multiagent-consensus
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A framework for running multi-agent consensus processes using multiple LLMs
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# Multiagent Consensus
[](https://www.npmjs.com/package/multiagent-consensus)
[](https://opensource.org/licenses/MIT)
A framework for running multi-agent consensus processes using multiple Large Language Models (LLMs). This library enables a "jury" of AI models to debate and reach consensus on queries, providing more robust and balanced responses.
## Features
- 🤖 **Multiple LLM Support**: Compatible with various LLM providers through the Vercel AI SDK
- 🔄 **Configurable Consensus Methods**: Choose from majority, supermajority (75%), or unanimous agreement
- 🧠 **Multi-round Debates**: Models can debate in multiple rounds to refine their thinking
- 📊 **Detailed Results**: Get comprehensive metadata including confidence scores and processing time
- 🧪 **Flexible Output**: Customize output format (text, JSON) and content detail
- 🛠️ **Highly Configurable**: Set bias, system prompts, and customize debate parameters
## Installation
```bash
npm install multiagent-consensus
```
Or with yarn:
```bash
yarn add multiagent-consensus
```
## Basic Usage
```typescript
import { ConsensusEngine } from 'multiagent-consensus';
// Create a consensus engine with your configuration
const engine = new ConsensusEngine({
models: ['claude-3-haiku', 'gpt-4', 'palm-2'],
consensusMethod: 'majority', // 'majority', 'supermajority', or 'unanimous'
maxRounds: 2, // Maximum number of debate rounds
output: {
includeHistory: true, // Include debate history in result
includeMetadata: true, // Include metadata in result
format: 'text', // 'text' or 'json'
},
});
// Run a consensus process
async function getConsensus() {
const result = await engine.run('What is the best approach to solve climate change?');
console.log('Final Answer:', result.answer);
if (result.history) {
console.log('Debate History:');
result.history.forEach((round, i) => {
console.log(`\nRound ${i + 1}:`);
round.responses.forEach(response => {
console.log(`${response.model}: ${response.response}`);
});
});
}
console.log('\nMetadata:', result.metadata);
}
getConsensus();
```
## API Reference
### ConsensusEngine
The main class for running consensus processes.
```typescript
constructor(config: ConsensusConfig)
```
#### ConsensusConfig
| Parameter | Type | Description | Default |
| --------------- | -------------------------------------------- | --------------------------------- | ---------- |
| models | string[] | Array of model identifiers to use | Required |
| consensusMethod | 'majority' \| 'supermajority' \| 'unanimous' | Method to determine consensus | 'majority' |
| maxRounds | number | Maximum number of debate rounds | 3 |
| output | OutputConfig | Output configuration | See below |
#### OutputConfig
| Parameter | Type | Description | Default |
| --------------- | ---------------- | --------------------------- | ------- |
| includeHistory | boolean | Include full debate history | false |
| includeMetadata | boolean | Include metadata in result | true |
| format | 'text' \| 'json' | Output format | 'text' |
### ConsensusResult
The result of a consensus process.
| Property | Type | Description |
| -------- | -------------- | ------------------------------------------ |
| answer | string | The final consensus answer |
| models | string[] | Models that participated in the debate |
| metadata | ResultMetadata | Information about the process |
| history? | RoundData[] | Debate history (if includeHistory is true) |
#### ResultMetadata
| Property | Type | Description |
| ---------------- | ---------------------- | ---------------------------------------------- |
| totalTokens | number | Total tokens used across all models and rounds |
| processingTimeMs | number | Total processing time in milliseconds |
| rounds | number | Number of debate rounds conducted |
| consensusMethod | string | Method used to determine consensus |
| confidenceScores | Record<string, number> | Self-reported confidence per model |
## Consensus Methods
### Majority
Requires more than 50% of the models to agree on an answer. This is the most lenient consensus method and works well for straightforward queries.
### Supermajority
Requires at least 75% of the models to agree. This provides a more stringent threshold for consensus, useful for complex or controversial topics.
### Unanimous
Requires all models to agree completely. This is the strictest form of consensus and may require multiple debate rounds to achieve.
## Setting Up Environment Variables
For using this package with LLM providers, you'll need to set up environment variables for API keys:
```
OPENAI_API_KEY=your_openai_key_here
ANTHROPIC_API_KEY=your_anthropic_key_here
COHERE_API_KEY=your_cohere_key_here
```
We recommend using dotenv for local development:
```typescript
// In your application's entry point
import 'dotenv/config';
```
## Examples
### Custom Debate with Specific System Prompts
```typescript
const engine = new ConsensusEngine({
models: ['claude-3-sonnet', 'gpt-4', 'gpt-3.5-turbo'],
consensusMethod: 'supermajority',
maxRounds: 3,
modelConfig: {
'claude-3-sonnet': {
systemPrompt: 'You are a scientific expert focused on evidence-based reasoning.',
temperature: 0.5,
},
'gpt-4': {
systemPrompt: 'You are a philosophical thinker who considers ethical implications.',
temperature: 0.7,
},
'gpt-3.5-turbo': {
systemPrompt: 'You are a practical problem-solver focusing on realistic solutions.',
temperature: 0.3,
},
},
output: {
includeHistory: true,
format: 'json',
},
});
```
### Using Bias Presets
```typescript
const engine = new ConsensusEngine({
models: ['claude-3-opus', 'gpt-4', 'llama-3'],
consensusMethod: 'majority',
biasPresets: ['centrist', 'progressive', 'conservative'],
output: {
includeHistory: true,
},
});
```
## Running the Examples
The package includes a JavaScript example to demonstrate functionality.
### As a Package Consumer
When you've installed the published package as a dependency in your project:
```bash
# Install the package
npm install multiagent-consensus
# Copy the example file to your project
# Run the JavaScript example
node simple-consensus.js
```
### As a Package Developer
When developing the package itself:
```bash
# From the package directory
npm run build # Build the package first - this creates the dist directory
npm run example # Run the JavaScript example
```
The build step is crucial as it compiles the TypeScript source files into JavaScript in the `dist` directory. The example imports code from this directory, so if you make changes to the source files, you'll need to rebuild the package before running the example again.
## License
This project is licensed under the MIT License - see the LICENSE file for details.