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@just-every/ensemble

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LLM provider abstraction layer with unified streaming interface

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# @just-every/ensemble [![npm version](https://badge.fury.io/js/@just-every%2Fensemble.svg)](https://www.npmjs.com/package/@just-every/ensemble) [![GitHub Actions](https://github.com/just-every/ensemble/workflows/Release/badge.svg)](https://github.com/just-every/ensemble/actions) A simple interface for interacting with multiple LLM providers during a single conversation. ## 🚀 Quick Demo Try the interactive demos to see Ensemble in action: ```bash npm run demo ``` This opens a unified demo interface at http://localhost:3000 with all demos: ### Demo Interface ![Ensemble Demos Interface](demo/screenshots/demo-overview.png) Navigate to http://localhost:3000 to access all demos through a unified interface. See the [demo README](demo/README.md) 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 ## Installation ```bash npm install @just-every/ensemble ``` ## Environment Setup Copy `.env.example` to `.env` and add your API keys: ```bash cp .env.example .env ``` Available API keys (add only the ones you need): ```bash # 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-key ``` **Note**: 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 ```typescript 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 === 'message_complete') { // Write response console.log(event.content); } else 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](docs/tool-execution.md) - Advanced tool calling features - [Interactive Demos](demo/) - Web-based demos for core features - Generated [API Reference](docs/api) with `npm run docs` Run `npm run docs` to regenerate the HTML documentation. ## Core Concepts ### Tools Define tools that LLMs can call: ```typescript 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 streaming - `tool_start` / `tool_delta` / `tool_done` - Tool execution - `cost_update` - Token usage and cost tracking - `error` - Error handling ### Agent Configuration Configure agent behavior with these optional properties: ```typescript 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 rounds - `maxToolCallRoundsPerTurn` - Limits sequential rounds where each round can have multiple parallel tool calls - `modelSettings` - 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: ```typescript 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` - ElevenLabs: `eleven_multilingual_v2`, `eleven_turbo_v2_5` ## Development ```bash # Install dependencies npm install # Run tests npm test # Build npm run build # Generate docs npm run docs # Lint npm run lint ``` ## Architecture Ensemble provides a unified interface across multiple LLM providers: 1. **Provider Abstraction** - All providers extend `BaseModelProvider` 2. **Event Streaming** - Consistent events across all providers 3. **Tool System** - Automatic parameter mapping and execution 4. **Message History** - Intelligent conversation management 5. **Cost Tracking** - Built-in usage monitoring ## Contributing Contributions are welcome! Please: 1. Fork the repository 2. Create a feature branch 3. Add tests for new features 4. 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