# LLM Council Examples

This page provides examples demonstrating the LLM Council pattern, inspired by Andrej Karpathy's llm-council implementation. The LLM Council uses multiple specialized AI agents that:

1. Each respond independently to queries
2. Review and rank each other's anonymized responses
3. Have a Chairman synthesize all responses into a final comprehensive answer

## Example Files

All LLM Council examples are located in the [`examples/multi_agent/llm_council_examples/`](https://github.com/kyegomez/swarms/tree/master/examples/multi_agent/llm_council_examples) directory.

### Marketing & Business

- **[marketing_strategy_council.py](https://github.com/kyegomez/swarms/blob/master/examples/multi_agent/llm_council_examples/marketing_strategy_council.py)** - Marketing strategy analysis and recommendations
- **[business_strategy_council.py](https://github.com/kyegomez/swarms/blob/master/examples/multi_agent/llm_council_examples/business_strategy_council.py)** - Comprehensive business strategy development

### Finance & Investment

- **[finance_analysis_council.py](https://github.com/kyegomez/swarms/blob/master/examples/multi_agent/llm_council_examples/finance_analysis_council.py)** - Financial analysis and investment recommendations
- **[etf_stock_analysis_council.py](https://github.com/kyegomez/swarms/blob/master/examples/multi_agent/llm_council_examples/etf_stock_analysis_council.py)** - ETF and stock analysis with portfolio recommendations

### Medical & Healthcare

- **[medical_treatment_council.py](https://github.com/kyegomez/swarms/blob/master/examples/multi_agent/llm_council_examples/medical_treatment_council.py)** - Medical treatment recommendations and care plans
- **[medical_diagnosis_council.py](https://github.com/kyegomez/swarms/blob/master/examples/multi_agent/llm_council_examples/medical_diagnosis_council.py)** - Diagnostic analysis based on symptoms

### Technology & Research

- **[technology_assessment_council.py](https://github.com/kyegomez/swarms/blob/master/examples/multi_agent/llm_council_examples/technology_assessment_council.py)** - Technology evaluation and implementation strategy
- **[research_analysis_council.py](https://github.com/kyegomez/swarms/blob/master/examples/multi_agent/llm_council_examples/research_analysis_council.py)** - Comprehensive research analysis on complex topics

### Legal

- **[legal_analysis_council.py](https://github.com/kyegomez/swarms/blob/master/examples/multi_agent/llm_council_examples/legal_analysis_council.py)** - Legal implications and compliance analysis

## Basic Usage Pattern

All examples follow the same pattern:

```python
from swarms.structs.llm_council import LLMCouncil

# Create the council
council = LLMCouncil(verbose=True)

# Run a query
result = council.run("Your query here")

# Access results
print(result["final_response"])  # Chairman's synthesized answer
print(result["original_responses"])  # Individual member responses
print(result["evaluations"])  # How members ranked each other
```

## Running Examples

Run any example directly:

```bash
python examples/multi_agent/llm_council_examples/marketing_strategy_council.py
python examples/multi_agent/llm_council_examples/finance_analysis_council.py
python examples/multi_agent/llm_council_examples/medical_diagnosis_council.py
```

## Key Features

| Feature              | Description                                                                                             |
|----------------------|---------------------------------------------------------------------------------------------------------|
| **Multiple Perspectives** | Each council member (GPT-5.1, Gemini, Claude, Grok) provides unique insights                         |
| **Peer Review**           | Members evaluate and rank each other's responses anonymously                                         |
| **Synthesis**             | Chairman combines the best elements from all responses                                               |
| **Transparency**          | See both individual responses and evaluation rankings                                                |


## Council Members

The default council consists of:

| Council Member                 | Description                   |
|-------------------------------|-------------------------------|
| **GPT-5.1-Councilor**         | Analytical and comprehensive  |
| **Gemini-3-Pro-Councilor**    | Concise and well-processed    |
| **Claude-Sonnet-4.5-Councilor** | Thoughtful and balanced     |
| **Grok-4-Councilor**          | Creative and innovative       |

## Customization

You can create custom council members:

```python
from swarms import Agent
from swarms.structs.llm_council import LLMCouncil, get_gpt_councilor_prompt

custom_agent = Agent(
    agent_name="Custom-Councilor",
    system_prompt=get_gpt_councilor_prompt(),
    model_name="gpt-4.1",
    max_loops=1,
)

council = LLMCouncil(
    council_members=[custom_agent, ...],
    chairman_model="gpt-5.1",
    verbose=True
)
```

## Documentation

For complete API reference and detailed documentation, see the [LLM Council Reference Documentation](../swarms/structs/llm_council.md).