The MediaPipe Text Proofreader task lets you identify spelling, grammatical, and stylistic errors in a text and generate a corrected version while maintaining the original meaning. This task operates on text data with a machine learning (ML) model and outputs the corrected text.  On-device demo Text Proofreader Detect and correct grammar, spelling, and style errors locally with Gemma 3 1B. Available on Android, iOS, and desktop Python with on-device Gemma 3 1B via LiteRT-LM. On-device benchmark · Pixel 10 Pro CPU Gemma 3 1B · 100 words Prefill1,280tok/sDecode170tok/sE2E980ms
## Quickstart Install the SDK for your platform, initialize the task with a model, and run inference. ### Android (Kotlin) Gradle`implementation("com.google.mediapipe:tasks-text:latest.release")`[Sample code](https://github.com/google-ai-edge/mediapipe-samples/tree/main/examples/text_proofreader/android)·[Setup guide](https://developers.google.com/edge/mediapipe/solutions/setup_android.md.txt) ```kotlin import com.google.mediapipe.tasks.text.textproofreader.TextProofreader import com.google.mediapipe.tasks.text.textproofreader.TextProofreader.TextProofreaderOptions val options = TextProofreaderOptions.builder() .setModelPath("${context.filesDir}/proofread_quant_200m.litertlm") .build() val proofreader = TextProofreader.createFromOptions(context, options) val inputText = "Their are severel typos in this sentance." val result = proofreader.proofread(inputText) val correctedText = result.proofreadText ``` ### Android (Java) Gradle`implementation 'com.google.mediapipe:tasks-text:latest.release'`[Sample code](https://github.com/google-ai-edge/mediapipe-samples/tree/main/examples/text_proofreader/android)·[Setup guide](https://developers.google.com/edge/mediapipe/solutions/setup_android.md.txt) ```java import com.google.mediapipe.tasks.text.textproofreader.TextProofreader; import com.google.mediapipe.tasks.text.textproofreader.TextProofreader.TextProofreaderOptions; import com.google.mediapipe.tasks.text.textproofreader.TextProofreaderResult; TextProofreaderOptions options = TextProofreaderOptions.builder() .setModelPath(context.getFilesDir() + "/proofread_quant_200m.litertlm") .build(); TextProofreader proofreader = TextProofreader.createFromOptions(context, options); String inputText = "Their are severel typos in this sentance."; TextProofreaderResult result = proofreader.proofread(inputText); String correctedText = result.getProofreadText(); ``` ### iOS SwiftPM`https://github.com/google-ai-edge/mediapipe → MediaPipeTasksText`[Package.swift](https://developers.google.com/edge/mediapipe/solutions/setup_ios.md.txt#package_swift)·[Sample code](https://github.com/google-ai-edge/mediapipe-samples/tree/main/examples/text_proofreader/ios)·[Setup guide](https://developers.google.com/edge/mediapipe/solutions/setup_ios.md.txt) ```swift import Foundation import MediaPipeTasksText guard let modelPath = Bundle.main.path(forResource: "proofread_quant_200m", ofType: "litertlm") else { return } let options = TextProofreaderOptions() options.baseOptions.modelAssetPath = modelPath let textProofreader = try TextProofreader(options: options) let inputText = "Their are severel typos in this sentance." let result = try textProofreader.proofread(text: inputText) let correctedText = result.proofreadText ``` ### Python pip`pip install mediapipe`[Sample code](https://colab.research.google.com/github/google-ai-edge/mediapipe-samples/blob/main/examples/text_proofreader/python/text_proofreader.ipynb)·[Setup guide](https://developers.google.com/edge/mediapipe/solutions/setup_python.md.txt) ```python import mediapipe as mp BaseOptions = mp.tasks.BaseOptions TextProofreader = mp.tasks.text.TextProofreader TextProofreaderOptions = mp.tasks.text.TextProofreaderOptions model_path = "proofread_quant_200m.litertlm" options = TextProofreaderOptions(base_options=BaseOptions(model_asset_path=model_path), max_num_tokens=4096) input_text = "Their are severel typos in this sentance." with TextProofreader.create_from_options(options) as text_proofreader: result = text_proofreader.proofread(input_text) corrected_text = result.proofread_text ``` ### Flutter pub`flutter pub add mediapipe_text`[Live gallery](https://google.github.io/flutter-mediapipe/)·[Sample code](https://github.com/google/flutter-mediapipe/tree/main/samples/text/text_proofreader)·[Setup guide](https://developers.google.com/edge/mediapipe/solutions/setup_flutter.md.txt) Text Proofreader isn't available in Flutter web apps yet. ```dart import 'package:mediapipe_text/mediapipe_text.dart'; Future proofread() async { final task = await TextProofreader.create( TextProofreaderOptions(model: TextModels.proofreader), ); try { final result = await task.proofread('She go home.'); print(result.proofreadText); for (final edit in result.corrections) { print('${edit.type.name}: ${edit.text}'); } await for (final update in task.proofreadStream( 'I recieved your mesage.', )) { if (update.chunk != null) print(update.chunk); if (update.done) print(update.corrections); } } finally { await task.dispose(); } } ``` ## Task details This section describes the capabilities, inputs, outputs, and configuration options of this task. ### Features - **Input text processing** - Handles text pre-processing, including tokenization if needed. - **Granular corrections** - Provides a detailed breakdown of granular corrections, allowing you to identify which words were inserted, deleted, or left unchanged. Inputs Text Proofreader accepts the following input data type: - String Outputs The Text Proofreader outputs the following results: - String: represents the proofread result. - List of corrections: detailed breakdown of granular edits (insertions, deletions, or unchanged text segments). ### Configuration options This task has the following configuration options: ### Android | Option Name | Description | Value Range | Default Value | |---|---|---|---| | `modelPath` | Path to the `.litertlm` model file in device storage (or use `modelAssetFileDescriptor`). | `String` | Required | | `maxNumTokens` | Optional limit on the maximum context length in tokens. If unset or `0`, defaults to the model's built-in capacity (`8192` tokens). | `Integer` | `0` (model default 8k) | ### iOS | Option Name | Description | Value Range | Default Value | |---|---|---|---| | `baseOptions.modelAssetPath` | Path or URL to the proofreader model (`modelPath` or `modelAssetFileDescriptor` on Android). | `String` | Required | | `maxNumTokens` | Optional limit on the maximum context length in tokens. If unset or `0`, defaults to the model's built-in capacity (`8192` tokens). | `Integer` | `0` (model default 8k) | | `cacheDirectory` | Optional writable directory for the model weight and program caches. Pass `":nocache"` to disable caching. | `String` | Not set | ### Python | Option Name | Description | Value Range | Default Value | |---|---|---|---| | `base_options.model_asset_path` | Path or URL to the proofreader model (`modelPath` or `modelAssetFileDescriptor` on Android). | `String` | Required | | `max_num_tokens` | Optional limit on the maximum context length in tokens. If unset or `0`, defaults to the model's built-in capacity (`8192` tokens). | `Integer` | `0` (model default 8k) | | `cache_dir` | Optional writable directory for the model weight and program caches. Pass `":nocache"` to disable caching. | `str` | `":nocache"` | ### Flutter | Option Name | Description | Value Range | Default Value | |---|---|---|---| | `model` | Google's pinned proofreader model, `TextModels.proofreader`, bundled at build time (or `modelPath` to a `.litertlm` file on the device). Supply exactly one; `modelBytes` isn't accepted. | `DownloadAsset` | Required | | `maxNumTokens` | Optional limit on the maximum context length in tokens, covering input and output. If `null` or `0`, defaults to the model's built-in capacity (`8192` tokens). | `int` `[0, 2147483647]` | `null` (model default 8k) | | `cacheDirectory` | Optional writable directory where Google's runtime caches the prepared model. If `null`, Google's default (beside the model) is used. | `String` | `null` | ### Task output Each `TextProofreaderResult` returns the corrected text together with a granular diff of word-level edits: | Field | Type | Description | |---|---|---| | `proofreadText` | `string` | Complete proofread text with spelling, grammar, and stylistic corrections applied (`proofread_text` in Python; a nullable `String?` in Dart). | | `corrections` | `Correction[]` | Ordered list of diff segments (`type`: `SAME`, `INSERTION`, or `DELETION`; `text`: `string`) comparing the original input to `proofreadText` (in Dart, `ProofreadingCorrection` with `type` as `ProofreadingCorrectionType.same`, `.insertion`, or `.deletion`). | #### Example `TextProofreaderResult` payload The following example shows the corrected string and granular edit segments returned for a sentence with typos: ```javascript { proofreadText: "There are several typos in this sentence.", corrections: [ { type: "DELETION", text: "Their" }, { type: "INSERTION", text: "There" }, { type: "SAME", text: " are " }, { type: "DELETION", text: "severel" }, { type: "INSERTION", text: "several" }, { type: "SAME", text: " typos in this " }, { type: "DELETION", text: "sentance." }, { type: "INSERTION", text: "sentence." } ] } ``` ## Models  We offer a default, recommended model when you start developing with this task. ### Proofread 200M model (recommended) A lightweight 200M parameter model fine-tuned to identify spelling, grammatical, and stylistic errors in a text and generate a corrected version. This model is subject to the [Gemma Terms of Use](https://ai.google.dev/gemma/terms). | Model name | Input | Quantization type | Terms of use | Versions | |---|---|---|---|---| | [Text Proofreader](https://storage.googleapis.com/mediapipe-models/text_proofreader/200m/latest/proofread_quant_200m.litertlm) | string | Mixed Precision (Int4 + Int8) | [Gemma](https://ai.google.dev/gemma/terms) | [Latest](https://storage.googleapis.com/mediapipe-models/text_proofreader/200m/latest/proofread_quant_200m.litertlm) | ## Task benchmarks Here are the task benchmarks for the whole pipeline on a Pixel 10 Pro CPU. Peak memory usage for on-device model inference varies from approximately 200MB to 350MB depending on the input length (100 to 2000 words). ### MediaPipe E2E Benchmark | Device | Input Words (tokens) | Prefill (tokens/s) | Decode (tokens/s) | E2E Latency (ms) | |---|---|---|---|---| | Pixel 10 Pro CPU | 100 (\~200 tokens) | 1280 | 170 | 980 | | Pixel 10 Pro CPU | 500 (\~900 tokens) | 1095 | 163 | 4,900 | | Pixel 10 Pro CPU | 1000 (\~1900 tokens) | 1025 | 150 | 16,000 | | Pixel 10 Pro CPU | 2000 (\~3600 tokens) | 980 | 140 | 28,000 |