TEN-framework/ten-framework

Features

• Real-Time Conversational AI Frameworks - Provides a low-latency framework for building multimodal conversational agents that integrate STT, LLMs, and TTS.
• Voice Activity Detection - Identifies speech segments within audio streams to manage natural turn-taking and conversational flow.
• Real-Time Transcription - Converts live audio input into text representations in real time for downstream language model processing.
• Multimodal AI Orchestrators - Coordinates multiple AI model types including vision, speech, and language into a unified context for agentic workflows.
• Multimodal Conversational Interfaces - Provides a framework for building conversational agents that integrate text, voice, and audio processing for real-time interaction.
• Full-Duplex Multimodal Interaction - Processes simultaneous audio and data flows to enable fluid, real-time conversational turns and natural interruptions.
• Real-Time Speech Processing - Implements a real-time speech processing pipeline for streaming transcription, voice activity detection, and speaker diarization.
• Unified Speech Pipelines - Ships a unified speech pipeline integrating transcription and activity detection for bidirectional voice interaction.
• Edge AI Model Deployment - Runs conversational logic and agent services on embedded hardware and edge devices for low-latency interaction.
• Speaker Diarization - Analyzes real-time audio streams to detect, separate, and label multiple distinct speakers.
• Containerized Deployments - Packages customized agent services into images for consistent execution across cloud platforms and virtual machines.
• Containerized Packaging - Bundles customized agent configurations into portable images for consistent deployment across cloud and edge environments.
• Embedded Hardware Deployment - Integrates agent logic directly onto embedded development boards for communication-driven physical device interaction.
• Edge AI Deployment Pipelines - Provides tools for packaging conversational agent logic into containers and deploying them onto embedded hardware boards.
• Hardware Integration - Allows agent logic to run directly on embedded development boards for physical device interactions.
• Audio-Visual Signal Alignment - Coordinates synthesized audio output with avatar lip movements to ensure precise temporal alignment.
• Modular Provider Interfaces - Implements a pluggable provider model to decouple multimodal capabilities like speech-to-text and avatar animation from core logic.
• Lip Synchronization Engines - Coordinates character avatar mouth movements with synthesized audio output for realistic speaking digital humans.
• Conversational Avatar Animators - Synchronizes character movements and facial expressions with LLM-driven conversational audio.

Star history