The story should involve:
- A protagonist who discovers they can manipulate time in small ways
- A mysterious organization that's been monitoring them
- A world where AI and humans coexist but tensions are rising
- An unexpected twist that challenges the reader's assumptions

Focus on:
- Strong character development
- Immersive world-building
- A hook that makes readers want to continue
- Balance between action and character moments
"""

result = creative_moa.run(writing_prompt)
print("Creative Writing Result:")
print("=" * 40)
print(result["final_output"])
print(f"\nWriting samples generated: {len(result['all_samples'])}")
print(f"Synthesis iterations: {result['aggregation_steps']}")