@just-every/ensemble
v0.2.168
Published
LLM provider abstraction layer with unified streaming interface
Maintainers
Readme
@just-every/ensemble
A simple interface for interacting with multiple LLM providers during a single conversation.
🚀 Quick Demo
Try the interactive demos to see Ensemble in action:
npm run demoThis opens a unified demo interface at http://localhost:3000 with all demos:
Demo Interface

Navigate to http://localhost:3000 to access all demos through a unified interface.
See the demo README for detailed information about each demo.
Features
- 🤝 Unified Streaming Interface - Consistent event-based streaming across all providers
- 🔄 Model/Provider Rotation - Automatic model selection and rotation
- 🛠️ Advanced Tool Calling - Parallel/sequential execution, timeouts, and background tracking
- 📝 Automatic History Compaction - Handle unlimited conversation length with intelligent summarization
- 🤖 Agent Orientated - Advanced agent capabilities with verification and tool management
- 🔌 Multi-Provider Support - OpenAI, Anthropic, Google, DeepSeek, xAI, OpenRouter, ElevenLabs
- 🖼️ Multi-Modal - Support for text, images, embeddings, and voice generation
- 📊 Cost & Quota Tracking - Built-in usage monitoring and cost calculation
- 🎯 Smart Result Processing - Automatic summarization and truncation for long outputs
Model Updates (Dec 2025)
- OpenAI: Added GPT-5.2 (base + chat-latest + pro) and refreshed GPT-5.1/GPT-5/Codex pricing
- Anthropic: Claude 4.5 (Sonnet/Haiku, incl. 1M context) and Claude Opus 4.1
- Google: Gemini 3 (Pro/Flash/Ultra) and refreshed Gemini 2.5 pricing incl. image/TTS/native-audio
- xAI: Grok 4.1 Fast and Grok 4 Fast with tiered pricing; updated Grok 4/3/mini variants
*Codex-Max pricing reflects current published rates and may change if OpenAI updates pricing.
Installation
npm install @just-every/ensembleEnvironment Setup
Copy .env.example to .env and add your API keys:
cp .env.example .envAvailable API keys (add only the ones you need):
# LLM Providers
OPENAI_API_KEY=your-openai-key
ANTHROPIC_API_KEY=your-anthropic-key
GOOGLE_API_KEY=your-google-key
XAI_API_KEY=your-xai-key
DEEPSEEK_API_KEY=your-deepseek-key
OPENROUTER_API_KEY=your-openrouter-key
# Voice & Audio Providers
ELEVENLABS_API_KEY=your-elevenlabs-key
# Search Providers
BRAVE_API_KEY=your-brave-keyNote: You only need to configure API keys for the providers you plan to use. The system will automatically select available providers based on configured keys.
Quick Start
import { ensembleRequest, ensembleResult } from '@just-every/ensemble';
const messages = [
{ type: 'message', role: 'user', content: 'How many of the letter "e" is there in "Ensemble"?' }
];
// Perform initial request
for await (const event of ensembleRequest(messages)) {
if (event.type === 'response_output') {
// Save out to continue conversation
messages.push(event.message);
}
}
// Create a validator agent
const validatorAgent = {
instructions: 'Please validate that the previous response is correct',
modelClass: 'code',
};
// Continue conversation with new agent
const stream = ensembleRequest(messages, validatorAgent);
// Alternative method of collecting response
const result = await ensembleResult(stream);
console.log('Validation Result:', {
message: result.message,
cost: result.cost,
completed: result.completed,
duration: result.endTime
? result.endTime.getTime() - result.startTime.getTime()
: 0,
messageIds: Array.from(result.messageIds),
});Documentation
- Tool Execution Guide - Advanced tool calling features
- Interactive Demos - Web-based demos for core features
- Generated API Reference with
npm run docs
Run npm run docs to regenerate the HTML documentation.
Core Concepts
Tools
Define tools that LLMs can call:
const agent = {
model: 'o3',
tools: [{
definition: {
type: 'function',
function: {
name: 'get_weather',
description: 'Get weather for a location',
parameters: {
type: 'object',
properties: {
location: { type: 'string' }
},
required: ['location']
}
}
},
function: async (location: string) => {
return `Weather in ${location}: Sunny, 72°F`;
}
}]
};Streaming Events
All providers emit standardized events:
message_start/message_delta/message_complete- Message streamingtool_start/tool_delta/tool_done- Tool executioncost_update- Token usage and cost trackingerror- Error handling
Agent Configuration
Configure agent behavior with these optional properties:
const agent = {
model: 'claude-4-sonnet',
maxToolCalls: 200, // Maximum total tool calls (default: 200)
maxToolCallRoundsPerTurn: 5, // Maximum sequential rounds of tool calls (default: Infinity)
tools: [...], // Available tools for the agent
modelSettings: { // Provider-specific settings
temperature: 0.7,
max_tokens: 4096
}
};Key configuration options:
maxToolCalls- Limits the total number of tool calls across all roundsmaxToolCallRoundsPerTurn- Limits sequential rounds where each round can have multiple parallel tool callsmodelSettings- Provider-specific parameters like temperature, max_tokens, etc.
Advanced Features
- Parallel Tool Execution - Tools run concurrently by default within each round
- Sequential Mode - Enforce one-at-a-time execution
- Timeout Handling - Automatic timeout with background tracking
- Result Summarization - Long outputs are intelligently summarized
- Abort Signals - Graceful cancellation support
Voice Generation
Generate natural-sounding speech from text using Text-to-Speech models:
import { ensembleVoice, ensembleVoice } from '@just-every/ensemble';
// Simple voice generation
const audioData = await ensembleVoice('Hello, world!', {
model: 'tts-1' // or 'gemini-2.5-flash-preview-tts'
});
// Voice generation with options
const audioData = await ensembleVoice('Welcome to our service', {
model: 'tts-1-hd'
}, {
voice: 'nova', // Voice selection
speed: 1.2, // Speech speed (0.25-4.0)
response_format: 'mp3' // Audio format
});
// Streaming voice generation
for await (const event of ensembleVoice('Long text...', {
model: 'gemini-2.5-pro-preview-tts'
})) {
if (event.type === 'audio_stream') {
// Process audio chunk
processAudioChunk(event.data);
}
}Supported Voice Models:
- OpenAI:
tts-1,tts-1-hd - Google Gemini:
gemini-2.5-flash-preview-tts,gemini-2.5-pro-preview-tts
Image generation
Use OpenAI GPT-Image-1 (or the new cost-efficient GPT-Image-1 Mini) or Google Gemini 2.5 Flash Image (Preview):
import { ensembleImage } from '@just-every/ensemble';
const images = await ensembleImage('A serene lake at dawn', { model: 'gemini-2.5-flash-image-preview' }, { size: 'portrait' });- ElevenLabs:
eleven_multilingual_v2,eleven_turbo_v2_5
Development
# Install dependencies
npm install
# Run tests
npm test
# Build
npm run build
# Generate docs
npm run docs
# Lint
npm run lintAdditional image providers
New providers added
- Fireworks AI (FLUX family: Kontext/Pro/Schnell) – async APIs with result polling. Docs: Fireworks Image API.
- Stability AI (Stable Image Ultra/SDXL) – REST v2beta endpoints supporting text-to-image and image-to-image.
- Runway Gen-4 Image – via FAL.ai.
- Recraft v3 – via FAL.ai (supports text-to-vector and vector-style outputs).
Environment
FIREWORKS_API_KEY=your_key
STABILITY_API_KEY=your_key
FAL_KEY=your_keyFallbacks
If Fireworks returns 401/403 or is not configured, requests for Flux-family models automatically fall back to FAL.ai equivalents when
FAL_KEYis set.Luma Photon (official): set
LUMA_API_KEYand useluma-photon-1orluma-photon-flash-1.Ideogram 3.0 (official): set
IDEOGRAM_API_KEYand useideogram-3.0.Midjourney v7 (3rd-party): set
MIDJOURNEY_API_KEY(orKIE_API_KEY) and optionalMJ_API_BASE; usemidjourney-v7.
Notes
- Gemini Flash Image does not expose hard size/AR controls; we add soft prompt hints and return the image unchanged.
- Luma Photon and Ideogram return URLs; we pass them through without altering pixels.
Architecture
Ensemble provides a unified interface across multiple LLM providers:
- Provider Abstraction - All providers extend
BaseModelProvider - Event Streaming - Consistent events across all providers
- Tool System - Automatic parameter mapping and execution
- Message History - Intelligent conversation management
- Cost Tracking - Built-in usage monitoring
Contributing
Contributions are welcome! Please:
- Fork the repository
- Create a feature branch
- Add tests for new features
- Submit a pull request
Troubleshooting
Provider Issues
- Ensure API keys are set correctly
- Check rate limits for your provider
- Verify model names match provider expectations
Tool Calling
- Tools must follow the OpenAI function schema
- Ensure tool functions are async
- Check timeout settings for long-running tools
Streaming Issues
- Verify network connectivity
- Check for provider-specific errors in events
- Enable debug logging with
DEBUG=ensemble:*
License
MIT
