lokutor-orchestrator
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- License — License: MIT
- Description — Repository has a description
- Active repo — Last push 0 days ago
- Low visibility — Only 8 GitHub stars
Code Gecti
- Code scan — Scanned 1 files during light audit, no dangerous patterns found
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- Permissions — No dangerous permissions requested
This tool is a high-performance orchestration engine written in Go designed to build AI-driven voice agents. It manages the complex lifecycle of voice interactions by seamlessly bridging Speech-to-Text, Large Language Models, and Text-to-Speech systems.
Security Assessment
Risk Rating: Low
The automated code scan found no dangerous patterns, no hardcoded secrets, and confirmed that the tool requests no inherently dangerous system permissions. However, because this is an orchestration library, it inherently makes external network requests to various third-party AI providers (such as Groq, OpenAI, Deepgram, and Anthropic) to function. You will be passing sensitive audio data and API keys through this library to those external services. The local risk is low, but standard precautions should be taken to secure your environment variables and ensure your chosen external providers meet your data privacy requirements.
Quality Assessment
The project is distributed under the permissive and standard MIT license. Based on repository activity, it appears to be an actively maintained project, having received code updates very recently. The primary concern is low community visibility. With only 8 GitHub stars, the tool is very new and has not yet undergone broad public scrutiny or widespread enterprise adoption. This means you may be relying heavily on the primary maintainers for bug fixes and support.
Verdict
Safe to use, provided you are comfortable adopting a low-visibility project and managing external API key security properly.
Why We Built One of the First Open-Source Voice AI Orchestrators in Go. Lokutor.
Lokutor Orchestrator
High-performance voice orchestration engine for building AI-driven voice agents.
Lokutor Orchestrator is a production-grade Go library for building voice-powered applications. It handles the complex lifecycle of voice interactions—bridging Speech-to-Text (STT), Large Language Models (LLM), and Text-to-Speech (TTS) into a seamless, low-latency experience.
Features
- Full-duplex voice orchestration (v1.3): real-time capture and playback with native 44.1kHz 16-bit PCM.
- Barge-in support: interrupts the agent promptly when the user begins speaking.
- Predictive audio buffering: prevents clipping of the start of user speech.
- High-performance echo suppression: correlation filters reduce self-interruption.
- Pluggable architecture: swap STT, LLM, and TTS implementations with minimal changes.
- Tool Calling (v1.4): Native support for function calling with automatic TTS suppression and recursive LLM triggers.
- Instrumentation: stage-by-stage latency tracking (STT, LLM, TTS, end-to-end).
Quick Start
1. Installation
go get github.com/lokutor-ai/lokutor-orchestrator
2. Run the Example Agent (CLI Demo)
Configure environment: Create a
.envfile in the root:STT_PROVIDER=groq|openai|deepgram|assemblyai LLM_PROVIDER=groq|openai|anthropic|google GROQ_API_KEY=your_key OPENAI_API_KEY=your_key LOKUTOR_API_KEY=your_key AGENT_LANGUAGE=es # en, fr, de, etc.Run the agent:
go run cmd/agent/main.go
3. Basic Library Usage (ManagedStream)
func main() {
// Initialize High-Performance Providers
stt := sttProvider.NewDeepgramSTT(apiKey)
llm := llmProvider.NewGroqLLM(apiKey, "meta-llama/llama-4-scout-17b-16e-instruct")
tts := ttsProvider.NewLokutorTTS(apiKey)
// Configure VAD & Orchestrator
vad := orchestrator.NewRMSVAD(0.02, 150*time.Millisecond)
orch := orchestrator.NewWithVAD(stt, llm, tts, vad, orchestrator.DefaultConfig())
// Start a duplex managed stream
session := orch.NewSessionWithDefaults("session_01")
stream := orch.NewManagedStream(context.Background(), session)
// Listen for events
for event := range stream.Events() {
switch event.Type {
case orchestrator.UserSpeaking:
stopSpeaker() // Fast barge-in
case orchestrator.AudioChunk:
playChunk(event.Data.([]byte))
}
}
}
Provider Ecosystem
Lokutor supports all major infrastructure providers out of the box:
- LLM: Groq (Llama), OpenAI (GPT-4), Anthropic (Claude), Google (Gemini)
- STT: Groq (Whisper), OpenAI (Whisper), Deepgram (Nova-2), AssemblyAI
- TTS: Lokutor (Versa - optimized for minimal Time-To-First-Byte)
Architecture
┌─────────────┐
│ Raw Mic In │
└──────┬──────┘
│
▼
┌─────────────────────────────────┐
│ Lokutor ManagedStream │
│ ┌────────────┐ ┌──────────┐ │
│ │ Echo Guard │──▶│ VAD │ │
│ └────────────┘ └──────────┘ │
│ │ │ │
│ ▼ ▼ │
│ ┌────────────┐ ┌──────────┐ │
│ │ STT Stream │◀──│ Buffers │ │
│ └────────────┘ └──────────┘ │
│ │ │ │
│ ▼ ▼ │
│ ┌────────────┐ ┌──────────┐ │
│ │ LLM Logic │──▶│ TTS Gen │─┐│
│ └────────────┘ └──────────┘ ││
└────────────────────────│────────┘
│
▼
┌───────────────────┐
│ Adaptive Output │
└───────────────────┘
Strategies for High-Quality Interactions
Recommendations to improve conversational quality:
- Use short filler utterances when model latency exceeds a threshold to maintain user engagement.
- Include prosody markers in system prompts to enable dynamic TTS adjustments.
- Use brief backchannel confirmations during extended user turns to indicate attention.
- Acknowledge interruptions gracefully to preserve conversational continuity.
Technical Details
Echo Suppression
The orchestrator tracks every sample sent to the speaker and uses sliding-window correlation search on mic input. This prevents "self-interruption" by identifying when the mic hears the agent's own voice.
Latency Breakdown
Every turn includes detailed instrumentation available via stream.GetLatencyBreakdown():
User-to-STT: Time from user stop to final transcript.TTFB: User stop to first audio sample.E2E: Full user-to-speaker turn-around.
Documentation
For more detailed guides, check out:
License
MIT. Built with ❤️ by the Lokutor AI team.
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