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LiteRT and LiteRT-LM sample apps, model recipes, agent skills and utilities.
| Date | Stars |
|---|---|
| 2026-07-31 | 381 |
| 2026-08-06 | 388 |
Today
+7 stars today
This week
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# **Google AI Edge LiteRT Samples** This repository contains official and community contributed sample applications, model recipes, agent skills and utilities for **[LiteRT](https://github.com/google-ai-edge/litert)** (formerly known as TensorFlow Lite), Google's open source, high-performance on-device machine learning framework and **[LiteRT-LM](https://github.com/google-ai-edge/litert-lm)**, a specialized orchestration layer for running LLMs with LiteRT, unlocking maximum performance and efficiency. **Note** Please access the interactive web page with a collections of demos there at: [https://google-ai-edge.github.io/litert-samples/](https://google-ai-edge.github.io/litert-samples/) The samples demonstrate different API paradigms (LiteRT CompiledModel API and legacy Interpreter API, Tensor API, LiteRT-LM) and provide end-to-end model conversion and deployment pipelines. --- ## **🔥 What's New** * 🐱 **Streaming TTS (KittenTTS nano)**: Added a tiny (15M-param, 32 MB) streaming text-to-speech Android sample — dynamic-length LiteRT graphs, sentence-level streaming playback, live TTFA/RTF metrics ([`samples/litert/text_to_speech_streaming/`](samples/litert/text_to_speech_streaming/)). * 🎙️ **Speech Recognition (ASR)**: Added end-to-end [Automatic Speech Recognition sample](samples/litert/speech_recognition) using the CompiledModel API. * 📸 **PhotoTalk Sample App**: Added multimodal sample app combining LiteRT vision processing with LiteRT-LM audio/text generation ([`samples/litert/phototalk_sample_app/`](samples/litert/phototalk_sample_app/)). * 🗣️ **Qwen3-TTS & Qwen3 ASR**: Added model recipes, conversion scripts, and Tensor API implementations for [Qwen3-TTS](models/qwen/qwen3_tts/) and [Qwen3 ASR](models/qwen/qwen_asr/). * 🎨 **Bonsai Image 4B**: Added text-to-image diffusion model sample with Python inference and conversion tools ([`models/bonsai/bonsai_image_4b/`](models/bonsai/bonsai_image_4b/)). * 🤖 **Agent Skills & Utilities**: Added four lifecycle agent skills ([`skills/`](skills/): conversion, quantization, on-device verification, app scaffolding), a GPU conversion toolkit ([`utilities/litert_gpu_toolkit/`](utilities/litert_gpu_toolkit/)), and shared Kotlin helpers ([`utilities/common/`](utilities/common/)). --- ## **📂 Repository Structure** ### **1. `samples/` — Application Samples** All runnable sample applications and interactive playgrounds are organized under `samples/`: * **`samples/litert/`**: Standard samples using the **LiteRT CompiledModel API**. Designed for modern hardware acceleration (GPU/NPU) and asynchronous execution. * *Samples:* Speech Recognition, PhotoTalk, Text-to-Speech, Image Generation (text-to-image), Image Segmentation, Image Classification, Digit Classification, Qualcomm NPU acceleration (Gemma, MobileNet, Fast VLM), Google TPU sample app. * **`samples/litert_interpreter/`**: Legacy samples using the **Interpreter API**. * *Samples:* Broad compatibility examples for Android, iOS, and Python (Image Classification, Object Detection, Image Segmentation, Audio Classification). * **`samples/litert_lm/`**: High-level Engine samples for Large Language Models (LLM/SLM). * **`samples/end_to_end/`**: Complete full-system pipelines (e.g. ImageNet model conversion, preprocessing, and classification). * **`samples/tensor_api_playground/`**: Interactive Web/WASM playground demonstrating LiteRT Tensor API capabilities directly in the browser (Gemma 3, Image Segmentation, Mandelbrot, Game of Life). ### **2. `models/` — Model Recipes & Export Pipelines** Contains standalone model conversion scripts, export recipes, and model-specific utilities. Many are working in process. ### **3. `utilities/` — Shared Tools & Helper Scripts** * **`utilities/common/`**: Shared Kotlin helpers for Android samples (camera pipeline, audio capture, CompiledModel runner, image/tensor and math helpers). * **`utilities/litert_gpu_toolkit/`**: Pre-conversion patches that rewrite common PyTorch patterns into f
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:ab007e776b4fd1f6, llm:Repository description: 'LiteRT and LiteRT-LM sample apps, model recipes, agent skills and utilities.' Topics: edge-ai, generative-ai, on-device-ai. Language: Python. Google AI Edge.
matched fp:ab007e776b4fd1f6, llm:Repository description: 'LiteRT and LiteRT-LM sample apps, model recipes, agent skills and utilities.' Topics: edge-ai, generative-ai, on-device-ai. Language: Python. Google AI Edge.
matched fp:ab007e776b4fd1f6, llm:Repository description: 'LiteRT and LiteRT-LM sample apps, model recipes, agent skills and utilities.' Topics: edge-ai, generative-ai, on-device-ai. Language: Python. Google AI Edge.
matched fp:ab007e776b4fd1f6, llm:Repository description: 'LiteRT and LiteRT-LM sample apps, model recipes, agent skills and utilities.' Topics: edge-ai, generative-ai, on-device-ai. Language: Python. Google AI Edge.